Abstract
ObjectiveTo 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.MethodsWe 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.ResultsFifty 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).ConclusionsAfter 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.
Highlights
Acute ischemic stroke is the most common type of stroke, accounting for 80% of all stroke patients [1–3]
A total of 205 patients met all eligibility criteria and were retained for analyses. 57 (27.8%) patients were diagnosed with Stroke-associated pneumonia (SAP), and 40 (19.5%) developed poor outcomes
No significant difference in the other neuroimaging findings of Cerebral small vessel disease (CSVD) were noted between the patients with SAP and the controls
Summary
Acute ischemic stroke is the most common type of stroke, accounting for 80% of all stroke patients [1–3]. Stroke-associated pneumonia (SAP) is one of the most common complications of acute ischemic stroke, with an incidence of 6.7–36.98% [4–6]. Early identification of SAP high-risk groups and timely treatment are crucial. Previous studies had identified older age, atrial fibrillation, congestive heart failure, stroke severity, stroke subtype, and dysphagia, as important risk factors [10–13], and established several SAP scales for early prediction, such as the A2DS2 scale, the ISAN scale and the AIS-APS scale [6, 12, 14]. The prediction efficiency of the A2DS2 scale was better than others [15]. To date, these risk factors only involve clinical data, and the predictive value of neuroimaging findings, especially from MRI, in SAP remains unclear
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