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1. The Efficacy of Transdermal Rivastigmine in Mild to Moderate Alzheimer’s Disease with Concomitant Small Vessel Cerebrovascular Disease: Findings from an Open-Label Study

Author: Yatawara C, Zailan FZ, Chua EV, Lim LLH, Silva E, Wang JS, Ng A, Ng KP, and Kandiah N
Subjects: rivastigmine, alzheimer’s disease, small vessel cerebrovascular disease, treatment, Geriatrics, RC952-954.6
Abstract: Chathuri Yatawara,1 Fatin Zahra Zailan,1 Esther Vanessa Chua,1 Linda Lay Hoon Lim,1 Eveline Silva,1 Joanna Sihan Wang,1 Adeline Ng,1 Kok Pin Ng,1 Nagaendran Kandiah1– 3 1Department of Neurology, National Neuroscience Institute, Singapore, Singapore; 2Duke-NUS Medical School, Singapore, Singapore; 3Lee Kong Chian School of Medicine-Imperial College London, Nanyang Technological University, Singapore, SingaporeCorrespondence: Nagaendran KandiahNational Neuroscience Institute, Level 3, Clinical Staff Office, 11 Jalan Tan Tock Seng, Singapore, 308433, SingaporeTel +65 6357 7171Fax +65 6357 7137Email Nagaendran.Kandiah@singhealth.com.sgBackground: Rivastigmine is used to treat cognitive impairment in Alzheimer’s disease (AD); however, the efficacy of Rivastigmine in patients with AD and concomitant small vessel cerebrovascular disease (svCVD) remains unclear. We investigated the effectiveness of Rivastigmine Patch in patients with AD and svCVD.Methods: In this open-label study, 100 patients with AD and MRI confirmed svCVD received 9.5mg/24 hours Rivastigmine transdermal treatment for 24 weeks. The primary outcome was global cognition indexed using the ADAS-Cog. Secondary outcomes included clinical-rated impression of change (indexed using (ADCS‐CGIC), activities of daily living (indexed using ADCS-ADL) and side effects.Results: Overall, performance on the ADAS-Cog after 24 weeks deteriorated by 1.78 (SD = 5.29) points. Fifty-two percent of the sample demonstrated improvement or remained stable, while 48% demonstrated worsening of ADAS-Cog scores. Of the 52%, significant improvement (2 or more-point decline) on the ADAS-Cog was observed in 25% of the sample, with a mean change of − 5.08 (SD = 3.11). A decline on the ADAS-Cog was observed in 48% of the sample, with a mean change of 6 (SD = 2.98) points. Cognitive outcome did not interact with severity of svCVD. ADCS-ADL scores remained stable from baseline to week 24 and ADCS‐CGIC reports indicated that 81% of the patients remained stable after treatment. Side effects were reported by 16% of the patients, with contact dermatitis being the most common.Conclusion: Our findings suggest that Rivastigmine may have a role in the management of patients having AD and concomitant mild-severe svCVD, with minimal side effects.Keywords: rivastigmine, Alzheimer’s disease, small vessel cerebrovascular disease, treatment
Published: 2021

2. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author: Best, J.G., Ambler, G., Wilson, D., Lee, K.J., Lim, J.S., Shiozawa, M., Koga, M., Li, L, Lovelock, C., Chabriat, H., Hennerici, M., Wong, Y.K., Mak, H.K.F., Prats-Sanchez, L., Martínez-Domeño, A., Inamura, S., Yoshifuji, K., Arsava, E.M., Horstmann, S., Purrucker, J., Lam, B.Y.K., Wong, A., Kim, Y.D., Song, T.J., Lemmens, R., Eppinger, S., Gattringer, T., Uysal, E., Tanriverdi, Z., Bornstein, N.M., Assayag, E. Ben, Hallevi, H., Molad, J., Nishihara, M., Tanaka, J., Coutts, S.B., Polymeris, A., Wagner, B., Seiffge, D.J., Lyrer, P., Algra, A., Kappelle, L.J., Al-Shahi Salman, R., Jäger, H.R., Lip, G.Y.H., Fischer, U., El-Koussy, M., Mas, J.L., Legrand, Laurence, Karayiannis, C., Phan, T., Gunkel, S., Christ, N., Abrigo, J., Leung, T., Chu, W., Chappell, F., Makin, S., Hayden, D., Williams, D.J., Mess, W.H., Nederkoorn, P.J., Barbato, C., Browning, S., Wiegertjes, K., Tuladhar, A.M., Maaijwee, N., Guevarra, A.C., Yatawara, C., Mendyk, A.M., Delmaire, C., Köhler, S., Oostenbrugge, R van, Zhou, Y, Xu, Chao, Hilal, S., Gyanwali, B., Chen, C, Lou, M., Staals, J., Bordet, R., Kandiah, N., Leeuw, F.E. de, Simister, R., Hendrikse, Jeroen, Kelly, P.J., Wardlaw, J., Soo, Y., Fluri, F., Srikanth, V., Calvet, D., Jung, S., Kwa, V.I.H., Engelter, S.T., Peters, Nils, Smith, E.E., Hara, H., Yakushiji, Y., Orken, D.N., Best, J.G., Ambler, G., Wilson, D., Lee, K.J., Lim, J.S., Shiozawa, M., Koga, M., Li, L, Lovelock, C., Chabriat, H., Hennerici, M., Wong, Y.K., Mak, H.K.F., Prats-Sanchez, L., Martínez-Domeño, A., Inamura, S., Yoshifuji, K., Arsava, E.M., Horstmann, S., Purrucker, J., Lam, B.Y.K., Wong, A., Kim, Y.D., Song, T.J., Lemmens, R., Eppinger, S., Gattringer, T., Uysal, E., Tanriverdi, Z., Bornstein, N.M., Assayag, E. Ben, Hallevi, H., Molad, J., Nishihara, M., Tanaka, J., Coutts, S.B., Polymeris, A., Wagner, B., Seiffge, D.J., Lyrer, P., Algra, A., Kappelle, L.J., Al-Shahi Salman, R., Jäger, H.R., Lip, G.Y.H., Fischer, U., El-Koussy, M., Mas, J.L., Legrand, Laurence, Karayiannis, C., Phan, T., Gunkel, S., Christ, N., Abrigo, J., Leung, T., Chu, W., Chappell, F., Makin, S., Hayden, D., Williams, D.J., Mess, W.H., Nederkoorn, P.J., Barbato, C., Browning, S., Wiegertjes, K., Tuladhar, A.M., Maaijwee, N., Guevarra, A.C., Yatawara, C., Mendyk, A.M., Delmaire, C., Köhler, S., Oostenbrugge, R van, Zhou, Y, Xu, Chao, Hilal, S., Gyanwali, B., Chen, C, Lou, M., Staals, J., Bordet, R., Kandiah, N., Leeuw, F.E. de, Simister, R., Hendrikse, Jeroen, Kelly, P.J., Wardlaw, J., Soo, Y., Fluri, F., Srikanth, V., Calvet, D., Jung, S., Kwa, V.I.H., Engelter, S.T., Peters, Nils, Smith, E.E., Hara, H., Yakushiji, Y., and Orken, D.N.
Abstract: Item does not contain fulltext, BACKGROUND: Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk. METHODS: We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602. FINDINGS: The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with
Published: 2021

3. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

Author: Best J.G., Ambler G., Wilson D., Lee K.-J., Lim J.-S., Shiozawa M., Koga M., Li L., Lovelock C., Chabriat H., Hennerici M., Wong Y.K., Mak H.K.F., Prats-Sanchez L., Martinez-Domeno A., Inamura S., Yoshifuji K., Arsava E.M., Horstmann S., Purrucker J., Lam B.Y.K., Wong A., Kim Y.D., Song T.-J., Lemmens R., Eppinger S., Gattringer T., Uysal E., Tanriverdi Z., Bornstein N.M., Ben Assayag E., Hallevi H., Molad J., Nishihara M., Tanaka J., Coutts S.B., Polymeris A., Wagner B., Seiffge D.J., Lyrer P., Algra A., Kappelle L.J., Al-Shahi Salman R., Jager H.R., Lip G.Y.H., Fischer U., El-Koussy M., Mas J.-L., Legrand L., Karayiannis C., Phan T., Gunkel S., Christ N., Abrigo J., Leung T., Chu W., Chappell F., Makin S., Hayden D., Williams D.J., Mess W.H., Nederkoorn P.J., Barbato C., Browning S., Wiegertjes K., Tuladhar A.M., Maaijwee N., Guevarra A.C., Yatawara C., Mendyk A.-M., Delmaire C., Kohler S., van Oostenbrugge R., Zhou Y., Xu C., Hilal S., Gyanwali B., Chen C., Lou M., Staals J., Bordet R., Kandiah N., de Leeuw F.-E., Simister R., Hendrikse J., Kelly P.J., Wardlaw J., Soo Y., Fluri F., Srikanth V., Calvet D., Jung S., Kwa V.I.H., Engelter S.T., Peters N., Smith E.E., Hara H., Yakushiji Y., Orken D.N., Fazekas F., Thijs V., Heo J.H., Mok V., Veltkamp R., Ay H., Imaizumi T., Gomez-Anson B., Lau K.K., Jouvent E., Rothwell P.M., Toyoda K., Bae H.-J., Marti-Fabregas J., Werring D.J., Harkness K., Shaw L., Sword J., Mohd Nor A., Sharma P., Kelly D., Harrington F., Randall M., Smith M., Mahawish K., Elmarim A., Esisi B., Cullen C., Nallasivam A., Price C., Barry A., Roffe C., Coyle J., Hassan A., Birns J., Cohen D., Sekaran L., Parry-Jones A., Parry A., Hargroves D., Proschel H., Datta P., Darawil K., Manoj A., Burn M., Patterson C., Giallombardo E., Smyth N., Mansoor S., Anwar I., Marsh R., Ispoglou S., Chadha D., Prabhakaran M., Meenakishundaram S., O'Connell J., Scott J., Krishnamurthy V., Aghoram P., McCormick M., Sprigg N., O'Mahony P., Cooper M., Choy L., Wilkinson P., Leach S., Caine S., Burger I., Gunathilagan G., Guyler P., Emsley H., Davis M., Manawadu D., Pasco K., Mamun M., Luder R., Sajid M., Okwera J., Warburton E., Saastamoinen K., England T., Putterill J., Flossman E., Power M., Dani K., Mangion D., Suman A., Corrigan J., Lawrence E., Vahidassr D., Shakeshaft C., Brown M., Charidimou A., Cohen H., Banerjee G., Houlden H., White M., Yousry T., Flossmann E., Muir K., Gratz P., Mattle H., Panos L., Korczyn A., Kliper E., Maeder P., Gass A., Pachai C., Bracoub L., Douste-Blazy M.-Y., Fratacci M.D., Vicaut E., Sato S., Miwa K., Fujita K., Ide T., Ma H., Ly J., Singhal S., Chandra R., Slater L.-A., Soufan C., Moran C., Traenka C., Thilemann S., Fladt J., Gensicke H., Bonati L., Kim B.J., Han M.-K., Kang J., Ko E., Yang M.H., Jang M.S., Murphy S., Carty F., Akijian L., Thornton J., Schembri M., Douven E., Delgado-Mederos R., Marin R., Camps-Renom P., Guisado-Alonso D., Nunez F., Medrano-Martorell S., Merino E., Iida K., Ikeda S., Irie H., Demirelli D.S., Medanta J.M., Zerna C., Hernandez M.V., Armitage P., Heye A., Munoz-Maniega S., Sakka E., Thrippleton M., Dennis M., Beigneux Y., Silva M., Venketasubramanian N., Ho S.L., Cheung R.T.F., Chan K.H., Teo K.C., Hui E., Kwan J.S.K., Chang R., Tse M.Y., Hoi C.P., Chan C.Y., Chan O.L., Cheung R.H.K., Wong E.K.M., Leung K.T., Tsang S.F., Ip H.L., Ma S.H., Ma K., Fong W.C., Li S.H., Li R., Ng P.W., Wong K.K., Liu W., Wong L., Ramos L., De Schryver E., Jobsis J., van der Sande J., Brouwers P., Roos Y., Stam J., Bakker S., Verbiest H., Schoonewille W., Linn C., Hertzberger L., van Gemert M., Berntsen P., Van Dam-Nolen D., Kooi M.E., Van der Lugt A., Koudstaal P., Leff A., Ward N., Nachev P., Perry R., Ozkan H., Mitchell J., Best J.G., Ambler G., Wilson D., Lee K.-J., Lim J.-S., Shiozawa M., Koga M., Li L., Lovelock C., Chabriat H., Hennerici M., Wong Y.K., Mak H.K.F., Prats-Sanchez L., Martinez-Domeno A., Inamura S., Yoshifuji K., Arsava E.M., Horstmann S., Purrucker J., Lam B.Y.K., Wong A., Kim Y.D., Song T.-J., Lemmens R., Eppinger S., Gattringer T., Uysal E., Tanriverdi Z., Bornstein N.M., Ben Assayag E., Hallevi H., Molad J., Nishihara M., Tanaka J., Coutts S.B., Polymeris A., Wagner B., Seiffge D.J., Lyrer P., Algra A., Kappelle L.J., Al-Shahi Salman R., Jager H.R., Lip G.Y.H., Fischer U., El-Koussy M., Mas J.-L., Legrand L., Karayiannis C., Phan T., Gunkel S., Christ N., Abrigo J., Leung T., Chu W., Chappell F., Makin S., Hayden D., Williams D.J., Mess W.H., Nederkoorn P.J., Barbato C., Browning S., Wiegertjes K., Tuladhar A.M., Maaijwee N., Guevarra A.C., Yatawara C., Mendyk A.-M., Delmaire C., Kohler S., van Oostenbrugge R., Zhou Y., Xu C., Hilal S., Gyanwali B., Chen C., Lou M., Staals J., Bordet R., Kandiah N., de Leeuw F.-E., Simister R., Hendrikse J., Kelly P.J., Wardlaw J., Soo Y., Fluri F., Srikanth V., Calvet D., Jung S., Kwa V.I.H., Engelter S.T., Peters N., Smith E.E., Hara H., Yakushiji Y., Orken D.N., Fazekas F., Thijs V., Heo J.H., Mok V., Veltkamp R., Ay H., Imaizumi T., Gomez-Anson B., Lau K.K., Jouvent E., Rothwell P.M., Toyoda K., Bae H.-J., Marti-Fabregas J., Werring D.J., Harkness K., Shaw L., Sword J., Mohd Nor A., Sharma P., Kelly D., Harrington F., Randall M., Smith M., Mahawish K., Elmarim A., Esisi B., Cullen C., Nallasivam A., Price C., Barry A., Roffe C., Coyle J., Hassan A., Birns J., Cohen D., Sekaran L., Parry-Jones A., Parry A., Hargroves D., Proschel H., Datta P., Darawil K., Manoj A., Burn M., Patterson C., Giallombardo E., Smyth N., Mansoor S., Anwar I., Marsh R., Ispoglou S., Chadha D., Prabhakaran M., Meenakishundaram S., O'Connell J., Scott J., Krishnamurthy V., Aghoram P., McCormick M., Sprigg N., O'Mahony P., Cooper M., Choy L., Wilkinson P., Leach S., Caine S., Burger I., Gunathilagan G., Guyler P., Emsley H., Davis M., Manawadu D., Pasco K., Mamun M., Luder R., Sajid M., Okwera J., Warburton E., Saastamoinen K., England T., Putterill J., Flossman E., Power M., Dani K., Mangion D., Suman A., Corrigan J., Lawrence E., Vahidassr D., Shakeshaft C., Brown M., Charidimou A., Cohen H., Banerjee G., Houlden H., White M., Yousry T., Flossmann E., Muir K., Gratz P., Mattle H., Panos L., Korczyn A., Kliper E., Maeder P., Gass A., Pachai C., Bracoub L., Douste-Blazy M.-Y., Fratacci M.D., Vicaut E., Sato S., Miwa K., Fujita K., Ide T., Ma H., Ly J., Singhal S., Chandra R., Slater L.-A., Soufan C., Moran C., Traenka C., Thilemann S., Fladt J., Gensicke H., Bonati L., Kim B.J., Han M.-K., Kang J., Ko E., Yang M.H., Jang M.S., Murphy S., Carty F., Akijian L., Thornton J., Schembri M., Douven E., Delgado-Mederos R., Marin R., Camps-Renom P., Guisado-Alonso D., Nunez F., Medrano-Martorell S., Merino E., Iida K., Ikeda S., Irie H., Demirelli D.S., Medanta J.M., Zerna C., Hernandez M.V., Armitage P., Heye A., Munoz-Maniega S., Sakka E., Thrippleton M., Dennis M., Beigneux Y., Silva M., Venketasubramanian N., Ho S.L., Cheung R.T.F., Chan K.H., Teo K.C., Hui E., Kwan J.S.K., Chang R., Tse M.Y., Hoi C.P., Chan C.Y., Chan O.L., Cheung R.H.K., Wong E.K.M., Leung K.T., Tsang S.F., Ip H.L., Ma S.H., Ma K., Fong W.C., Li S.H., Li R., Ng P.W., Wong K.K., Liu W., Wong L., Ramos L., De Schryver E., Jobsis J., van der Sande J., Brouwers P., Roos Y., Stam J., Bakker S., Verbiest H., Schoonewille W., Linn C., Hertzberger L., van Gemert M., Berntsen P., Van Dam-Nolen D., Kooi M.E., Van der Lugt A., Koudstaal P., Leff A., Ward N., Nachev P., Perry R., Ozkan H., and Mitchell J.
Abstract: Background: Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk. Method(s): We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602. Finding(s): The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0.73 (95% CI 0.69-0.77) with a calibration slope of 0.94 (0.81-1.06) for the intracranial haemorrhage model and 0.63 (0.62-0.65) w
Published: 2021

