A2DS2 Score Combined With Clinical and Neuroimaging Factors Better Predicts Stroke-Associated Pneumonia in Hyperacute Cerebral Infarction

Yaoyao Yu; Tianyi Xia; Zhouli Tan; Huwei Xia; Shenping He; Han Sun; Xifan Wang; Haolan Song; Weijian Chen

doi:10.3389/fneur.2022.800614

A²DS² Score Combined With Clinical and Neuroimaging Factors Better Predicts Stroke-Associated Pneumonia in Hyperacute Cerebral Infarction

Front Neurol. 2022 Feb 4:13:800614. doi: 10.3389/fneur.2022.800614. eCollection 2022.

Authors

Yaoyao Yu¹, Tianyi Xia², Zhouli Tan¹, Huwei Xia¹, Shenping He¹, Han Sun¹, Xifan Wang¹, Haolan Song¹, Weijian Chen¹

Affiliations

¹ Radiology Imaging Center, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
² Department of Radiology, Zhongda Hospital, Medical School of Southeast University, Nanjing, China.

Abstract

Objective: To investigate the predictors of stroke-associated pneumonia (SAP) and poor functional outcome in patients with hyperacute cerebral infarction (HCI) by combining clinical factors, laboratory tests and neuroimaging features.

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: Fifty seven (27.8%) patients were diagnosed with SAP and 40 (19.5%) developed poor outcomes. A²DS² score (OR = 1.284; 95% CI: 1.048-1.574; P = 0.016), previous stroke (OR = 2.630; 95% CI: 1.122-6.163; P = 0.026), consciousness (OR = 2.945; 95% CI: 1.514-5.729; P < 0.001), brain atrophy (OR = 1.427; 95% CI: 1.040-1.959; P = 0.028), and core infarct volume (OR = 1.715; 95% CI: 1.163-2.528; P = 0.006) were independently associated with the occurrence of SAP. Therefore, we combined these variables into a new SAP prediction model with the C-statistic of 0.84 (95% CI: 0.78-0.90). Fasting plasma glucose (OR = 1.404; 95% CI: 1.202-1.640; P < 0.001), NIHSS score (OR = 1.088; 95% CI: 1.010-1.172; P = 0.026), previous stroke (OR = 4.333; 95% CI: 1.645-11.418; P = 0.003), SAP (OR = 3.420; 95% CI: 1.332-8.787; P = 0.011), basal ganglia-dilated perivascular spaces (BG-dPVS) (OR = 2.124; 95% CI: 1.313-3.436; P = 0.002), and core infarct volume (OR = 1.680; 95% CI: 1.166-2.420; P = 0.005) were independently associated with poor outcome. The C-statistic 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 the A²DS² scale, with a C-statistic of 0.76 (95% CI: 0.69-0.83).

Conclusions: After the addition of neuroimaging features, 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 the A²DS² scale.

Keywords: cerebral small vessel disease; functional outcome; hyperacute cerebral infarction; magnetic resonance imaging; stroke-associated pneumonia.