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Risk factors for adverse clinical outcomes with COVID-19 in China: a multicenter, retrospective, observational study
Peng Peng Xu1, Rong Hua Tian2, Song Luo1
1Department of Medical Imaging, Jinling Hospital, Medical School of Nanjing University, Nanjing, Jiangsu, 210002, China.
Insights
Older age, multiple comorbidities, leukocytosis, lymphopenia, and high CT severity scores are key predictors of adverse outcomes in Coronavirus Disease-19 (COVID-19) patients, aiding early identification and intervention.
Area of Science:
- Medical research
- Infectious diseases
- Radiology
Background:
- Risk factors for adverse events in Coronavirus Disease-19 (COVID-19) require further elucidation.
- Understanding predictors of short-term outcomes is crucial for managing COVID-19 patients.
Purpose of the Study:
- To investigate the predictive value of clinical, laboratory, and CT imaging characteristics on admission for short-term outcomes in COVID-19 patients.
- To identify key risk factors associated with in-hospital death and composite adverse outcomes.
Main Methods:
- Multicenter, retrospective observational study involving 703 laboratory-confirmed COVID-19 patients.
- Data collected included demographics, clinical and laboratory findings, and CT imaging on admission.
- Multivariable Cox regression and Kaplan-Meier analysis were used to identify risk factors for in-hospital death and adverse outcomes (ICU admission, invasive mechanical ventilation).
Main Results:
- 55 patients (8%) experienced adverse outcomes, including 33 deaths.
- Risk factors for in-hospital death included: ≥ 2 comorbidities, leukocytosis, lymphopenia, and CT severity score > 14.
- Risk factors for composite adverse outcomes included: older age, ≥ 2 comorbidities, leukocytosis, lymphopenia, and CT severity score > 14.
Conclusions:
- Older age, multiple comorbidities, leukocytosis, lymphopenia, and a higher CT severity score are significant predictors of adverse events in COVID-19 patients.
- These identified risk factors can assist clinicians in identifying high-risk individuals for timely intervention and improved patient management.
Abstract:
Background: The risk factors for adverse events of Coronavirus Disease-19 (COVID-19) have not been well described. We aimed to explore the predictive value of clinical, laboratory and CT imaging characteristics on admission for short-term outcomes of COVID-19 patients. Methods: This multicenter, retrospective, observation study enrolled 703 laboratory-confirmed COVID-19 patients admitted to 16 tertiary hospitals from 8 provinces in China between January 10, 2020 and March 13, 2020. Demographic, clinical, laboratory data, CT imaging findings on admission and clinical outcomes were collected and compared. The primary endpoint was in-hospital death, the secondary endpoints were composite clinical adverse outcomes including in-hospital death, admission to intensive care unit (ICU) and requiring invasive mechanical ventilation support (IMV). Multivariable Cox regression, Kaplan-Meier plots and log-rank test were used to explore risk factors related to in-hospital death and in-hospital adverse outcomes. Results: Of 703 patients, 55 (8%) developed adverse outcomes (including 33 deceased), 648 (92%) discharged without any adverse outcome. Multivariable regression analysis showed risk factors associated with in-hospital death included ≥ 2 comorbidities (hazard ratio [HR], 6.734; 95% CI; 3.239-14.003, p < 0.001), leukocytosis (HR, 9.639; 95% CI, 4.572-20.321, p < 0.001), lymphopenia (HR, 4.579; 95% CI, 1.334-15.715, p = 0.016) and CT severity score > 14 (HR, 2.915; 95% CI, 1.376-6.177, p = 0.005) on admission, while older age (HR, 2.231; 95% CI, 1.124-4.427, p = 0.022), ≥ 2 comorbidities (HR, 4.778; 95% CI; 2.451-9.315, p < 0.001), leukocytosis (HR, 6.349; 95% CI; 3.330-12.108, p < 0.001), lymphopenia (HR, 3.014; 95% CI; 1.356-6.697, p = 0.007) and CT severity score > 14 (HR, 1.946; 95% CI; 1.095-3.459, p = 0.023) were associated with increased odds of composite adverse outcomes. Conclusion: The risk factors of older age, multiple comorbidities, leukocytosis, lymphopenia and higher CT severity score could help clinicians identify patients with potential adverse events.
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