Tashima Hiroyuki, Ito Mari, Kawakami Michiyuki, Ishii Ryota, Miyazaki Yuta, Akimoto Tomonori, Tsujikawa Masahiro, Kobayashi Keigo, Kondo Kunitsugu, Tsuji Tetsuya
Department of Rehabilitation Medicine, Tokyo Bay Rehabilitation Hospital, Chiba 275-0026, Japan.
Department of Rehabilitation Medicine, Keio University School of Medicine, Tokyo 160-8582, Japan.
J Clin Med. 2023 Sep 8;12(18):5835. doi: 10.3390/jcm12185835.
The risk of pneumonia and death is higher in acute stroke patients with signs of pulmonary infection on chest computed tomography (CT) at admission. However, few reports have examined the incidence of pneumonia and its predictors in subacute stroke patients. The aim of this study was to examine factors related to post-stroke pneumonia in subacute stroke patients. A total of 340 subacute stroke patients were included. Univariable logistic regression analysis was performed using variables that may contribute to pneumonia, with the development of pneumonia as the dependent variable. Multivariable logistic regression analysis using the three independent variables with the lowest -values on the univariable logistic regression analysis was also performed to calculate adjusted odds ratios. Twenty-two patients developed pneumonia during hospitalization. The univariable logistic regression analysis showed that the top three items were serum albumin (Alb), functional Oral Intake Scale (FOIS) score, and signs of pulmonary infection on chest CT at admission. Multivariable logistic regression analysis adjusted for these three items showed that the presence of signs of pulmonary infection on chest CT at admission was the independent variable (OR: 4.45; 95% CI: 1.54-12.9). When signs of pulmonary infection are seen on admission chest CT, careful follow-up is necessary because pneumonia is significantly more likely to occur during hospitalization.
入院时胸部计算机断层扫描(CT)显示有肺部感染迹象的急性中风患者发生肺炎和死亡的风险更高。然而,很少有报告研究亚急性中风患者肺炎的发病率及其预测因素。本研究的目的是探讨亚急性中风患者中风后肺炎的相关因素。共纳入340例亚急性中风患者。以肺炎的发生为因变量,对可能导致肺炎的变量进行单变量逻辑回归分析。还进行了多变量逻辑回归分析,使用单变量逻辑回归分析中P值最低的三个自变量来计算调整后的比值比。22例患者在住院期间发生肺炎。单变量逻辑回归分析显示,前三项是血清白蛋白(Alb)、功能性口服摄入量表(FOIS)评分和入院时胸部CT上的肺部感染迹象。对这三项进行调整的多变量逻辑回归分析显示,入院时胸部CT上存在肺部感染迹象是自变量(比值比:4.45;95%置信区间:1.54 - 12.9)。当入院胸部CT上出现肺部感染迹象时,由于住院期间肺炎发生的可能性显著增加,因此需要仔细随访。