摘要
目的探讨急性卒中患者发生卒中相关性肺炎(stroke-associated pneumonia,SAP)的预测因素,构建列线图和神经网络预测模型并验证其预测性能。方法回顾性纳入昆明医科大学第一附属医院和镇雄县人民医院收治的急性卒中患者。应用多变量logistic回归分析确定SAP的独立预测因素,并构建列线图和神经网络预测模型。通过受试者工作特征(receiver operating characteristic curve,ROC)曲线对预测效能进行验证和比较。结果共纳入450例急性卒中患者,男性286例(63.6%),年龄(64.28±13.24)岁;缺血性卒中344例(76.4%),出血性卒中106例(23.6%);128例(28.4%)发生SAP。按照随机数法分为建模队列(300例)和验证队列(150例)。在建模队列进行的多变量logistic回归分析显示,基线美国国立卫生研究院卒中量表(National Institutes of Health Stroke Scale,NIHSS)评分较高、留置胃管、使用质子泵抑制药、心力衰竭和中性粒细胞/淋巴细胞比值(neutrophil/lymphocyte ratio,NLR)较高为SAP的独立预测因素。ROC曲线分析显示,列线图模型在建模队列和验证队列预测SAP的ROC曲线下面积分别为0.841[95%置信区间(confidence interval,CI)0.795~0.880]和0.863(95%CI 0.798~0.914),预测SAP的敏感性分别为75.00%和70.45%,特异性分别为81.94%和92.45%;神经网络模型在建模队列和验证队列预测SAP的ROC曲线下面积分别为0.847(95%CI 0.802~0.866)和0.862(95%CI 0.796~0.913),预测SAP的敏感性分别为76.19%和72.73%,特异性分别为79.17%和89.62%。结论NIHSS评分较高、留置胃管、使用质子泵抑制药、心力衰竭和NLR较高为急性卒中患者发生SAP的独立危险因素。利用上述危险因素构建的列线图和神经网络预测模型对SAP均有较高的预测价值。
ObjectivesTo investigate the predictive factors of stroke associated-pneumonia(SAP)in patients with acute stroke,develop nomogram and neural network prediction models and verify their predictive performance.MethodsPatients with acute stroke admitted to the First Affiliated Hospital of Kunming Medical University and Zhenxiong County People's Hospital were included retrospectively.Multivariate logistic regression analysis was used to determine the independent predictive factors of SAP,and develop nomogram and neural network prediction models.Receiver operating characteristic curve(ROC)curves were used to validate and compare the predictive performances.ResultsA total of 450 patients with acute stroke were enrolled,including 286 males(63.6%),aged 64.28±13.24 years;344 patientss(76.4%)had ischemic stroke and 106(23.6%)had hemorrhagic stroke;128 patients(28.4%)experienced SAP.According to the random number method,they were divided into a modeling cohort(n=300)and a validation cohort(n=150).Multivariate logistic regression analysis in the modeling cohort showed that a higher baseline National Institutes of Health Stroke Scale(NIHSS)score,gastric tube placement,use of proton pump inhibitors,heart failure,and higher neutrophil/lymphocyte ratio(NLR)were the independent predictive factors of SAP.ROC curve analysis showed that the area under the ROC curve of the nomogram model for predicting SAP in the modeling cohort and validation cohort was 0.841(95%confidence interval[CI]0.795-0.880)and 0.863(95%CI 0.798-0.914),respectively.The sensitivity for predicting SAP were 75.00%and 70.45%,respectively,and the specificity was 81.94%and 92.45%,respectively.The area under the ROC curve of the neural network model for predicting SAP in the modeling cohort and validation cohort was 0.847(95%CI 0.802-0.866)and 0.862(95%CI 0.796-0.913),respectively.The sensitivity for predicting SAP were 76.19%and 72.73%,and the specificity was 79.17%and 89.62%,respectively.ConclusionsHigher NIHSS score,gastric tube placement,use of proton pump inhibitors,heart failure,and higher NLR are the independent risk factors for SAP in patients with acute stroke.The nomogram and neural network prediction model developed using the above risk factors have higher predictive value for SAP.
作者
高逢辰
孙海梅
周富强
李维湘
华思婷
龙学军
王瑞飞
Gao Fengchen;Sun Haimei;Zhou Fuqiang;Li Weixiang;Hua Siting;Long Xuejun;Wang Ruifei(School of Public Health,Kunming Medical University,Kunming 650500,China;Department of Neurology,The first Affiliated Hospital of Kunming Medical University,Kunming 650000,China;School of Basic Medicine,Kunming Medical University,Kunming 650500,China;Department of General Surgery,Shiping Hospital of Chinese Medicine,Honghe Hani and Yi Autonomous Prefecture 662200,China;Department of Neurosurgery,Zhenxiong People's Hospital,Zhaotong 657200,China)
出处
《国际脑血管病杂志》
2025年第3期173-179,共7页
International Journal of Cerebrovascular Diseases
基金
云南省科技厅-昆明医科大学应用基础研究联合专项基金资助项目(202101AY070001-117)。
作者简介
通信作者:王瑞飞,Email:wangruifei2638@126.com。
