Application of validated severity scores for pneumonia caused by SARS-CoV-2

Abstract

Objectives Compare the accuracy of PSI, CURB-65, MuLBSTA and COVID-GRAM prognostic scores to predict mortality, the need for invasive mechanical ventilation (IMV) in patients with pneumonia caused by SARS-CoV-2 and assess the coexistence of bacterial respiratory tract infection during admission. Methods Retrospective observational study that included hospitalized adults with pneumonia caused by SARS-CoV-2 from 15/03 to 15/05/2020. We excluded immunocompromised patients, nursing home residents and those admitted in the previous 14 days for another reasons. Analysis of ROC curves was performed, calculating the area under the curve for the different scales, as well as sensitivity, specificity and predictive values. Results 208 patients were enrolled, aged 63 ± 17 years, 57,7% were men. 38 patients were admitted to ICU (23,5%), of these patients 33 required IMV (86,8%), with an overall mortality of 12,5%. Area under the ROC curves for mortality of the scores were: PSI 0,82 (95% CI 0,73–0,91), CURB-65 0,82 (0,73–0,91), MuLBSTA 0,72 (0,62–0,81) and COVID-GRAM 0,86 (0,70–1). Area under the curve for needing IMV was: PSI 0,73 (95% CI 0,64–0,82), CURB-65 0,66 (0,55–0,77), MuLBSTA 0,78 (0,69–0,86) and COVID-GRAM 0,76 (0,67–0,85), respectively. Patients with bacterial co-infections of the respiratory tract were 20 (9,6%), the most frequent strains being Pseudomonas aeruginosa and Klebsiella pneumoniae . Conclusions In our study, the COVID-GRAM score was the most accurate to identify patients with higher mortality with pneumonia caused by SARS-CoV-2; however, none of these scores accurately predicts the need for IMV with ICU admission. 10% of patients admitted presented bacterial respiratory co-infection.

Antimicrobial resistance in patients with COVID-19: a systematic review and meta-analysis

“…The 148 included studies were published between December, 2019, and May, 2021. 19 , 20 , 21 , 22 , 23 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , ...…”

The Usefulness of the COVID-GRAM Score in Predicting the Outcomes of Study Population with COVID-19

“…According to the available literature, bacterial infections as a coinfection with COVID-19 are associated with higher morbidity and mortality. They occur in approximately 9-15% of the SARS-CoV-2 population [18,40]. In the group of patients we analyzed, we found that the need for antibiotics was greater in the high-risk groups according to the COVID-GRAM score than in the low-risk group.…”

Evaluation of risk scores as predictors of mortality and hospital length of stay for older COVID‐19 patients

“…In our study, the ideal cutoff was a score of 169 with an odds ratio of 7.483. The sensitivity of this score was evaluated with the Pneumonia Severity Index, CURB‐65 score, and MuLBSTA and determined to be superior to other scores for detecting high‐risk patients 23 . In another study with 523 patients, the accuracy of this score was evaluated, and a sensitivity of 77% and specificity of 85% were determined for 30‐day mortality 10 .…”