Details

Autor(en) / Beteiligte

• Soto‐Mota, Adrian
• Marfil‐Garza, Braulio A.
• Martínez Rodríguez, Erick
• Barreto Rodríguez, José Omar
• López Romo, Alicia Estela
• Alberti Minutti, Paolo
• Alejandre Loya, Juan Vicente
• Pérez Talavera, Félix Emmanuel
• Ávila Cervera, Freddy José
• Velazquez Burciaga, Adriana
• Morado Aramburo, Oscar
• Piña Olguín, Luis Alberto
• Soto‐Rodríguez, Adrian
• Castañeda Prado, Andrés
• Santillán Doherty, Patricio
• O Galindo, Juan
• Guízar García, Luis Alberto
• Hernández Gordillo, Daniel
• Gutiérrez Mejía, Juan

Titel

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

Ist Teil von

• Journal of the American College of Emergency Physicians Open, 2020-12, Vol.1 (6), p.1436-1443

Ort / Verlag

United States: John Wiley and Sons Inc

Erscheinungsjahr

2020

Quelle

Wiley Online Library Journals Frontfile Complete

Beschreibungen/Notizen

• 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.