2016 Annual report from the Italian VATS Group

Does morbid obesity influence perioperative outcomes after video-assisted thoracic surgery (VATS) lobectomy for non-small cell lung cancer? Analysis of the Italian VATS group registry

OBJECTIVES

Obesity in Europe, and worldwide, has been an increasing epidemic during the past decades. Moreover, obesity has important implications regarding technical issues and the risks associated with surgical interventions. Nevertheless, there is a lack of evidence assessing the influence of obesity on video-assisted thoracic surgery (VATS) lobectomy results. Our study aimed to assess the impact of morbid obesity on perioperative clinical and oncological outcomes after VATS lobectomy using a prospectively maintained nationwide registry.

METHODS

The Italian VATS lobectomy Registry was used to collect all consecutive cases from 55 Institutions. Explored outcome parameters were conversion to thoracotomy rates, complication rates, intra-operative blood loss, surgical time, hospital postoperative length of stay, chest tube duration, number of harvested lymph-node, and surgical margin positivity.

RESULTS

From 2016 to 2019, a total of 4412 patients were collected. 74 patients present morbid obesity (1.7%). Multivariable-adjusted analysis showed that morbid obesity was associated with a higher rate of complications (32.8% vs 20.3%), but it was not associated with a higher rate of conversion, and surgical margin positivity rates. Moreover, morbid obesity patients benefit from an equivalent surgical time, lymph-node retrieval, intraoperative blood loss, hospital postoperative length of stay, and chest tube duration than non-morbid obese patients. The most frequent postoperative complications in morbidly obese patients were pulmonary-related (35%).

CONCLUSION

Our results showed that VATS lobectomy could be safely and satisfactorily conducted even in morbidly obese patients, without an increase in conversion rate, blood loss, surgical time, hospital postoperative length of stay, and chest tube duration. Moreover, short-term oncological outcomes were preserved.

Establishment of Minimally Invasive Thoracic Surgery Program

The establishment of minimally invasive surgery is a complex and difficult task. Video-assisted thoracic surgery (VATS) refers to a minimally invasive surgical technique that represents a less invasive approach to thoracic surgery using thoracoscopy. For lung cancer or esophageal cancer surgery, planning and establishing a team for minimally invasive surgery for the first time is not a simple task. Technical advances in surgical devices and the enhanced skill of surgeons are cornerstones of the development of minimally invasive surgery. Here, we review the meaning of minimally invasive thoracic surgery and discuss how to establish a team approach for VATS procedures.

Predicting a Prolonged Air Leak After Video-Assisted Thoracic Surgery, Is It Really Possible?

Validation of predictive risk models for prolonged air leak (PAL) is essential to understand if they can help to reduce its incidence and complications. This study aimed to evaluate both the clinical and statistical performances of 4 existing models. We selected 4 predictive PAL risk models based on their scientific relevance. We referred to these models as Chicago, Bordeaux, Leeds and Pittsburgh model, respectively, according to the affiliation place of the first author. These predicting risk models were retrospectively applied to patients recorded on the second edition of the Italian Video-Assisted Thoracoscopic Surgery Group registry. Predictions for each patient were calculated based on the logistic regression coefficient values provided in the original manuscripts. All models were tested for their overall performance, discrimination, and calibration. We recalibrated the original models with the re-estimation of the model intercept and slope. We used curve decision analysis to describe and compare the clinical effects of the studied risk models. Better statistical metrics characterize the models developed on larger populations (Chicago and Bordeaux models). However, no model has a valid benefit for threshold probability greater than 0.30. The Net benefit of the most performing model (Bordeaux model) at the threshold probability of 0.11 is 23 of 1000 patients, burdened by 333 false positive cases. One of 1000 is the Net benefit at the threshold probability of 0.3. The use of PAL scores based on preoperative predictive factors cannot be currently used in a clinical setting because of a high false positive rate and low positive predictive value.