A pre-admission triaging tool to predict severe COVID-19 cases: ABCD score

Area of Science:

• Infectious Diseases
• Public Health
• Clinical Medicine

Background:

• Isolation of SARS-CoV-2 infected individuals is crucial for pandemic control.
• While most COVID-19 cases are uncomplicated, a subset develops severe, life-threatening disease.
• Effective pre-admission triaging is needed to identify high-risk individuals.

Purpose of the Study:

• To develop and validate a pre-admission tool for predicting severe COVID-19.
• To identify key clinical factors associated with severe disease progression.

Main Methods:

• Retrospective study of SARS-CoV-2 PCR-confirmed individuals (≥13 years) from October 2020 to January 2021.
• Disease severity assessed on admission and daily; severe COVID-19 defined by specific clinical criteria.
• Univariate and multivariate analyses performed using SPSS Statistics.

Main Results:

• Age ≥ 60 years, BMI ≥ 30.0, illness presentation on days 7-12, and ≥1 comorbidity were significantly associated with severe COVID-19.
• A scoring system based on these four variables demonstrated high predictive value (NPV 95.0%).
• A total score ≥2 indicated severe COVID-19 with 60.9% sensitivity and 88.2% specificity.

Conclusions:

• A simple pre-admission scoring system can effectively stratify COVID-19 patients by severity risk.
• This tool can assist healthcare providers in optimizing isolation placement and resource allocation.
• Early risk assessment is vital for managing the COVID-19 pandemic effectively.