Electrocardiogram abnormalities and higher body mass index as clinically applicable factors for predicting poor outcome in patients with coronavirus disease 2019
Zhidan Sun1
Yan Hou2
Zheng Zhang3
Benzhi Cai1
Jinliang Li4
1.Department of Pharmacy, The Second Affiliated Hospital of Harbin Medical University, Harbin 150086, China2.Department of Epidemiology and Biostatistics, Public Health School, Harbin Medical University, Harbin 150081, China3.Department of Critical Care Medicine, Harbin Infectious Disease Hospital, Harbin 150030, China4.Department of Cardiology, Harbin Infectious Disease Hospital, Harbin 150030, China
摘要：Background: Patients with coronavirus disease 2019 (COVID-19) have high resource utilization. Identifying the causes of severe COVID-19 is helpful for early intervention to reduce the consumption of medical resources. Methods: We included 103 patients with COVID-19 in this single-center observational study. To evaluate the incidence, predictors, and effects of COVID-19, we analyzed demographic information, laboratory results, comorbidities, and vital signs as factors for association with severe COVID-19. Results: The incidence of severe COVID-19 was 16.5％ and the percent poor outcome (including mortality, entering in ICU or transferred to a superior hospital) was 6.8％. The majority of severe COVID-19 patients had abnormal electrocardiogram (ECG) (82.35％), hypertension (76.47％) and other cardiac diseases (58.82％). Multivariate logistic regression was used to determine the predictors of severe illness. Abnormal body mass index (BMI) and ECG (P < 0.05) were independent predictors of severe COVID-19. ECG abnormality was associated with increased odds of poor outcome (area under the receiver operating characteristic curves [AUC], 0.793; P = 0.010) and severe COVID-19 (AUC, 0.807; P < 0.0001). Overweight was also associated with increased odds of poor outcome (AUC, 0.728; P = 0.045) and severe illness COVID-19 (AUC, 0.816; P < 0.0001). Conclusion: Overweight and electrophysiological disorders on admission are important predictors of prognosis of patients with COVID-19.
机标关键词：trocarhigherindexgrammasswithcardardi
论文发表日期：2022-10-30
在线出版日期：2025-08-15（本平台首次上网日期，不代表文献的发表时间）
页数：6( 251-256 )
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