4. Association of Prediabetes and Type 2 Diabetes With Cognitive Function After Stroke: A STROKOG Collaboration Study

Author: Lo, JW ; https://orcid.org/0000-0003-4778-8360, Crawford, JD ; https://orcid.org/0000-0001-5141-0673, Samaras, K, Desmond, DW, Köhler, S, Staals, J, Verhey, FRJ, Bae, HJ, Lee, KJ, Kim, BJ, Bordet, R, Cordonnier, C, Dondaine, T, Mendyk, AM, Lee, BC, Yu, KH, Lim, JS, Kandiah, N, Chander, RJ ; https://orcid.org/0000-0002-2110-5958, Yatawara, C, Lipnicki, DM ; https://orcid.org/0000-0002-1684-3577, Sachdev, PS ; https://orcid.org/0000-0002-9595-3220, Lo, JW ; https://orcid.org/0000-0003-4778-8360, Crawford, JD ; https://orcid.org/0000-0001-5141-0673, Samaras, K, Desmond, DW, Köhler, S, Staals, J, Verhey, FRJ, Bae, HJ, Lee, KJ, Kim, BJ, Bordet, R, Cordonnier, C, Dondaine, T, Mendyk, AM, Lee, BC, Yu, KH, Lim, JS, Kandiah, N, Chander, RJ ; https://orcid.org/0000-0002-2110-5958, Yatawara, C, Lipnicki, DM ; https://orcid.org/0000-0002-1684-3577, and Sachdev, PS ; https://orcid.org/0000-0002-9595-3220
Abstract: Background and Purpose - Type 2 diabetes mellitus (T2D) is associated with cognitive impairment and an increased risk of dementia, but the association between prediabetes and cognitive impairment is less clear, particularly in a setting of major cerebrovascular events. This article examines the impact of impaired fasting glucose and T2D on cognitive performance in a stroke population. Methods - Seven international observational studies from the STROKOG (Stroke and Cognition) consortium (n=1601; mean age, 66.0 years; 70% Asian, 26% white, and 2.6% African American) were included. Fasting glucose level (FGL) during hospitalization was used to define 3 groups, T2D (FGL ≥7.0 mmol/L), impaired fasting glucose (FGL 6.1-6.9 mmol/L), and normal (FGL <6.1 mmol/L), and a history of diabetes mellitus and the use of a diabetes mellitus medication were also used to support a diagnosis of T2D. Domain and global cognition Z scores were derived from standardized neuropsychological test scores. The cross-sectional association between glucose status and cognitive performance at 3 to 6 months poststroke was examined using linear mixed models, adjusting for age, sex, education, stroke type, ethnicity, and vascular risk factors. Results - Patients with T2D had significantly poorer performance in global cognition (SD, -0.59 [95% CI, -0.82 to -0.36]; P<0.001) and in all domains compared with patients with normal FGL. There was no significant difference between impaired fasting glucose patients and those with normal FGL in global cognition (SD, -0.10 [95% CI, -0.45 to 0.24]; P=0.55) or in any cognitive domain. Conclusions - Diabetes mellitus, but not prediabetes, is associated with poorer cognitive performance in patients 3 to 6 months after stroke.
Published: 2020

5. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author: Wilson, D., Ambler, G., Lee, K.J., Lim, J.S., Shiozawa, M., Koga, M., Li, L, Lovelock, C., Chabriat, H., Hennerici, M., Wong, Y.K., Mak, H.K.F., Prats-Sanchez, L., Martinez-Domeno, A., Inamura, S., Yoshifuji, K., Arsava, E.M., Horstmann, S., Purrucker, J., Lam, B.Y.K., Wong, A., Kim, Y.D., Song, T.J., Schrooten, M., Lemmens, R., Eppinger, S., Gattringer, T., Uysal, E., Tanriverdi, Z., Bornstein, N.M., Assayag, E.B., Hallevi, H., Tanaka, J., Hara, H., Coutts, S.B., Hert, L., Polymeris, A., Seiffge, D.J., Lyrer, P., Algra, A., Kappelle, J., Al-Shahi Salman, R., Jager, H.R., Lip, G.Y.H., Mattle, H.P., Panos, L.D., Mas, J.L., Legrand, L., Karayiannis, C., Phan, T., Gunkel, S., Christ, N., Abrigo, J., Leung, T., Chu, W., Chappell, F., Makin, S., Hayden, D., Williams, D.J., Kooi, M.E., Dam-Nolen, D.H.K., Barbato, C., Browning, S., Wiegertjes, K., Tuladhar, A.M., Maaijwee, N., Guevarra, C., Yatawara, C., Mendyk, A.M., Delmaire, C., Kohler, S., Oostenbrugge, R van, Zhou, Y, Xu, C., Hilal, S., Gyanwali, B., Chen, C, Lou, M., Staals, J., Bordet, R., Kandiah, N., Leeuw, F.E. de, Simister, R., Lugt, A. van der, Kelly, P.J., Wardlaw, J.M., Soo, Y., Fluri, F., Srikanth, V., Calvet, D., Jung, S., Kwa, V.I.H., Engelter, S.T., Peters, N, Smith, E.E., Yakushiji, Y., Orken, D.N., Fazekas, F., Marti-Fabregas, J., Werring, D.J., Wilson, D., Ambler, G., Lee, K.J., Lim, J.S., Shiozawa, M., Koga, M., Li, L, Lovelock, C., Chabriat, H., Hennerici, M., Wong, Y.K., Mak, H.K.F., Prats-Sanchez, L., Martinez-Domeno, A., Inamura, S., Yoshifuji, K., Arsava, E.M., Horstmann, S., Purrucker, J., Lam, B.Y.K., Wong, A., Kim, Y.D., Song, T.J., Schrooten, M., Lemmens, R., Eppinger, S., Gattringer, T., Uysal, E., Tanriverdi, Z., Bornstein, N.M., Assayag, E.B., Hallevi, H., Tanaka, J., Hara, H., Coutts, S.B., Hert, L., Polymeris, A., Seiffge, D.J., Lyrer, P., Algra, A., Kappelle, J., Al-Shahi Salman, R., Jager, H.R., Lip, G.Y.H., Mattle, H.P., Panos, L.D., Mas, J.L., Legrand, L., Karayiannis, C., Phan, T., Gunkel, S., Christ, N., Abrigo, J., Leung, T., Chu, W., Chappell, F., Makin, S., Hayden, D., Williams, D.J., Kooi, M.E., Dam-Nolen, D.H.K., Barbato, C., Browning, S., Wiegertjes, K., Tuladhar, A.M., Maaijwee, N., Guevarra, C., Yatawara, C., Mendyk, A.M., Delmaire, C., Kohler, S., Oostenbrugge, R van, Zhou, Y, Xu, C., Hilal, S., Gyanwali, B., Chen, C, Lou, M., Staals, J., Bordet, R., Kandiah, N., Leeuw, F.E. de, Simister, R., Lugt, A. van der, Kelly, P.J., Wardlaw, J.M., Soo, Y., Fluri, F., Srikanth, V., Calvet, D., Jung, S., Kwa, V.I.H., Engelter, S.T., Peters, N, Smith, E.E., Yakushiji, Y., Orken, D.N., Fazekas, F., Marti-Fabregas, J., and Werring, D.J.
Abstract: Contains fulltext : 208975.pdf (publisher's version ) (Open Access), BACKGROUND: Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke. METHODS: We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or transient ischaemic attack; included at least 50 participants; collected data on stroke events over at least 3 months follow-up; used an appropriate MRI sequence that is sensitive to magnetic susceptibility; and documented the number and anatomical distribution of cerebral microbleeds reliably using consensus criteria and validated scales. Our prespecified primary outcomes were a composite of any symptomatic intracranial haemorrhage or ischaemic stroke, symptomatic intracranial haemorrhage, and symptomatic ischaemic stroke. We registered this study with the PROSPERO international prospective register of systematic reviews, number CRD42016036602. FINDINGS: Between Jan 1, 1996, and Dec 1, 2018, we identified 344 studies. After exclusions for ineligibility or declined requests for inclusion, 20 322 patients from 38 cohorts (over 35 225 patient-years of follow-up; median 1.34 years [IQR 0.19-2.44]) were included in our analyses. The adjusted hazard ratio [aHR] comparing patients with cerebral microbleeds to those without was 1.35 (95% CI 1.20-1.50) for the composite outcome of intr
Published: 2019

6. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

Author: Jung S., van Dam-Nolen D.H.K., Douven E., Delgado-Mederos, R., Marin R., Camps-Renom P., Guisado-Alonso D., Nunez F., Medrano-Martorell S., Merino E., Iida K., Ikeda S., Nishihara M., Irie H., Demirelli D.S., Medanta J.M., Zerna C., Hernandez M.V., Armitage P., Heye A., Munoz-Maniega S., Sakka E., Thrippleton M., Dennis M., Beigneux Y., Silva M., Venketasubramanian N., Ho S.L., Cheung R.T.F., Chan K.H., Teo K.C., Hui E., Kwan J.S.K., Chang R., Tse M.Y., Hoi C.P., Chan C.Y., Chan O.L., Cheung R.H.K., Wong E.K.M., Leung K.T., Tsang S.F., Ip H.L., Ma S.H., Ma K., Fong W.C., Li S.H., Li R., Ng P.W., Wong K.K., Liu W., Wong L., Ramos L., De Schryver E., Jobsis J., van der Sande J., Brouwers P., Roos Y., Stam J., Bakker S., Verbiest H., Schoonewille W., Linn C., Hertzberger L., van Gemert M., Berntsen P., Hendrikse J., Nederkoorn P., Mess W., Koudstaal P., Leff A., Ward N., Nachev P., Perry R., Ozkan H., Mitchell J., Wilson D., Ambler G., Lee K.-J., Lim J.-S., Shiozawa M., Koga M., Li L., Lovelock C., Chabriat H., Hennerici M., Wong Y.K., Mak H.K.F., Prats-Sanchez L., Martinez-Domeno A., Inamura S., Yoshifuji K., Arsava E.M., Horstmann S., Purrucker J., Lam B.Y.K., Wong A., Kim Y.D., Song T.-J., Schrooten M., Lemmens R., Eppinger S., Gattringer T., Uysal E., Tanriverdi Z., Bornstein N.M., Assayag E.B., Hallevi H., Tanaka J., Hara H., Coutts S.B., Hert L., Polymeris A., Seiffge D.J., Lyrer P., Algra A., Kappelle J., Al-Shahi Salman R., Jager H.R., Lip G.Y.H., Mattle H.P., Panos L.D., Mas J.-L., Legrand L., Karayiannis C., Phan T., Gunkel S., Christ N., Abrigo J., Leung T., Chu W., Chappell F., Makin S., Hayden D., Williams D.J., Kooi M.E., Barbato C., Browning S., Wiegertjes K., Tuladhar A.M., Maaijwee N., Guevarra C., Yatawara C., Mendyk A.-M., Delmaire C., Kohler S., van Oostenbrugge R., Zhou Y., Xu C., Hilal S., Gyanwali B., Chen C., Lou M., Staals J., Bordet R., Kandiah N., de Leeuw F.-E., Simister R., van der Lugt A., Kelly P.J., Wardlaw J.M., Soo Y., Fluri F., Srikanth V., Calvet D., Kwa V.I.H., Engelter S.T., Peters N., Smith E.E., Yakushiji Y., Orken D.N., Fazekas F., Thijs V., Heo J.H., Mok V., Veltkamp R., Ay H., Imaizumi T., Gomez-Anson B., Lau K.K., Jouvent E., Rothwell P.M., Toyoda K., Bae H.-J., Marti-Fabregas J., Werring D.J., Harkness K., Shaw L., Sword J., Mohd Nor A., Sharma P., Kelly D., Harrington F., Randall M., Smith M., Mahawish K., Elmarim A., Esisi B., Cullen C., Nallasivam A., Price C., Barry A., Roffe C., Coyle J., Hassan A., Birns J., Cohen D., Sekaran L., Parry-Jones A., Parry A., Hargroves D., Proschel H., Datta P., Darawil K., Manoj A., Burn M., Patterson C., Giallombardo E., Smyth N., Mansoor S., Anwar I., Marsh R., Ispoglou S., Chadha D., Prabhakaran M., Meenakishundaram S., O'Connell J., Scott J., Krishnamurthy V., Aghoram P., McCormick M., Sprigg N., O'Mahony P., Cooper M., Choy L., Wilkinson P., Leach S., Caine S., Burger I., Gunathilagan G., Guyler P., Emsley H., Davis M., Manawadu D., Pasco K., Mamun M., Luder R., Sajid M., Okwera J., Warburton E., Saastamoinen K., England T., Putterill J., Flossman E., Power M., Dani K., Mangion D., Suman A., Corrigan J., Lawrence E., Vahidassr D., Shakeshaft C., Brown M., Charidimou A., Cohen H., Banerjee G., Houlden H., White M., Yousry T., Flossmann E., Muir K., El-Koussy M., Gratz P., Molad J., Korczyn A., Kliper E., Maeder P., Gass A., Pachai C., Bracoub L., Douste-Blazy M.-Y., Fratacci M.D., Vicaut E., Sato S., Miwa K., Fujita K., Ide T., Ma H., Ly J., Singhal S., Chandra R., Slater L.-A., Soufan C., Moran C., Traenka C., Thilemann S., Fladt J., Gensicke H., Bonati L., Kim B.J., Han M.-K., Kang J., Ko E., Yang M.H., Jang M.S., Murphy S., Carty F., Akijian L., Thornton J., Schembri M., Jung S., van Dam-Nolen D.H.K., Douven E., Delgado-Mederos, R., Marin R., Camps-Renom P., Guisado-Alonso D., Nunez F., Medrano-Martorell S., Merino E., Iida K., Ikeda S., Nishihara M., Irie H., Demirelli D.S., Medanta J.M., Zerna C., Hernandez M.V., Armitage P., Heye A., Munoz-Maniega S., Sakka E., Thrippleton M., Dennis M., Beigneux Y., Silva M., Venketasubramanian N., Ho S.L., Cheung R.T.F., Chan K.H., Teo K.C., Hui E., Kwan J.S.K., Chang R., Tse M.Y., Hoi C.P., Chan C.Y., Chan O.L., Cheung R.H.K., Wong E.K.M., Leung K.T., Tsang S.F., Ip H.L., Ma S.H., Ma K., Fong W.C., Li S.H., Li R., Ng P.W., Wong K.K., Liu W., Wong L., Ramos L., De Schryver E., Jobsis J., van der Sande J., Brouwers P., Roos Y., Stam J., Bakker S., Verbiest H., Schoonewille W., Linn C., Hertzberger L., van Gemert M., Berntsen P., Hendrikse J., Nederkoorn P., Mess W., Koudstaal P., Leff A., Ward N., Nachev P., Perry R., Ozkan H., Mitchell J., Wilson D., Ambler G., Lee K.-J., Lim J.-S., Shiozawa M., Koga M., Li L., Lovelock C., Chabriat H., Hennerici M., Wong Y.K., Mak H.K.F., Prats-Sanchez L., Martinez-Domeno A., Inamura S., Yoshifuji K., Arsava E.M., Horstmann S., Purrucker J., Lam B.Y.K., Wong A., Kim Y.D., Song T.-J., Schrooten M., Lemmens R., Eppinger S., Gattringer T., Uysal E., Tanriverdi Z., Bornstein N.M., Assayag E.B., Hallevi H., Tanaka J., Hara H., Coutts S.B., Hert L., Polymeris A., Seiffge D.J., Lyrer P., Algra A., Kappelle J., Al-Shahi Salman R., Jager H.R., Lip G.Y.H., Mattle H.P., Panos L.D., Mas J.-L., Legrand L., Karayiannis C., Phan T., Gunkel S., Christ N., Abrigo J., Leung T., Chu W., Chappell F., Makin S., Hayden D., Williams D.J., Kooi M.E., Barbato C., Browning S., Wiegertjes K., Tuladhar A.M., Maaijwee N., Guevarra C., Yatawara C., Mendyk A.-M., Delmaire C., Kohler S., van Oostenbrugge R., Zhou Y., Xu C., Hilal S., Gyanwali B., Chen C., Lou M., Staals J., Bordet R., Kandiah N., de Leeuw F.-E., Simister R., van der Lugt A., Kelly P.J., Wardlaw J.M., Soo Y., Fluri F., Srikanth V., Calvet D., Kwa V.I.H., Engelter S.T., Peters N., Smith E.E., Yakushiji Y., Orken D.N., Fazekas F., Thijs V., Heo J.H., Mok V., Veltkamp R., Ay H., Imaizumi T., Gomez-Anson B., Lau K.K., Jouvent E., Rothwell P.M., Toyoda K., Bae H.-J., Marti-Fabregas J., Werring D.J., Harkness K., Shaw L., Sword J., Mohd Nor A., Sharma P., Kelly D., Harrington F., Randall M., Smith M., Mahawish K., Elmarim A., Esisi B., Cullen C., Nallasivam A., Price C., Barry A., Roffe C., Coyle J., Hassan A., Birns J., Cohen D., Sekaran L., Parry-Jones A., Parry A., Hargroves D., Proschel H., Datta P., Darawil K., Manoj A., Burn M., Patterson C., Giallombardo E., Smyth N., Mansoor S., Anwar I., Marsh R., Ispoglou S., Chadha D., Prabhakaran M., Meenakishundaram S., O'Connell J., Scott J., Krishnamurthy V., Aghoram P., McCormick M., Sprigg N., O'Mahony P., Cooper M., Choy L., Wilkinson P., Leach S., Caine S., Burger I., Gunathilagan G., Guyler P., Emsley H., Davis M., Manawadu D., Pasco K., Mamun M., Luder R., Sajid M., Okwera J., Warburton E., Saastamoinen K., England T., Putterill J., Flossman E., Power M., Dani K., Mangion D., Suman A., Corrigan J., Lawrence E., Vahidassr D., Shakeshaft C., Brown M., Charidimou A., Cohen H., Banerjee G., Houlden H., White M., Yousry T., Flossmann E., Muir K., El-Koussy M., Gratz P., Molad J., Korczyn A., Kliper E., Maeder P., Gass A., Pachai C., Bracoub L., Douste-Blazy M.-Y., Fratacci M.D., Vicaut E., Sato S., Miwa K., Fujita K., Ide T., Ma H., Ly J., Singhal S., Chandra R., Slater L.-A., Soufan C., Moran C., Traenka C., Thilemann S., Fladt J., Gensicke H., Bonati L., Kim B.J., Han M.-K., Kang J., Ko E., Yang M.H., Jang M.S., Murphy S., Carty F., Akijian L., Thornton J., and Schembri M.
Abstract: Background: Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke. Method(s): We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or transient ischaemic attack; included at least 50 participants; collected data on stroke events over at least 3 months follow-up; used an appropriate MRI sequence that is sensitive to magnetic susceptibility; and documented the number and anatomical distribution of cerebral microbleeds reliably using consensus criteria and validated scales. Our prespecified primary outcomes were a composite of any symptomatic intracranial haemorrhage or ischaemic stroke, symptomatic intracranial haemorrhage, and symptomatic ischaemic stroke. We registered this study with the PROSPERO international prospective register of systematic reviews, number CRD42016036602. Finding(s): Between Jan 1, 1996, and Dec 1, 2018, we identified 344 studies. After exclusions for ineligibility or declined requests for inclusion, 20 322 patients from 38 cohorts (over 35 225 patient-years of follow-up; median 1.34 years [IQR 0.19-2.44]) were included in our analyses. The adjusted hazard ratio [aHR] comparing patients with cerebral microbleeds to those without was 1.35 (95% CI 1.20-1.50) for the composite outcome of
Published: 2019

7. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author: Wilson, D. (Duncan), Ambler, G. (Gareth), Lee, K.-J. (Keon-Joo), Lim, J.-S. (Jae-Sung), Shiozawa, M. (Masayuki), Koga, M. (Masatoshi), Li, L. (Linxin), Lovelock, C. (Caroline), Chabriat, H. (Hugues), Hennerici, M.G. (Michael), Wong, Y.K. (Yuen Kwun), Mak, H.K.F. (Henry Ka Fung), Prats-Sánchez, L. (Luis), Martínez-Domeño, A. (Alejandro), Inamura, S. (Shigeru), Yoshifuji, K. (Kazuhisa), Arsava, E.M. (Ethem Murat), Horstmann, S. (Solveig), Purrucker, J. (Jan), Lam, B.Y.K. (Bonnie Yin Ka), Wong, A. (Adrian), Kim, Y.D. (Young Dae), Song, T.-J. (Tae-Jin), Schrooten, M. (Maarten), Lemmens, R. (Robin), Eppinger, S. (Sebastian), Gattringer, T. (Thomas), Uysal, E. (Ender), Tanriverdi, Z. (Zeynep), Bornstein, S.R. (Stefan), Assayag, E.B. (Einor Ben), Hallevi, H. (Hen), Tanaka, J. (Jun), Hara, H. (Hideo), Coutts, S.B. (Shelagh B), Hert, L. (Lisa), Polymeris, A. (Alexandros), Seiffge, D.J. (David J), Lyrer, P.A. (Philippe), Algra, A. (Ale), Kappelle, L.J. (Jaap), Al-Shahi Salman, R. (Rustam), Jäger, H.R. (Rolf), Lip, G.Y.H. (Gregory Y H), Mattle, H., Panos, L.D. (Leonidas D), Mas, J.L. (J.), Legrand, L. (Laurence), Karayiannis, C. (Christopher), Phan, T.G. (Thanh), Gunkel, S. (Sarah), Christ, N. (Nicolas), Abrigo, J. (Jill), Leung, T. (Thomas), Chu, W. (Winnie), Chappell, F. (Francesca), Makin, S. (Stephen), Hayden, D. (Derek), Williams, D.J. (David J), Kooi, M.E. (M. Eline), van Dam-Nolen, D.H.K. (Dianne H K), Barbato, C. (Carmen), Browning, S. (Simone), Wiegertjes, K. (Kim), Tuladhar, A.M. (Anil M.), Maaijwee, N. (Noortje), Guevarra, C. (Christine), Yatawara, C. (Chathuri), Mendyk, A.-M. (Anne-Marie), Delmaire, C. (Christine), Köhler, S. (Sebastian), Oostenbrugge, R.J. (Robert) van, Zhou, Y. (Ying), Xu, C. (Chao), Hilal, S. (Saima), Gyanwali, B. (Bibek), Chen, C. (Christopher), Lou, M. (Min), Staals, J. (Julie), Bordet, R. (Régis), Kandiah, N. (Nagaendran), Leeuw, H.F. (Frank) de, Simister, R. (Robert), Lugt, A. (Aad) van der, Kelly, P.J. (Peter J), Wardlaw, J.M. (J.), Soo, Y. (Yannie), Fluri, F. (Felix), Srikanth, V. (Velandai), Calvet, D. (David), Jung, S. (Simon), Kwa, V.I.H., Engelter, S.T. (Stefan), Peters, N. (Nils), Smith, E.E. (Eric), Yakushiji, Y. (Yusuke), Orken, D.N. (Dilek Necioglu), Fazekas, F. (Franz), Thijs, V. (Vincent), Heo, J.H. (Ji Hoe), Mok, V. (Vincent), Veltkamp, R. (Roland), Ay, H. (Hakan), Imaizumi, T. (Toshio), Gomez-Anson, B. (Beatriz), Lau, K.K. (Kui Kai), Jouvent, E. (Eric), Rothwell, P.M. (Peter), Toyoda, K. (Kazunori), Bae, H.-J. (Hee-Joon), Marti-Fabregas, J. (Joan), Werring, D.J. (David), Harkness, K. (Kirsty), Shaw, L. (Louise), Sword, J. (Jane), Mohd Nor, A. (Azlisham), Sharma, P. (Pankaj), Kelly, D. (Deborah), Harrington, F. (Frances), Randall, M. (Marc), Smith, M. (Matthew), Mahawish, K. (Karim), Elmarim, A. (Abduelbaset), Esisi, B. (Bernard), Cullen, C. (Claire), Nallasivam, A. (Arumug), Price, C. (Christopher), Barry, A. (Adrian), Roffe, C. (Christine), Coyle, J. (John), Hassan, A. (Ahamad), Birns, J. (Jonathan), Cohen, D. (David), Sekaran, L. (Lakshmanan), Parry-Jones, A. (Adrian), Parry, A. (Anthea), Hargroves, D. (David), Proschel, H. (Harald), Datta, P. (Prabel), Darawil, K. (Khaled), Manoj, A. (Aravindakshan), Burn, M. (Mathew), Patterson, C. (Chris), Giallombardo, E. (Elio), Smyth, N. (Nigel), Mansoor, S. (Syed), Anwar, I. (Ijaz), Marsh, R. (Rachel), Ispoglou, S. (Sissi), Chadha, D. (Dinesh), Prabhakaran, M. (Mathuri), Meenakishundaram, S. (Sanjeevikumar), O'Connell, J. (Janice), Scott, J. (Jon), Krishnamurthy, V. (Vinodh), Aghoram, P. (Prasanna), McCormick, M. (Michael), Sprigg, N. (Nikola), O'Mahony, P. (Paul), Cooper, M. (Martin), Choy, L. (Lillian), Wilkinson, P. (Peter), Leach, S. (Simon), Caine, S. (Sarah), Burger, I. (Ilse), Gunathilagan, G. (Gunaratam), Guyler, P. (Paul), Emsley, H. (Hedley), Davis, M. (Michelle), Manawadu, D. (Dulka), Pasco, K. (Kath), Mamun, M. (Maam), Luder, R. (Robert), Sajid, M. (Mahmud), Okwera, J. (James), Warburton, E. (Elizabeth), Saastamoinen, K. (Kari), England, T. (Timothy), Putterill, J. (Janet), Flossman, E. (Enrico), Power, M. (Michael), Dani, K. (Krishna), Mangion, D. (David), Suman, A. (Appu), Corrigan, J. (John), Lawrence, E. (Enas), Vahidassr, D. (Djamil), Shakeshaft, C. (Clare), Brown, M. (Martin), Charidimou, A. (Andreas), Cohen, H. (Hannah), Banerjee, G. (Gargi), Houlden, H. (Henry), White, M. (Mark), Yousry, T. (Tarek), Flossmann, E. (Enrico), Muir, K. (Keith), El-Koussy, M. (Marwan), Gratz, P. (Pascal), Molad, J. (Jeremy), Korczyn, A.D. (A.), Kliper, E. (Efrat), Maeder, P. (Philippe), Gass, A. (Achim), Pachai, C. (Chahin), Bracoub, L. (Luc), Douste-Blazy, M.-Y. (Marie-Yvonne), Fratacci, M.D. (Marie Dominique), Vicaut, E. (Eric), Sato, S. (Shoichiro), Miwa, K. (Kaori), Fujita, K. (Kyohei), Ide, T. (Toshihiro), Ma, H. (Henry), Ly, J. (John), Singhal, S. (Shahoo), Chandra, R. (Ronil), Slater, L.-A. (Lee-Anne), Soufan, C. (Cathy), Moran, C. (Christopher), Traenka, C. (Christopher), Thilemann, S. (Sebastian), Fladt, J. (Joachim), Gensicke, H. (Henrik), Bonati, L. (Leo), Kim, B.J. (Beom Joon), Han, M.-K. (Moon-Ku), Kang, J. (Jihoon), Ko, E. (Eunbin), Yang, M.H. (Mi Hwa), Jang, M.S. (Myung Suk), Murphy, S. (Sean), Carty, F. (Fiona), Akijian, L. (Layan), Thornton, J. (John), Schembri, M. (Mark), Douven, E. (Elles), Delgado-Mederos;, R. (Raquel), Marín, R. (Rebeca), Camps-Renom, P. (Pol), Guisado-Alonso, D. (Daniel), Nuñez, F. (Fidel), Medrano-Martorell, S. (Santiago), Merino, E. (Elisa), Iida, K. (Kotaro), Ikeda, S. (Syuhei), Nishihara, M. (Masashi), Irie, H. (Hiroyuki), Demirelli, D.S. (Derya Selcuk), Medanta, J.M. (Jayesh Modi), Zerna, C. (Charlotte), Hernández, M.V. (Maria Valdés), Armitage, P. (Paul), Heye, A. (Anna), Muñoz Maniega, S. (Susana), Sakka, E. (Eleni), Thrippleton, M. (Michael), Dennis, M.S. (M.), Beigneux, Y. (Ysoline), Silva, M. (Mauro), Venketasubramanian, N. (Narayanaswamy), Ho, S.L. (Shu Leung), Cheung, R.T.F. (Raymond Tak Fai), Chan, K.H. (Koon Ho), Teo, K.C. (Kay Cheong), Hui, E. (Edward), Kwan, J.S.K. (Joseph Shiu Kwong), Chang, R. (Richard), Tse, M.Y. (Man Yu), Hoi, C.P. (Chu Peng), Chan, C.Y. (Chung Yan), Chan, O.L. (Oi Ling), Cheung, R.H.K. (Ryan Hoi Kit), Wong, E.K.M. (Edmund Ka Ming), Leung, K.T. (Kam Tat), Tsang, S.F. (Suk Fung), Ip, H.L. (Hing Lung), Ma, S.H. (Sze Ho), Ma, K. (Karen), Fong, W.C. (Wing Chi), Li, S.H. (Siu Hung), Li, R. (Richard), Ng, P.W. (Ping Wing), Wong, K.K. (Kwok Kui), Liu, W. (Wenyan), Wong, L. (Lawrence), Ramos, L. (Lino), Schryver, E.L.L.M. (Els) de, Jöbsis, J. (Joost), van der Sande, J. (Jaap), Brouwers, P.J. (Paul), Roos, Y.B.W.E.M. (Yvo), Stam, J. (Jan), Bakker, S.L.M. (Stef), Verbiest, H. (Henk), Schoonewille, W. (Wouter), Linn, C. (Cisca), Hertzberger, L., Gemert, M. (Maarten) van, Berntsen, P. (Paul), Hendrikse, J. (Jeroen), Nederkoorn, P.J. (Paul), Mess, W.H. (Werner), Koudstaal, P.J. (Peter), Leff, A. (Alexander), Ward, N. (Nicholas), Nachev, P. (Parashkev), Perry, R. (Richard), Ozkan, H. (Hatice), Mitchell, J. (John), Wilson, D. (Duncan), Ambler, G. (Gareth), Lee, K.-J. (Keon-Joo), Lim, J.-S. (Jae-Sung), Shiozawa, M. (Masayuki), Koga, M. (Masatoshi), Li, L. (Linxin), Lovelock, C. (Caroline), Chabriat, H. (Hugues), Hennerici, M.G. (Michael), Wong, Y.K. (Yuen Kwun), Mak, H.K.F. (Henry Ka Fung), Prats-Sánchez, L. (Luis), Martínez-Domeño, A. (Alejandro), Inamura, S. (Shigeru), Yoshifuji, K. (Kazuhisa), Arsava, E.M. (Ethem Murat), Horstmann, S. (Solveig), Purrucker, J. (Jan), Lam, B.Y.K. (Bonnie Yin Ka), Wong, A. (Adrian), Kim, Y.D. (Young Dae), Song, T.-J. (Tae-Jin), Schrooten, M. (Maarten), Lemmens, R. (Robin), Eppinger, S. (Sebastian), Gattringer, T. (Thomas), Uysal, E. (Ender), Tanriverdi, Z. (Zeynep), Bornstein, S.R. (Stefan), Assayag, E.B. (Einor Ben), Hallevi, H. (Hen), Tanaka, J. (Jun), Hara, H. (Hideo), Coutts, S.B. (Shelagh B), Hert, L. (Lisa), Polymeris, A. (Alexandros), Seiffge, D.J. (David J), Lyrer, P.A. (Philippe), Algra, A. (Ale), Kappelle, L.J. (Jaap), Al-Shahi Salman, R. (Rustam), Jäger, H.R. (Rolf), Lip, G.Y.H. (Gregory Y H), Mattle, H., Panos, L.D. (Leonidas D), Mas, J.L. (J.), Legrand, L. (Laurence), Karayiannis, C. (Christopher), Phan, T.G. (Thanh), Gunkel, S. (Sarah), Christ, N. (Nicolas), Abrigo, J. (Jill), Leung, T. (Thomas), Chu, W. (Winnie), Chappell, F. (Francesca), Makin, S. (Stephen), Hayden, D. (Derek), Williams, D.J. (David J), Kooi, M.E. (M. Eline), van Dam-Nolen, D.H.K. (Dianne H K), Barbato, C. (Carmen), Browning, S. (Simone), Wiegertjes, K. (Kim), Tuladhar, A.M. (Anil M.), Maaijwee, N. (Noortje), Guevarra, C. (Christine), Yatawara, C. (Chathuri), Mendyk, A.-M. (Anne-Marie), Delmaire, C. (Christine), Köhler, S. (Sebastian), Oostenbrugge, R.J. (Robert) van, Zhou, Y. (Ying), Xu, C. (Chao), Hilal, S. (Saima), Gyanwali, B. (Bibek), Chen, C. (Christopher), Lou, M. (Min), Staals, J. (Julie), Bordet, R. (Régis), Kandiah, N. (Nagaendran), Leeuw, H.F. (Frank) de, Simister, R. (Robert), Lugt, A. (Aad) van der, Kelly, P.J. (Peter J), Wardlaw, J.M. (J.), Soo, Y. (Yannie), Fluri, F. (Felix), Srikanth, V. (Velandai), Calvet, D. (David), Jung, S. (Simon), Kwa, V.I.H., Engelter, S.T. (Stefan), Peters, N. (Nils), Smith, E.E. (Eric), Yakushiji, Y. (Yusuke), Orken, D.N. (Dilek Necioglu), Fazekas, F. (Franz), Thijs, V. (Vincent), Heo, J.H. (Ji Hoe), Mok, V. (Vincent), Veltkamp, R. (Roland), Ay, H. (Hakan), Imaizumi, T. (Toshio), Gomez-Anson, B. (Beatriz), Lau, K.K. (Kui Kai), Jouvent, E. (Eric), Rothwell, P.M. (Peter), Toyoda, K. (Kazunori), Bae, H.-J. (Hee-Joon), Marti-Fabregas, J. (Joan), Werring, D.J. (David), Harkness, K. (Kirsty), Shaw, L. (Louise), Sword, J. (Jane), Mohd Nor, A. (Azlisham), Sharma, P. (Pankaj), Kelly, D. (Deborah), Harrington, F. (Frances), Randall, M. (Marc), Smith, M. (Matthew), Mahawish, K. (Karim), Elmarim, A. (Abduelbaset), Esisi, B. (Bernard), Cullen, C. (Claire), Nallasivam, A. (Arumug), Price, C. (Christopher), Barry, A. (Adrian), Roffe, C. (Christine), Coyle, J. (John), Hassan, A. (Ahamad), Birns, J. (Jonathan), Cohen, D. (David), Sekaran, L. (Lakshmanan), Parry-Jones, A. (Adrian), Parry, A. (Anthea), Hargroves, D. (David), Proschel, H. (Harald), Datta, P. (Prabel), Darawil, K. (Khaled), Manoj, A. (Aravindakshan), Burn, M. (Mathew), Patterson, C. (Chris), Giallombardo, E. (Elio), Smyth, N. (Nigel), Mansoor, S. (Syed), Anwar, I. (Ijaz), Marsh, R. (Rachel), Ispoglou, S. (Sissi), Chadha, D. (Dinesh), Prabhakaran, M. (Mathuri), Meenakishundaram, S. (Sanjeevikumar), O'Connell, J. (Janice), Scott, J. (Jon), Krishnamurthy, V. (Vinodh), Aghoram, P. (Prasanna), McCormick, M. (Michael), Sprigg, N. (Nikola), O'Mahony, P. (Paul), Cooper, M. (Martin), Choy, L. (Lillian), Wilkinson, P. (Peter), Leach, S. (Simon), Caine, S. (Sarah), Burger, I. (Ilse), Gunathilagan, G. (Gunaratam), Guyler, P. (Paul), Emsley, H. (Hedley), Davis, M. (Michelle), Manawadu, D. (Dulka), Pasco, K. (Kath), Mamun, M. (Maam), Luder, R. (Robert), Sajid, M. (Mahmud), Okwera, J. (James), Warburton, E. (Elizabeth), Saastamoinen, K. (Kari), England, T. (Timothy), Putterill, J. (Janet), Flossman, E. (Enrico), Power, M. (Michael), Dani, K. (Krishna), Mangion, D. (David), Suman, A. (Appu), Corrigan, J. (John), Lawrence, E. (Enas), Vahidassr, D. (Djamil), Shakeshaft, C. (Clare), Brown, M. (Martin), Charidimou, A. (Andreas), Cohen, H. (Hannah), Banerjee, G. (Gargi), Houlden, H. (Henry), White, M. (Mark), Yousry, T. (Tarek), Flossmann, E. (Enrico), Muir, K. (Keith), El-Koussy, M. (Marwan), Gratz, P. (Pascal), Molad, J. (Jeremy), Korczyn, A.D. (A.), Kliper, E. (Efrat), Maeder, P. (Philippe), Gass, A. (Achim), Pachai, C. (Chahin), Bracoub, L. (Luc), Douste-Blazy, M.-Y. (Marie-Yvonne), Fratacci, M.D. (Marie Dominique), Vicaut, E. (Eric), Sato, S. (Shoichiro), Miwa, K. (Kaori), Fujita, K. (Kyohei), Ide, T. (Toshihiro), Ma, H. (Henry), Ly, J. (John), Singhal, S. (Shahoo), Chandra, R. (Ronil), Slater, L.-A. (Lee-Anne), Soufan, C. (Cathy), Moran, C. (Christopher), Traenka, C. (Christopher), Thilemann, S. (Sebastian), Fladt, J. (Joachim), Gensicke, H. (Henrik), Bonati, L. (Leo), Kim, B.J. (Beom Joon), Han, M.-K. (Moon-Ku), Kang, J. (Jihoon), Ko, E. (Eunbin), Yang, M.H. (Mi Hwa), Jang, M.S. (Myung Suk), Murphy, S. (Sean), Carty, F. (Fiona), Akijian, L. (Layan), Thornton, J. (John), Schembri, M. (Mark), Douven, E. (Elles), Delgado-Mederos;, R. (Raquel), Marín, R. (Rebeca), Camps-Renom, P. (Pol), Guisado-Alonso, D. (Daniel), Nuñez, F. (Fidel), Medrano-Martorell, S. (Santiago), Merino, E. (Elisa), Iida, K. (Kotaro), Ikeda, S. (Syuhei), Nishihara, M. (Masashi), Irie, H. (Hiroyuki), Demirelli, D.S. (Derya Selcuk), Medanta, J.M. (Jayesh Modi), Zerna, C. (Charlotte), Hernández, M.V. (Maria Valdés), Armitage, P. (Paul), Heye, A. (Anna), Muñoz Maniega, S. (Susana), Sakka, E. (Eleni), Thrippleton, M. (Michael), Dennis, M.S. (M.), Beigneux, Y. (Ysoline), Silva, M. (Mauro), Venketasubramanian, N. (Narayanaswamy), Ho, S.L. (Shu Leung), Cheung, R.T.F. (Raymond Tak Fai), Chan, K.H. (Koon Ho), Teo, K.C. (Kay Cheong), Hui, E. (Edward), Kwan, J.S.K. (Joseph Shiu Kwong), Chang, R. (Richard), Tse, M.Y. (Man Yu), Hoi, C.P. (Chu Peng), Chan, C.Y. (Chung Yan), Chan, O.L. (Oi Ling), Cheung, R.H.K. (Ryan Hoi Kit), Wong, E.K.M. (Edmund Ka Ming), Leung, K.T. (Kam Tat), Tsang, S.F. (Suk Fung), Ip, H.L. (Hing Lung), Ma, S.H. (Sze Ho), Ma, K. (Karen), Fong, W.C. (Wing Chi), Li, S.H. (Siu Hung), Li, R. (Richard), Ng, P.W. (Ping Wing), Wong, K.K. (Kwok Kui), Liu, W. (Wenyan), Wong, L. (Lawrence), Ramos, L. (Lino), Schryver, E.L.L.M. (Els) de, Jöbsis, J. (Joost), van der Sande, J. (Jaap), Brouwers, P.J. (Paul), Roos, Y.B.W.E.M. (Yvo), Stam, J. (Jan), Bakker, S.L.M. (Stef), Verbiest, H. (Henk), Schoonewille, W. (Wouter), Linn, C. (Cisca), Hertzberger, L., Gemert, M. (Maarten) van, Berntsen, P. (Paul), Hendrikse, J. (Jeroen), Nederkoorn, P.J. (Paul), Mess, W.H. (Werner), Koudstaal, P.J. (Peter), Leff, A. (Alexander), Ward, N. (Nicholas), Nachev, P. (Parashkev), Perry, R. (Richard), Ozkan, H. (Hatice), and Mitchell, J. (John)
Abstract: Background: Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke. Methods: We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or
Published: 2019
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8. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

