A clinical prediction model for prolonged air leak after pulmonary resection

Abstract

Objective Prolonged air leak increases cost and worsens outcomes after pulmonary resection. We aimed to develop a clinical prediction tool for prolonged air leak using pretreatment and intraoperative variables. Methods Patients who underwent pulmonary resection for lung cancer/nodules (1/2009-6/2014) were stratified by prolonged parenchymal air leak (>5 days). Using backward stepwise logistic regression with bootstrap resampling for internal validation, candidate variables were identified and a nomogram risk calculator developed. Results A total of 2317 patients underwent pulmonary resection for lung cancer/nodules. Prolonged air leak (8.6%, n=200) was associated with significantly longer hospital stay (median 10 versus 4 days; p<0.001). Final model variables associated with increased risk included low percent forced expiratory volume in 1 second, smoking history, bilobectomy, higher annual surgeon caseload, prior chest surgery, Zubrod score>2, and interaction terms for right-sided thoracotomy and wedge-resection by thoracotomy. Wedge resection, higher body mass index, and unmeasured percent forced expiratory volume in 1 second were protective. Derived nomogram discriminatory accuracy was 76% (95% CI 0.72–0.79) and facilitated patient stratification into low, intermediate and high risk groups with monotonic increase in observed prolonged air leaks (2.0%; 8.9 %; and 19.2%, respectively; p-value<0.001). Intermediate and high risk patients were 4.80 (95% CI 2.86–8.07) and 11.86 times (95% CI 7.21–19.52) more likely to have prolonged air leak compared to low risk patients. Conclusions Using readily available candidate variables, our nomogram predicts increasing risk of prolonged air leak with good discriminatory ability. Risk stratification can support surgical decision-making, and help initiate proactive, patient-specific surgical management.

A nomogram to predict the survival of stage IIIA-N2 non–small cell lung cancer after surgery

“…Significant variables were selected by the backward stepwise selection method based on Akaike information criterion. 13 Variables no longer contributing either statistically or clinically on statistical adjustment were then excluded. Based on the significant variables, a nomogram was constructed via the RMS package in R 3.3.1 (R Foundation for Statistical Computing, Vienna, Austria).…”

The everlasting issue of prolonged air leaks after lobectomy for non‐small cell lung cancer: A data‐driven prevention planning model in the era of minimally invasive approaches

“…We identified a cut-off value at 24, which is similar to 25.5 pointed out by Brunelli. 18 This seems mostly because of a protective effect of diminished alveolar pressure, lower functional residual capacity and tidal volume, typical of overweight individuals ("biomechanical sealing milieu" 19,25 ). Lower FEV1 has long been recognized as a risk factor for PAL.…”

Intraoperative ventilatory leak predicts prolonged air leak after lung resection: A retrospective observational study

“…Elderly patients are more likely to have fragile lung parenchyma with reduced healing capacity, which may lead to PAL. Low BMI was also a significant risk factor of PAL, possibly because it represents poor nutritional status, which may also contribute to delayed healing [ 6 , 15 ]. Reduced preoperative pulmonary function, old age, and low BMI are consistent with the factors included in the previously reported scoring system to predict PAL [ 6 ].…”