Prediction of thirty-day morbidity and mortality after duodenal switch using an artificial neural network

Wise, Eric S.; Leslie, Daniel B.; Amateau, Stuart K.; Hocking, Kyle M.; Scott, A N; Dutta, Nirjhar; Ikramuddin, Sayeed

doi:10.1007/s00464-022-09378-5

Cited by 4 publications

(7 citation statements)

References 22 publications

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“…17 In contrast, our data specifically sought to examine independent risk factors for occurrence of the highly clinically relevant and previously validated composite endpoint in patients undergoing conversion while excluding primary RYGB patients. 7,8 Nearly half of all SG patients may develop GERD in 8.5 years follow-up. 18 In the studied cohort, 61% of the patients were converted for GERD, consistent with previous studies recognizing it as the most common indication, though long-term outcomes may not necessarily be improved with RYGB anatomy.…”

Section: Discussionmentioning

confidence: 99%

“…Specifically, a previously validated composite endpoint representing the occurrence of at least 1 of these 4 endpoints was chosen for comparison between ANN and multivariable logistic regression models. 7,8 The 8895 patient cohort was comprehensively characterized. Demographics obtained included female gender, age at conversion, non-white race, and BMI.…”

Section: Methodsmentioning

confidence: 99%

“…The ANN model was generated using 80% of the patients (training set), with 20% randomly withheld (validation set), and created using a back-propagation technique with 3 nodes each assigned a .3333 training value. 8 The multivariable logistic regression and ANN predictive models were assessed using R 2 and area under the curve (AUC) of the Receiver Operating Characteristic curves (ROCs) as principal measures of goodness of fit. P ≤ .05 was taken as the criterion to denote statistical significance.…”

Section: Methodsmentioning

confidence: 99%

Figure 1.Derivation of 8895 patient cohort from the 2021 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program national database of patients having undergone sleeve gastrectomy to Roux-en-Y gastric bypass conversion procedures. GERD, gastroesophageal reflux disease.…”

Section: Methodsmentioning

confidence: 99%

“…Subsequently, bivariate analysis was used to determine association with the composite endpoint, using Fisher’s exact test or the Mann-Whitney U test as appropriate. 8 Factors associated with the composite endpoint ( P ≤ .05) were imputed in a multivariable logistic regression model to determine independent association. Additionally, these same factors were used to derive an ANN algorithm.…”

Section: Methodsmentioning

confidence: 99%

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Prediction of 30-Day Morbidity and Mortality After Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass: Use of an Artificial Neural Network

Scott,

Amateau,

Leslie

et al. 2024

The American Surgeon™

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Background Conversion of sleeve gastrectomy to Roux-en-Y gastric bypass is indicated primarily for unsatisfactory weight loss or gastroesophageal reflux disease (GERD). This study aimed to use a comprehensive database to define predictors of 30-day reoperation, readmission, reintervention, or mortality. An artificial neural network (ANN) was employed to optimize prediction of the composite endpoint (occurrence of 1+ morbid event). Methods Areview of 8895 patients who underwent conversion for weight-related or GERD-related indications was performed using the 2021 MBSAQIP national dataset. Demographics, comorbidities, laboratory values, and other factors were assessed for bivariate and subsequent multivariable associations with the composite endpoint ( P ≤ .05). Factors considered in the multivariable model were imputed into a three-node ANN with 20% randomly withheld for internal validation, to optimize predictive accuracy. Models were compared using receiver operating characteristic (ROC) curve analysis. Results 39% underwent conversion for weight considerations and 61% for GERD. Rates of 30-day reoperation, readmission, reintervention, mortality, and the composite endpoint were 3.0%, 7.1%, 2.1%, .1%, and 9.1%, respectively. Of the nine factors associated with the composite endpoint on bivariate analysis, only non-white race ( P < .001; odds ratio 1.4), lower body-mass index ( P < .001; odds ratio .22), and therapeutic anticoagulation ( P = .001; odds ratio 2.0) remained significant upon multivariable analysis. Areas under ROC curves for the multivariable regression, ANN training, and validation sets were .587, .601, and .604, respectively. Discussion Identification of risk factors for morbidity after conversion offers critical information to improve patient selection and manage postoperative expectations. ANN models, with appropriate clinical integration, may optimize prediction of morbidity.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Prediction of 30-Day Morbidity and Mortality After Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass: Use of an Artificial Neural Network

Scott,

Amateau,

Leslie

et al. 2024

The American Surgeon™

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Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis

Wang,

Tozzi,

Ashraf Ganjouei

et al. 2024

Journal of Gastrointestinal Surgery

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Rates and Risk Factors for 30-Day Morbidity After One-Stage Vertical Banded Gastroplasty Conversions: A Retrospective Analysis

Scott,

Amateau,

Leslie

et al. 2024

The American Surgeon™

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Background: The vertical banded gastroplasty (VBG) is a historic restrictive bariatric operation often requiring further surgery. In this investigation utilizing the 2021 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) national dataset, we aim to better define the outcomes of VBG conversions. Methods: We queried the 2021 MBSAQIP dataset for patients who underwent a conversion from a VBG to Roux-en-Y gastric bypass (RYGB) or sleeve gastrectomy (SG). Demographics, comorbidities, laboratory values, and additional patient factors were examined. Rates of key consequential outcome measures 30-day readmission, reoperation, reintervention, mortality, and a composite endpoint (at least 1 of the 4) were further calculated. Results: We identified 231 patients who underwent conversion from VBG to SG (n = 23), RYGB (n = 208), or other anatomy (n = 6), of which 93% of patients were female, and 22% of non-white race. The median age was 56 years and body-mass index (BMI) was 43 kg/m2. The most common surgical indications included weight considerations (48%), reflux (25%), anatomic causes (eg, stricture, fistula, and ulcer; 10%), and dysphagia (6.5%). Thirty-day morbidity rates included reoperation (7.8%), readmission (9.1%), reintervention (4.3%), mortality (.4%), and the composite endpoint (15%). Upon bivariate analysis, we did not identify any specific risk factor for the 30-day composite endpoint. Discussion: One-stage VBG conversions to traditional bariatric anatomy are beset with higher 30-day morbidity relative to primary procedures. Additional MBSAQIP data will be required for aggregation, to better characterize the risk factors inherent in these operations.

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Prediction of thirty-day morbidity and mortality after duodenal switch using an artificial neural network

Cited by 4 publications

References 22 publications

Prediction of 30-Day Morbidity and Mortality After Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass: Use of an Artificial Neural Network

Prediction of 30-Day Morbidity and Mortality After Conversion of Sleeve Gastrectomy to Roux-en-Y Gastric Bypass: Use of an Artificial Neural Network

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis

Rates and Risk Factors for 30-Day Morbidity After One-Stage Vertical Banded Gastroplasty Conversions: A Retrospective Analysis

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