ArticleCureus2024
Analysis of Risk Factors for Death in the Coronavirus Disease 2019 (COVID-19) Population: Data Analysis from a Large General Hospital in Anhui, China.
Article in Cureus, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Red Blood Cell-Related Phenotype-Genotype Correlations in Chronic and Acute Critical Illnesses (Traumatic Brain Injury Cohort and COVID-19 Cohort).International journal of molecular sciences · 2025Article
- A tri-light warning system for hospitalized COVID-19 patients: Credibility-based risk stratification for future pandemic preparedness.European journal of radiology open · 2024Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
During the coronavirus disease 2019 (COVID-19) pandemic, clinical prevention, early diagnosis, and hematological monitoring were challenging areas. This study aims to compare risk factors and hematological and biochemical data in non-survivor group patients with COVID-19 versus survivor group patients. A total of 204 patients with COVID-19 were selected as research subjects from December 2022 to January 2023. We analyzed the age, sex, time from onset to admission, and laboratory test indicators upon admission. The differences between surviving and deceased patients and mortality-related risk factors were examined. Among the 204 patients, 168 survived, whereas 36 died during hospitalization. Significant differences were observed between the two groups with COVID-19 across various factors, including age (p < 0.0001), WBC count (p < 0.0001), RBC count (p < 0.05), neutrophils (p < 0.0001), lymphocytes (p < 0.05), mean corpuscular hemoglobin concentration (MCHC) (p < 0.0001), RBC distribution width-standard deviation (RDW-SD) (p < 0.0001), RBC distribution width coefficient of variation (RDW-CV) (p < 0.0001), aspartate aminotransferase (AST) (p < 0.05), albumin (ALB) (p < 0.0001), creatinine (CR) (p < 0.0001), uric acid (UA) (p < 0.0001), blood urea nitrogen (BUN) (p < 0.0001), plasma thrombin time (TT) (p < 0.05), prothrombin time (PT) (p < 0.0001), and D-dimer (p < 0.0001). Multivariate logistic analysis revealed that older age, CR, UA, and ALB were independent factors associated with death (p < 0.05). Elderly patients with underlying diseases, abnormal routine blood test indices, and abnormal renal function and coagulation indices are at an increased worse prognosis and should be identified early. Age, UA, CR, and ALB can be used as predictors to assess the worse prognosis in the hospital.
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