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152. Correction: Predictive value for cardiovascular events of common carotid intima media thickness and its rate of change in individuals at high cardiovascular risk - Results from the PROG-IMT collaboration (PLoS One (2018) 13:4 (e0191172) DOI: 10.1371/journal.pone.0191172)

Author

Lorenz M. W., Gao L., Ziegelbauer K., Norata G. D., Empana J. P., Schmidtmann I., Lin H. -J., McLachlan S., Bokemark L., Ronkainen K., Amato M., Schminke U., Srinivasan S. R., Lind L., Okazaki S., Stehouwer C. D. A., Willeit P., Polak J. F., Steinmetz H., Sander D., Poppert H., Desvarieux M., Arfan Ikram M., Johnsen S. H., Staub D., Sirtori C. R., Iglseder B., Beloqui O., Engstrom G., Friera A., Rozza F., Xie W., Parraga G., Grigore L., Plichart M., Blankenberg S., Su T. -C., Schmidt C., Tuomainen T. -P., Veglia F., Volzke H., Nijpels G., Willeit J., Sacco R. L., Franco O. H., Uthoff H., Hedblad B., Suarez C., Izzo R., Zhao D., Wannarong T., Catapano A., Ducimetiere P., Espinola-Klein C., Chien K. -L., Price J. F., Bergstrom G., Kauhanen J., Tremoli E., Dorr M., Berenson G., Kitagawa K., Dekker J. M., Kiechl S., Sitzer M., Bickel H., Rundek T., Hofman A., Mathiesen E. B., Castelnuovo S., Landecho M. F., Rosvall M., Gabriel R., De Luca N., Liu J., Baldassarre D., Kavousi M., De Groot E., Bots M. L., Yanez D. N., Thompson S. G., Lorenz, M. W., Gao, L., Ziegelbauer, K., Norata, G. D., Empana, J. P., Schmidtmann, I., Lin, H. -J., Mclachlan, S., Bokemark, L., Ronkainen, K., Amato, M., Schminke, U., Srinivasan, S. R., Lind, L., Okazaki, S., Stehouwer, C. D. A., Willeit, P., Polak, J. F., Steinmetz, H., Sander, D., Poppert, H., Desvarieux, M., Arfan Ikram, M., Johnsen, S. H., Staub, D., Sirtori, C. R., Iglseder, B., Beloqui, O., Engstrom, G., Friera, A., Rozza, F., Xie, W., Parraga, G., Grigore, L., Plichart, M., Blankenberg, S., Su, T. -C., Schmidt, C., Tuomainen, T. -P., Veglia, F., Volzke, H., Nijpels, G., Willeit, J., Sacco, R. L., Franco, O. H., Uthoff, H., Hedblad, B., Suarez, C., Izzo, R., Zhao, D., Wannarong, T., Catapano, A., Ducimetiere, P., Espinola-Klein, C., Chien, K. -L., Price, J. F., Bergstrom, G., Kauhanen, J., Tremoli, E., Dorr, M., Berenson, G., Kitagawa, K., Dekker, J. M., Kiechl, S., Sitzer, M., Bickel, H., Rundek, T., Hofman, A., Mathiesen, E. B., Castelnuovo, S., Landecho, M. F., Rosvall, M., Gabriel, R., De Luca, N., Liu, J., Baldassarre, D., Kavousi, M., De Groot, E., Bots, M. L., Yanez, D. N., and Thompson, S. G.

Abstract

An affiliation for Moise Desvarieux is missing. In addition to affiliation #22, Moise Desvarieux is affiliated with: METHODS Core, Centre de Recherche Epidémiologie et Statistique Paris Sorbonne Cité (CRESS), Institut National de la Santé et de la Recherche Médicale (INSERM) UMR 1153, Paris France.

