Risk of stroke-associated pneumonia during hospitalization: predictive ability of combined A2DS2 score and hyperglycemia
Risk of stroke-associated pneumonia during hospitalization: predictive ability of combined A2DS2 score and hyperglycemia
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DOI：
10.1186/s12866-019-1636-y
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发表时间：
2019-11-25
期刊：
影响因子：
2.6
通讯作者：
Chang, Junsen
中科院分区：
文献类型：
--
作者：
Li, Yang;Zhang, Yu;Chang, Junsen
背景：脑卒中相关性肺炎（SAP）是脑血管病的常见并发症。A（2）DS（2）评分已用于预测SAP的风险。然而，高血糖不包括在该量表中。本研究的目的是探讨A（2）DS（2）评分系统和高血糖是否能比传统的A（2）DS（2）量表更有效地预测SAP的风险。收集两组患者的A（2）DS（2）评分、空腹血糖及入院时血糖水平。采用回归分析确定SAP的独立危险因素。结果：空腹高血糖是SAP的独立危险因素（OR = 2.95，95%CI：2.11-4.12，P < 0.001）。A（2）DS（2）评分与空腹血糖联合应用的曲线下面积显著高于A（2）DS（2）评分单独应用的曲线下面积（0.814 vs.0.793; P = 0.020）。与A2 DS 2评分相比，改良的A（2）DS（2）评分（结合A（2）DS（2）评分和空腹高血糖）更能预测SAP的发生。
Background: Stroke-associated pneumonia (SAP) is a common complication of cerebrovascular disease. The A(2)DS(2) score has been used to predict the risk of SAP. However, hyperglycemia is not included in this scale. The purpose of the present study was to explore whether the A(2)DS(2) scoring system and hyperglycemia could predict the risk of SAP more effectively than the conventional A(2)DS(2) scale.Methods: This retrospective study enrolled 2552 patients with acute ischemic stroke. The A(2)DS(2) scores, fasting blood glucose level and blood glucose level on admission were collected. Regression analysis was used to identify the independent risk factors of SAP. ROC curve analysis was used to evaluate the specificity and sensitivity of the combined A(2)DS(2) score and fasting hyperglycemia for predicting SAP.Results: Fasting hyperglycemia was an independent risk factor for SAP (OR = 2.95; 95% confidence interval: 2.11-4.12; P < 0.001). The area under curve of the combined A(2)DS(2) score and fasting hyperglycemia was significantly higher than that of the A(2)DS(2) score alone (0.814 vs. 0.793; P = 0.020).Conclusion: Fasting hyperglycemia is an independent risk factor for predicting SAP. Compared with the A2DS2 score, the modified A(2)DS(2) score (combined A(2)DS(2) score and fasting hyperglycemia) is more effective in predicting the risk of SAP.