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.

- Importance: Many COVID-19 prognostic factors for disease severity have been identified and many scores have already been proposed to predict death and other outcomes. However, hospitals in developing countries often cannot measure some of the variables that have been reported as useful. - Objective: To assess the sensitivity, specificity, and predictive values of the novel LOW-HARM score (Lymphopenia, Oxygen saturation, White blood cells, Hypertension, Age, Renal injury, and Myocardial injury). - Design: Demographic and clinical data from patients with known clinical outcomes (death or discharge) was obtained. Patients were grouped according to their outcome. The LOW-HARM score was calculated for each patient and its distribution, potential cut-off values and demographic data were compared. - Setting: Twelve hospitals in ten different cities in Mexico. - Participants: Data from 438 patients was collected. A total of 400 (200 per group) was included in the analysis. - Exposure: All patients had an infection with SARS-CoV-2 confirmed by PCR. - Main Outcome: The sensitivity, specificity, and predictive values of different cut-offs of the LOW-HARM score to predict death. - Results: Mean scores at admission and their distributions were significantly lower in patients who were discharged compared to those who died during their hospitalization 10 (SD: 17) vs 70 (SD: 28). The overall AUC of the model was 95%. A cut-off > 65 points had a specificity of 98% and a positive predictive value of 96%. More than a third of the cases (36%) in the sample had a LOW-HARM score > 65 points. - Conclusions and relevance: The LOW-HARM score measured at admission is highly specific and useful for predicting mortality. It is easy to calculate and can be updated with individual clinical progression.