Oh Sang Gi, Jung Yochun, Jheon Sanghoon, Choi Yunhee, Yun Ju Sik, Na Kook Joo, Ahn Byoung Hee
Department of Thoracic and Cardiovascular Surgery, Chonnam National University Hospital, Chonnam National University School of Medicine, 42 Jebong-ro, 501-757, Dong-gu, Gwangju, South Korea.
Department of Thoracic and Cardiovascular Surgery, Seoul National University Bundang Hospital, Seongnam, South Korea.
J Cardiothorac Surg. 2017 Jan 23;12(1):1. doi: 10.1186/s13019-017-0568-6.
Results of studies to predict prolonged air leak (PAL; air leak longer than 5 days) after pulmonary lobectomy have been inconsistent and are of limited use. We developed a new scale representing the amount of early postoperative air leak and determined its correlation with air leak duration and its potential as a predictor of PAL.
We grade postoperative air leak using a 5-grade scale. All 779 lobectomies from January 2005 to December 2009 with available medical records were reviewed retrospectively. We devised six 'SUM' variables using air leak grades in the initial 72 h postoperatively.
Excluding unrecorded cases and postoperative broncho-pleural fistulas, there were 720 lobectomies. PAL occurred in 135 cases (18.8%). Correlation analyses showed each SUM variable highly correlated with air leak duration, and the SUM, which was the sum of six consecutive values of air leak grades for every 8 h record on postoperative days 2 and 3, was proved to be the most powerful predictor of PAL; PAL could be predicted with 75.7% and 77.7% positive and negative predictive value, respectively, when SUM ≥ 16. When 4 predictors derived from multivariable logistic regression of perioperative variables were combined with SUM, there was no significant increase in predictability compared with SUM alone.
This simple new method to predict PAL using SUM showed that the amount of early postoperative air leak is the most powerful predictor of PAL, therefore, grading air leak after pulmonary lobectomy is a useful method to predict PAL.
预测肺叶切除术后持续性漏气（PAL，漏气时间超过5天）的研究结果并不一致，且用途有限。我们开发了一种新的量表来表示术后早期漏气量，并确定其与漏气持续时间的相关性以及作为PAL预测指标的潜力。
我们使用5级量表对术后漏气进行分级。回顾性分析了2005年1月至2009年12月期间所有779例有可用病历的肺叶切除术。我们利用术后最初72小时内的漏气分级设计了六个“SUM”变量。
排除未记录的病例和术后支气管胸膜瘘，共有720例肺叶切除术。135例（18.8%）发生了PAL。相关性分析表明，每个SUM变量与漏气持续时间高度相关，并且SUM（即术后第2天和第3天每8小时记录的漏气分级的六个连续值之和）被证明是PAL的最强预测指标；当SUM≥16时，预测PAL的阳性预测值和阴性预测值分别为75.7%和77.7%。当将围手术期变量多变量逻辑回归得出的4个预测指标与SUM相结合时，与单独使用SUM相比，预测能力没有显著提高。
这种使用SUM预测PAL的简单新方法表明，术后早期漏气量是PAL的最强预测指标，因此，肺叶切除术后对漏气进行分级是预测PAL的一种有用方法。
