原发性手汗症交感神经切断术后严重代偿性多汗的临床预测模型构建

Construction of a clinical prediction model for severe compensatory hyperhidrosis after thoraco-scopic thoracic sympathectomy for primary palmar hyperhidrosis

目的原发性手汗症(PPH)胸腔镜下胸交感神经切断术(ETS)后严重的代偿性多汗(SCH)的临床预测模型构建.方法选取2017年2月至2023年3月在新疆医科大学第一附属医院胸外科行ETS的115例PPH患者资料,并随访收集患者术后SCH的发生情况.根据是否发生术后SCH,将患者分为非SCH(NSCH)组的患者89例,和SCH的患者26例比较两组患者的临床资料.进行单因素和多因素Logistic回归分析判定出发生术后SCH独立危险因素,并构建出预测模型,采用ROC曲线评估预测模型,组间比较采用t检验.结果多因素Logistic回归分析显示,年龄[比值比(OR)=1.111,95%CI:1.026~1.214,P<0.05]、吸烟史(OR=20.345,95%CI:5.623~29.768,P<0.05)和手汗症症状严重程度(OR=4.093,95%CI:1.308~14.702,P<0.05)是发生术后SCH独立危险因素,将这些独立危险因素纳入构建预测模型的ROC曲线下面积为0.874,灵敏度为0.885,特异度为0.697.结论进行ETS术的患者年龄大、有吸烟史以及手汗症症状严重者更容易出现SCH,利用临床预测模型可以识别ETS术后SCH发生的高危人群.

Objective To construct a clinical prediction model for severe compensatory hyper-hidrosis(SCH)following endoscopic thoracic sympathectomy(ETS)for primary palmar hyperhidrosis(PPH).Methods The study included 115 PPH patients who underwent ETS surgery at the Department of Thoracic Surgery,First Affiliated Hospital of Xinjiang Medical University,from February 2017 to March 2023.Patient follow-up was conducted to collect information on postoperative SCH occurrence.Patients were divided into two groups:a non-SCH(NSCH)group with 89 patients and an SCH group with 26 pa-tients.Logistic regression analysis was done to identify independent risk factors for postoperative SCH and build a predictive model,then the model was evaluated using ROC curves.Tukey's test was used for pair-wise comparison.Results The results of multivariate Logistic regression analysis revealed that age[odds ratio(OR)=1.111,95%CI:1.026-1.214,P<0.05],smoking(OR=20.345,95%CI:5.623-29.768,P<0.05),and severity of PPH symptoms(OR=4.093,95%CI:1.308-14.702,P<0.05)were identified as independent risk factors for SCH.These significant risk factors were incorporated into the development of a clinical prediction model.The area under the ROC curve of the predictive model was 0.874,with a sensitivity of 0.885 and specificity of 0.697.Conclusion ETS patients who are older,have a history of smoking,and experience severe symptom are more prone to developing SCH.High-risk individuals after surgery can be identified through the use of clinical prediction models.