[1]程佳伟,施 健,张 琪,等.老年面部皮肤肿瘤患者术后切口感染风险的临床预测模型的构建[J].医学信息,2024,37(08):46-51.[doi:10.3969/j.issn.1006-1959.2024.08.008]
　CHENG Jia-wei,SHI Jian,ZHANG Qi,et al.Construction of a Clinical Prediction Model for the Risk of Postoperative Incision Infection in Elderly Patients with Facial Skin Tumors[J].Journal of Medical Information,2024,37(08):46-51.[doi:10.3969/j.issn.1006-1959.2024.08.008]
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老年面部皮肤肿瘤患者术后切口感染风险的临床预测模型的构建()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
37卷
期数:
2024年08期
页码:
46-51
栏目:
临床信息学
出版日期:
2024-04-15

文章信息/Info

Title:
Construction of a Clinical Prediction Model for the Risk of Postoperative Incision Infection in Elderly Patients with Facial Skin Tumors
文章编号:
1006-1959（2024）08-0046-06
作者:
程佳伟; 施 健; 张 琪; 等
（南通市第一人民医院皮肤科，江苏 南通 226006）
Author(s):
CHENG Jia-wei; SHI Jian; ZHANG Qi; et al.
(Dermatological Department of Nantong First People’s Hospital,Nantong 226006,Jiangsu,China)
关键词:
面部皮肤肿瘤; 切口感染; 列线图; 预测模型
Keywords:
Facial skin tumor; Incision infection; Nomogram; Predictive model
分类号:
R739.5
DOI:
10.3969/j.issn.1006-1959.2024.08.008
文献标志码:
A
摘要:
目的 建立老年面部皮肤肿瘤患者术后切口感染风险的列线图预测模型并验证其预测能力。方法 采用回顾性分析方法，收集2018年1月-2021年12月447例于本院行皮肤肿瘤切除术的老年患者病历资料，根据诊断标准分为感染组（31例）和非感染组（416例）。使用单因素分析和多因素Logistic回归分析确定术后感染的独立危险因素，并建立包含这些因素的列线图。通过Bootstrap抽样法进行内部验证，应用一致性指数（C-index）、受试者工作特征曲线（ROC曲线）、校准曲线、和决策曲线（DCA曲线）评估模型的预测能力。结果 447例患者术后切口感染发生率为6.94%。单因素分析显示，两组吸烟史、糖尿病病史、手术部位、手术类型、术后抗生素使用、术后康复教育及护理比较，差异有统计学意义（P＜0.05）。Logistic回归分析显示，老年面部皮肤肿瘤患者术后切口感染的独立危险因素为吸烟、糖尿病、手术部位为鼻部、面颊部和耳部、皮瓣手术、术后未使用抗生素以及术后未进行康复教育及护理。根据危险因素，成功构建列线图预测模型。列线图预测模型的C-index为0.811，ROC曲线下面积为0.811。校准曲线表明列线图校准良好，DCA曲线表明列线图模型具有良好的临床应用能力。结论 吸烟、糖尿病、手术部位、手术类型、术后未使用抗生素以及术后未进行康复教育及护理是老年面部皮肤肿瘤患者术后切口感染的独立危险因素。基于这些因素构建的临床预测模型稳定性好，并具有一定的预测效能。
Abstract:
Objective To establish a nomogram prediction model for the risk of postoperative incision infection in elderly patients with facial skin tumors and verify its predictive ability.Methods The medical records of 447 elderly patients who underwent skin tumor resection in our hospital from January 2018 to December 2021 were collected by retrospective analysis. According to the diagnostic criteria, they were divided into infection group (31 patients) and non-infection group (416 patients). Univariate analysis and multivariate logistic regression analysis were used to determine the independent risk factors for postoperative infection, and a nomogram containing these factors was established. The internal validation was performed by Bootstrap sampling method, and the predictive ability of the model was evaluated by consistency index (C-index), receiver operating characteristic curve ( ROC curve ), calibration curve and decision curve (DCA curve).Results The incidence of postoperative incision infection in 447 patients was 6.94 %. Univariate analysis showed that there were significant differences in smoking history, diabetes history, surgical site, surgical type, postoperative antibiotic use, postoperative rehabilitation education and nursing between the two groups (P<0.05). Logistic regression analysis showed that the independent risk factors for postoperative incision infection in elderly patients with facial skin tumors were smoking, diabetes, surgical sites of nose, cheek and ear, flap surgery, no use of antibiotics after surgery, and no rehabilitation education and nursing after surgery. According to the risk factors, the nomogram prediction model was successfully constructed. The C-index of the nomogram prediction model was 0.811, and the area under the ROC curve was 0.811. The calibration curve showed that the nomogram was well calibrated, and the DCA curve showed that the nomogram model had good clinical application ability.Conclusion Smoking, diabetes, surgical site, type of operation, no use of antibiotics after operation and no rehabilitation education and nursing after operation are independent risk factors for postoperative incision infection in elderly patients with facial skin tumors. The clinical prediction model based on these factors has good stability and certain prediction efficiency.

参考文献/References:

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更新日期/Last Update: 1900-01-01