崔翔, 黄太满. 预测全麻胸腔镜肺部手术病人术后呼吸抑制列线图模型的建立[J]. 蚌埠医科大学学报, 2024, 49(9): 1145-1149. DOI: 10.13898/j.cnki.issn.1000-2200.2024.09.005
    引用本文: 崔翔, 黄太满. 预测全麻胸腔镜肺部手术病人术后呼吸抑制列线图模型的建立[J]. 蚌埠医科大学学报, 2024, 49(9): 1145-1149. DOI: 10.13898/j.cnki.issn.1000-2200.2024.09.005
    CUI Xiang, HUANG Taiman. Establishment of a nomogram model for predicting postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia[J]. Journal of Bengbu Medical University, 2024, 49(9): 1145-1149. DOI: 10.13898/j.cnki.issn.1000-2200.2024.09.005
    Citation: CUI Xiang, HUANG Taiman. Establishment of a nomogram model for predicting postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia[J]. Journal of Bengbu Medical University, 2024, 49(9): 1145-1149. DOI: 10.13898/j.cnki.issn.1000-2200.2024.09.005

    预测全麻胸腔镜肺部手术病人术后呼吸抑制列线图模型的建立

    Establishment of a nomogram model for predicting postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia

    • 摘要: 目的: 构建预测全麻胸腔镜肺部手术病人术后呼吸抑制的列线图模型。方法: 选取220例行全身麻醉胸腔镜肺部手术的病人作为研究对象,根据术后是否发生呼吸抑制将病人分为呼吸抑制组41例和非呼吸抑制组179例。收集病人的临床资料,使用单因素和多因素logistic回归分析评价全麻胸腔镜肺部手术病人术后呼吸抑制的危险因素。采用R语言绘制列线图模型,并对其预测效能进行验证。结果: 220例病人中41例发生术后呼吸抑制,发生率18.64%。多因素logistic回归分析显示,年龄≥60岁、BMI≥28 kg/m2、手术时间长和使用右美托咪定是全麻胸腔镜肺部手术病人术后呼吸抑制的独立危险因素(P<0.05~P<0.01)。根据多因素回归分析结果建立预测全麻胸腔镜肺部手术病人术后呼吸抑制发生风险的列线图模型,模型验证结果显示C-index为0.801,校正曲线与理想曲线走势基本一致,AUC为0.792(95%CI:0.754~0.830),在12%~100%范围内,列线图预测的净获益值较高,表明该模型具有良好的预测能力。结论: 年龄≥60岁,BMI≥28 kg/m2、手术时间长和使用右美托咪定会增加全麻胸腔镜肺部手术病人术后呼吸抑制的风险。基于列线图构建的临床模型能有效预测全麻胸腔镜肺部手术病人术后呼吸抑制的风险。

       

      Abstract: Objective: To construct a nomogram model for predicting postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia. Methods: A total of 220 patients treated with thoracoscopic lung surgery under general anesthesia were selected as the study subjects.According to whether respiratory depression occurred after surgery,the patients were divided into the respiratory depression group(41 cases) and non-respiratory depression group(179 cases).The clinical data of patients were collected,and the univariate and multivariate logistic regression analysis were used to evaluate the risk factors of postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia.The R language was used to draw a nomogram model,and its prediction efficiency was verified. Results: Among 220 patients,the postoperative respiratory depression in 41 cases was found,and the incidene rate of which was 18.64%.The results of multivariate logistic regression analysis showed that the age ≥60 years,BMI≥28 kg/m2,long operation time and dexmedetomidine use were the independent risk factors of postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia(P<0.05 to P<0.01).Based on the results of multivariate regression analysis,a nomogram model was established to predict the risk of postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia.The results of model verification results showed that the C-index was 0.801,the correction curve was basically consistent with the ideal curve,the AUC was 0.792 (95%CI:0.754-0.830),and the net benefit value predicted by the column graph was high in the range of 12%-100%,which indicated that the model had good forecasting ability. Conclusions: The age≥60 years,BMI≥28 kg/m2,long operation time and use of dexmedetomidine increase the risk of postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia.The clinical model based on nomogram can effectively predict the risk of postoperative respiratory depression in patients treated with thoracoscopic lung surgery under general anesthesia.

       

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