A novel prediction method for intracerebral hemorrhage-associated pneumonia: A single center analysis

Abstract

Stroke-associated pneumonia (SAP) is a common complication leading to death and disability after a stroke. Currently, more studies tend to focus on stroke-associated pneumonia in patients with ischemic stroke, while there are few studies on predictors of intracerebral hemorrhage-associated pneumonia (ICHAP). It is necessary to discover new predictors to build more accurate prediction models for ICHAP. We continuously collected 498 patients with acute intracerebral hemorrhage and then divided them into ICHAP and non-ICHAP groups. Then we conducted univariate analyses and multivariate regression analyses on the collected data. Afterward, the new predictors of ICHAP were found and the predictive model was designed. Of the 498 patients, 158 were diagnosed with ICHAP. Advanced age (odds ratio =  1.031; 95% confidence interval, 1.015–1.047; P <  0.001), high NIHSS score (odds ratio =  1.081; 95% confidence interval, 1.038–1.126; P <  0.001), dysphagia (odds ratio =  4.191; 95% confidence interval, 2.240–7.841 P <  0.001), and fast pulse (odds ratio =  1.038; 95% confidence interval, 1.019–1.057; P <  0.001) were risk factors for ICHAP. The predictive model (P <  0.001) included age, NIHSS, dysphagia, and pulse. After that, the receiver operating characteristic (ROC) curve and the corresponding area under the curve (AUC) were used to measure their predictive accuracy. The prediction ability of the model (AUC: 0.819) which contained age, NIHSS, dysphagia, and pulse was higher than that of advanced age (AUC = 0.670), high NIHSS score (AUC = 0.761), and fast pulse (AUC = 0.609). The predictive accuracy of the model was 81.5%. These findings might help identify high-risk patients for ICHAP and provide a reference for the timely preventive use of antibiotics.