Zhamak Khorgami

Several studies have developed predictive models for venous thromboembolism (VTE) after metabolic and bariatric surgery (MBS), but none have incorporated complications that increase VTE risk. This study aimed to evaluate the risk factors for VTE following MBS using machine learning (ML) algorithms, using models that either excluded or included time-aware postoperative complication variables-these were engineered to include only complications that occurred before the VTE event. We used the MBSAQIP database from 2020 to 2023. XGBoost, random forest classifiers, support vector machines (SVMs), artificial neural networks (ANNs), and logistic regression models were used to predict VTE after MBS in models with and without considering other postoperative complications that occurred before VTE occurrence. The study included 2198 and 698,284 VTE and non-VTE cases, respectively. For models excluding complications, the area under the curve (AUC) values were as follows: XGBoost (0.668), RandomForestClassifier (0.660), SVM (0.649), ANN (0.657), and logistic regression (0.669). Including time-adjusted complications improved all model performances, with AUCs of XGBoost (0.680), RandomForestClassifier (0.664), SVM (0.666), ANN (0.697), and logistic regression (0.690). The strongest postoperative predictor of VTE was the need for reoperation. Other postoperative predictors included prolonged length of stay, ICU admission, reintervention, organ-space surgical site infection, sepsis, and anastomotic leak. Postoperative complications and prolonged length of stay were strongly associated with VTE after MBS, suggesting that patients with these risk factors may benefit from enhanced prophylactic strategies.

Introduction Exploratory laparotomy has been the main method for surgical interventions in penetrating abdominal trauma (PAT). Minimally invasive surgery (MIS) has been utilized in the treatment of selected trauma patients as an alternative to laparotomy. This study aimed to investigate the utilization of MIS and open approaches in patients with PAT. Methods Patients who underwent surgical treatment for PAT were included in this study using the National Inpatient Sample 2016–2020. Patients who underwent diagnostic laparoscopy or other laparoscopic or robotic procedures during admission were categorized as MIS. Results A total of 94,280 patients with PAT were analyzed (open: 82,745 (87.8%), MIS: 8,630 (9.2%), and conversion to open: 2,905 (3.1%)). The trend of using a MIS approach remained stable between 2016 and 2020 (8.6–9.7%). Independent predictors of using MIS were younger age, female gender, higher median income of residence area, and urban nonteaching hospitals. Independent factors associated with less MIS intervention were Midwest and South locations, Black race, firearm mechanism, and a higher Charlson Comorbidity Index score or Injury Severity Score. MIS approach had significantly lower hospitalization cost median and interquartile range ($16,822 [11,764–26,489] vs $32,913 [20,270–63,016]) and shorter length of stay (4 [2–7] vs 8 [5–14] days) compared to open approach. The complication rate was lower in the MIS group. Conclusion The MIS approach is utilized in a subgroup of patients with PAT with acceptable outcomes, shorter length of stay, and reduced costs. Further research is needed to develop strategies to increase the utilization of MIS in the management of patients with trauma.

Background There is still a lack of sufficient data regarding the trend of cirrhosis and its impact on the perioperative and postoperative outcomes, and healthcare resource utilization in patients who underwent metabolic and bariatric surgery (MBS). Therefore, our study aimed to examine the impact of cirrhosis on MBS outcomes. Methods The current study used the Nationwide Readmissions Database (NRD) 2016–2020. Patients who underwent MBS were divided into cirrhosis and non-cirrhosis groups. Patients younger than 18 years, those with a history of upper gastrointestinal malignancy, and patients with decompensated cirrhosis (portal hypertension, ascites, or varices) and individuals with a previous history of MBS were excluded. Results The cirrhosis and non-cirrhosis groups consisted of 3064 and 538,329 patients, respectively. There was no significant change in the cirrhosis trend in patients who underwent MBS from 2016 to 2020. Cirrhosis was not associated with higher rates of in-hospital mortality (< 11 (< 0.36%) vs 99 (0.02%), p = 0.140), 90-day readmission (180 (6.57%) vs 24,204 (5.01%), p = 0.453), or most major complications. Although the overall incidence was low, cirrhosis was linked to higher rates of hepatic encephalopathy and acute heart failure. Patients with cirrhosis also had longer hospital stays, higher costs, and were more likely to have a non-home discharge. Among patients with cirrhosis, Roux-en-Y gastric bypass (OR 1.63, 95% CI 1.18–2.25, p = 0.003) and duodenal switch (OR 3.54, 95% CI 1.42–8.85, p = 0.007) were associated with a higher readmission rates compared to sleeve gastrectomy. Conclusion These results may indicate the safety of MBS in patients with compensated cirrhosis and obesity.

