Abstract
Certain high-risk factors related to the death of COVID-19 have been reported, however, there were few studies on a death prediction model. This study was conducted to delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) of different degree and establish a death prediction model. In this multi-centered, retrospective, observational study, we enrolled 523 COVID-19 cases discharged before February 20, 2020 in Henan Province, China, compared clinical data, screened for high-risk fatal factors, built a death prediction model and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan. Out of the 523 cases, 429 were mild, 78 severe survivors, 16 non-survivors. The non-survivors with median age 71 were older and had more comorbidities than the mild and severe survivors. Non-survivors had a relatively delay in hospitalization, with higher white blood cell count, neutrophil percentage, D-dimer, LDH, BNP, and PCT levels and lower proportion of eosinophils, lymphocytes and albumin. Discriminative models were constructed by using random forest with 16 non-survivors and 78 severe survivors. Age was the leading risk factors for poor prognosis, with AUC of 0.907 (95% CI 0.831–0.983). Mixed model constructed with combination of age, demographics, symptoms, and laboratory findings at admission had better performance (p = 0.021) with a generalized AUC of 0.9852 (95% CI 0.961–1). We chose 0.441 as death prediction threshold (with 0.85 sensitivity and 0.987 specificity) and validated the model in 429 mild cases, six fatal cases discharged after February 16, 2020 from Henan and 14 cases from Wuhan successfully. Mixed model can accurately predict clinical outcomes of COVID-19 patients.
Highlights
In late December 2019, Wuhan City, Hubei Province, China found several cases of unexplained pneumonia
Henan Province has a large population of 95.593 million people, bordering Hubei Province, China
We collected data of 523 confirmed COVID-19 cases who had been discharged from 18 cities in Henan Province before February 20, 2020 and conducted statistical analysis
Summary
In late December 2019, Wuhan City, Hubei Province, China found several cases of unexplained pneumonia. On January 12, 2020, the World Health Organization temporarily named this new virus 2019 novel coronavirus (2019-nCoV). On February 11, 2020, the World Health Organization announced that the same time the International Virus Classification Committee named the new coronavirus “SARS-CoV-2.”. SARS-CoV-2 can cause pneumonia and systemic inflammation, leading to multiple organ failure in high-risk patients. How to quickly identify high-risk patients in the early stage of the disease and actively adopt supportive treatment to reduce mortality is an urgent problem to be solved in the clinic. Using admission characteristics and laboratory test results to establish a predictive model can calculate the probability of over-all mortality due to SARS-CoV-2, identify high-risk patients as early as possible and give support to reduce mortality as soon as possible
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