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Clin Pathol
. 2022 Jan 7;15:2632010X211068427.
doi: 10.1177/2632010X211068427. eCollection Jan-Dec 2022.
Practical Risk Scoring System for Predicting Severity of COVID-19 Disease
Jeffrey Petersen 1 2 , Darshana Jhala 1 2
Affiliations
- PMID: 35024610
- PMCID: PMC8744169
- DOI: 10.1177/2632010X211068427
Abstract
Objectives: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19 disease, has become an international pandemic with numerous casualties. It had been noted that the severity of the COVID-19 disease course depends on several clinical, laboratory, and radiological factors. This has led to risk scoring systems in various populations such as in China, but similar risk scoring systems based on the American veteran population are sparse, particularly with the vulnerable Veteran population. As a simple risk scoring system would be very useful, we propose a simple Jhala Risk Scoring System (JRSS) to assess the severity of disease risk.
Methods: A retrospective review of all SARS-CoV-2 reverse transcriptase-polymerase chain reaction (RT-PCR) tests collected and performed at the regional Veterans Administration Medical Center (VAMC) serving the Philadelphia and surrounding areas from March 17th, 2020 to May 20th, 2020. Data was collected and analyzed in the same year. These tests were reviewed within the computerized medical record system for demographic, medical history, laboratory test history, and clinical course. Information from the medical records were then scored based on the criteria of the Jhala Risk Scoring System (JRSS).
Results: The JRSS, based on age, ethnicity, presence of any lung disease, presence of cardiovascular disease, smoking history, and diabetes history with laboratory parameters correlated and predicted (with statistical significance) which patients would be hospitalized.
Conclusion: The JRSS may play a role in informing which COVID-19 positive patients in the emergency room/urgent care for risk stratification.
Keywords: COVID-19; Clinical Prognosis; SARS-CoV-2; clinical pathology; epidemiology; evidence-based medicine; quality assurance; risk scoring.