4.4 Article

Prediction of Ischemic Stroke-Associated Pneumonia: A Comparison between 3 Scores

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JOURNAL OF STROKE & CEREBROVASCULAR DISEASES
卷 25, 期 11, 页码 2756-2761

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.jstrokecerebrovasdis.2016.07.030

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Stroke-associated pneumonia; Ischemic stroke; A(2)DS(2) score; PANTHERIS score; AIS-APS

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Background: Stroke is a leading cause of death and disability worldwide. Among all poststroke complications, pneumonia constitutes a major complication with a strong impact on morbidity and mortality. To identify patients at high risk of stroke-associated pneumonia (SAP) and to tailor a prophylactic approach, a reliable scoring model for prediction may be useful in daily stroke care. Objectives: This study aimed to compare the performance of the Age, Atrial fibrillation, Dysphagia, Sex, Stroke Severity (A(2)DS(2)) score, the acute ischemic stroke-associated pneumonia score (AIS-APS), and the Preventive ANtibacterial THERapy in acute Ischemic Stroke (PANTHERIS) score in predicting SAP. Methods: Seventy consecutive patients with ischemic stroke admitted to the Critical Care Medicine Department of Alexandria Main University Hospital were included. Patients were prospectively followed up for primary outcome of pneumonia within the first 7 days after admission diagnosed by the Centers for Disease Control and Prevention criteria. Accuracy in predicting outcome measures was assessed by calculating the area under receiver operating characteristic curve (AUC). Results: Twenty-six (37.1%) patients developed pneumonia by the seventh day; the A(2)DS(2) score AUC was .847 (95% CI: .741-.922), and the AIS-APS AUC was .798 (95% CI:.685-.884). The PANTHERIS score AUC was .715 (95% CI:.595-.817). The A(2)DS(2) score AUC was significantly higher than the AIS-APS and the PANTHERIS score AUCs (P=.048 and P=.009 respectively), and the AIS-APS AUC was significantly higher than the PANTHERIS score AUC (P=.044). Conclusions: The A(2)DS(2) score is a valid tool for the prediction of SAP based on routinely collected data, and among the 3 studied scores, it shows the best performance in predicting SAP.

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