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.

COVID-19 represents the greatest health challenge of modern years. The spectrum of illness comprises respiratory and non-respiratory manifestations. We report the case of an adult man with COVID-19 who presented with rhabdomyolysis as a principal extrapulmonary manifestation. Our patient presented with dyspnea, fever, and muscle pain. After a comprehensive approach, the diagnosis of COVID-19 and rhabdomyolysis was made. He developed acute kidney injury requiring renal replacement therapy without reversibility, despite optimal treatment. We performed a literature search for similar cases, discuss the potential mechanisms implied, and propose a diagnostic-therapeutic algorithm.

- 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.

Background Obesity has been described as a risk factor for COVID‐19 severity and mortality. Previous studies report a linear association between BMI and adverse outcomes, meanwhile in other critical illness, excessive fat tissue is related to improved survival. Whether different BMI is related with the survival of patients with severe COVID‐19 deserves further analysis. Objective To determine the mortality rate among hospitalized patients with severe COVID‐19 stratified according to BMI. Methods The clinical files of all patients hospitalized from March to December 2020 with a positive PCR test for SARS‐CoV‐2 discharged due to improvement or death, were analyzed. A mixed effects logistic regression was carried out to determine which clinical and biochemical characteristics and comorbidities were associated with in‐hospital mortality. Results The cohort consisted of 608 patients with a median age of 59 years (interquartile ranges, IQR 46–69 years), median BMI of 28.7 kg/m 2 (IQR 25.4–32.4 kg/m 2 ), 65.5% were male. In‐hospital mortality rate was 43.4%. Of the cohort 0.8% had low weight, 20.9% normal weight, 36.0% overweight, 26.5% obesity grade I, 10.2% obesity grade II and 5.6% obesity grade III. Mortality rate was highest in patients with low weight (80%), followed by patients with obesity grade III (58.8%) and grade II (50.0%). Overweight and underweight/obesity grade III were associated with higher mortality (OR of 9.75 [1.01–1.10] and OR 4.08 [1.64–10.14]), after adjusting by sex and age. Conclusions The patients in the underweight/overweight and grade 3 obesity categories are at higher risk of COVID‐19 related mortality, compared to those with grade I or II obesity.