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Background: The aim was to characterize end‐of‐life care in patients who have had a leg amputated for peripheral artery disease (PAD) or diabetes. Methods: This was a population‐based retrospective cohort study of patients with PAD or diabetes who died in Ontario, Canada, between 2011 and 2017. Those who had a leg amputation within 3 years of death were compared with a control cohort of deceased patients with PAD or diabetes, but without leg amputation. The patients were identified from linked health records within the single‐payer healthcare system. Place and cause of death, as well as health services and costs within 90 days of death, were compared between the amputee and control cohorts. Among amputees, multivariable regression models were used to characterize the association between receipt of home palliative care and in‐hospital death, as well as time spent in hospital at the end of life. Results: Compared with 213 300 controls, 3113 amputees were less likely to die at home (15·5 versus 24·9 per cent; P < 0·001) and spent a greater number of their last 90 days of life in hospital (median 19 versus 8 days; P < 0·001). Amputees also had higher end‐of‐life healthcare costs across all sectors. However, receipt of palliative care was less frequent among amputees than controls (inpatient: 13·4 versus 16·8 per cent, P < 0·001; home: 14·5 versus 23·8 per cent, P < 0·001). Among amputees, receipt of home palliative care was associated with a lower likelihood of in‐hospital death (odds ratio 0·49, 95 per cent c.i. 0·40 to 0·60) and fewer days in hospital (rate ratio 0·84, 0·76 to 0·93). Conclusion: Palliative care is underused after amputation in patients with PAD or diabetes, and could contribute to reducing in‐hospital death and time spent in hospital at the end of life. [ABSTRACT FROM AUTHOR]

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., (© The Author(s) 2023. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: Robotic surgery was integrated into some healthcare systems despite there being few well designed, real-world studies on safety or benefit. This study compared the safety of robotic with laparoscopic, thoracoscopic, and open approaches in common robotic procedures., Methods: This was a population-based, retrospective study of all adults who underwent prostatectomy, hysterectomy, pulmonary lobectomy, or partial nephrectomy in Ontario, Canada, between 2008 and 2018. The primary outcome was 90-day total adverse events using propensity score overlap weights, and secondary outcomes were minor or major morbidity/adverse events., Results: Data on 24 741 prostatectomy, 75 473 hysterectomy, 18 252 pulmonary lobectomy, and 6608 partial nephrectomy operations were included. Relative risks for total adverse events in robotic compared with open surgery were 0.80 (95 per cent c.i. 0.74 to 0.87) for radical prostatectomy, 0.44 (0.37 to 0.52) for hysterectomy, 0.53 (0.44 to 0.65) for pulmonary lobectomy, and 0.72 (0.54 to 0.97) for partial nephrectomy. Relative risks for total adverse events in robotic surgery compared with a laparoscopic/thoracoscopic approach were 0.94 (0.77 to 1.15), 1.00 (0.82 to 1.23), 1.01 (0.84 to 1.21), and 1.23 (0.82 to 1.84) respectively., Conclusion: The robotic approach is associated with fewer adverse events than an open approach but similar to a laparoscopic/thoracoscopic approach. The benefit of the robotic approach is related to the minimally-invasive approach rather than the platform itself., (© The Author(s) 2022. Published by Oxford University Press on behalf of BJS Society Ltd. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)