Author: Wilson, D, Ambler, G, Lee, K-J, Lim, J-S, Shiozawa, M, Koga, M, Li, L, Lovelock, C, Chabriat, H, Hennerici, M, Wong, YK, Mak, HKF, Prats-Sanchez, L, Martinez-Domeno, A, Inamura, S, Yoshifuji, K, Arsava, EM, Horstmann, S, Purrucker, J, Lam, BYK, Wong, A, Kim, YD, Song, T-J, Schrooten, M, Lemmens, R, Eppinger, S, Gattringer, T, Uysal, E, Tanriverdi, Z, Bornstein, NM, Ben Assayag, E, Hallevi, H, Tanaka, J, Hara, H, Coutts, SB, Hert, L, Polymeris, A, Seiffge, DJ, Lyrer, P, Algra, A, Kappelle, J, Salman, RA-S, Jager, HR, Lip, GYH, Mattle, HP, Panos, LD, Mas, J-L, Legrand, L, Karayiannis, C, Phan, T, Gunkel, S, Christ, N, Abrigo, J, Leung, T, Chu, W, Chappell, F, Makin, S, Hayden, D, Williams, DJ, Kooi, ME, van Dam-Nolen, DHK, Barbato, C, Browning, S, Wiegertjes, K, Tuladhar, AM, Maaijwee, N, Guevarra, C, Yatawara, C, Mendyk, A-M, Delmaire, C, Kohler, S, van Oostenbrugge, R, Zhou, Y, Xu, C, Hilal, S, Gyanwali, B, Chen, C, Lou, M, Staals, J, Bordet, R, Kandiah, N, de Leeuw, F-E, Simister, R, van der Lugt, A, Kelly, PJ, Wardlaw, JM, Soo, Y, Fluri, F, Srikanth, V, Calvet, D, Jung, S, Kwa, VIH, Engelter, ST, Peters, N, Smith, EE, Yakushiji, Y, Orken, DN, Fazekas, F, Thijs, V, Heo, JH, Mok, V, Veltkamp, R, Ay, H, Imaizumi, T, Gomez-Anson, B, Lau, KK, Jouvent, E, Rothwell, PM, Toyoda, K, Bae, H-J, Marti-Fabregas, J, Werring, DJ, Wilson, D, Ambler, G, Lee, K-J, Lim, J-S, Shiozawa, M, Koga, M, Li, L, Lovelock, C, Chabriat, H, Hennerici, M, Wong, YK, Mak, HKF, Prats-Sanchez, L, Martinez-Domeno, A, Inamura, S, Yoshifuji, K, Arsava, EM, Horstmann, S, Purrucker, J, Lam, BYK, Wong, A, Kim, YD, Song, T-J, Schrooten, M, Lemmens, R, Eppinger, S, Gattringer, T, Uysal, E, Tanriverdi, Z, Bornstein, NM, Ben Assayag, E, Hallevi, H, Tanaka, J, Hara, H, Coutts, SB, Hert, L, Polymeris, A, Seiffge, DJ, Lyrer, P, Algra, A, Kappelle, J, Salman, RA-S, Jager, HR, Lip, GYH, Mattle, HP, Panos, LD, Mas, J-L, Legrand, L, Karayiannis, C, Phan, T, Gunkel, S, Christ, N, Abrigo, J, Leung, T, Chu, W, Chappell, F, Makin, S, Hayden, D, Williams, DJ, Kooi, ME, van Dam-Nolen, DHK, Barbato, C, Browning, S, Wiegertjes, K, Tuladhar, AM, Maaijwee, N, Guevarra, C, Yatawara, C, Mendyk, A-M, Delmaire, C, Kohler, S, van Oostenbrugge, R, Zhou, Y, Xu, C, Hilal, S, Gyanwali, B, Chen, C, Lou, M, Staals, J, Bordet, R, Kandiah, N, de Leeuw, F-E, Simister, R, van der Lugt, A, Kelly, PJ, Wardlaw, JM, Soo, Y, Fluri, F, Srikanth, V, Calvet, D, Jung, S, Kwa, VIH, Engelter, ST, Peters, N, Smith, EE, Yakushiji, Y, Orken, DN, Fazekas, F, Thijs, V, Heo, JH, Mok, V, Veltkamp, R, Ay, H, Imaizumi, T, Gomez-Anson, B, Lau, KK, Jouvent, E, Rothwell, PM, Toyoda, K, Bae, H-J, Marti-Fabregas, J, and Werring, DJ
Abstract: BACKGROUND: Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke. METHODS: We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or transient ischaemic attack; included at least 50 participants; collected data on stroke events over at least 3 months follow-up; used an appropriate MRI sequence that is sensitive to magnetic susceptibility; and documented the number and anatomical distribution of cerebral microbleeds reliably using consensus criteria and validated scales. Our prespecified primary outcomes were a composite of any symptomatic intracranial haemorrhage or ischaemic stroke, symptomatic intracranial haemorrhage, and symptomatic ischaemic stroke. We registered this study with the PROSPERO international prospective register of systematic reviews, number CRD42016036602. FINDINGS: Between Jan 1, 1996, and Dec 1, 2018, we identified 344 studies. After exclusions for ineligibility or declined requests for inclusion, 20 322 patients from 38 cohorts (over 35 225 patient-years of follow-up; median 1·34 years [IQR 0·19-2·44]) were included in our analyses. The adjusted hazard ratio [aHR] comparing patients with cerebral microbleeds to those without was 1·35 (95% CI 1·20-1·50) for the composite outcome of intr
Published: 2019

9. The effect of oxytocin nasal spray on social interaction deficits observed in young children with autism: a randomized clinical crossover trial

Author: Yatawara, C J, primary, Einfeld, S L, additional, Hickie, I B, additional, Davenport, T A, additional, and Guastella, A J, additional
Published: 2015
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10. The effect of oxytocin nasal spray on social interaction deficits observed in young children with autism: a randomized clinical crossover trial

Author: Yatawara, C J, Einfeld, S L, Hickie, I B, Davenport, T A, and Guastella, A J
Abstract: Interventions for autism are limited. The synthetic hormone oxytocin may provide a potential treatment to improve core social and behavioral difficulties in autism, but its efficacy has yet to be evaluated in young children who potentially may benefit to a greater extent. We investigated the efficacy, tolerability and safety of oxytocin treatment in young children with autism using a double-blind, randomized, placebo-controlled, crossover, clinical trial. Thirty-one children with autism received 12 International Units (IU) of oxytocin and placebo nasal spray morning and night (24 IU per day) for 5 weeks, with a 4-week washout period between each treatment. Compared with placebo, oxytocin led to significant improvements on the primary outcome of caregiver-rated social responsiveness. Overall, nasal spray was well tolerated, and the most common reported adverse events were thirst, urination and constipation. This study is the first clinical trial to support the potential of oxytocin as an early intervention for young children with autism to help improve social interaction deficits.
Published: 2016
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11. ChemInform Abstract: Roritoxins, New Macrocyclic Trichothecenes from Myrothecium roridum.

Author: JARVIS, B. B., primary and YATAWARA, C. S., additional
Published: 1987
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12. Roritoxins. New macrocyclic trichothecenes from Myrothecium roridum

Author: Jarvis, Bruce B., primary and Yatawara, C. S., additional
Published: 1986
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13. Production of Verrucarol

Author: Jarvis, Bruce B., primary, Yatawara, C. S., additional, Greene, Sharon L., additional, and Vrudhula, Vivekanada M., additional
Published: 1984
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14. Trichothecenes produced by Stachybotrys atra from Eastern Europe

Author: Jarvis, B B, primary, Lee, Y W, additional, Cömezoglu, S N, additional, and Yatawara, C S, additional
Published: 1986
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15. 7 alpha-hydroxytrichodermol, a new trichothecene from Myrothecium roridum

Author: Jarvis, B B, primary, Lee, Y W, additional, Yatawara, C S, additional, Mazzocchi, D B, additional, Flippen-Anderson, J L, additional, Gilardi, R, additional, and George, C, additional
Published: 1985
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16. Airborne outbreak of trichothecene toxicosis

Author: Yatawara, C. S., Croft, W. A., and Jarvis, B. B.
Subjects: FUNGI, PUBLIC health
Published: 1986

17. Long-Term Cognitive Decline After Stroke: An Individual Participant Data Meta-Analysis.

Author: Lo JW, Crawford JD, Desmond DW, Bae HJ, Lim JS, Godefroy O, Roussel M, Kang Y, Jahng S, Köhler S, Staals J, Verhey F, Chen C, Xu X, Chong EJ, Kandiah N, Yatawara C, Bordet R, Dondaine T, Mendyk AM, Brodaty H, Traykov L, Mehrabian S, Petrova N, Kim KW, Bae JB, Han JW, Lipnicki DM, Lam B, and Sachdev PS
Subjects: Aged, Cognition, Executive Function, Humans, Neuropsychological Tests, Cognitive Dysfunction epidemiology, Cognitive Dysfunction etiology, Stroke
Abstract: Background: Poststroke cognitive impairment is common, but the trajectory and magnitude of cognitive decline after stroke is unclear. We examined the course and determinants of cognitive change after stroke using individual participant data from the Stroke and Cognition Consortium., Methods: Nine longitudinal hospital-based cohorts from 7 countries were included. Neuropsychological test scores and normative data were used to calculate standardized scores for global cognition and 5 cognitive domains. One-step individual participant data meta-analysis was used to examine the rate of change in cognitive function and risk factors for cognitive decline after stroke. Stroke-free controls were included to examine rate differences. Based on the literature and our own data that showed short-term improvement in cognitive function after stroke, key analyses were restricted to the period beginning 1-year poststroke to focus on its long-term effects., Results: A total of 1488 patients (mean age, 66.3 years; SD, 11.1; 98% ischemic stroke) were followed for a median of 2.68 years (25th-75th percentile: 1.21-4.14 years). After an initial period of improvement through up to 1-year poststroke, decline was seen in global cognition and all domains except executive function after adjusting for age, sex, education, vascular risk factors, and stroke characteristics (-0.053 SD/year [95% CI, -0.073 to -0.033]; P <0.001 for global cognition). Recurrent stroke and older age were associated with faster decline. Decline was significantly faster in patients with stroke compared with controls (difference=-0.078 SD/year [95% CI, -0.11 to -0.045]; P <0.001 for global cognition in a subgroup analysis)., Conclusions: Patients with stroke experience cognitive decline that is faster than that of stroke-free controls from 1 to 3 years after onset. An increased rate of decline is associated with older age and recurrent stroke.
Published: 2022
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18. APOE4 and Confluent White Matter Hyperintensities Have a Synergistic Effect on Episodic Memory Impairment in Prodromal Dementia.

Author: Kumar D, Yatawara C, Wang B, Wong B, Tan YJ, Zailan FZ, Ng KP, and Kandiah N
Subjects: Brain pathology, Dementia diagnostic imaging, Dementia genetics, Dementia pathology, Humans, Magnetic Resonance Imaging, Neuropsychological Tests, Apolipoprotein E4 genetics, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction genetics, Cognitive Dysfunction pathology, Leukoaraiosis diagnostic imaging, Leukoaraiosis genetics, Leukoaraiosis pathology, Memory Disorders diagnostic imaging, Memory Disorders genetics, Memory Disorders pathology, Memory, Episodic, White Matter diagnostic imaging, White Matter pathology
Abstract: Background: White matter hyperintensities (WMH) are a known risk factor for cognitive decline. While the ɛ4 allele of apolipoprotein E gene (APOE4) is another risk factor for cognitive decline, it remains unclear how APOE4 affects the relationship between WMH and cognitive decline, specifically in the prodromal stage of dementia., Objective: To determine how APOE4 moderates the relationship between WMH and cognition in prodromal dementia., Methods: Two-hundred-sixteen participants with prodromal dementia underwent magnetic resonance imaging (MRI), neuropsychological testing (global and domain wise), cardiovascular risk factor assessments, and APOE genotyping. Visual ratings for WMH as well as total and lobar WMH volumes were quantified. Moderation analysis was performed to determine the influence of APOE4 on the relationship between WMH and performance on global and domain-specific cognitive measures. The role of confluent and non-confluent WMH on cognition was additionally studied using logistic regression., Results: APOE4 carriers (n = 49) had poorer memory and higher global WMH (10.01 mL versus 6.23 mL, p = 0.04), temporal WMH (1.17 mL versus 0.58 mL, p = 0.01), and occipital WMH (0.38mL versus 0.22 mL, p = 0.02) compared to APOE4 non-carriers (n = 167). Moderation analysis revealed that APOE4 positivity strengthened the relationship between higher global as well as lobar WMH burden and poorer episodic memory. Furthermore, APOE4 carriers with confluent WMH were 4.81 times more likely to have impaired episodic memory compared to non-confluent WMH and non-APOE carriers., Conclusion: The impact of WMH on memory may be strongest among APOE4 carriers. Clinicians targeting WMH would need to consider the APOE4 allele and WMH severity status to strategize cognitive interventions.
Published: 2022
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19. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

