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    Immune Cell-Based versus Albumin-Based Ratios as Outcome Predictors in Critically Ill COVID-19 Patients by Zeba S, Surbatovic M, Udovicic I, Stanojevic I, Vojvodic D, Rondovic G, Mladenovic K, Abazovic T, Hasanovic A, Ilic AN, Abazovic D, Khan W, Djordjevic D

    Published 2025-01-01
    “…Snjezana Zeba,1 Maja Surbatovic,2 Ivo Udovicic,1 Ivan Stanojevic,3 Danilo Vojvodic,3 Goran Rondovic,1 Katarina Mladenovic,1 Tanja Abazovic,2 Almina Hasanovic,4 Aleksandra N Ilic,5 Dzihan Abazovic,6 Wasim Khan,7 Dragan Djordjevic1 1Clinic of Anesthesiology and Intensive Therapy, Military Medical Academy, Faculty of Medicine of the Military Medical Academy, University of Defense, Belgrade, Serbia; 2Clinic of Anesthesiology and Intensive Therapy, Military Medical Academy, Belgrade, Serbia; 3Institute for Medical Research, Military Medical Academy, Faculty of Medicine of the Military Medical Academy, University of Defense, Belgrade, Serbia; 4Nephrology Clinic, Military Medical Academy, Belgrade, Serbia; 5Faculty of Medicine, University of Pristina, Kosovska Mitrovica, Serbia; 6Atlas Hospital, Belgrade, Serbia, Aba Medica Healthcare Centre, Ulcinj, Montenegro; 7Division of Trauma & Orthopaedic Surgery, University of Cambridge, Addenbrooke’s Hospital, Cambridge, CB2 2QQ, UKCorrespondence: Maja Surbatovic, Clinic of Anesthesiology and Intensive Therapy, Military Medical Academy, 17 Crnotravska Street, Belgrade, 11000, Serbia, Tel +381 11 2665 125, Email maja.surbatovic@gmail.comPurpose: The aim of the retrospective, single-center study was to assess the prognostic value of immune cell-based and albumin-based ratios regarding lethal outcome in critically ill COVID-19 patients.Patients and Methods: We analyzed 612 adult critically ill COVID-19 patients admitted to the intensive care unit (ICU) between April 2020 and November 2022. …”
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    Assessing the Effectiveness of Interactive Robot-Assisted Virtual Health Coaching for Health Literacy and Disease Knowledge of Patients with Chronic Kidney Disease: Quasiexperiment... by Nai-Jung Chen, Ching-Hao Chang, Chiu-Mieh Huang, Fen-He Lin, Li-Ting Lu, Kuan-Yi Liu, Chih-Lin Lai, Chin-Yao Lin, Yi-Chou Hou, Jong-Long Guo

    Published 2025-01-01
    “…Despite the challenges posed by the COVID-19 pandemic, which constrained sample sizes, the findings indicate that this program is a promising patient education tool in clinical nephrology. Future research should involve larger sample sizes to enhance generalizability and examine additional factors influencing effectiveness.…”
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    Prediction of Acute Kidney Injury for Critically Ill Cardiogenic Shock Patients with Machine Learning Algorithms by Zhang X, Xiong Y, Liu H, Liu Q, Chen S

    Published 2025-01-01
    “…Xiaofei Zhang,1,* Yonghong Xiong,2,* Huilan Liu,3 Qian Liu,4 Shubin Chen5 1Department of Gerontology, China Aerospace Science & Industry Corporation 731 hospital, Beijing, People’s Republic of China; 2Department of Cardiology, Beijing Feng Tai Hospital, Beijing, People’s Republic of China; 3Department of Nephrology, Zhongnan Hospital of Wuhan University, Wuhan, People’s Republic of China; 4Department of Cardiology, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, People’s Republic of China; 5Department of Intensive Care Unit, China Aerospace Science & Industry Corporation 731 hospital, Beijing, People’s Republic of China*These authors contributed equally to this workCorrespondence: Qian Liu, Department of Cardiology, Wuhan Children’s Hospital, Tongji Medical College, Huazhong University of Science & Technology, No. 100 of Xianggang Road, Jiangan District, Wuhan, 430015, People’s Republic of China, Tel +86027-82433350, Email qian_liu1124@126.com Shubin Chen, Department of Intensive Care Unit, China Aerospace Science & Industry Corporation 731 hospital, No. 3 Zhen Gang Nan Li, Yun Gang Town, Feng Tai District, Beijing, 100074, People’s Republic of China, Tel +86010-68374065, Email 18610074016@163.comBackground: The aim of this study was to use five machine learning approaches and logistic regression to design and validate the acute kidney injury (AKI) prediction model for critically ill individuals with cardiogenic shock (CS).Methods: All patients who diagnosed with CS from the MIMIC-IV database, the eICU database, and Zhongnan hospital of Wuhan university were included in this study. …”
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