Robotic free pericardial fat pledget technique for treating pulmonary air leak.
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ABSTRACT:
SUBMITTER: Takase Y
PROVIDER: S-EPMC9737043 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
Publications
Robotic free pericardial fat pledget technique for treating pulmonary air leak.
Takase Yoshiaki Y Takahashi Yuki Y Miyajima Masahiro M Watanabe Atsushi A
JTCVS techniques 20221019
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Project description:Here, we introduce a new method for intraoperative control of air leak using a free pericardial fat pad covering to lung damage with sutureless fixation. We covered the damaged lung tissue with a free pericardial fat pad with a polyglycol acid sheet and fibrin glue fixation. This method provides a good air leak controlling effect with the use of a free pericardial fat pad and relatively short operative time with sutureless fixation.
| S-EPMC10481144 | biostudies-literature
Project description:Background and objectiveProlonged air leak (PAL) following lung resection is related to an increase in morbidity and both direct and indirect costs. In recent years, robotic-assisted thoracic surgery (RATS) has proved to be a safe technique with comparable perioperative outcomes of video-assisted thoracic surgery (VATS), optimal oncological results, and potential advantages in case of sublobar resection. We here focus on the incidence and clinical impact of PAL in the field of robotic surgery and discuss the therapeutic strategies currently available.MethodsWe conducted a search on PubMed/MEDLINE and Scopus database from inception until May 27th 2022 to select the relevant literature published in English exploring the occurrence of PAL following RATS.Key content and findingsThe implementation of robotic surgery led to a significant reduction in PAL occurrence after pulmonary resection compared to open thoracotomy, while there is still no clear advantage with respect to VATS. However, the enhanced dexterity and improved visualization of the robot seem to particularly valuable in case of sublobar lung resection, especially complex ones. Accurate selection of patients based on the presence of risk factors allows the implementation of intraoperative measures in order to reduce the occurrence of PAL.ConclusionsRobotic lung resection is a safe technique, advantageous compared to traditional open thoracotomy in terms of PAL occurrence reduction and it is a valid alternative to manual VATS. Moreover, with the extension of indications for sublobar resection in the treatment of early stage lung cancer, RATS may prove to be the technique of choice thanks to its intrinsic advantages.
| S-EPMC9992620 | biostudies-literature
Project description: Not available
| S-EPMC11632388 | biostudies-literature
Project description:Pulmonary air leak is the most common complication of lung surgery, with air leaks that persist longer than 5 days representing a major source of post-surgery morbidity. Clinical management of air leaks is challenging due to limited methods to precisely locate and assess leaks. Here, we present a sound-guided methodology that enables rapid quantitative assessment and precise localization of air leaks by analyzing the distinct sounds generated as the air escapes through defective lung tissue. Air leaks often present after lung surgery due to loss of tissue integrity at or near a staple line. Accordingly, we investigated air leak sounds from a focal pleural defect in a rat model and from a staple line failure in a clinically relevant swine model to demonstrate the high sensitivity and translational potential of this approach. In rat and swine models of free-flowing air leak under positive pressure ventilation with intrapleural microphone 1 cm from the lung surface, we identified that: (a) pulmonary air leaks generate sounds that contain distinct harmonic series, (b) acoustic characteristics of air leak sounds can be used to classify leak severity, and (c) precise location of the air leak can be determined with high resolution (within 1 cm) by mapping the sound loudness level across the lung surface. Our findings suggest that sound-guided assessment and localization of pulmonary air leaks could serve as a diagnostic tool to inform air leak detection and treatment strategies during video-assisted thoracoscopic surgery (VATS) or thoracotomy procedures.
| S-EPMC9842055 | biostudies-literature
Project description:ObjectiveProlonged air leak increases costs and worsens outcomes after pulmonary resection. We aimed to develop a clinical prediction tool for prolonged air leak using pretreatment and intraoperative variables.MethodsPatients who underwent pulmonary resection for lung cancer/nodules (from January 2009 to June 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 was developed.ResultsA 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 vs 4 days; P < .001). Final model variables associated with increased risk included low percent forced expiratory volume in 1 second, smoking history, bilobectomy, higher annual surgeon caseload, previous 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% confidence interval [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 < .001). Patients at intermediate and high risk were 4.80 times (95% CI, 2.86-8.07) and 11.86 times (95% CI, 7.21-19.52) more likely to have prolonged air leak compared with patients at low risk.ConclusionsUsing 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.
