CHEST Guidelines-Risk-Factors-of-Fatal-Outcome-in-Hospitalized-Subj

Risk-Factors-of-Fatal-Outcome-in-Hospitalized-Subj

Pdf Summary

This study aimed to identify risk factors associated with fatal outcomes in COVID-19 patients through a multivariate Cox regression analysis and a nomogram model, using data from a nationwide cohort of 1,590 hospitalized patients in China. The researchers found that certain factors were significantly associated with higher mortality rates. These included advanced age (particularly those over 75), the presence of coronary heart disease and cerebrovascular disease, the symptom of dyspnea, elevated procalcitonin levels, and elevated aspartate aminotransferase levels.<br /><br />The study used a Kaplan-Meier method and Cox proportional hazards model to analyze the prognostic effects of these variables. A nomogram, which is a predictive tool, was developed and demonstrated good discriminatory power with a C-index of 0.91, indicating that it effectively predicted the clinical outcomes of COVID-19 patients.<br /><br />The findings underscore the importance of early identification, enhanced surveillance, and appropriate therapy for high-risk patients. Despite the limitations of retrospective data collection and the exclusion of a validation cohort, this study provides valuable insight into factors that can predict severe outcomes in COVID-19, facilitating better preparedness and patient management strategies.<br /><br />In summary, the study highlights advanced age, specific chronic diseases, and certain clinical indicators as independent risk factors for COVID-19 mortality. The use of a nomogram based on these findings can help predict patient outcomes and guide treatment decisions.

Keywords

COVID-19

risk factors

mortality

Cox regression

nomogram model

prognostic analysis

advanced age

chronic diseases

predictive tool

patient management