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Risk factors for mortality in critically ill patients with COVID-19 in Huanggang, China: A single-center multivariate
Yinyin Chen1,2,3, Zeqiang Linli4,5, Yuting Lei1
1Department of Nephrology and Laboratory of Kidney Disease, Hunan Provincial People's Hospital, Hunan Normal University, Changsha, China.
Insights
Simple patient indicators like age and symptom duration are key predictors of mortality in critically ill COVID-19 patients. Early identification of these risk factors can improve patient outcomes.
Area of Science:
- Critical Care Medicine
- Infectious Diseases
- Biostatistics
Background:
- COVID-19 has a global impact, with limited understanding of mortality risk factors in critically ill patients.
- Detailed self-reported and laboratory indicators for predicting COVID-19 mortality require further investigation.
Purpose of the Study:
- To identify and analyze risk factors for mortality in critically ill COVID-19 patients.
- To develop a predictive model for COVID-19 mortality using self-evaluation and laboratory data.
Main Methods:
- Retrospective analysis of 192 critically ill COVID-19 patients (142 survivors, 50 non-survivors).
- Comparison of demographic, clinical, symptom, and laboratory data between survivors and non-survivors.
- Multivariate pattern analysis (MVPA) to identify significant mortality predictors.
Main Results:
- MVPA model achieved 93% classification accuracy using both self-evaluation and laboratory indicators.
- Key self-evaluation risk factors for mortality included age, illness duration, and Barthel Index score.
- Laboratory indicators like C-reactive protein, WBC, platelet count, fibrin degradation products, oxygenation index, lymphocyte count, and d-dimer were also significant predictors.
- Illness duration was identified as the strongest predictor of all-cause mortality.
Conclusions:
- Accessible self-evaluation indicators, alongside laboratory results, can predict mortality in critically ill COVID-19 patients.
- A predictive model utilizing these factors can aid clinicians in identifying high-risk individuals.
- This approach can enhance public health awareness and inform clinical decision-making for COVID-19 patient management.
Abstract:
To date, the coronavirus disease 2019 (COVID-19) has a worldwide distribution. Risk factors for mortality in critically ill patients, especially detailed self-evaluation indicators and laboratory-examination indicators, have not been well described. In this paper, a total of 192 critically ill patients (142 were discharged and 50 died in the hospital) with COVID-19 were included. Self-evaluation indicators including demographics, baseline characteristics, and symptoms and detailed lab-examination indicators were extracted. Data were first compared between survivors and nonsurvivors. Multivariate pattern analysis (MVPA) was performed to identify possible risk factors for mortality of COVID-19 patients. MVPA achieved a relatively high classification accuracy of 93% when using both self-evaluation indicators and laboratory-examination indicators. Several self-evaluation factors related to COVID-19 were highly associated with mortality, including age, duration (time from illness onset to admission), and the Barthel index (BI) score. When the duration, age increased by 1 day, 1 year, BI decreased by 1 point, the mortality increased by 3.6%, 2.4%, and 0.9% respectively. Laboratory-examination indicators including C-reactive protein, white blood cell count, platelet count, fibrin degradation products, oxygenation index, lymphocyte count, and d-dimer were also risk factors. Among them, duration was the strongest predictor of all-cause mortality. Several self-evaluation indicators that can simply be obtained by questionnaires and without clinical examination were the risk factors of all-cause mortality in critically ill COVID-19 patients. The prediction model can be used by individuals to improve health awareness, and by clinicians to identify high-risk individuals.
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