Published
2018

164. Mendelian randomization integrating GWAS and eQTL data reveals genetic determinants of complex and clinical traits

Author

Porcu, E. (Eleonora), Rueger, S. (Sina), Lepik, K. (Kaido), Agbessi, M. (Mawusse), Ahsan, H. (Habibul), Alves, I. (Isabel), Andiappan, A. (Anand), Arindrarto, W. (Wibowo), Awadalla, P. (Philip), Battle, A. (Alexis), Beutner, F. (Frank), Bonder, M. J. (Marc Jan), Boomsma, D. (Dorret), Christiansen, M. (Mark), Claringbould, A. (Annique), Deelen, P. (Patrick), Esko, T. (Tonu), Fave, M.-J. (Marie-Julie), Franke, L. (Lude), Frayling, T. (Timothy), Gharib, S. A. (Sina A.), Gibson, G. (Gregory), Heijmans, B. T. (Bastiaan T.), Hemani, G. (Gibran), Jansen, R. (Rick), Kahonen, M. (Mika), Kalnapenkis, A. (Anette), Kasela, S. (Silva), Kettunen, J. (Johannes), Kim, Y. (Yungil), Kirsten, H. (Holger), Kovacs, P. (Peter), Krohn, K. (Knut), Kronberg-Guzman, J. (Jaanika), Kukushkina, V. (Viktorija), Lee, B. (Bernett), Lehtimaki, T. (Terho), Loeffler, M. (Markus), Marigorta, U. M. (Urko M.), Mei, H. (Hailang), Milani, L. (Lili), Montgomery, G. W. (Grant W.), Mueler-Nurasyid, M. (Martina), Nauck, M. (Matthias), Nivard, M. (Michel), Penninx, B. (Brenda), Perola, M. (Markus), Pervjakova, N. (Natalia), Pierce, B. L. (Brandon L.), Powell, J. (Joseph), Prokisch, H. (Holger), Psaty, B. M. (Bruce M.), Raitakari, O. T. (Olli T.), Ripatti, S. (Samuli), Rotzschke, O. (Olaf), Saha, A. (Ashis), Scholz, M. (Markus), Schramm, K. (Katharina), Seppala, I. (Ilkka), Slagboom, E. P. (Eline P.), Stehouwer, C. D. (Coen D. A.), Stumvoll, M. (Michael), Sullivan, P. (Patrick), Teumer, A. (Alexander), Thiery, J. (Joachim), Tong, L. (Lin), Tonjes, A. (Anke), van Dongen, J. (Jenny), van Iterson, M. (Maarten), van Meurs, J. (Joyce), Veldink, J. H. (Jan H.), Verlouw, J. (Joost), Visscher, P. M. (Peter M.), Volker, U. (Uwe), Vosa, U. (Urmo), Westra, H.-J. (Harm-Jan), Wijmenga, C. (Cisca), Yaghootkar, H. (Hanieh), Yang, J. (Jian), Zeng, B. (Biao), Zhang, F. (Futao), Beekman, M. (Marian), Boomsma, D. I. (Dorret I.), Bot, J. (Jan), Deelen, J. (Joris), Hofman, B. A. (Bert A.), Hottenga, J. J. (Jouke J.), Isaacs, A. (Aaron), Jhamai, P. M. (P. Mila), Kielbasa, S. M. (Szymon M.), Lakenberg, N. (Nico), Luijk, R. (Rene), Mei, H. (Hailiang), Moed, M. (Matthijs), Nooren, I. (Irene), Pool, R. (Rene), Schalkwijk, C. G. (Casper G.), Slagboom, P. E. (P. Eline), Suchiman, H. E. (H. Eka D.), Swertz, M. A. (Morris A.), Tigchelaar, E. F. (Ettje F.), Uitterlinden, A. G. (Andre G.), van den Berg, L. H. (Leonard H.), van der Breggen, R. (Ruud), van der Kallen, C. J. (Carla J. H.), van Dijk, F. (Freerk), van Duijn, C. M. (Cornelia M.), van Galen, M. (Michiel), van Greevenbroek, M. M. (Marleen M. J.), van Heemst, D. (Diana), van Rooij, J. (Jeroen), Van't Hof, P. (Peter), van Zwet, E. W. (Erik. W.), Vermaat, M. (Martijn), Verbiest, M. (Michael), Verkerk, M. (Marijn), Zhernakova, D. V. (Dasha V.), Zhernakova, S. (Sasha), Santoni, F. A. (Federico A.), Reymond, A. (Alexandre), and Kutalik, Z. (Zoltan)

