The low-harm score for predicting mortality in patients diagnosed with COVID-19: A multicentric validation study

Abstract

Objective: We sought to determine the accuracy of the LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury) for predicting death from coronavirus disease 2019) COVID-19. Methods: We derived the score as a concatenated Fagan's nomogram for Bayes theorem using data from published cohorts of patients with COVID-19. We validated the score on 400 consecutive COVID-19 hospital admissions (200 deaths and 200 survivors) from 12 hospitals in Mexico. We determined the sensitivity, specificity, and predictive values of LOW-HARM for predicting hospital death. Results: LOW-HARM scores and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 5 (SD: 14) versus 70 (SD: 28). The overall area under the curve for the LOW-HARM score was 0.96, (95% confidence interval: 0.94–0.98). A cutoff > 65 points had a specificity of 97.5% and a positive predictive value of 96%. Conclusions: The LOW-HARM score measured at hospital admission is highly specific and clinically useful for predicting mortality in patients with COVID-19.