Department of Cardiovascular and Thoracic Surgery, Rush University Medical Center, Chicago, Illinois.
Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois.
Ann Thorac Surg. 2019 Nov;108(5):1478-1483. doi: 10.1016/j.athoracsur.2019.05.069. Epub 2019 Jul 16.
The objective of this study was to create a simple preoperative tool to assess the risk of prolonged air leak (PAL) using The Society of Thoracic Surgeons General Thoracic Surgery Database (STS GTSD).
The STS GTSD was queried for patients who underwent elective lung cancer resection between 2009 and 2016. Exclusion criteria included pneumonectomy, sleeve lobectomy, chest wall resection, bilateral procedures, and patients with incomplete data sets. The primary outcome was PAL exceeding 5 days. Multivariable logistic regression was used to identify risk factors for a PAL. Model coefficients were used to generate a PAL score (PALS). The approach was cross-validated in 100 replications of a training set consisting of two-thirds of the cohort that was randomly selected and a validation set of remaining patients.
A total of 52,198 patients from the STS GTSD met inclusion criteria, with an overall rate of PAL of 10.4% (n = 5453). Final variables incorporated into the PALS included body mass index of 25 kg/m or less (7 points), lobectomy or bilobectomy (6 points), forced expiratory volume in 1 second of 70% predicted or less (5 points), male sex (4 points), and right upper lobe procedure (3 points). A cumulative PALS exceeding 17 points stratified patients as high-risk or low-risk for PAL (19.6% vs 9% rate of PAL) with a cross-validated mean negative predictive value of 91%, positive predictive value of 19%, sensitivity of 30%, specificity of 85%, and correctly classifies 79% of patients.
The PALS is a simple preoperative clinical tool that can reliably risk-stratify patients for PAL who are undergoing lung cancer resection.
本研究旨在使用胸外科医师学会普通胸外科数据库(STS GTSD)创建一种简单的术前工具,以评估延长漏气(PAL)的风险。
从 STS GTSD 中查询 2009 年至 2016 年间接受择期肺癌切除术的患者。排除标准包括全肺切除术、袖状肺叶切除术、胸壁切除术、双侧手术以及数据不完整的患者。主要结局是 PAL 超过 5 天。多变量逻辑回归用于确定 PAL 的危险因素。模型系数用于生成 PAL 评分(PALS)。该方法在从队列中随机选择的三分之二的训练集和剩余患者的验证集中进行了 100 次交叉验证。
STS GTSD 共纳入 52198 例患者,PAL 总发生率为 10.4%(n=5453)。纳入 PALS 的最终变量包括体重指数为 25kg/m2 或以下(7 分)、肺叶切除术或双肺叶切除术(6 分)、第 1 秒用力呼气量预测值的 70%或以下(5 分)、男性(4 分)和右上叶手术(3 分)。累积 PALS 超过 17 分将患者分为 PAL 高危或低危(PAL 发生率分别为 19.6%和 9%),交叉验证平均阴性预测值为 91%,阳性预测值为 19%,敏感性为 30%,特异性为 85%,正确分类 79%的患者。
PALS 是一种简单的术前临床工具,可可靠地对接受肺癌切除术的患者进行 PAL 风险分层。