Abstract

Genome-wide association studies (GWAS) have identified thousands of variants associated with complex traits, but their biological interpretation often remains unclear. Most of these variants overlap with expression QTLs, indicating their potential involvement in regulation of gene expression. Here, we propose a transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) that uses multiple SNPs as instruments and multiple gene expression traits as exposures, simultaneously. Applied to 43 human phenotypes, it uncovers 3,913 putatively causal gene–trait associations, 36% of which have no genome-wide significant SNP nearby in previous GWAS. Using independent association summary statistics, we find that the majority of these loci were missed by GWAS due to power issues. Noteworthy among these links is educational attainment-associated BSCL2, known to carry mutations leading to a Mendelian form of encephalopathy. We also find pleiotropic causal effects suggestive of mechanistic connections. TWMR better accounts for pleiotropy and has the potential to identify biological mechanisms underlying complex traits.

Published
2019

171. Association between bone metabolism regulators and arterial stiffness in type 2 diabetes patients

Author

Sharif, S., Bots, M. L., Schalkwijk, C., Stehouwer, C. D.A., Visseren, F. L.J., Westerink, J., and SMART study group

Subjects
Diabetes mellitus type 2, Nutrition and Dietetics, Endocrinology, Diabetes and Metabolism, Osteocalcin, Medicine (miscellaneous), Osteonectin, Osteopontin, Cardiology and Cardiovascular Medicine, Arteriall stiffness, Biomarkers, Bone metabolism regulators
Abstract

Background and Aim: Osteopontin (OPN), osteonectin (ON) and osteocalcin (OC) play an important role in the development of vascular calcifications, but it is unclear whether these bone metabolism regulators contribute to the development of arterial stiffness in type 2 diabetes patients. We therefore aim to determine the relationship between plasma concentrations of OPN, ON, OC and arterial stiffness in type 2 diabetes patients. Methods: Cross-sectional study of 1003 type 2 diabetes patients included in the Second Manifestations of ARTerial disease (SMART)-cohort. Generalized linear models were used to evaluate the relation between plasma levels of OPN, ON and OC and arterial stiffness as measured by pulse pressure (PP), ankle-brachial index (ABI) (≥0.9), carotid artery distension and an arterial stiffness summary score. Analyses were adjusted for age, sex, kidney function, diabetes duration and diastolic blood pressure. Higher OPN plasma levels were significantly related to a lower ABI (β-0.013; 95%CI −0.024 to −0.002) and a higher arterial stiffness summary score (OR1.24; 95%CI 1.03–1.49). OPN levels were not related to PP (β 0.59; 95%CI −0.63–1.81) or absolute carotid artery distention (β −7.03; 95%CI −20.00–5.93). ON and OC plasma levels were not related to any of the arterial stiffness measures. Conclusion: Only elevated plasma levels of OPN are associated with increased arterial stiffness in patients with type 2 diabetes as measured by the ankle-brachial index and arterial stiffness summary score. These findings indicate that OPN may be involved in the pathophysiology of arterial stiffness and call for further clinical investigation.

Published
2018

173. Adipose Tissue Macrophages Induce Hepatic Neutrophil Recruitment And Macrophage Accumulation Without Affecting Atherosclerosis Development In Mice.

Author

Bijnen, M., primary, Josefs, T., additional, van de Gaar, J., additional, Vroomen, M., additional, Wijnands, E., additional, Rensen, S., additional, Greve, J.W., additional, Hofker, M., additional, Biessen, E., additional, de Winther, M., additional, Stehouwer, C., additional, Schalkwijk, C., additional, and Wouters, K., additional

Published
2019
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177. Covariate-adjusted measures of discrimination for survival data

