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Your search keyword '"Wen Hua Lin"' showing total 5 results
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5 results on '"Wen Hua Lin"'

1. Metabolomics and Biomarkers for Paroxysmal and Persistent Atrial Fibrillation

Author

Li‐Li Zhang, Wen‐Hua Lin, Cheng‐Ye Di, Hai‐Tao Hou, Huan‐Xin Chen, Jie Zhou, Qin Yang, and Guo‐Wei He

Subjects
atrial fibrillation, metabolites, metabolomics, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Atrial fibrillation (AF) is the most common type of arrhythmia worldwide and is associated with serious complications. This study investigated the metabolic biomarkers associated with AF and the differences in metabolomics and associated metabolic biomarkers between paroxysmal AF (AFPA) and persistent AF. Methods and Results Plasma samples were prospectively collected from patients with AF and patients in sinus rhythm with negative coronary angiography. The patients were divided into 3 groups: AFPA, persistent AF, and sinus rhythm (N=54). Metabolomics (n=36) using ultra‐high‐performance liquid chromatography mass spectrometry was used to detect differential metabolites that were validated in a new cohort (n=18). The validated metabolites from the validation phase were further analyzed by receiver operating characteristic. Among the 36 differential metabolites detected by omics assay, 4 were successfully validated with area under the curve >0.8 (P

Published
2024
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2. A Brief Introduction to Mixed Methods Systematic Review (MMSR).

Author

Chung-Ying LIN, Wen-Hua LIN, and Bih-Ching SHU

Subjects
SYSTEMATIC reviews, RESEARCH methodology
Abstract

Systematic reviews provide important empirical evidence for healthcare providers to make the best clinical decisions. While qualitative research provides subjective information on the human experience, quantitative research may be used to provide quantified evaluations of interventions. To overcome the lack of objectivity in qualitative research and of context considerations in quantitative research, recent efforts have focused on developing mixed-method approaches that combine meta-analysis (quantitative systematic reviews) and meta-synthesis (qualitative systematic reviews). This new idea may help conceptualize studied phenomena more thoroughly. However, the typology remains inconsistent and the currently proposed approaches lack unified guidance and principles. In this paper, "mixed methods systematic review", a term promoted by the Joanna Briggs Institute, is used to indicate the newly developed systematic review. The use of systematic review in quantitative research and in qualitative research and the use of mixed methods systematic review are introduced chronologically, with an emphasis on procedures, examples, and quality appraisal tools. The concepts and concrete procedures for integrating results from different research method are presented for researchers and healthcare providers to allow them to better understand this approach and explore related phenomena more thoroughly. [ABSTRACT FROM AUTHOR]

Published
2023
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3. Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19