Author: Best JG, Ambler G, Wilson D, Lee KJ, Lim JS, Shiozawa M, Koga M, Li L, Lovelock C, Chabriat H, Hennerici M, Wong YK, Mak HKF, Prats-Sanchez L, Martínez-Domeño A, Inamura S, Yoshifuji K, Arsava EM, Horstmann S, Purrucker J, Lam BYK, Wong A, Kim YD, Song TJ, Lemmens R, Eppinger S, Gattringer T, Uysal E, Tanriverdi Z, Bornstein NM, Ben Assayag E, Hallevi H, Molad J, Nishihara M, Tanaka J, Coutts SB, Polymeris A, Wagner B, Seiffge DJ, Lyrer P, Algra A, Kappelle LJ, Al-Shahi Salman R, Jäger HR, Lip GYH, Fischer U, El-Koussy M, Mas JL, Legrand L, Karayiannis C, Phan T, Gunkel S, Christ N, Abrigo J, Leung T, Chu W, Chappell F, Makin S, Hayden D, Williams DJ, Mess WH, Nederkoorn PJ, Barbato C, Browning S, Wiegertjes K, Tuladhar AM, Maaijwee N, Guevarra AC, Yatawara C, Mendyk AM, Delmaire C, Köhler S, van Oostenbrugge R, Zhou Y, Xu C, Hilal S, Gyanwali B, Chen C, Lou M, Staals J, Bordet R, Kandiah N, de Leeuw FE, Simister R, Hendrikse J, Kelly PJ, Wardlaw J, Soo Y, Fluri F, Srikanth V, Calvet D, Jung S, Kwa VIH, Engelter ST, Peters N, Smith EE, Hara H, Yakushiji Y, Orken DN, Fazekas F, Thijs V, Heo JH, Mok V, Veltkamp R, Ay H, Imaizumi T, Gomez-Anson B, Lau KK, Jouvent E, Rothwell PM, Toyoda K, Bae HJ, Marti-Fabregas J, and Werring DJ
Subjects: Adult, Aged, Female, Humans, Ischemic Attack, Transient complications, Ischemic Attack, Transient diagnostic imaging, Ischemic Attack, Transient drug therapy, Ischemic Stroke diagnostic imaging, Magnetic Resonance Imaging, Male, Middle Aged, Recurrence, Risk, Fibrinolytic Agents therapeutic use, Intracranial Hemorrhages etiology, Ischemic Stroke complications, Ischemic Stroke drug therapy
Abstract: Background: Balancing the risks of recurrent ischaemic stroke and intracranial haemorrhage is important for patients treated with antithrombotic therapy after ischaemic stroke or transient ischaemic attack. However, existing predictive models offer insufficient performance, particularly for assessing the risk of intracranial haemorrhage. We aimed to develop new risk scores incorporating clinical variables and cerebral microbleeds, an MRI biomarker of intracranial haemorrhage and ischaemic stroke risk., Methods: We did a pooled analysis of individual-patient data from the Microbleeds International Collaborative Network (MICON), which includes 38 hospital-based prospective cohort studies from 18 countries. All studies recruited participants with previous ischaemic stroke or transient ischaemic attack, acquired baseline MRI allowing quantification of cerebral microbleeds, and followed-up participants for ischaemic stroke and intracranial haemorrhage. Participants not taking antithrombotic drugs were excluded. We developed Cox regression models to predict the 5-year risks of intracranial haemorrhage and ischaemic stroke, selecting candidate predictors on biological relevance and simplifying models using backward elimination. We derived integer risk scores for clinical use. We assessed model performance in internal validation, adjusted for optimism using bootstrapping. The study is registered on PROSPERO, CRD42016036602., Findings: The included studies recruited participants between Aug 28, 2001, and Feb 4, 2018. 15 766 participants had follow-up for intracranial haemorrhage, and 15 784 for ischaemic stroke. Over a median follow-up of 2 years, 184 intracranial haemorrhages and 1048 ischaemic strokes were reported. The risk models we developed included cerebral microbleed burden and simple clinical variables. Optimism-adjusted c indices were 0·73 (95% CI 0·69-0·77) with a calibration slope of 0·94 (0·81-1·06) for the intracranial haemorrhage model and 0·63 (0·62-0·65) with a calibration slope of 0·97 (0·87-1·07) for the ischaemic stroke model. There was good agreement between predicted and observed risk for both models., Interpretation: The MICON risk scores, incorporating clinical variables and cerebral microbleeds, offer predictive value for the long-term risks of intracranial haemorrhage and ischaemic stroke in patients prescribed antithrombotic therapy for secondary stroke prevention; external validation is warranted., Funding: British Heart Foundation and Stroke Association., (Copyright © 2021 Elsevier Ltd. All rights reserved.)
Published: 2021
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20. Cerebral Small Vessel Disease Influences Hippocampal Subfield Atrophy in Mild Cognitive Impairment.

Author: Wong FCC, Yatawara C, Low A, Foo H, Wong BYX, Lim L, Wang B, Kumar D, Ng KP, and Kandiah N
Subjects: Aged, Atrophy pathology, Hippocampus diagnostic imaging, Hippocampus pathology, Humans, Magnetic Resonance Imaging, Cerebral Small Vessel Diseases complications, Cerebral Small Vessel Diseases diagnostic imaging, Cerebral Small Vessel Diseases pathology, Cognitive Dysfunction diagnostic imaging, Cognitive Dysfunction etiology, Cognitive Dysfunction pathology
Abstract: To investigate patterns of hippocampal subfield atrophy among patients with amnestic mild cognitive impairment, stratified by severity of small vessel disease (SVD) and corresponding associations with cognitive domains. One hundred seventy-six MCI subjects (mean age = 65.56 years, SD = 8.77) underwent neuropsychological assessments and magnetic resonance imaging. SVD was rated 0 (no SVD), 1 (mild SVD) and 2 (moderate to severe SVD) based on load of white matter hyperintensities (WMH) and lacunes. Demographics, cerebrovascular risk factors, grey and white matter volumes and hippocampal subfield atrophies were compared across SVD severity through ANCOVA analyses. Subjects were categorized into positive or negative SVD-hippocampal subfield atrophy (HSA) and influence of positive SVD-HSA on episodic memory and frontal executive function was evaluated through ANCOVA analyses. All analyses corrected for covariates and bias-corrected bootstrap estimation with 1000 resamples was applied with Bonferroni correction. Hippocampal subfield atrophy worsened with increasing SVD severity. Positive SVD-HSA was characterised by significant atrophy in the subiculum, CA1, CA4, molecular layer and dentate gyrus. Greater atrophy was seen with moderate to severe SVD compared to mild SVD in these subfields. Atrophy in the five subfields of SVD-HSA was significantly associated with poor episodic memory and frontal executive function. Presence and burden of SVD influences the pattern and severity of hippocampal subfield atrophy. SVD-related hippocampal subfield atrophy is associated with poorer episodic memory and frontal executive function in mild cognitive impairment.
Published: 2021
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21. Influence of White Matter Hyperintensities on Baseline and Longitudinal Amyloid-β in Cognitively Normal Individuals.

Author: Wong FCC, Saffari SE, Yatawara C, Ng KP, and Kandiah N
Subjects: Aged, Aging physiology, Amyloid beta-Peptides cerebrospinal fluid, Brain diagnostic imaging, Female, Humans, Magnetic Resonance Imaging, Male, Memory physiology, Time Factors, Amyloid beta-Peptides metabolism, Cerebral Small Vessel Diseases diagnostic imaging, Cognition physiology, Healthy Volunteers, Peptide Fragments cerebrospinal fluid, White Matter diagnostic imaging
Abstract: Background: The associations between small vessel disease (SVD) and cerebrospinal amyloid-β1-42 (Aβ1-42) pathology have not been well-elucidated., Objective: Baseline (BL) white matter hyperintensities (WMH) were examined for associations with month-24 (M24) and longitudinal Aβ1-42 change in cognitively normal (CN) subjects. The interaction of WMH and Aβ1-42 on memory and executive function were also examined., Methods: This study included 72 subjects from the Alzheimer's Disease Neuroimaging Initiative. Multivariable linear regression models evaluated associations between baseline WMH/intracranial volume ratio, M24 and change in Aβ1-42 over two years. Linear mixed effects models evaluated interactions between BL WMH/ICV and Aβ1-42 on memory and executive function., Results: Mean age of the subjects (Nmales = 36) = 73.80 years, SD = 6.73; mean education years = 17.1, SD = 2.4. BL WMH was significantly associated with M24 Aβ1-42 (p = 0.008) and two-year change in Aβ1-42 (p = 0.006). Interaction between higher WMH and lower Aβ1-42 at baseline was significantly associated with worse memory at baseline and M24 (p = 0.003)., Conclusion: BL WMH was associated with M24 and longitudinal Aβ1-42 change in CN. The interaction between higher WMH and lower Aβ1-42 was associated with poorer memory. Since SVD is associated with longitudinal Aβ1-42 pathology, and the interaction of both factors is linked to poorer cognitive outcomes, the mitigation of SVD may be correlated with reduced amyloid pathology and milder cognitive deterioration in Alzheimer's disease.
Published: 2021
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22. The Association Between Diabetes Mellitus and Mild Behavioral Impairment Among Mild Cognitive Impairment: Findings from Singapore.

Author: Soo SA, Ng KP, Wong F, Saffari SE, Yatawara C, Ismail Z, and Kandiah N
Subjects: Aged, Cognitive Dysfunction psychology, Diabetes Mellitus drug therapy, Female, Heart Disease Risk Factors, Humans, Hyperlipidemias drug therapy, Hyperlipidemias epidemiology, Hypertension drug therapy, Hypertension epidemiology, Male, Mental Disorders psychology, Middle Aged, Motivation, Perceptual Disorders psychology, Singapore, Cognitive Dysfunction epidemiology, Diabetes Mellitus epidemiology, Emotional Regulation, Impulsive Behavior, Mental Disorders epidemiology, Perceptual Disorders epidemiology, Thinking
Abstract: Background: Mild behavioral impairment (MBI) describes persistent behavioral changes in later life as an at-risk state for dementia. While cardiovascular risk factors (CVRFs) are linked to dementia, it is uncertain how CVRFs are associated with MBI., Objective: To determine the prevalence of MBI and its association with CVRFs among cognitively normal (CN) and mild cognitive impairment (MCI) individuals in Singapore., Methods: 172 individuals (79 CN and 93 MCI) completed the MBI-checklist (MBI-C). The prevalence of MBI and MBI-C sub-domain characteristics among CN and MCI were examined. Regression models evaluated the relationships between MBI-C sub-domain scores with CVRFs., Results: The prevalence of MBI and mean MBI-C total score were significantly higher among MCI than CN (34.4%versus 20.3%, p = 0.022 and 7.01 versus 4.12, p = 0.04). The highest and lowest-rated sub-domains among CN and MCI were impulse dyscontrol and abnormal thoughts and perception respectively. Within the MCI cohort, a higher proportion of individuals with diabetes mellitus (DM) had MBI compared to individuals without DM (28.1%versus 10.4%, p = 0.025). The interaction of DM and MCI cohort resulted in significantly higher mean MBI-C total, decreased motivation, emotional dysregulation, impulse dyscontrol, and abnormal thoughts and perception sub-domain scores., Conclusion: The prevalence of MBI is higher among a Singapore cohort compared to Caucasian cohorts. The associations of DM with both the presence and severity of MBI among MCI suggest that DM may be a risk factor for MBI. The optimization of DM may be a potential therapeutic approach to improve clinical outcomes among MCI with MBI.
Published: 2021
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23. Baseline Neurodegeneration Influences the Longitudinal Effects of Tau on Cognition.

Author: Ng KP, Cheng GH, Yatawara C, Rosa-Neto P, Gauthier S, and Kandiah N
Subjects: Aged, Alzheimer Disease diagnosis, Amyloid beta-Peptides cerebrospinal fluid, Female, Humans, Male, Neuropsychological Tests, Biomarkers cerebrospinal fluid, Cognitive Dysfunction cerebrospinal fluid, Executive Function physiology, Memory physiology, tau Proteins cerebrospinal fluid
Abstract: Background: Cerebrospinal fluid t-tau (CSF t-tau) is a measure of neurodegeneration in Alzheimer's disease (AD) and has been increasingly demonstrated to be a non-specific biomarker within the AD continuum., Objective: We sought to test whether t-tau influences the longitudinal effects of amyloid-β (Aβ) and phospho-tau (p-tau) on memory and executive function (EF) in mild cognitive impairment (MCI)., Methods: 319 MCI individuals from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with baseline and 2-year CSF Aβ, p-tau, t-tau, and neuropsychological assessments were studied. Mediation and moderation analyses evaluated the role of t-tau in the effects of Aβ and p-tau on memory and EF over 2 years., Results: We found that high baseline p-tau but not Aβ was associated with higher t-tau and lower memory scores at 2 years follow-up. The association between p-tau and memory impairment was partially mediated by t-tau, whereby higher p-tau was indirectly associated with lower memory via higher t-tau. t-tau also moderated the association between p-tau and memory. When t-tau level was relatively lower, higher p-tau was associated with lower memory scores at 2 years. When t-tau level was higher, the memory scores were low regardless of the p-tau level., Conclusion: Tau-induced neurodegeneration is one key pathway by which AD pathology (p-tau) affects memory impairment. Furthermore, in individuals with lower levels of tau-induced neurodegeneration, higher levels of p-tau were required for memory impairment. Our findings suggest that t-tau plays a significant role in how early AD pathology affects cognitive outcomes.
Published: 2021
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24. Interactions Between Acute Infarcts and Cerebrovascular Pathology Predict Poststroke Dementia.

Author: Yatawara C, Guevarra A, Ng KP, Chander R, and Kandiah N
Subjects: Aged, Case-Control Studies, Cerebrovascular Disorders pathology, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests statistics & numerical data, Stroke physiopathology, Brain pathology, Cognition physiology, Dementia diagnosis, Dementia epidemiology, Infarction complications, Stroke complications
Abstract: Background: Chronic cerebrovascular pathology accelerates the incidence of poststroke dementia (PSD). Whether the risk of PSD varies according to different types of chronic cerebrovascular pathology remains unclear., Objectives: We investigated whether PSD is associated with a unique pattern of interactions between chronic cerebrovascular pathologies and acute stroke lesions., Materials and Method: In this case-control study of acute mild stroke patients (n=185), cases included patients who developed PSD at a 6-month poststroke follow-up, and controls included patients who remained nondemented at 6 months, matched on prestroke cognitive status. Magnetic resonance imaging was performed at initial stroke presentation; neuropsychological assessments were performed 6 months after the stroke., Results: White matter hyperintensities (WMH), chronic lacunes, microbleeds, and acute infarcts were not associated with PSD after controlling for demographics, cardiovascular risk, and global cortical atrophy. The risk of PSD was largest for patients with acute large subcortical infarcts (>15 mm) and concomitant periventricular WMH compared with patients with large subcortical infarcts and punctate/absent periventricular WMH [odds ratio (OR)=5.85, 95% confidence interval (CI)=1.85-40.04]. A moderate risk of PSD was observed for patients with acute multiple small infarcts (3 to 15 mm) and concomitant lacunes (OR=2.48, 95% CI=0.94-6.51) or concomitant lobar microbleeds (OR=2.20, 95% CI=0.89-5.41), compared with patients with acute multiple small infarcts and absent lacunes or microbleeds. Single small infarcts did not interact with cerebrovascular pathology to affect PSD., Conclusions: The risk of PSD varies depending on the presence of chronic cerebrovascular pathologies and type of acute infarcts. Clinical implications support a precision medicine approach for stratifying those at highest risk of PSD.
Published: 2020
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25. Association of Prediabetes and Type 2 Diabetes With Cognitive Function After Stroke: A STROKOG Collaboration Study.

