A2DS2 Score Combined With Clinical and Neuroimaging Factors Better Predicts Stroke-Associated Pneumonia in Hyperacute Cerebral Infarction - Yu, Yaoyao; Xia, Tianyi; Tan, Zhouli; Xia, Huwei; He, Shenping; Sun, Han; Wang, Xifan; Song, Haolan; Chen, Weijian (Frontiers in Neurology, 2022)
Objective: To investigate the prediction of stroke-associated pneumonia (SAP) and poor outcome in patients with hyperacute cerebral infarction (HCI) by combining MR features of cerebral small vessel disease (CSVD). Methods: We included 205 patients with HCI from November 2018 to December 2019. The diagnostic criterion for SAP was occurrence within 7 days of the onset of stroke. Poor outcome was defined as a functional outcome based on a 3-months MRS score ˃ 3. The relationship of demographic, laboratory and neuroimaging variables with SAP and poor outcome was investigated using univariate and multivariate analyses. Results: 57 (27.8%) patients were diagnosed with SAP and 40 (19.5%) developed poor outcomes. A2DS2 score, previous stroke, consciousness, brain atrophy score, and core infarct volume were independently associated with the occurrence of SAP. Fasting plasma glucose, NIHSS score, previous stroke, SAP, dilated perivascular spaces, and core infarct volume were independently associated with poor outcome. The C-statistic of the SAP model was 0.84 (95% CI 0.78-0.90), and that of the outcome model was 0.87 (95% CI 0.81-0.94). Furthermore, the SAP model significantly improved discrimination and net benefit more than a single A2DS2 score, with a C-statistic of 0.76 (95% CI 0.69-0.83). Conclusions: After the addition of CSVD, the models exhibit good differentiation and calibration for the prediction of the occurrence of SAP and the development of poor outcomes in HCI patients. The SAP model could better predict the SAP, representing a helpful and valid tool to obtain a net benefit compared with a single A2DS2 score.