Clinical features and predictors of early neurological deterioration in acute isolated pontine infarction

Abstract

Objective: To investigate the clinical and imaging characteristics of early neurological deterioration (END) in acute isolated pontine infarction (AIPI) and analyze the predictive factors of END. Methods: Patients with AIPI who were confirmed by magnetic resonance imaging (MRI) in Zhengzhou University People's Hospital from January 2020 to December 2021were collected and divided into END group and non-END group (NEND group). General data and imaging characteristics of the patients were compared between the two groups, the neurological function of patients was evaluated by using the modified Rankin scale (mRS) at 1 and 3 months after stroke. Multivariate binary logistic regression model was used to analyze the risk factors of END after isolated pontine infarction, and the receiver operating characteristic curve(ROC) curve was drawn. Z-test was used to compare the area under the curve to determine the best predictor of END. Results: A total of 113 patients with AIPI were enrolled, including 72 males and 41 females, aged (62±11) years, with 40 cases in the END group and 73 cases in the NEND group. The incidence of END in AIPI was 35.4% (40/113). The National Institutes of Health Stroke Scale (NIHSS) score in the END group (5.15±1.88) was higher than that in the NEND group (4.10±1.63), and the infarcts size in the END group [(2.15±0.39) mm2] was larger than that in the NEND group [(1.61±0.46) mm2] (P=0.002 and P<0.001, respectively). Multivariate binary logistic regression analysis showed that NIHSS score on admission (OR=1.393, 95%CI: 1.017-1.909, P=0.039), infarct size (OR=11.539, 95%CI: 3.574-37.255, P<0.001) were associated with END. Comparing the area of ROC curve, infarct size [area under curve (AUC)=0.787, with a sensitivity of 0.750 and specificity of 0.545] and NIHSS score on admission (AUC=0.688, with a sensitivity of 0.700 and specificity of 0.589) showed no significant difference in the value of predicting END (P=0.056). Conclusion: Patients with AIPI had higher NIHSS score and larger infarct size on admission, and both of them exhibit good predictive performance for END.