Department of Critical Care Medicine, West China Hospital, Sichuan University and Institute of Critical Care Medicine, No. 17, Section 3, Renmin South Road, Wuhou District, Chengdu City, Sichuan Province, 610041, China.
BMC Pulm Med. 2024 Aug 29;24(1):420. doi: 10.1186/s12890-024-03153-z.
Postoperative pulmonary complication (PPC) is a leading cause of mortality and poor outcomes in postoperative patients. No studies have enrolled intensive care unit (ICU) patients after noncardiac thoracic surgery, and effective prediction models for PPC have not been developed. This study aimed to explore the incidence and risk factors and construct prediction models for PPC in these patients.
This study retrospectively recruited patients admitted to the ICU after noncardiac thoracic surgery at West China Hospital, Sichuan University, from July 2019 to December 2022. The patients were randomly divided into a development cohort and a validation cohort at a 70% versus 30% ratio. The preoperative, intraoperative and postoperative variables during the ICU stay were compared. Univariate and multivariate logistic regression analyses were applied to identify candidate predictors, establish prediction models, and compare the accuracy of the models with that of reported risk models.
A total of 475 ICU patients were enrolled after noncardiac thoracic surgery (median age, 58; 72% male). At least one PPC occurred in 171 patients (36.0%), and the most common PPC was pneumonia (153/475, 32.21%). PPC significantly increased the duration of mechanical ventilation (p < 0.001), length of ICU stay (p < 0.001), length of hospital stay (LOS) (p < 0.001), and rate of reintubation (p = 0.047) in ICU patients. Seven risk factors were identified, and then the prediction nomograms for PPC were constructed. At ICU admission, the area under the curve (AUC) was 0.766, with a sensitivity of 0.71 and specificity of 0.60; after extubation, the AUC was 0.841, with a sensitivity of 0.75 and specificity of 0.83. The models showed robust discrimination in both the development cohort and the validation cohort, and they were well calibrated and more accurate than reported risk models.
ICU patients who underwent noncardiac thoracic surgery were at high risk of developing PPCs. Prediction nomograms were constructed and they were more accurate than reported risk models, with excellent sensitivity and specificity. Moreover, these findings could help assess individual PPC risk and enhance postoperative management of patients.
术后肺部并发症（PPC）是术后患者死亡和预后不良的主要原因。尚无研究纳入非心脏胸外科术后的重症监护病房（ICU）患者，也没有开发出用于 PPC 的有效预测模型。本研究旨在探讨这些患者 PPC 的发生率、风险因素，并构建预测模型。
本研究回顾性纳入 2019 年 7 月至 2022 年 12 月在四川大学华西医院 ICU 接受非心脏胸外科手术后的患者。患者按 70%与 30%的比例随机分为发展队列和验证队列。比较 ICU 住院期间的术前、术中及术后变量。应用单因素和多因素 logistic 回归分析确定候选预测因素，建立预测模型，并比较模型与报告的风险模型的准确性。
共纳入 475 例非心脏胸外科手术后 ICU 患者（中位年龄 58 岁，72%为男性）。至少发生 1 次 PPC 的患者有 171 例（36.0%），最常见的 PPC 是肺炎（153/475，32.21%）。PPC 显著增加了 ICU 患者机械通气时间（p<0.001）、ICU 住院时间（p<0.001）、住院时间（LOS）（p<0.001）和再次插管率（p=0.047）。确定了 7 个风险因素，然后构建了 PPC 预测列线图。入 ICU 时，曲线下面积（AUC）为 0.766，敏感性为 0.71，特异性为 0.60；拔管后，AUC 为 0.841，敏感性为 0.75，特异性为 0.83。模型在发展队列和验证队列中均具有良好的区分度，且校准良好，优于报告的风险模型。
接受非心脏胸外科手术的 ICU 患者发生 PPC 的风险较高。构建的预测列线图比报告的风险模型更准确，具有良好的敏感性和特异性。此外，这些发现有助于评估个体 PPC 风险，并增强对患者术后的管理。