Author

White, Ian R, Rapsomaniki, Eleni, Wannamethee, S. G., Morris, R. W., Willeit, J., Willeit, P., Santer, P., Kiechl, S., Wald, N., Ebrahim, S., Lawlor, D. A., Gallacher, J., Yarnell, J. W. G., Ben Shlomo, Y., Casiglia, Edoardo, Tikhonoff, V., Sutherland, S. E., Nietert, P. J., Keil, J. E., Bachman, D. L., Psaty, B. M., Cushman, M., Nordestgaard, B. G., Tybjærg Hansen, A., Frikke Schmidt, R., Giampaoli, S., Palmieri, L., Panico, S., Pilotto, L., Vanuzzo, D., Simons, L. A., Friedlander, Y., Mccallum, J., Price, J. F., Mclachlan, S., Taylor, J. O., Guralnik, J. M., Wallace, R. B., Kohout, F. J., Cornoni Huntley, J. C., Blazer, D. G., Phillips, C. L., Wareham, N. J., Khaw, K. T., Brenner, H., Schöttker, B., Müller, H. T., Rothenbacher, D., Nissinen, A., Donfrancesco, C., Harald, K., Jousilahti, P. R., Vartiainen, E., Salomaa, V., D'Agostino, R. B., Wolf, P. A., Vasan, R. S., Daimon, M., Oizumi, T., Kayama, T., Kato, T., Chetrit, A., Dankner, R., Lubin, F., Welin, L., Svärdsudd, K., Eriksson, H., Lappas, G., Lissner, L., Mehlig, K., Björkelund, C., Nagel, D., Kiyohara, Y., Arima, H., Ninomiya, T., Hata, J., Rodriguez, B., Dekker, J. M., Nijpels, G., Stehouwer, C. D. A., Iso, H., Kitamura, A., Yamagishi, K., Noda, H., Goldbourt, U., Kauhanen, J., Salonen, J. T., Tuomainen, T. P., Meade, T. W., Destavola, B. L., Blokstra, A., Verschuren, W. M. M., de Boer, I. H., Folsom, A. R., Koenig, W., Meisinger, C., Peters, A., Bueno de Mesquita, H. B., Rosengren, A., Wilhelmsen, L., Kuller, L. H., Grandits, G., Cooper, J. A., Bauer, K. A., Davidson, K. W., Kirkland, S., Shaffer, J. A., Shimbo, D., Sato, S., Dullaart, R. P. F., Bakker, S. J. L., Gansevoort, R. T., Ducimetiere, P., Amouyel, P., Arveiler, D., Evans, A., Ferrières, J., Schulte, H., Assmann, G., Jukema, J. W., Westendorp, R. G. J., Sattar, N., Cantin, B., Lamarche, B., Després, J. P., Null, E. Barrett Connor, Wingard, D. L., Daniels, L. B., Gudnason, V., Aspelund, T., Trevisan, M., Hofman, A., Franco, O. H., Tunstall Pedoe, H., Tavendale, R., Lowe, G. D. O., Woodward, M., Howard, W. J., Howard, B. V., Zhang, Y., Best, L. G., Umans, J., Davey Smith, G., Onat, A., Nakagawa, H., Sakurai, M., Nakamura, K., Morikawa, Y., Njølstad, I., Mathiesen, E. B., Wilsgaard, T., Sundström, J., Gaziano, J. M., Ridker, P. M., Marmot, M., Clarke, R., Collins, R., Fletcher, A., Brunner, E., Shipley, M., Kivimaki, M., Buring, J., Rifai, N., Cook, N., Ford, I., Robertson, M., Marín Ibañez, A., Feskens, E. J. M., Geleijnse, J. M., MUMC+: HVC Pieken Maastricht Studie (9), Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: FHML non-thematic output, Apollo - University of Cambridge Repository, White, Ian R, Rapsomaniki, Eleni, and Panico, Salvatore

Subjects
Statistics and Probability, Male, Biometry, C-index, D-index, Discrimination, Analysis of Variance, Cardiovascular Diseases, Clinical Trials as Topic, Discriminant Analysis, Female, Humans, Middle Aged, Risk Factors, Survival Analysis, Medicine (all), Statistics, Probability and Uncertainty, 01 natural sciences, Article, Unit (housing), 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Survival data, Cardiovascular Disease, Covariate, Statistics, 030212 general & internal medicine, 0101 mathematics, 10. No inequality, Prognostic models, Survival analysis, Medicine(all), Proportional hazards model, Risk Factor, General Medicine, Probability and Uncertainty, Discriminant Analysi, Demography, Human
Abstract

Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data.To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s).We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration.The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices.The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.? 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Published
2015
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178. Irbesartan treatment does not influence plasma levels of the dicarbonyls methylglyoxal, glyoxal and 3‐deoxyglucosone in participants with type 2 diabetes and microalbuminuria: An IRMA2 sub‐study.

