Search

Background: Endovascular aneurysm repair (EVAR) for abdominal aortic aneurysm (AAA) carries important perioperative risks; however, there are no widely used outcome prediction tools. The aim of this study was to apply machine learning (ML) to develop automated algorithms that predict 1-year mortality following EVAR. Methods: The Vascular Quality Initiative database was used to identify patients who underwent elective EVAR for infrarenal AAA between 2003 and 2023. Input features included 47 preoperative demographic/clinical variables. The primary outcome was 1-year all-cause mortality. Data were split into training (70 per cent) and test (30 per cent) sets. Using 10-fold cross-validation, 6 ML models were trained using preoperative features with logistic regression as the baseline comparator. The primary model evaluation metric was area under the receiver operating characteristic curve (AUROC). Model robustness was evaluated with calibration plot and Brier score. Results: Some 63 655 patients were included. One-year mortality occurred in 3122 (4.9 per cent) patients. The best performing prediction model for 1-year mortality was XGBoost, achieving an AUROC (95 per cent c.i.) of 0.96 (0.95-0.97). Comparatively, logistic regression had an AUROC (95 per cent c.i.) of 0.69 (0.68-0.71). The calibration plot showed good agreement between predicted and observed event probabilities with a Brier score of 0.04. The top 3 predictive features in the algorithm were 1) unfit for open AAA repair, 2) functional status, and 3) preoperative dialysis. Conclusions: In this data set, machine learning was able to predict 1-year mortality following EVAR using preoperative data and outperformed standard logistic regression models. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Surgery is the property of CMA Impact Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: Vascular injuries add substantial complexity to trauma care, yet Canadian epidemiologic data on such injuries are not readily available. We conducted a retrospective cross-sectional study to examine temporal trends in the rate of hospital admissions for vascular injuries from 1991 to 2009 in Ontario. Methods: Individuals of any age admitted to hospital because of vascular trauma in Ontario were included. Details of vascular injury and patient demographic characteristics were recorded, hospital admission rates estimated and analyses stratified by sex, age, mechanism of injury, economic status and geographic location. Time-series analysis was used to examine trends in hospital admission rates. Results: Of the 8252 hospital admissions for vascular trauma, 4287 (52.0%) involved injuries to the upper limb and 1819 (22.0%) were due to transport-related causes. Overall, the annual rate declined significantly over time, from 3.3 per 100 000 in 1991 to 2.7 per 100 000 in 2009 (p < 0.01). The subgroups with the highest rates were young men, patients with a low economic status and those living in a rural location. Declines occurred in both sexes and in all age groups except those 65 years and older. The rates of vascular injury to the neck, thorax, upper limbs and lower limbs declined over time, but not the rate of abdominal vascular injury. Although the rate of non-transport-related vascular injuries declined, the rate of transport-related vascular injuries did not change significantly over time. Decreases in annual rates occurred in both low- and high-economic status groups and in urban populations but not in rural populations. Interpretation: Overall, the annual rate of hospital admissions for vascular trauma declined significantly in Ontario over the study period. Our findings have important implications for public health and the development of injury-prevention strategies, particularly for population subgroups at high risk of vascular injury. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Surgery is the property of CMA Impact Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Examines the epidemiology of acute appendicitis in Ontario. Age and sex of patients; Length of hospital stay; Incidence and seasonal variation of acute appendicitis.