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    Systemic Immune-Inflammation Index (SII) and Neutrophil-to-Lymphocyte Ratio (NLR): A Strong Predictor of Disease Severity in Large-Artery Atherosclerosis (LAA) Stroke Patients by Liu K, Yang L, Liu Y, Zhang Y, Zhu J, Zhang H, He Z

    Published 2025-01-01
    “…Keting Liu,1,2,* Li Yang,1,* Yang Liu,3 Yun Zhang,1 Juncheng Zhu,4 Haofeng Zhang,5 Zemin He6 1Department of Neurology, Chengdu Seventh People’s Hospital (Affiliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan Province, 610213, People’s Republic of China; 2Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong Province, 510515, People’s Republic of China; 3Department of Clinical Medicine, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, 610075, People’s Republic of China; 4Department of Radiology, Chengdu Seventh People’s Hospital (Affiliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan Province, 610213, People’s Republic of China; 5Department of Information, Chengdu Seventh People’s Hospital (Affiliated Cancer Hospital of Chengdu Medical College), Chengdu, Sichuan Province, 610213, People’s Republic of China; 6Department of Thoracic Surgery, The First People’s Hospital of Shuangliu District (West China Airport Hospital of Sichuan University), Chendu, Sichuan Province, 610200, People’s Republic of China*These authors contributed equally to this workCorrespondence: Zemin He, Email 993092572@qq.comBackground: Systemic immune-inflammation index (SII) and neutrophil-to-lymphocyte ratio (NLR) are novel inflammatory markers based on neutrophil, platelet and lymphocyte counts. …”
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    Rapid identification and phenotyping of nonalcoholic fatty liver disease patients using a machine‐based approach in diverse healthcare systems by Anna O. Basile, Anurag Verma, Leigh Anne Tang, Marina Serper, Andrew Scanga, Ava Farrell, Brittney Destin, Rotonya M. Carr, Anuli Anyanwu‐Ofili, Gunaretnam Rajagopal, Abraham Krikhely, Marc Bessler, Muredach P. Reilly, Marylyn D. Ritchie, Nicholas P. Tatonetti, Julia Wattacheril

    Published 2025-01-01
    “…The algorithm uses the Observational Medical Outcomes Partnership (OMOP) Common Data Model and queries structured and unstructured data elements, including diagnosis codes, laboratory measurements, and radiology and pathology modalities. Our approach identified 16,006 CUIMC NAFLD patients, 10,753 (67%) previously unidentifiable by NAFLD diagnosis codes. …”
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