Author

Christos P Kotanidis, Cheng Xie, Donna Alexander, Jonathan C L Rodrigues, Katie Burnham, Alexander Mentzer, Daniel O’Connor, Julian Knight, Muhammad Siddique, Helen Lockstone, Sheena Thomas, Rafail Kotronias, Evangelos K Oikonomou, Ileana Badi, Maria Lyasheva, Cheerag Shirodaria, Sheila F Lumley, Bede Constantinides, Nicholas Sanderson, Gillian Rodger, Kevin K Chau, Archie Lodge, Maria Tsakok, Fergus Gleeson, David Adlam, Praveen Rao, Das Indrajeet, Aparna Deshpande, Amrita Bajaj, Benjamin J Hudson, Vivek Srivastava, Shakil Farid, George Krasopoulos, Rana Sayeed, Ling-Pei Ho, Stefan Neubauer, David E Newby, Keith M Channon, John Deanfield, Charalambos Antoniades, David J Ahern, Zhichao Ai, Mark Ainsworth, Chris Allan, Alice Allcock, Brian Angus, M Azim Ansari, Carolina Arancibia-Cárcamo, Dominik Aschenbrenner, Moustafa Attar, J Kenneth Baillie, Eleanor Barnes, Rachael Bashford-Rogers, Archana Bashyal, Sally Beer, Georgina Berridge, Amy Beveridge, Sagida Bibi, Tihana Bicanic, Luke Blackwell, Paul Bowness, Andrew Brent, Andrew Brown, John Broxholme, David Buck, Helen Byrne, Susana Camara, Ivan Candido Ferreira, Philip Charles, Wentao Chen, Yi-Ling Chen, Amanda Chong, Elizabeth Clutterbuck, Mark Coles, Christopher Conlon, Richard Cornall, Adam Cribbs, Fabiola Curion, Emma Davenport, Neil Davidson, Simon Davis, Calliope Dendrou, Julie Dequaire, Lea Dib, James Docker, Christina Dold, Tao Dong, Damien Downes, Hal Drakesmith, Susanna Dunachie, David Duncan, Chris Eijsbouts, Robert Esnouf, Alexis Espinosa, Rachel Etherington, Benjamin Fairfax, Rory Fairhead, Hai Fang, Shayan Fassih, Sally Felle, Maria Fernandez Mendoza, Ricardo Ferreira, Roman Fischer, Thomas Foord, Aden Forrow, John Frater, Anastasia Fries, Veronica Gallardo Sanchez, Lucy Garner, Clementine Geeves, Dominique Georgiou, Leila Godfrey, Tanya Golubchik, Maria Gomez Vazquez, Angie Green, Hong Harper, Heather Harrington, Raphael Heilig, Svenja Hester, Jennifer Hill, Charles Hinds, Clare Hird, Renee Hoekzema, Benjamin Hollis, Jim Hughes, Paula Hutton, Matthew Jackson-Wood, Ashwin Jainarayanan, Anna James-Bott, Kathrin Jansen, Katie Jeffery, Elizabeth Jones, Luke Jostins, Georgina Kerr, David Kim, Paul Klenerman, Vinod Kumar, Piyush Kumar Sharma, Prathiba Kurupati, Andrew Kwok, Angela Lee, Aline Linder, Teresa Lockett, Lorne Lonie, Maria Lopopolo, Martyna Lukoseviciute, Jian Luo, Spyridoula Marinou, Brian Marsden, Jose Martinez, Philippa Matthews, Michalina Mazurczyk, Simon McGowan, Stuart McKechnie, Adam Mead, Yuxin Mi, Claudia Monaco, Ruddy Montadon, Giorgio Napolitani, Isar Nassiri, Alex Novak, Darragh O'Brien, Daniel O'Connor, Denise O'Donnell, Graham Ogg, Lauren Overend, Inhye Park, Ian Pavord, Yanchun Peng, Frank Penkava, Mariana Pereira Pinho, Elena Perez, Andrew Pollard, Fiona Powrie, Bethan Psaila, T Phuong Quan, Emmanouela Repapi, Santiago Revale, Laura Silva-Reyes, Jean-Baptiste Richard, Charlotte Rich-Griffin, Thomas Ritter, Christine Rollier, Matthew Rowland, Fabian Ruehle, Mariolina Salio, Stephen Nicholas Sansom, Raphael Sanches Peres, Alberto Santos Delgado, Tatjana Sauka-Spengler, Ron Schwessinger, Giuseppe Scozzafava, Gavin Screaton, Anna Seigal, Malcolm Semple, Martin Sergeant, Christina Simoglou Karali, David Sims, Donal Skelly, Hubert Slawinski, Alberto Sobrinodiaz, Nikolaos Sousos, Lizzie Stafford, Lisa Stockdale, Marie Strickland, Otto Sumray, Bo Sun, Chelsea Taylor, Stephen Taylor, Adan Taylor, Supat Thongjuea, Hannah Thraves, John Todd, Adriana Tomic, Orion Tong, Amy Trebes, Dominik Trzupek, Felicia Anna Tucci, Lance Turtle, Irina Udalova, Holm Uhlig, Erinke van Grinsven, Iolanda Vendrell, Marije Verheul, Alexandru Voda, Guanlin Wang, Lihui Wang, Dapeng Wang, Peter Watkinson, Robert Watson, Michael Weinberger, Justin Whalley, Lorna Witty, Katherine Wray, Luzheng Xue, Hing Yuen Yeung, Zixi Yin, Rebecca Young, Jonathan Youngs, Ping Zhang, Yasemin-Xiomara Zurke, Adrian Banning, Alexios Antonopoulos, Andrew Kelion, Attila Kardos, Benjamin Hudson, Bon-Kwon Koo, Christos Kotanidis, Ciara Mahon, Colin Berry, David Newby, Derek Connolly, Diane Scaletta, Ed Nicol, Elisa McAlindon, Evangelos Oikonomou, Francesca Pugliese, Gianluca Pontone, Giulia Benedetti, Guo-Wei He, Henry West, Hidekazu Kondo, Imre Benedek, Intrajeet Das, John Graby, John Greenwood, Jonathan Rodrigues, Junbo Ge, Keith Channon, Larissa Fabritz, Li-Juan Fan, Lucy Kingham, Marco Guglielmo, Matthias Schmitt, Meinrad Beer, Michelle Anderson, Milind Desai, Mohamed Marwan, Naohiko Takahashi, Nehal Mehta, Neng Dai, Nicholas Screaton, Nikant Sabharwal, Pál Maurovich-Horvat, Rajesh Kharbanda, Rebecca Preston, Richard Wood, Ron Blankstein, Ronak Rajani, Saeed Mirsadraee, Shahzad Munir, Steffen Klömpken, Steffen Petersen, Stephan Achenbach, Susan Anthony, Sze Mak, Tarun Mittal, Theodora Benedek, Vinoda Sharma, and Wen-Hua Lin