Objective: This study aimed to characterize the underdocumentation of obesity by comparing the rates of obesity in databases based on measured BMI, BMI measured while inpatient, and obesity ICD‐10 codes input by health providers for inpatients in the United States. Methods: We compared three datasets to test the prevalence of obesity in the United States general population and the inpatient hospital in the United States. The 2017–2018 National Health and Nutrition Examination (NHANES) dataset was used to estimate the prevalence in the general population. For the inpatient hospitals, we used data from the 2017 National Inpatient Sample (NIS) and the 2017–2018 American College of Surgeons–National Surgical Quality Improvement Program (NSQIP) datasets. Results: There were 5434 participants in the NHANES, 2,006,047 participants in the NSQIP, and 6,084,184 participants in the NIS databases for analysis. The overall prevalence/diagnosis of obesity was 41.9% for NHANES (nationwide survey), 44.5% for NSQIP (in‐hospital measurements), and 15.4% for NIS (ICD codes retrieved from medical charts). Conclusions: The prevalence of obesity in NIS (based on recorded obesity in medical charts) is significantly lower than NHANES and NSQIP (based on measured BMI) suggesting underrecognition or underdocumentation of obesity in the inpatient setting.

Introduction Patients who underwent bariatric surgery are at risk of dehydration and postoperative acute kidney injury (AKI). This study aimed to investigate the predictive factors of AKI after sleeve gastrectomy and gastric bypass, considering preoperative chronic kidney disease and postoperative complications as predisposing factors for AKI. Methods The MBSAQIP database was analyzed to assess patients who had AKI after gastric bypass or sleeve gastrectomy between 2015 and 2020. Patients were categorized based on postoperative AKI. Multivariate logistic regression was used to identify independent predictive factors of AKI in all the patients who underwent laparoscopic primary bariatric surgery. The analysis was repeated in patients without postoperative major complications, with subgroups with or without preoperative chronic kidney disease. Results Patients were divided into AKI (N = 1376) and non-AKI (N = 1,137,775) groups. The AKI group consists of a significantly older, more male, and black race, compared to the non-AKI group. The factors most predictive of AKI in all the patients consist of readmission within 30 days (OR = 10.10), ICU admission (OR = 7.90), septic shock (OR = 6.72), preoperative chronic kidney disease (OR = 5.95), myocardial infarction (OR = 3.9), cardiac arrest (OR = 3.5), using hypertension medication (OR = 3.3), previous organ transplant (OR = 3.2) and reintubation (OR = 3.08). Conclusion Various factors have been identified as independent predictors of AKI in patients who have undergone bariatric surgery. Recognizing these risk factors enables surgeons and clinicians to categorize patients more effectively and prioritize attention toward those at high risk, thus aiding in the prevention of AKI and its associated consequences.

This study aimed to systematically review existing evidence on the preoperative use of GLP-1 receptor agonists (GLP-1 RA) before metabolic and bariatric surgery (MBS). Web of Science, Embase, PubMed, and Scopus were searched systematically with relevant keywords for articles on the effect of preoperative GLP-1 RA use on MBS outcomes. Eleven observational studies evaluated the effects of preoperative GLP-1 RAs. GLP-1 RAs enhance preoperative weight loss with earlier optimization for MBS. Preoperative use of these agents were associated with increased postoperative nausea but showed no significant differences in the rate of major complications or readmissions. Benefits included improved diabetes outcomes, although findings on postoperative weight loss were inconsistent, and some studies reported higher surgical adhesion rates. More robust evidence is needed to guide the incorporation of GLP-1 RAs into preoperative pathways for MBS.

Purpose Protracted in-patient stays affect trauma patient costs and hospital resource utilizations. Proper discharge placement stratification may help with early discharge planning in this group of patients. No standardized discharge destination prediction model exists. A scoring model has been developed after examining Oklahoma Trauma Database discharge destination predictors. This study’s goal was patient data-driven model validation. Methods Level II trauma center patient data over three months, including comorbidities, injuries, and demographics were analyzed. We compared the scoring model discharge destination prediction with actual destinations. Results The study included 459 patients, with 108 facility discharges. The scoring model demonstrated significant facility placement prediction (Scores ≤ 7: 11.94% or Negative Predictive Value of 88.1%; Score 8–14: 47.22% as Positive Predictive Value: and Score ≥ 15: 60.00%). Scoring 8–14 showed a 6.60-fold (95%CI: 4.11, 10.61) increase compared to ≤ 7. Scoring ≥ 15 was 11.07 times (95%CI: 1.79, 68.42) more likely than ≤ 7. Conclusion The Oklahoma Trauma Discharge Predictive Scoring Model demonstrated significant facility discharge prediction and may assist with decreasing delay of anticipated patient discharge destination.