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2026, 04, v.28 419-423
老年高血压脑出血患者术后肺部感染的独立危险因素及风险预测模型构建
基金项目(Foundation): 湖北省自然科学基金(2025AFD880)
邮箱(Email): Wmy198609328@126.com;
DOI:
发布时间: 2026-04-14
出版时间: 2026-04-14
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摘要:

目的 筛选老年高血压脑出血患者术后肺部感染的独立危险因素,构建个体化风险预测模型。方法 回顾性分析2023年8月至2025年8月武汉市第一医院神经外科收治的高血压脑出血手术患者160例,根据术后是否并发肺部感染将研究对象分为感染组36例和非感染组124例。通过单因素分析初步筛选出可能影响术后肺部感染的潜在因素,利用多因素logistic回归模型进一步分析,以筛选出的具有统计学意义的变量为基础构建列线图风险预测模型,明确导致术后肺部感染的独立危险因素。结果 本研究术后肺部感染发生率为22.50%。感染组年龄≥70岁(72.22%vs 36.29%)、糖尿病(38.89%vs 22.58%)、低蛋白血症(50.00%vs 28.23%)、吸烟史(55.56%vs 36.29%)、慢性阻塞性肺疾病患病率(22.22%vs 8.06%)、格拉斯哥昏迷评分(Glasgow coma scale,GCS)≥8分(77.78%vs 28.23%)、意识障碍(83.33%vs44.35%)、脑出血量≥50 mL(55.56%vs 32.26%)、气管切开(61.11%vs 28.23%)、机械通气时间>24 h(69.44%vs 30.65%)、气管插管时间>1 d比例(66.67%vs 41.94%)明显高于未感染组,差异有统计学意义(P<0.05,P<0.01)。多因素logistic回归分析显示,GCS<8分、机械通气时间>24 h、接受气管切开术、年龄≥70岁、糖尿病是高血压脑出血患者术后肺部感染的独立危险因素(P<0.05,P<0.01)。ROC曲线分析显示,训练集高血压脑出血患者术后肺部感染风险预测模型的曲线下面积为0.713(95%CI:0.619~0.719),验证集的AUC为0.669(95%CI:0.632~0.723)。结论 高龄、合并糖尿病、存在意识障碍、接受气管切开术及需要较长时间的机械通气是高血压脑出血患者术后发生肺部感染的关键诱发因素,依据这些危险因素构建的风险模型具有较好的预测价值。

Abstract:

Objective To screen independent risk factors for postoperative pulmonary infection in elderly patients with hypertensive intracerebral hemorrhage(ICH) and construct an individualized risk prediction model. Methods A retrospective analysis was conducted on 160 elderly patients with hypertensive ICH admitted to our department from August 2023 to August 2025. According to whether postoperative pulmonary infection occurred, the participants were divided into an infection group(36 cases) and a non-infection group(124 cases). Univariate analysis was used to preliminarily screen potential factors that might affect postoperative pulmonary infection, and multivariate logistic regression analysis was employed for further analysis. Based on the statistically significant variables screened out, a nomogram risk prediction model was constructed, and the independent risk factors for postoperative pulmonary infection were identified. Results The incidence of postoperative pulmonary infection was 22.50% in the cohort. The infection group exhibited significantly larger proportions of age ≥70 years(72.22% vs 36.29%), diabetes mellitus(38.89% vs 22.58%), hypoalbuminemia(50.00% vs 28.23%), smoking history(55.56% vs 36.29%), chronic obstructive pulmonary disease(22.22% vs 8.06%), Glasgow coma scale(GCS) score≥8(77.78% vs 28.23%), consciousness disturbance(83.33% vs 44.35%), intracerebral hemorrhage volume ≥50 mL(55.56% vs 32.26%), tracheotomy(61.11% vs 28.23%), mechanical ventilation time >24 h(69.44% vs 30.65%), and endotracheal intubation time >1 d(66.67% vs 41.94%) when compared with the non-infection group(P<0.05, P<0.01). Multivariate logistic regression analysis indicated that GCS score <8, mechanical ventilation time >24 h, tracheotomy, age ≥70 years, and diabetes mellitus were independent risk factors for postoperative pulmonary infection in patients with hypertensive ICH(P<0.05, P<0.01). ROC curve analysis showed that the area under the curve of the postoperative pulmonary infection risk prediction model for hypertensive ICH was 0.713(95%CI:0.619-0.719) in the training set, and was 0.669(95%CI:0.632-0.723) in the validation set. Conclusion Advanced age, concomitant diabetes mellitus, consciousness disturbance, tracheotomy, and prolonged mechanical ventilation are key risk factors for postoperative pulmonary infection in patients with hypertensive ICH. Our risk model constructed based on these risk factors demonstrates good predictive value.