Subjects
Inflammation, SARS-CoV-2, lnfectious Diseases and Global Health Radboud Institute for Molecular Life Sciences [Radboudumc 4], Angiography, Medicine (miscellaneous), COVID-19, Health Informatics, State Medicine, Health Information Management, Artificial Intelligence, Cytokines, Humans, Decision Sciences (miscellaneous), Prospective Studies, Tomography, X-Ray Computed
Abstract

Contains fulltext : 286832.pdf (Publisher’s version ) (Open Access) BACKGROUND: Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19. METHODS: For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes. FINDINGS: Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [

Published
2022

5. Relationship between platelet-lymphocyte ratio and carotid atherosclerosis in middle-aged and elderly patients with type 2 diabetes mellitus.

Author

Jing Hu, Kun Zhao, Shao-Ling Yang, Feng-Ling Wang, Qiao-Na Zhang, Lin-Yan Fan, Hong-Zhen Zhang, Wen-Hua Lin, and Jia-Hong Gu

Subjects
ATHEROSCLEROSIS, OLDER patients, BLOOD platelets, CAROTID artery
Abstract

Objective: To investigate the relationship between platelet-lymphocyte ratio (PLR) and carotid atherosclerosis (CAS) in middle-aged and elderly patients with T2DM. Methods: A total of 420 middle-aged and elderly patients with T2DM who were hospitalized in the Endocrinology Department of our hospital from September 2018 to September 2020 and were examined by ultrasound were selected as the subjects. The carotid artery intima-media thickness (CIMT) was examined by color Doppler ultrasonography, including normal CIMT group (n=111), CIMT thickening group (n=103) and CAS plaque group (n=206). The differences of serum PLR levels among the three groups were compared. Multivariate Logistic regression was used to analyze the relationship between PLR and CAS plaque formation. The receiver operating curve (ROC) was used to evaluate the value of multivariate Logistic regression model (Logit P) in the diagnosis of CAS lesions. Results: The mean value of PLR in CAS plaque group (127.86±48.54) was significantly higher than that in CIMT normal group (109.15±48.35). Multivariate Logistic regression analysis showed that after adjusting for other confounding factors, the increase of PLR was an independent risk factor for the occurrence of CAS plaque. ROC showed that the efficacy of multivariate Logit P model in the diagnosis of CAS plaque was (AUC=0.807,95%CI=0.759-0.858). Conclusions: PLR is one of the important risk factors for the occurrence of CAS lesions. At the same time, the multivariate Logistic regression model established in this study has clinical reference value in predicting CAS lesions in middle-aged and elderly patients with T2DM. [ABSTRACT FROM AUTHOR]

Published
2022

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