Dataset Information

Validation of pneumonia prognostic scores in a statewide cohort of hospitalised patients with COVID-19.

ABSTRACT:

Objective

We aimed to externally validate the predictive performance of two recently developed COVID-19-specific prognostic tools, the COVID-GRAM and CALL scores, and prior prognostic scores for community-acquired pneumonia (CURB-65), viral pneumonia (MuBLSTA) and H1N1 influenza pneumonia (Influenza risk score) in a contemporary US cohort.

Methods

We included 257 hospitalised patients with laboratory-confirmed COVID-19 pneumonia from three teaching hospitals in Rhode Island. We extracted data from within the first 24 hours of admission. Variables were excluded if values were missing in >20% of cases, otherwise, missing values were imputed. One hundred and fifteen patients with complete data after imputation were used for the primary analysis. Sensitivity analysis was performed after the exclusion of one variable (LDH) in the complete dataset (n = 257). Primary and secondary outcomes were in-hospital mortality and critical illness (mechanical ventilation or death), respectively.

Results

Only the areas under the receiver-operating characteristic curves (RO-AUC) of COVID-GRAM (RO-AUC = 0.775, 95% CI 0.525-0.915) for in-hospital death, and CURB65 for in-hospital death (RO-AUC = 0.842, 95% CI 0.674-0.932) or critical illness (RO-AUC = 0.766, 95% CI 0.584-0.884) were significantly better than random. Sensitivity analysis yielded similar trends. Calibration plots showed better agreement between the estimated and observed probability of in-hospital death for CURB65, compared with COVID-GRAM. The negative predictive value (NPV) of CURB65 ≥2 was 97.2% for in-hospital death and 88.1% for critical illness.

Conclusions

The COVID-GRAM score demonstrated acceptable predictive performance for in-hospital death. The CURB65 score had better prognostic utility for in-hospital death and critical illness. The high NPV of CURB65 values ≥2 may be useful in triaging and allocation of resources.

SUBMITTER: Shi Y

PROVIDER: S-EPMC7883205 | biostudies-literature |

REPOSITORIES: biostudies-literature

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