Author

Piazza, M., Hanssen, N. M. J., Persson, F., Scheijen, J. L., van de Waarenburg, M. P. H., van Greevenbroek, M. M. J., Rossing, P., Hovind, P., Stehouwer, C. D. A., Parving, H‐H., and Schalkwijk, C. G.

Subjects
ANALYSIS of variance, CLINICAL trials, LIQUID chromatography, TYPE 2 diabetes, ADVANCED glycation end-products, TREATMENT effectiveness, COMPARATIVE studies, ALDEHYDES, LACTATES, MASS spectrometry, DESCRIPTIVE statistics, DEOXY sugars, IRBESARTAN, ALBUMINURIA, PHARMACODYNAMICS
Abstract

Aim: Angiotensin receptor blockers (ARBs) reduce vascular complications in diabetes independently of blood pressure. Experimental studies suggested that ARBs may restore the detoxifying enzyme glyoxalase 1, thereby lowering dicarbonyls such as methylglyoxal. Human data on the effects of ARBs on plasma dicarbonyl levels are lacking. We investigated, in individuals with type 2 diabetes, whether irbesartan lowered plasma levels of the dicarbonyls methylglyoxal, glyoxal, 3‐deoxyglucosone and their derived advanced glycation end products (AGEs), and increased d‐lactate, reflecting greater methylglyoxal flux. Methods: We analysed a subset of the Irbesartan in Patients with T2D and Microalbuminuria (IRMA2) study. We measured plasma dicarbonyls methylglyoxal, glyoxal and 3‐deoxyglucosone, free AGEs and d‐lactate using ultra‐performance liquid chromatography tandem mass‐spectrometry (UPLC‐MS/MS) in the treatment arm receiving 300 mg irbesartan (n = 121) and a placebo group (n = 101) at baseline and after 1 and 2 years. Effect of treatment was analysed with repeated measurements ANOVA. Results: There was a slight, but significant difference in baseline median methylglyoxal levels [placebo 1119 (907–1509) nmol/l vs. irbesartan 300 mg 1053 (820–1427) nmol/l], but no significant changes were observed in any of the plasma dicarbonyls over time in either group and there was no effect of irbesartan treatment on plasma free AGEs or d‐lactate levels at either 1 or 2 years. Conclusion: Irbesartan treatment does not change plasma levels of the dicarbonyls methylglyoxal, glyoxal and 3‐deoxyglucosone, free AGEs or d‐lactate in type 2 diabetes. This indicates that increased dicarbonyls in type 2 diabetes are not targetable by ARBs, and other approaches to lower systemic dicarbonyls are needed in type 2 diabetes. (Clinical Trial Registry No: #NCT00317915). [ABSTRACT FROM AUTHOR]

Published
2021
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182. Use of proton pump inhibitors and risk of iron deficiency: a population-based case-control study

Author

Tran-Duy, A, Tran-Duy, A, Connell, N J, Vanmolkot, F H, Souverein, P C, de Wit, N J, Stehouwer, C D A, Hoes, A W, de Vries, F, de Boer, A, Tran-Duy, A, Tran-Duy, A, Connell, N J, Vanmolkot, F H, Souverein, P C, de Wit, N J, Stehouwer, C D A, Hoes, A W, de Vries, F, and de Boer, A

Abstract

BACKGROUND: Hypochlorhydric states are an important cause of iron deficiency (ID). Nevertheless, the association between therapy with proton pump inhibitors (PPIs) and ID has long been a subject of debate. This case-control study aimed to investigate the risk of ID associated with the use of PPIs using the UK Clinical Practice Research Datalink (CPRD) database.METHODS: Cases were patients aged 19 years or older with first-time diagnosis of ID between 2005 and 2016 (n = 26 806). The dates of first diagnosis of ID in cases defined the index dates. For each case, one control was matched by age, gender and general practice. A PPI "full" user (PFU) was defined as a subject who had received PPIs for a continuous duration of at least 1 year prior to the index date. A PPI "limited" users (PLU) was a subject who intermittently received PPI therapy. A PPI non-user (PNU) was a subject who received no PPI prescriptions prior to the index date. The odds ratio of ID in PFU and PLU compared to PNU was estimated using conditional logistic regression.RESULTS: Among cases, 2960 were PFU, 6607 PLU and 17 239 PNU. Among controls, 1091 were PFU, 5058 PLU and 20 657 PNU. Adjusted odds ratio of ID in PFU and PLU compared to PNU was 3.60 (95%CI, [3.32-3.91]) and 1.51 (95% CI, [1.44-1.58]). Positive dose-response and time-response relationships were observed.CONCLUSIONS: Chronic PPI use increases the risk of ID. Physicians should consider this when balancing the risks and benefits of chronic PPI prescription.

