A Tri-light Warning System for Hospitalized COVID-19 Patients: Credibility-based Risk Stratification under Data Shift

OBJECTIVE To develop a tri-light warning system for the early warning of novel coronavirus pneumonia (COVID-19) and stratification of patients. MATERIALS AND METHODS The system extracts radiomic features from CT images and integrates clinical record information to output a prediction probability and credibility of each prediction. It classifies patients in the general ward into red (high risk), yellow (uncertain risk), and green (low risk) labels. The system was tested using a multi-center cohort of 8,721 patients. RESULTS The system demonstrated reliability and performance validation under data distribution shifts, and was applicable to both the original strain and variant strains of COVID-19. DISCUSSION The tri-light warning system has the potential to improve patient stratification performance and identify epidemiological risks early, thus allowing for timely treatment and optimization of medical resource allocation. CONCLUSION The tri-light warning system based on conformal prediction is a reliable and effective method for the early warning and stratification of COVID-19 patients. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This work was supported by the Young Scientists Fund of the National Natural Science Foundation of China (grant No. 82202150 to Xiao Li). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The protocol of this multi-center study was approved by the institutional review board of Jinling Hospital, Nanjing University School of Medicine (2020NZKY-005-02). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The data that support the findings of this study are available on request from the corresponding author (G.M.L.). The data with participant privacy/consent are not publicly available due to hospital regulation restrictions.