■通过确定与脊柱手术后肺炎风险增加相关的术前因素来开发和验证风险预测模型。
■这项研究纳入了2021年1月至2023年6月来自两家医院的脊柱疾病患者。将患者分为训练集和验证集,分为术后肺炎(POP)或非POP,分别。本研究使用多变量逻辑回归分析确定了POP的独立风险变量。使用风险因素开发并验证了列线图预测模型,接收机工作特性(ROC)曲线,校正曲线,和决策曲线分析(DCA)来评估预测性能。
■排除后,2223名来自长征医院的患者被纳入培训集,357名患者被纳入培训集。解放军海军905医院入选验证集。单因素和多因素逻辑回归分析显示,手术时间,美国麻醉医师协会(ASA)等级,吸烟,不戴医用口罩,缺乏术前呼吸训练,慢性阻塞性肺疾病(COPD),潜在的疾病,和脊柱切段是脊柱疾病患者发生POP的危险因素。训练集的ROC曲线下面积为0.950,而验证集为0.879。模型校准曲线表现出良好的一致性,DCA显示较高的预期净收益值。
■POP风险预测模型在预测脊柱疾病患者POP方面具有很高的准确性和效率。POP发展受手术时间、ASA等级,吸烟,不戴医用口罩,缺乏术前呼吸训练,COPD,潜在的疾病,还有腰椎手术.
UNASSIGNED: To develop and validate a risk prediction model by identifying the preoperative factors associated with an increased risk of pneumonia after spinal surgery.
UNASSIGNED: This study included patients with spinal disease from two hospitals between January 2021 and June 2023. The patients were divided into the training and validation sets, which were categorized as postoperative pneumonia (POP) or non-POP, respectively. This study identified the independent risk variables for POP using a multivariate logistic regression analysis. A nomogram prediction model was developed and validated using risk factors, receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) to assess predictive performance.
UNASSIGNED: Following exclusion, 2223 patients from Changzheng Hospital were enrolled in the training set and 357 patients from the No. 905 Hospital of PLA Navy were enrolled in the validation set. Univariate and multivariate logistic regression analyses revealed that operation time, American Society of Anesthesiologists (ASA) grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, chronic obstructive pulmonary disease (COPD), underlying diseases, and spinal section were risk factors for POP development in patients with spinal diseases. The area under the ROC curve of the training set was 0.950, whereas that of the validation set was 0.879. The model calibration curves demonstrated good agreement, and the DCA indicated a high expected net benefit value.
UNASSIGNED: The POP risk prediction model has high accuracy and efficiency in predicting POP in patients with spinal diseases. POP development is influenced by factors such as operation length, ASA grade, smoking, non-wearing of medical masks, lack of preoperative respiratory training, COPD, underlying diseases, and lumbar surgery.