| S-EPMC5651171 | biostudies-literature
Project description:Purpose:Prolonged air leak (PAL) is a challenging complication in thoracic surgery. The aim of this study was to analyze the incidence, risk factors, and outcomes of PAL. Methods:We retrospectively analyzed 319 patients treated in a single center submitted to lobectomy, bilobectomy, segmentectomy, and wedge resections from January 2012 until August 2015. PAL was defined as air leak lasting more than 7 days after surgery. Results:The incidence of PAL was 14.7%. Bronchial obstruction (p?<?0.05), low body mass index (BMI, p?<?0.05), and hypoproteinemia (p?<?0.001) were identified as independent preoperative risk factors of PAL. Intraoperative risk factors were lob- (p?<?0.01) and bilobectomies (p?<?0.05), pleural adhesions (p <?0.001), and length of stapler line (p?<?0.001). Among the postoperative risk factors, we identified the use of active drainage (p?<?0.01), the presence of subcutaneous emphysema (p?<?0.001), massive air leak on the first postoperative day (POD 1, p?<?0.001), and an incomplete re-expansion of the lung (p?<?0.001). PAL was not associated with more complications in the postoperative period. One patient required reoperation due to a massive air leak. Twenty-six patients were discharged with a Heimlich valve with no complications and no need for re-admission. Conclusions:Bronchial obstruction, low BMI, hypoproteinemia, lob- and bilobectomies, pleural adhesions, length of stapler line, use of active drainage, the presence of subcutaneous emphysema, massive air leak on POD 1, and incomplete re-expansion of the lung were identified as independent risk factors of PAL. It had no influence on outcomes.
| S-EPMC7525848 | biostudies-literature
Project description:BackgroundProlonged air leak (PAL) is one of the most common postoperative complications after lung surgery. This study aimed to identify risk factors of PAL after lung resection and develop a preoperative predictive model to estimate its risk for individual patients.MethodsPatients with pulmonary malignancies or metastasis who underwent pulmonary resection between January 2014 and January 2018 were included. PAL was defined as an air leak more than 5 days after surgery, risk factors were analyzed. Forward stepwise multivariable logistic regression analysis was performed to identify independent risk factors, and a derived nomogram was built. Data from February 2018 to September 2018 were collected for internal validation.ResultsA total of 1,511 patients who met study criteria were enrolled in this study. The overall incidence of PAL was 9.07% (137/1,511). Age, percent forced expiratory volume in 1 second, surgical type, surgical approach and smoking history were included in the final model. A nomogram was developed according to the multivariable logistic regression results. The C-index of the predictive model was 0.70, and the internal validation value was 0.77. The goodness-of-fit test was non-significant for model development and internal validation.ConclusionsThe predictive model and derived nomogram achieved satisfied preoperative prediction of PAL. Using this nomogram, the risk for an individual patient can be estimated, and preventive measures can be applied to high-risk patients.
| S-EPMC8435390 | biostudies-literature
Project description: Not available
| S-EPMC10713297 | biostudies-literature
Project description: Not available
| S-EPMC10636457 | biostudies-literature
Project description:BackgroundProlonged air leak (PAL) remains one of the most frequent postoperative complications after pulmonary resection. This study aimed to develop a predictive nomogram to estimate the risk of PAL for individual patients after minimally invasive pulmonary resection.MethodsPatients who underwent minimally invasive pulmonary resection for either benign or malignant lung tumors between January 2020 and December 2021 were included. All eligible patients were randomly assigned to the training cohort or validation cohort at a 3:1 ratio. Univariate and multivariate logistic regression were performed to identify independent risk factors. All independent risk factors were incorporated to establish a predictive model and nomogram, and a web-based dynamic nomogram was then built based on the logistic regression model. Nomogram discrimination was assessed using the receiver operating characteristic (ROC) curve. The calibration power was evaluated using the Hosmer-Lemeshow test and calibration curves. The nomogram was also evaluated for clinical utility by the decision curve analysis (DCA).ResultsA total of 2213 patients were finally enrolled in this study, among whom, 341 cases (15.4%) were confirmed to have PAL. The following eight independent risk factors were identified through logistic regression: age, body mass index (BMI), smoking history, percentage of the predicted value for forced expiratory volume in 1 second (FEV1% predicted), surgical procedure, surgical range, operation side, operation duration. The area under the ROC curve (AUC) was 0.7315 [95% confidence interval (CI): 0.6979-0.7651] for the training cohort and 0.7325 (95% CI: 0.6743-0.7906) for the validation cohort. The P values of the Hosmer-Lemeshow test were 0.388 and 0.577 for the training and validation cohorts, respectively, with well-fitted calibration curves. The DCA demonstrated that the nomogram was clinically useful. An operation interface on a web page ( https://lirongyangql.shinyapps.io/PAL_DynNom/ ) was built to improve the clinical utility of the nomogram.ConclusionThe nomogram achieved good predictive performance for PAL after minimally invasive pulmonary resection. Patients at high risk of PAL could be identified using this nomogram, and thus some preventive measures could be adopted in advance.
| S-EPMC9347096 | biostudies-literature