tetano
Editor, Senior Moderator
Eur Rev Med Pharmacol Sci
. 2023 Jan;27(1):384-394.
doi: 10.26355/eurrev_202301_30892.
Development and validation of COVID-19 Radiological Risk Score (COVID-RRS): a multivariable radiological score to estimate the in-hospital mortality risk in COVID-19 patients
W Schmidt[SUP] 1 [/SUP], K Pawlak-Buś, B Jóźwiak, K Katulska, P Leszczyński
Affiliations
Abstract
Objective: To develop and validate in-hospital mortality risk score comprising radiological aberrances in chest computed tomography (CT) performed on admission.
Patients and methods: Single-center, longitudinal cohort study in adult patients admitted with Coronavirus Disease 2019 (COVID-19) to our ward. Patients were followed-up during hospitalization until discharge or death. Eligibility criteria for the study comprised positive real-time reverse transcription-polymerase chain reaction test (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and ground-glass opacities in chest CT. In-hospital death was the outcome of interest. Radiological, laboratory, and clinical data were analyzed. Radiological determinants of mortality were used as variables in multivariate logistic regression analysis, and results were used to build a radiological risk score.
Results: 371 patients were enrolled in development and validation cohorts (181 and 190 respectively), with a total of 47 non-survivors. Univariate analysis data determined 12 predictive factors (nine risk and three protective). In multivariate analysis, we developed COVID-RRS (COVID-19 Radiological Risk Score) - a radiological score predicting in-hospital COVID-19 mortality risk comprising estimated lung involvement percentage, pleural effusion, and domination of consolidation-type changes in chest CT. Our score was superior in the prediction of COVID-19 mortality to the percentage of lung involvement alone, Chest Computed Tomography Severity Score (CTSS), and Total Severity Score (TSS) in both groups with AUC of 0.910 and 0.902, respectively (p <0.001).
Conclusions: Additional imaging features independently contribute to COVID-19 mortality risk. Our model comprising lung involvement estimation, pleural effusion, and domination of consolidations performed significantly better than scores based on the extent of the changes alone. COVID-RRS is a simple, reliable, and ready-to-use tool for clinical practice.
. 2023 Jan;27(1):384-394.
doi: 10.26355/eurrev_202301_30892.
Development and validation of COVID-19 Radiological Risk Score (COVID-RRS): a multivariable radiological score to estimate the in-hospital mortality risk in COVID-19 patients
W Schmidt[SUP] 1 [/SUP], K Pawlak-Buś, B Jóźwiak, K Katulska, P Leszczyński
Affiliations
- PMID: 36647887
- DOI: 10.26355/eurrev_202301_30892
Abstract
Objective: To develop and validate in-hospital mortality risk score comprising radiological aberrances in chest computed tomography (CT) performed on admission.
Patients and methods: Single-center, longitudinal cohort study in adult patients admitted with Coronavirus Disease 2019 (COVID-19) to our ward. Patients were followed-up during hospitalization until discharge or death. Eligibility criteria for the study comprised positive real-time reverse transcription-polymerase chain reaction test (RT-PCR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and ground-glass opacities in chest CT. In-hospital death was the outcome of interest. Radiological, laboratory, and clinical data were analyzed. Radiological determinants of mortality were used as variables in multivariate logistic regression analysis, and results were used to build a radiological risk score.
Results: 371 patients were enrolled in development and validation cohorts (181 and 190 respectively), with a total of 47 non-survivors. Univariate analysis data determined 12 predictive factors (nine risk and three protective). In multivariate analysis, we developed COVID-RRS (COVID-19 Radiological Risk Score) - a radiological score predicting in-hospital COVID-19 mortality risk comprising estimated lung involvement percentage, pleural effusion, and domination of consolidation-type changes in chest CT. Our score was superior in the prediction of COVID-19 mortality to the percentage of lung involvement alone, Chest Computed Tomography Severity Score (CTSS), and Total Severity Score (TSS) in both groups with AUC of 0.910 and 0.902, respectively (p <0.001).
Conclusions: Additional imaging features independently contribute to COVID-19 mortality risk. Our model comprising lung involvement estimation, pleural effusion, and domination of consolidations performed significantly better than scores based on the extent of the changes alone. COVID-RRS is a simple, reliable, and ready-to-use tool for clinical practice.