Published
2019

183. Use of proton pump inhibitors and risk of iron deficiency: a population-based case–control study

Author

Child Health, Cancer, JC Overig onderzoek, General Practice & Nursing Science, Circulatory Health, Julius Centrum, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Tran-Duy, A., Connell, N. J., Vanmolkot, F. H., Souverein, P. C., de Wit, N. J., Stehouwer, C. D.A., Hoes, A. W., de Vries, F., de Boer, A., Child Health, Cancer, JC Overig onderzoek, General Practice & Nursing Science, Circulatory Health, Julius Centrum, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Tran-Duy, A., Connell, N. J., Vanmolkot, F. H., Souverein, P. C., de Wit, N. J., Stehouwer, C. D.A., Hoes, A. W., de Vries, F., and de Boer, A.

Published
2019

191. Characteristics associated with polypharmacy in people with type 2 diabetes: the Dutch Diabetes Pearl cohort.

Author

Oort, S., Rutters, F., Warlé‐van Herwaarden, M. F., Schram, M. T., Stehouwer, C. D., Tack, C. J., Abbink, E. J., Wolffenbuttel, B. H., Klauw, M. M., DeVries, J. H., Siegelaar, S. E., Sijbrands, E. J., Özcan, B., Valk, H. W., Silvius, B., Schroijen, M. A., Jazet, I. M., Ballegooijen, A. J., Beulens, J. W. J., and Elders, P. J.

Subjects
LIFESTYLES, CARDIOVASCULAR diseases risk factors, POLYPHARMACY, AGE distribution, MULTIVARIATE analysis, TERTIARY care, HYPOGLYCEMIC agents, CARDIOVASCULAR diseases, TYPE 2 diabetes, PRIMARY health care, SOCIOECONOMIC factors, DESCRIPTIVE statistics, DISEASE duration, LOGISTIC regression analysis, SMOKING, BODY mass index, LONGITUDINAL method, EDUCATIONAL attainment
Abstract

Aim: To describe the prevalence and characteristics of polypharmacy in a Dutch cohort of individuals with type 2 diabetes. Methods: We included people with type 2 diabetes from the Diabetes Pearl cohort, of whom 3886 were treated in primary care and 2873 in academic care (secondary/tertiary). With multivariable multinomial logistic regression analyses stratified for line of care, we assessed which sociodemographic, lifestyle and cardiometabolic characteristics were associated with moderate (5–9 medications) and severe polypharmacy (≥10 medications) compared with no polypharmacy (0–4 medications). Results: Mean age was 63 ± 10 years, and 40% were women. The median number of daily medications was 5 (IQR 3–7) in primary care and 7 (IQR 5–10) in academic care. The prevalence of moderate and severe polypharmacy was 44% and 10% in primary care, and 53% and 29% in academic care respectively. Glucose‐lowering and lipid‐modifying medications were most prevalent. People with severe polypharmacy used a relatively large amount of other (i.e. non‐cardiovascular and non‐glucose‐lowering) medication. Moderate and severe polypharmacy across all lines of care were associated with higher age, low educational level, more smoking, longer diabetes duration, higher BMI and more cardiovascular disease. Conclusions: Severe and moderate polypharmacy are prevalent in over half of people with type 2 diabetes in primary care, and even more in academic care. People with polypharmacy are characterized by poorer cardiometabolic status. These results highlight the significance of polypharmacy in type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2021
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192. Vascular risk factors for optical coherence tomography-detected cystoid macular edema : the Maastricht study

