Validation of PSI/PORT, CURB‐65 and SCAP scoring system in COVID‐19 pneumonia for prediction of disease severity and 14‐day mortality

Anurag, Aditya; Preetam, Mukul

doi:10.1111/crj.13326

Cited by 23 publications

(18 citation statements)

References 5 publications

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Section: Discussionmentioning

confidence: 98%

“…While many studies showed the PSI and CURB-65 systems to be beneficial in the assessment of COVID-19 severity and good predictors of mortality, some found other scoring systems better. SCAP score (Severe Community-Acquired Pneumonia) was found to be a more accurate marker of 14-day mortality ( Anurag and Preetam, 2021 ). Another cohort found the COVID-GRAM score as the preferred means to identify patients with higher mortality with pneumonia caused by SARS-CoV-2 ( Esteban Ronda et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

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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

Elmoheen¹,

Abdelhafez²,

Salem³

et al. 2021

International Journal of Infectious Diseases

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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.

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Section: Discussionmentioning

confidence: 98%

Section: Discussionmentioning

confidence: 99%

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

Elmoheen¹,

Abdelhafez²,

Salem³

et al. 2021

International Journal of Infectious Diseases

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“…Despite in the early phase of pandemic several other COVID-19 and non-COVID-19 specific scores have been employed in an attempt to stratify according to mortality or ICU admission risk, validation studies failed to confirm their applicability in larger populations (5)(6)(7)(8)(9)(10)(11)(12)(13)(14)(15). According to a recent review article analyzing the existing scores predicting COVID-19 mortality, the 4C mortality score, designed specifically for COVID-19, is likely to have the best performance, though it has intrinsic limitations and a relatively low positive predictive value (16)(17)(18).…”

Section: Introductionmentioning

confidence: 99%

The COVID-19 Assessment for Survival at Admission (CASA) Index: A 12 Months Observational Study

et al. 2021

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Objective: Coronavirus disease 2019 (COVID-19) is a disease with a high rate of progression to critical illness. However, the stratification of patients at risk of mortality is not well defined. In this study, we aimed to define a mortality risk index to allocate patients to the appropriate intensity of care.Methods: This is a 12 months observational longitudinal study designed to develop and validate a pragmatic mortality risk score to stratify COVID-19 patients aged ≥18 years and admitted to hospital between March 2020 and March 2021. Main outcome was in-hospital mortality.Results: 244 patients were included in the study (mortality rate 29.9%). The Covid-19 Assessment for Survival at Admission (CASA) index included seven variables readily available at admission: respiratory rate, troponin, albumin, CKD-EPI, white blood cell count, D-dimer, Pa02/Fi02. The CASA index showed high discrimination for mortality with an AUC of 0.91 (sensitivity 98.6%; specificity 69%) and a better performance compared to SOFA (AUC = 0.76), age (AUC = 0.76) and 4C mortality (AUC = 0.82). The cut-off identified (11.994) for CASA index showed a negative predictive value of 99.16% and a positive predictive value of 57.58%.Conclusions: A quick and readily available index has been identified to help clinicians stratify COVID-19 patients according to the appropriate intensity of care and minimize hospital admission to patients at high risk of mortality.

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“…Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan, China, in December 2019, viral pneumonia has become a significant public health issue (1). The disease caused by this virus, called coronavirus disease 2019 (COVID-19), is characterized by a wide range of symptoms, from mild to severe, with acute respiratory distress syndrome being its main complication (2).…”

Section: Introductionmentioning

confidence: 99%

“…The disease caused by this virus, called coronavirus disease 2019 (COVID-19), is characterized by a wide range of symptoms, from mild to severe, with acute respiratory distress syndrome being its main complication (2). Therefore, assessing the severity of COVID-19 at the time of hospital admission acquired fundamental importance during the pandemic (1).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of PORT/PSI and SOFA scores in predicting in-hospital mortality of patients with COVID-19

Alanís-Naranjo

Hernández-Sandoval

Anguiano-Álvarez

et al. 2021

MIC

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Introduction: There is limited information analyzing the utility of different prognostic scores in predicting in-hospital mortality among patients with COVID-19. This study aimed to evaluate the performance of PORT/PSI and SOFA scores in predicting the in-hospital mortality of patients with COVID-19. Material and methods: This was an observational, analytical, and retrospective study that included consecutive patients hospitalized for COVID-19 from April 1, 2020, to May 31, 2020. The study population was characterized, and ROC analysis was performed and used to calculate the area under the curve of PORT/PSI and SOFA scores as well as the sensitivity, specificity, and predictive values. Results: A total of 151 patients were included, with a median age of 52 years (IQR 45-64); 69.5% were men, with a median BMI of 29.3 kg/m2 (IQR 25.5-34.7). Of the total, 102 patients died during hospitalization (67.5%). The areas under the ROC curves for predicting in-hospital mortality were 0.74 (95% CI 0.67-0.81) for the SOFA score and 0.85 (95% CI 0.78-0.90) for the PORT/PSI score. When compared, the PORT/PSI score predicted mortality significantly better than the SOFA score (p: 0.01). Conclusions: The PORT/PSI score is a good tool to predict in-hospital mortality in patients with COVID-19.

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Validation of PSI/PORT, CURB‐65 and SCAP scoring system in COVID‐19 pneumonia for prediction of disease severity and 14‐day mortality

Cited by 23 publications

References 5 publications

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

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

The COVID-19 Assessment for Survival at Admission (CASA) Index: A 12 Months Observational Study

Evaluation of PORT/PSI and SOFA scores in predicting in-hospital mortality of patients with COVID-19

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