Association of Overlapped and Un-overlapped Comorbidities with COVID-19 Severity and Treatment Outcomes: A Retrospective Cohort Study from Nine Provinces in China

Abstract

Objective

Several COVID-19 patients have overlapping comorbidities. The independent role of each component contributing to the risk of COVID-19 is unknown, and how some non-cardiometabolic comorbidities affect the risk of COVID-19 remains unclear.

Methods

A retrospective follow-up design was adopted. A total of 1,160 laboratory-confirmed patients were enrolled from nine provinces in China. Data on comorbidities were obtained from the patients’ medical records. Multivariable logistic regression models were used to estimate the odds ratio (OR) and 95% confidence interval (95% CI) of the associations between comorbidities (cardiometabolic or non-cardiometabolic diseases), clinical severity, and treatment outcomes of COVID-19.

Results

Overall, 158 (13.6%) patients were diagnosed with severe illness and 32 (2.7%) had unfavorable outcomes. Hypertension (2.87, 1.30–6.32), type 2 diabetes (T2DM) (3.57, 2.32–5.49), cardiovascular disease (CVD) (3.78, 1.81–7.89), fatty liver disease (7.53, 1.96–28.96), hyperlipidemia (2.15, 1.26–3.67), other lung diseases (6.00, 3.01–11.96), and electrolyte imbalance (10.40, 3.00–26.10) were independently linked to increased odds of being severely ill. T2DM (6.07, 2.89–12.75), CVD (8.47, 6.03–11.89), and electrolyte imbalance (19.44, 11.47–32.96) were also strong predictors of unfavorable outcomes. Women with comorbidities were more likely to have severe disease on admission (5.46, 3.25–9.19), while men with comorbidities were more likely to have unfavorable treatment outcomes (6.58, 1.46–29.64) within two weeks.

Conclusion

Besides hypertension, diabetes, and CVD, fatty liver disease, hyperlipidemia, other lung diseases, and electrolyte imbalance were independent risk factors for COVID-19 severity and poor treatment outcome. Women with comorbidities were more likely to have severe disease, while men with comorbidities were more likely to have unfavorable treatment outcomes.

Biographies

Biographical notes of the first authors: MA Yan, female, born in 1980, MD, majoring in epidemiology, prevention and control of infectious disease

ZHU Dong Shan, male, born in 1982, PhD, longitudinal study and life course epidemiology

CHEN Ren Bo, male, born in 1980, PhD, majoring in diagnosis and treatment of chronic pathology in Chinese medicine

SHI Nan Nan, female, born in 1982, PhD, majoring in prevention and control of infectious disease, formulation of clinical practice Guidelines for Traditional Chinese Medicine

LIU Si Hong, female, born in 1989, PhD, majoring in data mining of Traditional Chinese Medicine literature.