参考文献

[1]Chen M, Da L, Huang C, et al. In-depth analysis of risk factors for postoperative pulmonary infection in patients with basal ganglia haemorrhage and construction of prediction model:based on domestic and international cutting-edge clinical research and big data analysis[J]. Front Med(Lausanne), 2025, 12:1627298. DOI:10.3389/fmed.2025.1627298.

[2]Ma J, Xue B, Zhang Z, et al. Incidence, risk factors, and predictive modeling of pulmonary infection after high-risk surgery for lung cancer:a retrospective case-control study[J]. J Thorac Dis, 2025, 17(6):3702-3715. DOI:10.21037/jtd-2024-2276.

[3]Sanikommu S, Panchawagh S, Eatz T, et al. Recurrence of atypical and anaplastic intracranial Meningiomas:a meta-analysis of risk factors[J]. Clin Neurol Neurosurg, 2024, 244:108450. DOI:10.1016/j.clineuro.2024.108450.

[4]李梦璐,霍艳凤,张颜礼,等.老年高血压性脑出血患者微创血肿清除术后再出血风险及预防策略[J].中华老年多器官疾病杂志,2025,24(8):596-600. DOI:10.11915/j.issn.1671-5403.2025.08.129.

[5]Xu S, Du B, Shan A, et al. The risk factors for the postoperative pulmonary infection in patients with hypertensive cerebral hemorrhage:a retrospective analysis[J]. Medicine(Baltimore), 2020, 99(51):e23544. DOI:10.1097/MD.0000000000023544.

[6]Gu J, Dai L, Hu W, et al. Analysis of prognostic factors for drilling drainage surgery in patients with hypertensive intracerebral hemorrhage and development of a predictive Nomogram[J]. Risk Manag Healthc Policy, 2025, 18:1159-1169. DOI:10.2147/RMHP.S502982.

[7]邓里娜,吴波.《中国脑出血诊治指南2019》更新要点及解读[J].心脑血管病防治,2021,21(1):13-17. DOI:10.3969/j.issn.1009-816x.2021.01.002.

[8]于翠香,王西艳.《中国成人医院获得性肺炎与呼吸机相关性肺炎诊断和治疗指南(2018年版)》解读[J].中国医刊,2021,56(9):951-953. DOI:10.3969/j.issn.1008-1070.2021.09.008.

[9]Lan J, Wei Y, Zhu Y, et al. Risk factors for post-operative pulmonary infection in patients with brain tumors:a systematic review and meta-analysis[J]. Surg Infect(Larchmt), 2023, 24(7):588-597. DOI:10.1089/sur.2023.130.

[10]Lan J, Liu X, Mo L, et al. Construction and validation of a risk prediction model for postoperative pulmonary infection in patients with brain tumor:a retrospective study[J]. PeerJ, 2025,13:e18996. DOI:10.7717/peerj.18996.

[11]Xu J, Han X, Qi Y, et al. Development and validation of a clinical prediction model for concurrent pulmonary infection in convalescent patients with intracerebral hemorrhage[J]. Biomed Eng Online, 2025,24(1):88. DOI:10.1186/s12938-025-01425-1.

[12]Han J, Yao T, Gao L, et al. Development and validation of a risk prediction model related to inflammatory and nutritional indexes for postoperative pulmonary infection after radical colorectal cancer surgery[J]. BMJ Open, 2025, 15(1):e087426. DOI:10.1136/bmjopen-2024-087426.

