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Objective: To develop machine learning (ML) models that predict outcomes following endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA). Background: EVAR carries non-negligible perioperative risks; however, there are no widely used outcome prediction tools. Methods: The National Surgical Quality Improvement Program targeted database was used to identify patients who underwent EVAR for infrarenal AAA between 2011 and 2021. Input features included 36 preoperative variables. The primary outcome was 30-day major adverse cardiovascular event (composite of myocardial infarction, stroke, or death). Data were split into training (70%) and test (30%) sets. Using 10- fold cross-validation, 6 ML models were trained using preoperative features. The primary model evaluation metric was area under the receiver operating characteristic curve. Model robustness was evaluated with calibration plot and Brier score. Subgroup analysis was performed to assess model performance based on age, sex, race, ethnicity, and prior AAA repair. Results: Overall, 16,282 patients were included. The primary outcome of 30-day major adverse cardiovascular event occurred in 390 (2.4%) patients. Our best-performing prediction model was XGBoost, achieving an area under the receiver operating characteristic curve (95% CI) of 0.95 (0.94-0.96) compared with logistic regression [0.72 [0.70-0.74)]. The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.06. Model performance remained robust on all subgroup analyses. Conclusions: Our newer ML models accurately predict 30-day outcomes following EVAR using preoperative data and perform better than logistic regression. Our automated algorithms can guide risk mitigation strategies for patients being considered for EVAR. [ABSTRACT FROM AUTHOR]

Supplemental Digital Content is available in the text Objective: Describe clinical outcomes (eg, postoperative complications, survival) after robotic surgery compared to open or laparoscopic surgery. Background: Robotic surgery utilization has increased over the years across a wide range of surgical procedures. However, evidence supporting improved clinical outcomes after robotic surgery is limited. Methods: We systematically searched MEDLINE, EMBASE, and the Cochrane Central Register of systematic reviews from inception to January 2019 for systematic reviews describing postoperative outcomes after robotic surgery. We qualitatively described patient outcomes of commonly performed robotic procedures: radical prostatectomy, hysterectomy, lobectomy, thymectomy, rectal resection, partial nephrectomy, distal gastrectomy, Roux-en-Y gastric bypass, hepatectomy, distal pancreatectomy, and cholecystectomy. Results: One hundred fifty-four systematic reviews included 336 studies and 18 randomized controlled trials reporting on patient outcomes after robotic compared to laparoscopic or open procedures. Data from the randomized controlled trials demonstrate that robotic-assisted radical prostatectomy offered fewer biochemical recurrence and improvement in quality of recovery and pain scores only up to 6 weeks postoperatively compared to open radical prostatectomy. When compared to laparoscopic prostatectomy, robotic surgery offered improved urinary and sexual functions. Robotic surgery for endometrial cancer had fewer conversion to open compared to laparoscopic. Otherwise, robotic surgery outcomes were similar to conventional surgical approaches for other procedures except for radical hysterectomy where minimally invasive approaches may result in patient harm compared to open approach. Conclusion: Robotic surgery has been widely incorporated into practise despite limited supporting evidence. More rigorous research focused on patient-important benefits is needed before further expansion of robotic surgery. [ABSTRACT FROM AUTHOR]

Objective: To characterize the association between ambulatory cardiology or general internal medicine (GIM) assessment prior to surgery and outcomes following scheduled major vascular surgery., Background: Cardiovascular risk assessment and management prior to high-risk surgery remains an evolving area of care., Methods: This is population-based retrospective cohort study of all adults who underwent scheduled major vascular surgery in Ontario, Canada, April 1, 2004-March 31, 2019. Patients who had an ambulatory cardiology and/or GIM assessment within 6 months prior to surgery were compared to those who did not. The primary outcome was 30-day mortality. Secondary outcomes included: composite of 30-day mortality, myocardial infarction or stroke; 30-day cardiovascular death; 1-year mortality; composite of 1-year mortality, myocardial infarction or stroke; and 1-year cardiovascular death. Cox proportional hazard regression using inverse probability of treatment weighting (IPTW) was used to mitigate confounding by indication., Results: Among 50,228 patients, 20,484 (40.8%) underwent an ambulatory assessment prior to surgery: 11,074 (54.1%) with cardiology, 8,071 (39.4%) with GIM and 1,339 (6.5%) with both. Compared to patients who did not, those who underwent an assessment had a higher Revised Cardiac Risk Index (N with Index over 2= 4,989[24.4%] vs. 4,587[15.4%], P<0.001) and more frequent pre-operative cardiac testing (N=7,772[37.9%] vs. 6,113[20.6%], P<0.001) but, lower 30-day mortality (N=551[2.7%] vs. 970[3.3%], P<0.001). After application of IPTW, cardiology or GIM assessment prior to surgery remained associated with a lower 30-day mortality (weighted Hazard Ratio [95%CI] = 0.73 [0.65-0.82]) and a lower rate of all secondary outcomes., Conclusions: Major vascular surgery patients assessed by a cardiology or GIM physician prior to surgery have better outcomes than those who are not. Further research is needed to better understand potential mechanisms of benefit., Competing Interests: The authors report no conflicts of interest., (Copyright © 2024 Wolters Kluwer Health, Inc. All rights reserved.)