Dataset Information

30-Day Outcomes After Intraoperative Leak Testing for Bariatric Surgery Patients.

ABSTRACT: BACKGROUND:Intraoperative testing of anastomoses and staples lines is commonly performed to minimize the risk of postoperative leaks in bariatric surgery, but its impact is unclear. The aim of this study was to determine the association between leak testing and 30-d postoperative leak, bleed, reoperation, and readmission rates for patients undergoing laparoscopic sleeve gastrectomy (LSG) or Roux-en-Y gastric bypass (RYGB). METHODS:This is a retrospective observational study utilizing 2015-2016 data from the Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database. Postoperative outcomes were compared using ?2 test. Multivariable logistic regression was used to identify factors associated with 30-d outcomes. RESULTS:We included 237,081 patients. Leak testing was performed on 73.0% and 92.1% of LSG and RYGB patients, respectively. LSG was associated with lower rates of leak, bleed, reoperation, and readmission than RYGB. On multivariable analysis, intraoperative leak testing was associated with increased rates of postoperative leak for LSG and RYGB (OR 1.48 and 1.90, respectively) and lower rates of bleed for LSG (OR 0.76). There were no significant associations between leak testing and rates of reoperation or readmission. CONCLUSIONS:Use of intraoperative leak testing was not associated with improved outcomes for either LSG or RYGB. A prospective trial investigating leak testing is warranted to better elucidate its impact.

SUBMITTER: Liu N

PROVIDER: S-EPMC6679992 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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30-Day Outcomes After Intraoperative Leak Testing for Bariatric Surgery Patients.

Liu Natalie N Cusack Meghan C MC Venkatesh Manasa M Pontes Anisa L AL Shea Grace G Svoboda Dillon C DC Greenberg Jacob A JA Lidor Anne O AO Funk Luke M LM

The Journal of surgical research 20190508

<h4>Background</h4>Intraoperative testing of anastomoses and staples lines is commonly performed to minimize the risk of postoperative leaks in bariatric surgery, but its impact is unclear. The aim of this study was to determine the association between leak testing and 30-d postoperative leak, bleed, reoperation, and readmission rates for patients undergoing laparoscopic sleeve gastrectomy (LSG) or Roux-en-Y gastric bypass (RYGB).<h4>Methods</h4>This is a retrospective observational study utiliz ...[more]

PMID: 31077945

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Project description:IntroductionBariatric surgery performed at high volume centers decreases length of stay, cost, and morbidity and mortality. The effect of a high volume of bariatric surgery procedures on outcomes may extend not just to bariatric surgery but to any general surgical procedure in morbidly obese patients. We hypothesized that patients with morbid obesity (body mass index >40 kg/m2) undergoing common, nonbariatric general surgery would have decreased morbidity and mortality at centers performing high volumes of bariatric surgery.MethodsThe 2016 National Inpatient Sample (NIS) was used to identify the number of laparoscopic gastric bypass and sleeve gastrectomy performed at each hospital. Hospitals were classified as high volume bariatric hospitals (HVBH) ≥10 reported cases (50 actual)/year or low volume bariatric hospitals (LVBH) <10 reported cases (50 actual)/year, as NIS reports a 20% sample of actual cases. Patients with morbid obesity undergoing laparoscopic or open appendectomy, cholecystectomy, or ventral hernia repair were included for analysis. Propensity scores were developed based on available demographics, comorbidities, and hospital procedure volume. Postoperative complications during the index hospital admission, determined by ICD-10 code, were compared using inverse propensity weights. Differences were considered significant with a p value of <0.05.ResultsThe total number of general surgery patient cases analyzed was 14,028 from 2,482 hospitals, representing 70,140 admissions. The cohort of patients undergoing operations treated at HVBH were younger (p=0.03) with higher rates of COPD (p=0.04). Patients at LVBH had higher rates of nicotine dependence (p=0.0001) and obstructive sleep apnea (p < 0.001). On propensity-weighted analysis adjusting for preoperative comorbidities and hospital procedure volume, there were significantly higher rates of multiple postprocedure complications at LVBH, specifically, postprocedure respiratory failure for patients undergoing elective laparoscopic cholecystectomy, elective ventral hernia repair with mesh and appendectomy.ConclusionPatients with morbid obesity may have an advantage in having general surgery procedures at HVBH. HVBH may have a volume-outcomes relationship where the hospital and staff familiarity with the management principles required to minimize the postoperative risk associated with morbid obesity and improve patient outcomes.

Project description:ImportanceQuality improvement programs for colorectal cancer surgery have been introduced with benchmarking based on quality indicators, such as mortality. Detailed (pre)operative characteristics may offer relevant information for proper case-mix correction.ObjectiveTo investigate the added value of machine learning to predict quality indicators for colorectal cancer surgery and identify previously unrecognized predictors of 30-day mortality based on a large, nationwide colorectal cancer registry that collected extensive data on comorbidities.Design, setting, and participantsAll patients who underwent resection for primary colorectal cancer registered in the Dutch ColoRectal Audit between January 1, 2011, and December 31, 2016, were included. Multiple machine learning models (multivariable logistic regression, elastic net regression, support vector machine, random forest, and gradient boosting) were made to predict quality indicators. Model performance was compared with conventionally used scores. Risk factors were identified by logistic regression analyses and Shapley additive explanations (ie, SHAP values). Statistical analysis was performed between March 1 and September 30, 2020.Main outcomes and measuresThe primary outcome of this cohort study was 30-day mortality. Prediction models were trained on a training set by performing 5-fold cross-validation, and outcomes were measured by the area under the receiver operating characteristic curve on the test set. Machine learning was further used to identify risk factors, measured by odds ratios and SHAP values.ResultsThis cohort study included 62 501 records, most patients were male (35 116 [56.2%]), were aged 61 to 80 years (41 560 [66.5%]), and had an American Society of Anesthesiology score of II (35 679 [57.1%]). A 30-day mortality rate of 2.7% (n = 1693) was found. The area under the curve of the best machine learning model for 30-day mortality (0.82; 95% CI, 0.79-0.85) was significantly higher than the American Society of Anesthesiology score (0.74; 95% CI, 0.71-0.77; P < .001), Charlson Comorbidity Index (0.66; 95% CI, 0.63-0.70; P < .001), and preoperative score to predict postoperative mortality (0.73; 95% CI, 0.70-0.77; P < .001). Hypertension, myocardial infarction, chronic obstructive pulmonary disease, and asthma were comorbidities with a high risk for increased mortality. Machine learning identified specific risk factors for a complicated course, intensive care unit admission, prolonged hospital stay, and readmission. Laparoscopic surgery was associated with a decreased risk for all adverse outcomes.Conclusions and relevanceThis study found that machine learning methods outperformed conventional scores to predict 30-day mortality after colorectal cancer surgery, identified specific patient groups at risk for adverse outcomes, and provided directions to optimize benchmarking in clinical audits.

Dataset Information

30-Day Outcomes After Intraoperative Leak Testing for Bariatric Surgery Patients.

Publications

30-Day Outcomes After Intraoperative Leak Testing for Bariatric Surgery Patients.

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