Mortality Prediction of COVID-19 in Hospitalized Patients Using the 2020 Diagnosis Procedure Combination Administrative Database of Japan

Objectives Numerous people have died from coronavirus disease 2019 (COVID-19) infection. Identifying crucial predictive biomarkers of disease mortality is critical to support decision-making and logistic planning in healthcare systems. This study investigated the association between mortality and medical factors and prescription records in 2020 in Japan, where COVID-19 prevalence and mortality remain relatively low.Methods This retrospective cohort study analyzed anonymous administrative data from the Diagnosis Procedure Combination (DPC) database in Japan.Results A total of 22,795 patients were treated in DPC hospitals in 2020 in Japan, and of these, 5,980 patients over 50 years old were hospitalized, with 299 (5.0%) dying. There were 2,399 severe patients among 11,440 total hospitalized patients (all ages). The results of a logistic model analysis revealed that an older age, male sex, Parkinson's disease, cerebrovascular diseases, and chronic kidney diseases were risk factors for mortality. A machine learning analysis identified an older age, male sex (mortality), pneumonia, drugs for nal disorders, drugs for obstructive airway diseases, topical products for joint and muscular pain, diabetes, lipid-modifying agents, calcium channel blockers, drugs for diabetes, and agents acting on the reninConclusions This COVID-19 mortality risk tool is a well-calibrated and accurate model for predicting mortality risk among hospitalized patients with COVID-19 in Japan, which is characterized by a relatively low COVID-19 prevalence, aging society, and high population density. This COVID-19 mortality prediction model can assist in resource utilization and patient and caregiver education and be useful as a risk stratification instrument for future research trials.

Automated summary

This study investigated the association between mortality and medical factors and prescription records in Japan in 2020. The results showed that age, sex, Parkinson's disease, cerebrovascular diseases, and chronic kidney diseases were risk factors for mortality. The COVID-19 mortality risk tool proposed in this study can support decision-making and resource utilization.