IL-6-based mortality prediction model for COVID-19: Validation and update in multicenter and second wave cohorts

Coronavirus disease 2019 (COVID-19) is a highly variable condition. Validated tools to assist in the early detection of patients at high risk of mortality can help guide medical decisions.

We sought to validate externally, as well as in patients from the second pandemic wave in Europe, our previously developed mortality prediction model for hospitalized COVID-19 patients.

Three validation cohorts were generated: 2 external with 185 and 730 patients from the first wave and 1 internal with 119 patients from the second wave. The probability of death was calculated for all subjects using our prediction model, which includes peripheral blood oxygen saturation/fraction of inspired oxygen ratio, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, IL-6, and age. Discrimination and calibration were evaluated in the validation cohorts. The prediction model was updated by reestimating individual risk factor effects in the overall cohort (N = 1477).

The mortality prediction model showed good performance in the external validation cohorts 1 and 2, and in the second wave validation cohort 3 (area under the receiver-operating characteristic curve, 0.94, 0.86, and 0.86, respectively), with excellent calibration (calibration slope, 0.86, 0.94, and 0.79; intercept, 0.05, 0.03, and 0.10, respectively). The updated model accurately predicted mortality in the overall cohort (area under the receiver-operating characteristic curve, 0.91), which included patients from both the first and second COVID-19 waves. The updated model was also useful to predict fatal outcome in patients without respiratory distress at the time of evaluation.

This is the first COVID-19 mortality prediction model validated in patients from the first and second pandemic waves. The COR+12 online calculator is freely available to facilitate its implementation (https://utrero-rico.shinyapps.io/COR12_Score/).