Author

De Clerck, E. E. B., Schouten, J. S. A. G., Berendschot, T. T. J. M., Goezinne, F., Liesenborghs, I., Dagnelie, P. C., Schaper, N. C., Kroon, A. A., Henry, R. M. A., Reesink, K. D., Schram, M. T., Stehouwer, C. D. A., Webers, C. A. B., Medical Image Analysis, MUMC+: MA AIOS Oogheelkunde (9), Oogheelkunde, MUMC+: MA Oogheelkunde (9), RS: MHeNs - R3 - Neuroscience, RS: NUTRIM - R1 - Obesity, diabetes and cardiovascular health, Maastricht Centre for Systems Biology, RS: FSE MaCSBio, RS: FPN MaCSBio, Interne Geneeskunde, RS: CAPHRI - R5 - Optimising Patient Care, RS: CARIM - R3.01 - Vascular complications of diabetes and the metabolic syndrome, MUMC+: MA Endocrinologie (9), RS: CAPHRI - R2 - Creating Value-Based Health Care, RS: CARIM - R3.02 - Hypertension and target organ damage, MUMC+: MA Alg Interne Geneeskunde (9), MUMC+: HVC Pieken Maastricht Studie (9), Biomedische Technologie, RS: CARIM - R2.09 - Cardiovascular system dynamics, RS: MHeNs - R1 - Cognitive Neuropsychiatry and Clinical Neuroscience, MUMC+: MA Interne Geneeskunde (3), and MUMC+: MA Oogheelkunde (3)

Published
2018

193. Automatic identification of variables in epidemiological datasets using logic regression

Author

Lorenz, Matthias W., Abdi, Negin Ashtiani, Scheckenbach, Frank, Pflug, Anja, Bülbül, Alpaslan, Catapano, Alberico L., Agewall, Stefan, Ezhov, Marat, Bots, Michiel L., Kiechl, Stefan, Orth, Andreas, Norata, Giuseppe D., Empana, Jean Philippe, Lin, Hung Ju, McLachlan, Stela, Bokemark, Lena, Ronkainen, Kimmo, Amato, Mauro, Schminke, Ulf, Srinivasan, Sathanur R., Lind, Lars, Kato, Akihiko, Dimitriadis, Chrystosomos, Przewlocki, Tadeusz, Okazaki, Shuhei, Stehouwer, C. D.A., Lazarevic, Tatjana, Willeit, Peter, Yanez, David N., Steinmetz, Helmuth, Sander, Dirk, Poppert, Holger, Desvarieux, Moise, Ikram, M. Arfan, Bevc, Sebastjan, Staub, Daniel, Sirtori, Cesare R., Iglseder, Bernhard, Engström, Gunnar, Tripepi, Giovanni, Beloqui, Oscar, Lee, Moo Sik, Friera, Alfonsa, Xie, Wuxiang, Grigore, Liliana, Plichart, Matthieu, Su, Ta Chen, Robertson, Christine, Schmidt, Caroline, Tuomainen, Tomi Pekka, Veglia, Fabrizio, Völzke, Henry, Nijpels, Giel, Jovanovic, Aleksandar, Willeit, Johann, Sacco, Ralph L., Franco, Oscar H., Hojs, Radovan, Uthoff, Heiko, Hedblad, Bo, Park, Hyun Woong, Suarez, Carmen, Zhao, Dong, Catapano, Alberico, Ducimetiere, Pierre, Chien, Kuo Liong, Price, Jackie F., Bergström, Göran, Kauhanen, Jussi, Tremoli, Elena, Dörr, Marcus, Berenson, Gerald, Papagianni, Aikaterini, Kablak-Ziembicka, Anna, Kitagawa, Kazuo, Dekker, Jaqueline M., Stolic, Radojica, Polak, Joseph F., Sitzer, Matthias, Bickel, Horst, Rundek, Tatjana, Hofman, Albert, Ekart, Robert, Frauchiger, Beat, Castelnuovo, Samuela, Rosvall, Maria, Zoccali, Carmine, Landecho, Manuel F., Bae, Jang Ho, Gabriel, Rafael, Liu, Jing, Baldassarre, Damiano, Kavousi, Maryam, APH - Health Behaviors & Chronic Diseases, AII - Infectious diseases, APH - Aging & Later Life, and Epidemiology

