@article{203d938ebcf04a4ea85988130c7093a1,
title = "High admission blood glucose independently predicts poor prognosis in COVID-19 patients: A systematic review and dose-response meta-analysis",
abstract = "Aims: To investigate the prognostic value of admission blood glucose (BG) in predicting COVID-19 outcomes, including poor composite outcomes (mortality/severity), mortality, and severity. Methods: Eligible studies evaluating the association between admission fasting BG (FBG) and random BG (RBG) levels with COVID-19 outcomes were included and assessed for risk of bias with the Quality in Prognosis Studies tool. Random-effects dose-response meta-analysis was conducted to investigate potential linear or non-linear exposure-response gradient. Results: The search yielded 35 studies involving a total of 14,502 patients. We discovered independent association between admission FBG and poor COVID-19 prognosis. Furthermore, we demonstrated non-linear relationship between admission FBG and severity (Pnon-linearity < 0.001), where each 1 mmol/L increase augmented the risk of severity by 33% (risk ratio 1.33 [95% CI: 1.26–1.40]). Albeit exhibiting similar trends, study scarcity limited the evidence strength on the independent prognostic value of admission RBG. GRADE assessment yielded high-quality evidence for the association between admission FBG and COVID-19 severity, and moderate-quality evidence for its association with mortality and poor outcomes. Conclusion: High admission FBG level independently predicted poor COVID-19 prognosis. Further research to confirm the prognostic value of admission RBG and to ascertain the estimated dose-response risk between admission FBG and COVID-19 severity are required.",
keywords = "Blood glucose, COVID-19, Fasting, Patient admission, Prognosis",
author = "Gilbert Lazarus and Jessica Audrey and Wangsaputra, {Vincent Kharisma} and Alice Tamara and Tahapary, {Dicky L.}",
note = "Funding Information: The authors would like to express their gratitude to Dr. Long Qi (Department of Critical Care Medicine, Hubei Provincial Hospital of Traditional Chinese Medicine, China), Dr. Ting Chen (Department of Endocrinology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, China), as well as Prof. Gian Paolo Fadini and Dr. Mario Luca Morieri (Department of Medicine, University of Padova, Italy) for the provision of additional data for analysis. The authors would also like to thank Dr. Miguel Marcos (Department of Internal Medicine, University Hospital of Salamanca-IBSAL, University of Salamanca, Spain), Dr. Celestino Sardu (Department of Advanced Medical and Surgical Sciences, University of Campania ?Luigi Vanvitelli,?, Italy), Prof. Giuseppe Penno (Section of Diabetes and Metabolic Diseases, University of Pisa, Italy) and Dr. Juan Berenguer (Hospital General Universitario Gregorio Mara??n, Spain) for the confirmation of study settings. Lastly, the authors would like to acknowledge Dr. Eka Dian Safitri (Clinical Epidemiology and Evidence-Based Medicine Unit, Dr. Cipto Mangunkusumo General Hospital - Faculty of Medicine Universitas Indonesia, Jakarta, Indonesia) and Dr. Besral (Department of Biostatistics, School of Public Health University of Indonesia, Depok, West Java, Indonesia) for the methodological and statistical advices. GL and DLT conceptualized the idea for the project and designed the methodology. GL, JA, VKW, and AT performed the literature search, study screening, and data abstraction. GL administered the study protocol, undertook the formal analysis, and visualized the results. GL, JA, and VKW developed the risk of bias tool and drafted the manuscript, and risk of bias assessment was conducted by JA and VKW. GL, VKW, AT, and DLT reviewed and edited the manuscript for final submission. DLT validated and supervised the project. All authors have approved of the final manuscript for publication. This project received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Publisher Copyright: {\textcopyright} 2020 Elsevier B.V. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.",
year = "2021",
month = jan,
doi = "10.1016/j.diabres.2020.108561",
language = "English",
volume = "171",
journal = "Diabetes Research and Clinical Practice",
issn = "0168-8227",
publisher = "Elsevier Ireland Ltd",
}
