1. External Validation and Recalibration of the CURB-65 and PSI for Predicting 30-Day Mortality and Critical Care Intervention in Multiethnic Patients with COVID-19
- Author
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Samah Taha, Fatima Emam, Waleed Awad Salem, Maryam Al-Hitmi, Ibrahim Abdelhafez, Amr Elmoheen, Khoulod Mohamed, Mona Saad, Nauman Arshad, Khalid Bashir, Aftab Azad, Ali Elkandow, Amina Tarig, and Mohamed Bahgat
- Subjects
Microbiology (medical) ,medicine.medical_specialty ,Critical Care ,Pneumonia severity index ,Infectious and parasitic diseases ,RC109-216 ,Hematocrit ,Logistic regression ,Severity of Illness Index ,Article ,Lasso (statistics) ,Severity of illness ,medicine ,Humans ,critical care intervention ,PSI ,Hospital Mortality ,Retrospective Studies ,CURB-65 ,medicine.diagnostic_test ,business.industry ,SARS-CoV-2 ,Area under the curve ,COVID-19 ,Retrospective cohort study ,General Medicine ,Pneumonia ,Prognosis ,mortality ,humanities ,Community-Acquired Infections ,Infectious Diseases ,Emergency medicine ,business - Abstract
Objectives: To validate and recalibrate the CURB-65 and pneumonia severity index (PSI) in predicting 30-day mortality and critical care intervention (CCI) in a multiethnic population with COVID-19, along with evaluating both models in predicting CCI. Methods: Retrospective data was collected for 1181 patients admitted to the largest hospital in Qatar with COVID-19 pneumonia. The area under the curve (AUC), calibration curves, and other metrics were bootstrapped to examine the performance of the models. Variables constituting the CURB-65 and PSI scores underwent further analysis using the Least Absolute Shrinkage and Selection Operator (LASSO) along with logistic regression to develop a model predicting CCI. Complex machine learning models were built for comparative analysis. Results: The PSI performed better than CURB-65 in predicting 30-day mortality (AUC 0.83, 0.78 respectively), while CURB-65 outperformed PSI in predicting CCI (AUC 0.78, 0.70 respectively). The modified PSI/CURB-65 model (respiratory rate, oxygen saturation, hematocrit, age, sodium, and glucose) predicting CCI had excellent accuracy (AUC 0.823) and good calibration. Conclusions: Our study recalibrated, externally validated the PSI and CURB-65 for predicting 30-day mortality and CCI, and developed a model for predicting CCI. Our tool can potentially guide clinicians in Qatar to stratify patients with COVID-19 pneumonia.
- Published
- 2021