THE LOW-HARM SCORE FOR PREDICTING MORTALITY IN PATIENTS DIAGNOSED WITH COVID-19: A MULTICENTRIC VALIDATION STUDY

- 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

The score was designed using data from already published cohorts of patients diagnosed with COVID-19. Afterwards, it was calculated it in 438 consecutive hospital admissions at twelve different institutions in ten different cities in Mexico.

- Setting

Twelve hospitals in ten different cities in Mexico.

- Participants

Data from 438 patients was collected. Data from 400 patients (200 deaths and 200 survivors) 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.

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