Author: Lo JW, Crawford JD, Samaras K, Desmond DW, Köhler S, Staals J, Verhey FRJ, Bae HJ, Lee KJ, Kim BJ, Bordet R, Cordonnier C, Dondaine T, Mendyk AM, Lee BC, Yu KH, Lim JS, Kandiah N, Chander RJ, Yatawara C, Lipnicki DM, and Sachdev PS
Subjects: Aged, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Blood Glucose metabolism, Cognition, Diabetes Complications blood, Diabetes Complications physiopathology, Diabetes Complications therapy, Diabetes Mellitus, Type 2 blood, Diabetes Mellitus, Type 2 drug therapy, Diabetes Mellitus, Type 2 physiopathology, Prediabetic State blood, Prediabetic State drug therapy, Prediabetic State physiopathology, Stroke blood, Stroke etiology, Stroke physiopathology, Stroke therapy
Abstract: Background and Purpose- Type 2 diabetes mellitus (T2D) is associated with cognitive impairment and an increased risk of dementia, but the association between prediabetes and cognitive impairment is less clear, particularly in a setting of major cerebrovascular events. This article examines the impact of impaired fasting glucose and T2D on cognitive performance in a stroke population. Methods- Seven international observational studies from the STROKOG (Stroke and Cognition) consortium (n=1601; mean age, 66.0 years; 70% Asian, 26% white, and 2.6% African American) were included. Fasting glucose level (FGL) during hospitalization was used to define 3 groups, T2D (FGL ≥7.0 mmol/L), impaired fasting glucose (FGL 6.1-6.9 mmol/L), and normal (FGL <6.1 mmol/L), and a history of diabetes mellitus and the use of a diabetes mellitus medication were also used to support a diagnosis of T2D. Domain and global cognition Z scores were derived from standardized neuropsychological test scores. The cross-sectional association between glucose status and cognitive performance at 3 to 6 months poststroke was examined using linear mixed models, adjusting for age, sex, education, stroke type, ethnicity, and vascular risk factors. Results- Patients with T2D had significantly poorer performance in global cognition (SD, -0.59 [95% CI, -0.82 to -0.36]; P <0.001) and in all domains compared with patients with normal FGL. There was no significant difference between impaired fasting glucose patients and those with normal FGL in global cognition (SD, -0.10 [95% CI, -0.45 to 0.24]; P =0.55) or in any cognitive domain. Conclusions- Diabetes mellitus, but not prediabetes, is associated with poorer cognitive performance in patients 3 to 6 months after stroke.
Published: 2020
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26. The role of cerebral microbleeds in the incidence of post-stroke dementia.

Author: Yatawara C, Guevarra AC, Ng KP, Chander R, Lam BYK, Wong A, Mok V, and Kandiah N
Subjects: Cerebral Hemorrhage complications, Cerebral Hemorrhage diagnostic imaging, Cerebral Hemorrhage epidemiology, Humans, Incidence, Magnetic Resonance Imaging, Cerebral Amyloid Angiopathy, Dementia epidemiology, Dementia etiology, Stroke complications, Stroke epidemiology
Abstract: Microbleeds are a marker of cerebrovascular disease however its role in incident post-stroke dementia (PSD) remains unclear. We investigated whether microbleeds are associated with incident PSD, domain-specific cognitive impairment and cognitive decline over a 2-year follow-up; and whether microbleeds interact with acute stroke-related infarcts to synergistically affect cognitive outcomes. In a cohort of patients with first-episode mild ischemic stroke and no pre-stroke dementia, we found patients with 3 or more mixed microbleeds (presence of both lobar and deep) were 4 times more at risk of developing PSD compared to patients with no microbleeds. Patients with strictly lobar microbleeds were 10 times more at risk of developing memory impairment while patients with possible CAA-related microbleeds were 8 times more at risk of developing memory impairment compared to patients with no microbleeds. Microbleeds did not predict cognitive decline at the 2-year follow-up. Acute stroke infarcts were not related to any cognitive outcomes. Microbleeds did not interact with stroke infracts to synergistically affect cognitive outcomes. Our findings suggest that the combined effect of possible CAA and hypertension-related microbleeds play a large and direct role in incident PSD. Management of vasculopathy and amyloid deposition may positively impact cognitive outcomes after stroke., Competing Interests: Declaration of Competing Interest None to disclose., (Copyright © 2020. Published by Elsevier B.V.)
Published: 2020
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27. Suicidal ideation is common in autosomal dominant Alzheimer's disease at-risk persons.

Author: Ng KP, Richard-Devantoy S, Bertrand JA, Jiang L, Pascoal TA, Mathotaarachchi S, Therriault J, Yatawara C, Kandiah N, Greenwood CMT, Rosa-Neto P, and Gauthier S
Subjects: Adult, Cross-Sectional Studies, Female, Humans, Male, Middle Aged, Mutation, Risk Assessment, Alzheimer Disease genetics, Alzheimer Disease psychology, Suicidal Ideation
Abstract: Objectives: To study the frequency of suicidal ideation and its association with clinical and neurobiological correlates among cognitively intact autosomal dominant Alzheimer's disease (ADAD) at-risk individuals., Methods/design: In a cross-sectional study of 183 ADAD at-risk individuals (91 mutation carriers and 92 noncarriers), we compared the frequency of suicidal ideation among carriers and noncarriers. Linear mixed-effects models with family-level random effects evaluated the relationships between geriatric depression scale (GDS), neuropsychiatric inventory-questionnaire (NPI-Q), and suicidal ideation scores among all ADAD at-risk individuals. An interaction term was added to the regression models to evaluate the interactions of suicidal ideation and mutation status on neuropsychiatric symptoms., Results: Twenty-six (14.20%) ADAD at-risk individuals (13 [14.28%] carriers and 13 [14.13%] noncarriers) had suicidal ideation. The frequency of suicidal ideation did not differ between carriers and noncarriers. Suicidal ideation was associated with higher GDS among all ADAD at-risk individuals. When stratified into mutation carrier status, noncarriers with suicidal ideation had higher GDS than carriers. There was no statistically significant association between suicidal ideation and NPI-Q among ADAD at-risk individuals. Awareness of mutation status, neuropsychological performances, and cerebrospinal fluid AD biomarkers were not associated with suicidal ideation among carriers and noncarriers., Conclusions: Suicidal ideation is common among cognitively intact ADAD at-risk individuals. While ADAD at-risk individuals with suicidal ideation have greater depressive symptoms, noncarriers with suicidal ideation have higher GDS scores than carriers. Interestingly, awareness of the mutation status was not associated with suicidal ideation in our study. Early identification of suicidal thoughts can facilitate timely interventions to prevent suicidal behaviours. Keywords autosomal dominant Alzheimer's diseasedominantly inherited Alzheimer's networkneuropsychiatric symptomssuicidal ideation., (© 2019 John Wiley & Sons, Ltd.)
Published: 2020
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28. Small Vessel Disease and Associations with Cerebrospinal Fluid Amyloid, Tau, and Neurodegeneration (ATN) Biomarkers and Cognition in Young Onset Dementia.

Author: Yatawara C, Ng KP, Cristine Guevarra A, Wong B, Yong T, and Kandiah N
Subjects: Age of Onset, Biomarkers cerebrospinal fluid, Dementia diagnostic imaging, Dementia epidemiology, Female, Humans, Male, Middle Aged, Neurodegenerative Diseases diagnostic imaging, Neurodegenerative Diseases epidemiology, Singapore epidemiology, Amyloid beta-Peptides cerebrospinal fluid, Cognition physiology, Dementia cerebrospinal fluid, Microvessels diagnostic imaging, Neurodegenerative Diseases cerebrospinal fluid, Peptide Fragments cerebrospinal fluid, tau Proteins cerebrospinal fluid
Abstract: Background: Small vessel disease (SVD) and Alzheimer's disease (AD) frequently coexist; however, it remains unclear how they collectively affect cognition., Objective: We investigated associations between SVD and AD biomarkers, namely amyloid, tau, and neurodegeneration (ATN) in young onset dementia (YOD) and explored how SVD and ATN interact to affect cognition., Methods: 80 YOD individuals were recruited from a memory clinic. SVD burden (SVD+) was operationalized as a score >1 on the Staals scale and ATN was measured using cerebrospinal fluid (CSF)., Results: SVD+ was associated with lower CSF Aβ1-42 (B = -0.20, 95% CI: -0.32 to -0.08) and greater neurodegeneration, indexed as hippocampal atrophy (B = -0.24, 95% CI: -0.40 to -0.04). SVD+ was not associated with tau. Cognitive impairment was associated with CSF Aβ1-42 (B = -0.35, 95% CI: -0.55 to -0.18) but not SVD. Rather, SVD was indirectly associated with cognition via reduced CSF Aβ1-42, specifically with global cognition (B = -0.03, 95% CI: -0.09 to -0.01) and memory (B = 0.08, 95% CI: -.01 to .21). SVD was indirectly associated with cognition via increased neurodegeneration in grey matter (Global cognition: B = -0.06, 95% CI: -0.17 to -0.03; Memory: B = 0.05, 95% CI: 0.01 to 0.18) and the hippocampus (Global cognition: B = -0.05, 95% CI: -0.11 to -0.01; Memory: B = 0.06, 95% CI: 0.01 to 0.17)., Conclusion: In YOD, SVD burden was associated with AD pathology, namely CSF Aβ1-42. SVD indirectly contributed to cognitive impairment via reducing CSF Aβ1-42 and increasing neurodegeneration.
Published: 2020
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29. Mechanisms Linking White Matter Lesions, Tract Integrity, and Depression in Alzheimer Disease.

Author: Yatawara C, Lee D, Ng KP, Chander R, Ng D, Ji F, Shim HY, Hilal S, Venketasubramanian N, Chen C, Zhou J, and Kandiah N
Subjects: Aged, Aged, 80 and over, Alzheimer Disease complications, Alzheimer Disease diagnostic imaging, Cerebral Cortex diagnostic imaging, Corpus Callosum diagnostic imaging, Cross-Sectional Studies, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Neural Pathways diagnostic imaging, Neural Pathways pathology, White Matter diagnostic imaging, Alzheimer Disease pathology, Alzheimer Disease physiopathology, Cerebral Cortex pathology, Corpus Callosum pathology, Depression physiopathology, White Matter pathology
Abstract: Objective: Late-life depression involves the disconnection of white matter tracts that regulate mood. A pathogenic link between poor tract integrity and depressive symptoms is believed to be white matter lesions (WML), however the mechanisms linking tract integrity, WML, and depression remains unexplored. The authors sought to identify whether the association between reduced tract integrity and depressive symptoms is mediated by WML in patients with Alzheimer disease (AD), and whether individual characteristics moderate this effect., Methods: This was a cross-sectional study in a tertiary memory clinic. A total of 91 patients with mild AD and 79 healthy elderly, comparable in depressive symptoms, white matter hyperintensities (WMH) volume, cardiovascular risk, age, and sex were chosen. Tract integrity was assessed using diffusion tensor imaging, WML were indexed as WMH, measured using fluid-attenuation inversion recovery imaging, and depressive symptoms were measured with the informant-based Geriatric Depression Scale., Results: In patients with mild AD, reduced tract integrity in right hemispheric cortical-subcortical tracts and the genu of the corpus callosum was moderately associated with depressive symptoms. This association was fully mediated by WML. Moderation analysis indicated that old age strengthened the association between all tracts and depressive symptoms, as mediated by WML. In cognitively healthy elderly, neither tracts nor WML were related to depressive symptoms., Conclusion: Reduced tract integrity may be important but not sufficient for the manifestation of depressive symptoms in mild AD. Instead, WML may drive the pathogenic link between reduced tract integrity and depressive symptoms., (Copyright © 2019 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.)
Published: 2019
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30. Cerebrovascular Disease Is a Risk for Getting Lost Behavior in Prodromal Dementia.

Author: Yatawara C, Ng KP, Lim L, Chander R, Zhou J, and Kandiah N
Subjects: Aged, Female, Humans, Male, Middle Aged, Risk, Alzheimer Disease epidemiology, Alzheimer Disease pathology, Alzheimer Disease physiopathology, Behavioral Symptoms epidemiology, Behavioral Symptoms pathology, Behavioral Symptoms physiopathology, Cerebrovascular Disorders epidemiology, Cerebrovascular Disorders pathology, Cerebrovascular Disorders physiopathology, Cognitive Dysfunction epidemiology, Cognitive Dysfunction pathology, Cognitive Dysfunction physiopathology, Hypertension epidemiology, Prodromal Symptoms, White Matter pathology
Abstract: Cerebrovascular disease (CVD) contributes to spatial navigation deficits; however, the everyday outcomes of this association remain unexplored. We investigated whether CVD was a risk for getting lost behavior (GLB) in elderly with mild cognitive impairment (MCI) and mild Alzheimer disease (AD). Getting lost behavior was assessed using a semistructured clinical interview and was associated with white matter lesions (WMLs) in patients with MCI. Specifically, right occipital WMLs increased the odds of GLB by 12 times ( P = .03) and right temporal WMLs increased the odds of GLB by 4 times ( P = .01), regardless of age, gender, global cognitive impairment, and occipital or medial temporal gray matter atrophy. Hypertension increased the risk of GLB in MCI by contributing to the burden of WMLs. White matter lesions were not associated with GLB in mild AD. Our findings suggest that interventions aimed at reducing GLB in prodromal dementia may involve preventing WMLs by optimizing hypertension control.
Published: 2019
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31. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

