A Clinical Prediction Model Based on Post Large Artery Atherosclerosis Infarction Pneumonia

Stroke-associated pneumonia (SAP) has been found as a common complication in acute ischemic stroke (AIS) patients. Large artery atherosclerosis (LAA) infarct is a major subtype of AIS. This study aimed to build a clinical prediction model for SAP of LAA type AIS patients.

This study included 295 patients with LAA type AIS. Univariate analyses and logistic regression analyses were conducted to determine the independent predictors for the modeling purpose. Nomogram used receiver operating characteristics to assess the accuracy of the model, and the calibration plots were employed to assess the fitting degree between the model and the practical scenario. One hundred and five patients were employed for the external validation to test the stability of the model.

From the univariate analysis, patients' ages, neutrophil-to-lymphocyte ratios, National Institute of Health Stroke scale (NIHSS) scores, red blood cell, sex, history of coronary artery disease, stroke location and volume-viscosity swallow test showed statistical difference in the development group for the occurrence of SAP. By incorporating the factors above into a multivariate logistic regression analysis, patients' ages, neutrophil-to-lymphocyte ratios, NIHSS, and volume-viscosity swallow test emerged as the independent risk factors of the development of SAP. The nomogram based on the mentioned 4 variables above achieved a receiver operating characteristic of 0.951 and a validation group of 0.946.

The proposed nomogram is capable of predicting predict the occurrence of SAP in LAA type AIS patients, and it may identify high-risk patients in time and present information for in-depth treatment.