ABSTRACT
Prognostic models to predict the deterioration and mortality risk in COVID-19 patients are utterly needed to assist in informed decision making. Most of these models, however, are at high risk of bias, model overfitting, and unclear reporting. Here, we aimed to externally validate the modified (urea was omitted) 4C Deterioration Model and 4C Mortality Score in a cohort of Swiss COVID-19 patients and, second, to evaluate whether the inclusion of the neutrophil-to-lymphocyte ratio (NLR) improves the predictive performance of the models. We conducted a retrospective single-centre study with adult patients hospitalized with COVID-19. Both prediction models were updated by including the NLR. Model performance was assessed via the models' discriminatory performance (area under the curve, AUC), calibration (intercept and slope), and their performance overall (Brier score). For the validation of the 4C Deterioration Model and Mortality Score, 546 and 527 patients were included, respectively. In total, 133 (24.4%) patients met the definition of in-hospital deterioration. Discrimination of the 4C Deterioration Model was AUC = 0.78 (95% CI 0.73-0.82). A total of 55 (10.44%) patients died in hospital. Discrimination of the 4C Mortality Score was AUC = 0.85 (95% CI 0.79-0.89). There was no evidence for an incremental value of the NLR. Our data confirm the role of the modified 4C Deterioration Model and Mortality Score as reliable prediction tools for the risk of deterioration and mortality. There was no evidence that the inclusion of NLR improved model performance.
ABSTRACT
Among people infected with SARS-CoV-2, the determination of clinical features associated with poor outcome is essential to identify those at high risk of deterioration. Here, we aimed to investigate clinical phenotypes of patients hospitalized due to COVID-19 and to examine the predictive value of the neutrophil-to-lymphocyte ratio (NLR) in a representative patient collective of the Swiss population. We conducted a retrospective monocentriccohort study with patients hospitalized due to COVID-19 between 27 February and 31 December 2020. Data were analyzed descriptively, using the binary logistic regression model, proportional odds logistic regression model, competing risk analysis, and summary measure analysis. A total of 454 patients were included in our study. Dyspnea, elevated respiratory rate, low oxygen saturation at baseline, age, and presence of multiple comorbidities were associated with a more severe course of the disease. A high NLR at baseline was significantly associated with disease severity, unfavorable outcome, and mortality. In non-survivors, NLR further increased during hospital stay, whereas in survivors, NLR decreased. In conclusion, our data emphasize the importance of accurate history taking and clinical examination upon admission and confirm the role of baseline NLR as a surrogate marker for increased disease severity, unfavorable outcome, and mortality in patients hospitalized due to infection with SARS-CoV-2.