[13]Ren C, Wu C, Pan Z, et al. Pulmonary infection after cardiopulmonary bypass surgery in children:a risk estimation model in China[J].J Cardiothorac Surg, 2021, 16(1):71. DOI:10.1186/s13019-021-01450-w.

[14]Shi Y, Hu Y, Xu GM, et al. Development and validation of a predictive model for pulmonary infection risk in patients with traumatic brain injury in the ICU:a retrospective cohort study based on MIMIC-IV[J]. BMJ Open Respir Res, 2024,11(1):e002263. DOI:10.1136/bmjresp-2023-002263.

[15]吴珂,杨晓滨,李平,等.自发性脑出血患者术后肺部感染的列线图风险预测模型的建立[J].中华医院感染学杂志,2022,32(7):1041-1045. DOI:10.11816/cn.ni.2022-210900.

[16]Li W, Xu L, Zhao H, et al. Analysis of clinical distribution and drug resistance of klebsiella pneumoniae pulmonary infection in patients with hypertensive intra cerebral hemorrhage after minimally invasive surgery[J]. Pak J Med Sci, 2022, 38(1):237-242. DOI:10.12669/pjms.38.1.4439.

[17]Wang W, Lv W, Yang J. Analysis of efficacy and safety of modified transfrontal puncture drainage in hypertensive basal ganglia hemorrhage patients[J]. Front Surg, 2022, 9:837008. DOI:10.3389/fsurg.2022.837008.

[18]Tang C, Zhang M, Li W. Meta-analysis of stereotactic hematoma removal and craniotomy hematoma removal in the treatment of hypertensive intracerebral hemorrhage in the elderly[J].Medicine(Baltimore), 2023, 102(49):e36533. DOI:10.1097/MD.0000000000036533.

[19]Ren W, Wang W, Wang L, et al. Efficacy and safety of minimally invasive neuroendoscopic surgery in the therapy of supratentorial hypertensive intracerebral hemorrhage:a meta-analysis[J]. J Craniofac Surg, 2024, 35(8):2275-2281. DOI:10.1097/SCS.0000000000010529.

[20]Liu S, Long J, Cao S, et al. Endoport assisted endoscopic surgery for hypertensive basal ganglia hemorrhage by transsylvian approach:technical nuances and preliminary clinical results[J]. World Neurosurg, 2023, 179:e593-e600. DOI:10.1016/j.wneu.2023.09.013.

[21]Wang S, Wang R, Li X, et al. A nomogram based on systemic inflammation response index and clinical risk factors for prediction of short-term prognosis of very elderly patients with hypertensive intracerebral hemorrhage[J]. Front Med(Lausanne),2025,12:1535443. DOI:10.3389/fmed.2025.1535443.

[22]Huang J, Ge H, Zhu X, et al. Risk factors analysis and nomogram construction for postoperative pulmonary infection in elderly patients with hip fractures[J]. Aging Clin Exp Res, 2023, 35(9):1891-1899. DOI:10.1007/s40520-023-02480-1.

[23]Chen X, Wu L, Lan G, et al. Construction and validation of a risk prediction model for postoperative lung infection in elderly patients with lung cancer[J]. Medicine(Baltimore), 2024,103(44):e40337. DOI:10.1097/MD.0000000000040337.

[24]Hu SQ, Hu JN, Chen RD, et al. A predictive model using risk factor categories for hospital-acquired pneumonia in patients with aneurysmal subarachnoid hemorrhage[J]. Front Neurol, 2022,13:1034313. DOI:10.3389/fneur.2022.1034313.

[25]Liu L, Yuan Y, Zeng J, et al. Development and validation of a nomogram for predicting postoperative new-onset constipation in elderly patients undergoing hip fracture surgery[J]. Sci Rep, 2025,15(1):15289. DOI:10.1038/s41598-025-00493-6.

基本信息:

中图分类号:R563.1;R651.1

引用信息:

[1]陈闾琦,王孟阳,罗志华,等.老年高血压脑出血患者术后肺部感染的独立危险因素及风险预测模型构建[J].中华老年心脑血管病杂志,2026,28(04):419-423.

基金信息:

湖北省自然科学基金(2025AFD880)

发布时间:

2026-04-14

出版时间:

2026-04-14

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