In December 2022, the Chinese suffered widespread Omicron of SARS-CoV-2 with variable symptom severity and outcome. We wanted to develop a scoring model to predict the mortality risk of older Omicron pneumonia patients by analyzing admission data. We enrolled 227 Omicron pneumonia patients aged 60 years and older, admitted to our hospital from December 15, 2022, to January 16, 2023, and divided them randomly into a 70% training set and a 30% test set. The former were used to identify predictors and develop a model, the latter to verify the model, using the area under the receiver operating characteristic curve (AUC), the Hosmer-Lemeshow goodness-of-fit test, a calibration curve to test its performance and comparing it to the existing scores. The MLWAP score was calculated based on a multivariate logistic regression model to predict mortality with a weighted score that included immunosuppression, lactate ≥ 2.4, white blood cell count ≥ 6.70 × 109/L, age ≥ 77 years, and PaO2/FiO2 ≤ 211. The AUC for the model in the training and test sets was 0.852 (95% CI, 0.792-0.912) and 0.875 (95% CI, 0.789-0.961), respectively. The calibration curves showed a good fit. We grouped the risk scores into low (score 0-7 points), medium (8-10 points), and high (11-13 points). This model had a sensitivity of 0.849, specificity of 0.714, and better predictive ability than the CURB-65 and PSI scores (AUROC = 0.859 vs. 0.788 vs. 0.801, respectively). The MLWAP-mortality score may help clinicians to stratify hospitalized older Omicron pneumonia patients into relevant risk categories, rationally allocate medical resources, and reduce the mortality.
Keywords: Omicron pneumonia; Predicting mortality; Predictive score model; SARS-CoV-2.
© 2023. The Author(s).