Subjects
Carotid Artery Diseases, Matching (statistics), Databases, Factual, Epidemiologic Factors, Computer science, Epidemiology, Sample (statistics), Health Informatics, Logistic regression, computer.software_genre, lcsh:Computer applications to medicine. Medical informatics, Data management, Carotid Intima-Media Thickness, Set (abstract data type), 03 medical and health sciences, 0302 clinical medicine, Meta-Analysis as Topic, Backup, Predictive Value of Tests, Statistics, Journal Article, Data Mining, Humans, 030212 general & internal medicine, Medical Informatics Applications, Health Policy, Prognosis, Logic regression, Computer Science Applications, Identification (information), Variable (computer science), Meta-analysis, Logistic Models, 030220 oncology & carcinogenesis, Data quality, lcsh:R858-859.7, Data mining, computer, Algorithms, Research Article
Abstract

Background For an individual participant data (IPD) meta-analysis, multiple datasets must be transformed in a consistent format, e.g. using uniform variable names. When large numbers of datasets have to be processed, this can be a time-consuming and error-prone task. Automated or semi-automated identification of variables can help to reduce the workload and improve the data quality. For semi-automation high sensitivity in the recognition of matching variables is particularly important, because it allows creating software which for a target variable presents a choice of source variables, from which a user can choose the matching one, with only low risk of having missed a correct source variable. Methods For each variable in a set of target variables, a number of simple rules were manually created. With logic regression, an optimal Boolean combination of these rules was searched for every target variable, using a random subset of a large database of epidemiological and clinical cohort data (construction subset). In a second subset of this database (validation subset), this optimal combination rules were validated. Results In the construction sample, 41 target variables were allocated on average with a positive predictive value (PPV) of 34%, and a negative predictive value (NPV) of 95%. In the validation sample, PPV was 33%, whereas NPV remained at 94%. In the construction sample, PPV was 50% or less in 63% of all variables, in the validation sample in 71% of all variables. Conclusions We demonstrated that the application of logic regression in a complex data management task in large epidemiological IPD meta-analyses is feasible. However, the performance of the algorithm is poor, which may require backup strategies.

Published
2017
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194. Burden of disease of type 2 diabetes mellitus: cost of illness and quality of life estimated using the Maastricht Study.

Author

Janssen, L. M. M., Hiligsmann, M., Elissen, A. M. J., Joore, M. A., Schaper, N. C., Bosma, J. H. A., Stehouwer, C. D. A., Sep, S. J. S., Koster, A., Schram, M. T., and Evers, S. M. A. A.

Subjects
AGE distribution, ECONOMIC aspects of diseases, HEALTH surveys, MEDICAL care costs, TYPE 2 diabetes, PREDIABETIC state, QUALITY of life, QUESTIONNAIRES, SEX distribution, SECONDARY analysis, GLUCOSE intolerance
Abstract

Aims: To estimate the societal costs and quality of life of people with type 2 diabetes and to compare these results with those of people with normal glucose tolerance or prediabetes. Methods: Data from 2915 individuals from the population‐based Maastricht Study were included. Costs were assessed through a resource‐use questionnaire completed by the participants; cost prices were based on Dutch costing guidelines. Quality of life was expressed in utilities using the Dutch EuroQol 5D‐3L questionnaire and the SF‐36 health survey. Based on normal fasting glucose and 2‐h plasma glucose values, participants were classified into three groups: normal glucose tolerance (n = 1701); prediabetes (n = 446); or type 2 diabetes (n = 768). Results: Participants with type 2 diabetes had on average 2.2 times higher societal costs than those with normal glucose tolerance (€3,006 and €1,377 per 6 months, respectively) and had lower utilities (0.77 and 0.81, respectively). No significant differences were found between participants with normal glucose tolerance and those with prediabetes. Subgroup analyses showed that higher age, being female and having two or more diabetes‐related complications resulted in higher costs (P < 0.05) and lower utilities. Conclusions: This study showed that people with type 2 diabetes have substantially higher societal costs and lower quality of life than people with normal glucose tolerance. The results provide important input for future model‐based economic evaluations and for policy decision‐making. What's new?: The high costs of type 2 diabetes, together with its impact on quality of life, place a great burden on both the individual affected and society as a whole.People with type 2 diabetes have, on average, 2.2 times higher societal costs and experience a lower quality of life than people without type 2 diabetes.The total societal costs for people with ≥2 diabetes complications are 4.4 times higher than total societal costs for people without complications. [ABSTRACT FROM AUTHOR]

Published
2020
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