RESUMO
BackgroundRisk stratification of COVID-19 patients upon hospital admission is key for their successful treatment and efficient utilization of hospital resources. ObjectiveTo evaluate the risk factors associated with ventilation need and mortality. Design, setting and participantsWe established a retrospective cohort of COVID-19 patients from Mass General Brigham hospitals. Demographic, clinical, and admission laboratory data were obtained from electronic medical records of patients admitted to hospital with laboratory-confirmed COVID-19 before May 19th, 2020. Using patients admitted to Massachusetts General Hospital (MGH, derivation cohort), multivariable logistic regression analyses were used to construct the Ventilation in COVID Estimator (VICE) and Death in COVID Estimator (DICE) risk scores. MeasurementsThe primary outcomes were ventilation status and death. ResultsThe entire cohort included 1042 patients (median age, 64 years; 56.8% male). The derivation and validation cohorts for the risk scores included 578 and 464 patients, respectively. We found seven factors to be independently predictive for ventilation requirement (diabetes mellitus, dyspnea, alanine aminotransferase, troponin, C-reactive protein, neutrophil-lymphocyte ratio, and lactate dehydrogenase), and 10 factors to be predictors of in-hospital mortality (age, sex, diabetes mellitus, chronic statin use, albumin, C-reactive protein, neutrophil-lymphocyte ratio, mean corpuscular volume, platelet count, and procalcitonin). Using these factors, we constructed the VICE and DICE risk scores, which performed with C-statistics of at least 0.8 in our cohorts. Importantly, the chronic use of a statin was associated with protection against death due to COVID-19. The VICE and DICE score calculators have been placed on an interactive website freely available to the public (https://covid-calculator.com/). LimitationsOne potential limitation is the modest sample sizes in both our derivation and validation cohorts. ConclusionThe risk scores developed in this study may help clinicians more appropriately determine which COVID-19 patients will need to be managed with greater intensity.