Author: Wilson D, Ambler G, Lee KJ, Lim JS, Shiozawa M, Koga M, Li L, Lovelock C, Chabriat H, Hennerici M, Wong YK, Mak HKF, Prats-Sánchez L, Martínez-Domeño A, Inamura S, Yoshifuji K, Arsava EM, Horstmann S, Purrucker J, Lam BYK, Wong A, Kim YD, Song TJ, Schrooten M, Lemmens R, Eppinger S, Gattringer T, Uysal E, Tanriverdi Z, Bornstein NM, Assayag EB, Hallevi H, Tanaka J, Hara H, Coutts SB, Hert L, Polymeris A, Seiffge DJ, Lyrer P, Algra A, Kappelle J, Al-Shahi Salman R, Jäger HR, Lip GYH, Mattle HP, Panos LD, Mas JL, Legrand L, Karayiannis C, Phan T, Gunkel S, Christ N, Abrigo J, Leung T, Chu W, Chappell F, Makin S, Hayden D, Williams DJ, Kooi ME, van Dam-Nolen DHK, Barbato C, Browning S, Wiegertjes K, Tuladhar AM, Maaijwee N, Guevarra C, Yatawara C, Mendyk AM, Delmaire C, Köhler S, van Oostenbrugge R, Zhou Y, Xu C, Hilal S, Gyanwali B, Chen C, Lou M, Staals J, Bordet R, Kandiah N, de Leeuw FE, Simister R, van der Lugt A, Kelly PJ, Wardlaw JM, Soo Y, Fluri F, Srikanth V, Calvet D, Jung S, Kwa VIH, Engelter ST, Peters N, Smith EE, Yakushiji Y, Orken DN, Fazekas F, Thijs V, Heo JH, Mok V, Veltkamp R, Ay H, Imaizumi T, Gomez-Anson B, Lau KK, Jouvent E, Rothwell PM, Toyoda K, Bae HJ, Marti-Fabregas J, and Werring DJ
Subjects: Brain Ischemia diagnostic imaging, Humans, Intracranial Hemorrhages diagnostic imaging, Ischemic Attack, Transient diagnostic imaging, Magnetic Resonance Imaging, Neuroimaging, Stroke diagnostic imaging, Brain diagnostic imaging, Brain Ischemia complications, Intracranial Hemorrhages etiology, Ischemic Attack, Transient complications, Stroke complications
Abstract: Background: Cerebral microbleeds are a neuroimaging biomarker of stroke risk. A crucial clinical question is whether cerebral microbleeds indicate patients with recent ischaemic stroke or transient ischaemic attack in whom the rate of future intracranial haemorrhage is likely to exceed that of recurrent ischaemic stroke when treated with antithrombotic drugs. We therefore aimed to establish whether a large burden of cerebral microbleeds or particular anatomical patterns of cerebral microbleeds can identify ischaemic stroke or transient ischaemic attack patients at higher absolute risk of intracranial haemorrhage than ischaemic stroke., Methods: We did a pooled analysis of individual patient data from cohort studies in adults with recent ischaemic stroke or transient ischaemic attack. Cohorts were eligible for inclusion if they prospectively recruited adult participants with ischaemic stroke or transient ischaemic attack; included at least 50 participants; collected data on stroke events over at least 3 months follow-up; used an appropriate MRI sequence that is sensitive to magnetic susceptibility; and documented the number and anatomical distribution of cerebral microbleeds reliably using consensus criteria and validated scales. Our prespecified primary outcomes were a composite of any symptomatic intracranial haemorrhage or ischaemic stroke, symptomatic intracranial haemorrhage, and symptomatic ischaemic stroke. We registered this study with the PROSPERO international prospective register of systematic reviews, number CRD42016036602., Findings: Between Jan 1, 1996, and Dec 1, 2018, we identified 344 studies. After exclusions for ineligibility or declined requests for inclusion, 20 322 patients from 38 cohorts (over 35 225 patient-years of follow-up; median 1·34 years [IQR 0·19-2·44]) were included in our analyses. The adjusted hazard ratio [aHR] comparing patients with cerebral microbleeds to those without was 1·35 (95% CI 1·20-1·50) for the composite outcome of intracranial haemorrhage and ischaemic stroke; 2·45 (1·82-3·29) for intracranial haemorrhage and 1·23 (1·08-1·40) for ischaemic stroke. The aHR increased with increasing cerebral microbleed burden for intracranial haemorrhage but this effect was less marked for ischaemic stroke (for five or more cerebral microbleeds, aHR 4·55 [95% CI 3·08-6·72] for intracranial haemorrhage vs 1·47 [1·19-1·80] for ischaemic stroke; for ten or more cerebral microbleeds, aHR 5·52 [3·36-9·05] vs 1·43 [1·07-1·91]; and for ≥20 cerebral microbleeds, aHR 8·61 [4·69-15·81] vs 1·86 [1·23-1·82]). However, irrespective of cerebral microbleed anatomical distribution or burden, the rate of ischaemic stroke exceeded that of intracranial haemorrhage (for ten or more cerebral microbleeds, 64 ischaemic strokes [95% CI 48-84] per 1000 patient-years vs 27 intracranial haemorrhages [17-41] per 1000 patient-years; and for ≥20 cerebral microbleeds, 73 ischaemic strokes [46-108] per 1000 patient-years vs 39 intracranial haemorrhages [21-67] per 1000 patient-years)., Interpretation: In patients with recent ischaemic stroke or transient ischaemic attack, cerebral microbleeds are associated with a greater relative hazard (aHR) for subsequent intracranial haemorrhage than for ischaemic stroke, but the absolute risk of ischaemic stroke is higher than that of intracranial haemorrhage, regardless of cerebral microbleed presence, antomical distribution, or burden., Funding: British Heart Foundation and UK Stroke Association., (Copyright © 2019 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2019
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32. Associations between lesions and domain-specific cognitive decline in poststroke dementia.

Author: Yatawara C, Ng KP, Chander R, and Kandiah N
Subjects: Aged, Brain Infarction diagnostic imaging, Case-Control Studies, Dementia etiology, Female, Follow-Up Studies, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Risk Factors, Stroke complications, Brain Infarction etiology, Cerebral Cortex diagnostic imaging, Cognition Disorders diagnostic imaging, Cognition Disorders etiology, Dementia complications
Abstract: Objective: To investigate whether the effect of prestroke and stroke-related lesions on incident poststroke dementia (PSD) is mediated by a unique pattern of domain-specific cognitive impairment, and the relative strength of these anatomical-cognitive associations in predicting incident PSD., Methods: In this incident case-control study (n = 150), we defined incident cases as acute stroke patients who developed PSD and controls as acute stroke patients who remained free from dementia at a 6 month follow-up, matched on age, prestroke cognitive status, and number of stroke-related lesions. MRI was performed at initial clinical presentation; neuropsychological assessments and clinical diagnosis of PSD was performed 6 months poststroke. Moderated mediation analysis evaluated the interactions among PSD, anatomical lesions, cognitive domains, and individual demographic and medical characteristics., Results: Compared to stroke-related lesions, prestroke lesions were associated with the widest range of cognitive domain impairments and had stronger clinical utility in predicting incident PSD. Specifically, global cortical atrophy (GCA) and deep white matter hyperintensities (WMH) were indirectly associated with PSD by disrupting executive functions, memory, and language. Acute infarcts were indirectly associated with PSD by disrupting executive functions and language. The strongest mediator was executive dysfunction, increasing risk of PSD in patients with deep WMH, GCA, and large infarcts by more than 9 times, with sex and educational attainment moderating the magnitude of association. Periventricular WMH were directly associated with incident PSD but not mediated by deficits in cognitive domains., Conclusion: We provide an anatomical-cognitive framework that can be applied to stratify patients at highest risk of PSD and to guide personalized interventions., (© 2018 American Academy of Neurology.)
Published: 2018
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33. Neuropsychiatric symptoms in South-East Asian patients with mild cognitive impairment and dementia: prevalence, subtypes, and risk factors.

Author: Yatawara C, Hiu S, Tan L, and Kandiah N
Subjects: Aged, Aged, 80 and over, Anxiety epidemiology, Cohort Studies, Female, Humans, Logistic Models, Male, Middle Aged, Mood Disorders epidemiology, Neuropsychological Tests, Prevalence, Psychomotor Agitation epidemiology, Psychotic Disorders epidemiology, Risk Factors, Singapore epidemiology, Sleep Wake Disorders epidemiology, Cognitive Dysfunction psychology, Dementia psychology
Abstract: Background: The subtypes and risk factors of neuropsychiatric symptoms remain largely unexplored in South-East Asian populations., Objective: We investigated the prevalence, subtypes, and risk factors, namely, demographic, medical morbidity, and cognitive impairment associated with neuropsychiatric symptoms in a South-East Asian cohort of patients with mild cognitive impairment (MCI) and dementia., Methods: A clinical cohort of 38 MCI and 198 mild-moderate dementia patients were assessed using the Neuropsychiatric Inventory-Questionnaire., Results: Neuropsychiatric symptoms were equally prevalent among patients with MCI (74%) and mild-moderate dementia (85%). Three subtypes of symptoms were identified for each diagnostic group; for MCI, they included mood disturbances, anxiety/sleep problems, and psychosis, while for dementia, the subtypes included behavioral disturbances, psychosis/mood, and hyperactive behaviors. The largest risk for neuropsychiatric symptoms for both MCI and dementia patients was male gender. Among patients with MCI, burden of cerebrovascular disease and global cognitive impairment were small risks for neuropsychiatric symptoms, while for patients with dementia, an older age (>65 years) was a small risk and lower educational attainment was a moderate risk., Discussion: These findings contribute to the worldwide epidemiology of neuropsychiatric symptoms in MCI and dementia and highlight that the profile of symptoms, subtypes, and risks is fairly homogenous across Western and Asian cultures. Copyright © 2017 John Wiley & Sons, Ltd., (Copyright © 2017 John Wiley & Sons, Ltd.)
Published: 2018
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34. Getting Lost Behavior in Patients with Mild Alzheimer's Disease: A Cognitive and Anatomical Model.

Author: Yatawara C, Lee DR, Lim L, Zhou J, and Kandiah N
Abstract: Background: Getting lost behavior (GLB) in the elderly is believed to involve poor top-down modulation of visuospatial processing, by impaired executive functions. However, since healthy elderly and elderly with Alzheimer's disease (AD) experience a different pattern of cognitive decline, it remains unclear whether this hypothesis can explain GLB in dementia., Objective: We sought to identify whether poor executive functions and working memory modulate the relationship between visuospatial processing and prevalence of GLB in healthy elderly and patients with AD. Complementary to this, we explored whether brain regions critical for executive functions modulate the relationship between GLB and brain regions critical for visuospatial processing., Method: Ninety-two participants with mild AD and 46 healthy age-matched controls underwent neuropsychological assessment and a structural MRI. GLB was assessed using a semistructured clinical interview. Path analysis was used to explore interactions between visuospatial deficits, executive dysfunction/working memory, and prevalence of GLB, in AD and controls independently., Results: For both healthy controls and patients with mild AD, visuospatial processing deficits were associated with GLB only in the presence of poor working memory. Anatomically, GLB was associated with medial temporal atrophy in patients with mild AD, which was not strengthened by low frontal gray matter (GM) volume as predicted. Instead, medial temporal atrophy was more strongly related to GLB in patients with high frontal GM volumes. For controls, GLB was not associated with occipital, parietal, medial temporal, or frontal GM volume., Conclusion: Cognitively, a top-down modulation deficit may drive GLB in both healthy elderly and patients with mild AD. This modulation effect may be localized in the medial temporal lobe for patients with mild AD. Thus, anatomical substrates of GLB in mild AD may not follow the typical top-down modulation mechanisms often reported in the healthy aging population. Implications advance therapeutic practices by highlighting the need to target both working memory and visuospatial deficits simultaneously, and that anatomical substrates of GLB may be disease specific.
Published: 2017
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35. Depressive symptoms influence global cognitive impairment indirectly by reducing memory and executive function in patients with mild cognitive impairment.

Author: Yatawara C, Lim L, Chander R, Zhou J, and Kandiah N
Subjects: Aged, Aged, 80 and over, Comorbidity, Disease Progression, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Alzheimer Disease diagnosis, Alzheimer Disease psychology, Cognitive Dysfunction diagnosis, Cognitive Dysfunction psychology, Depressive Disorder diagnosis, Depressive Disorder psychology
Abstract: Background: Depressive symptoms negatively influence global cognition in the elderly; however, the mechanism of this effect remains unclear., Objective: To investigate whether depressive symptoms influence global cognitive function in patients with mild cognitive impairment (MCI) and mild Alzheimer's disease (AD) by impeding specific neuropsychological abilities and under what conditions this effect might occur., Method: A sample of 259 participants (104 cognitively normal elderly controls, 66 patients with MCI and 89 patients with mild AD) underwent a comprehensive neuropsychological assessment. Global cognitive impairment was indexed by the composite of Mini-Mental State Examination and Montreal Cognitive Assessment scores and severity of depressive symptoms was measured with the Geriatric Depression Scale (GDS)., Results: Among patients with MCI, greater severity of depressive symptoms was associated with greater global cognitive impairment, with a moderate effect size. A mediation analysis revealed that patients with MCI experiencing depressive symptoms may exhibit global cognitive impairment because their depressive symptoms were reducing their capacity for working memory, episodic memory and non-speed-based executive functions. A moderation analysis indicated that this effect was consistent across age, gender, years of education and APOE-e4 status for working memory and episodic memory, and was observed in patients with MCI older than 65 years for executive functions. In cognitively normal elderly adults and patients with AD, depressive symptoms were not associated with global cognitive impairment., Conclusions: Depressive symptoms influence global cognitive function in patients with MCI indirectly by reducing mental space, mental flexibility and their capacity for consolidating and retrieving memories. These findings may guide clinicians to better diagnose and manage cognitive impairment in the context of concomitant depressive symptoms., (Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.)
Published: 2016
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35 results on '"Yatawara C"'

1. The Efficacy of Transdermal Rivastigmine in Mild to Moderate Alzheimer’s Disease with Concomitant Small Vessel Cerebrovascular Disease: Findings from an Open-Label Study

2. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

3. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

4. Association of Prediabetes and Type 2 Diabetes With Cognitive Function After Stroke: A STROKOG Collaboration Study

5. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

6. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

7. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

8. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies

9. The effect of oxytocin nasal spray on social interaction deficits observed in young children with autism: a randomized clinical crossover trial

10. The effect of oxytocin nasal spray on social interaction deficits observed in young children with autism: a randomized clinical crossover trial

11. ChemInform Abstract: Roritoxins, New Macrocyclic Trichothecenes from Myrothecium roridum.

12. Roritoxins. New macrocyclic trichothecenes from Myrothecium roridum

13. Production of Verrucarol

14. Trichothecenes produced by Stachybotrys atra from Eastern Europe

15. 7 alpha-hydroxytrichodermol, a new trichothecene from Myrothecium roridum

16. Airborne outbreak of trichothecene toxicosis

17. Long-Term Cognitive Decline After Stroke: An Individual Participant Data Meta-Analysis.

18. APOE4 and Confluent White Matter Hyperintensities Have a Synergistic Effect on Episodic Memory Impairment in Prodromal Dementia.

19. Development of imaging-based risk scores for prediction of intracranial haemorrhage and ischaemic stroke in patients taking antithrombotic therapy after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

20. Cerebral Small Vessel Disease Influences Hippocampal Subfield Atrophy in Mild Cognitive Impairment.

21. Influence of White Matter Hyperintensities on Baseline and Longitudinal Amyloid-β in Cognitively Normal Individuals.

22. The Association Between Diabetes Mellitus and Mild Behavioral Impairment Among Mild Cognitive Impairment: Findings from Singapore.

23. Baseline Neurodegeneration Influences the Longitudinal Effects of Tau on Cognition.

24. Interactions Between Acute Infarcts and Cerebrovascular Pathology Predict Poststroke Dementia.

25. Association of Prediabetes and Type 2 Diabetes With Cognitive Function After Stroke: A STROKOG Collaboration Study.

26. The role of cerebral microbleeds in the incidence of post-stroke dementia.

27. Suicidal ideation is common in autosomal dominant Alzheimer's disease at-risk persons.

28. Small Vessel Disease and Associations with Cerebrospinal Fluid Amyloid, Tau, and Neurodegeneration (ATN) Biomarkers and Cognition in Young Onset Dementia.

29. Mechanisms Linking White Matter Lesions, Tract Integrity, and Depression in Alzheimer Disease.

30. Cerebrovascular Disease Is a Risk for Getting Lost Behavior in Prodromal Dementia.

31. Cerebral microbleeds and stroke risk after ischaemic stroke or transient ischaemic attack: a pooled analysis of individual patient data from cohort studies.

32. Associations between lesions and domain-specific cognitive decline in poststroke dementia.

33. Neuropsychiatric symptoms in South-East Asian patients with mild cognitive impairment and dementia: prevalence, subtypes, and risk factors.

34. Getting Lost Behavior in Patients with Mild Alzheimer's Disease: A Cognitive and Anatomical Model.

35. Depressive symptoms influence global cognitive impairment indirectly by reducing memory and executive function in patients with mild cognitive impairment.

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35 results on '"Yatawara C"'

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