British journal of anaesthesia
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Postoperative hypotension is associated with adverse outcomes, but intraoperative prediction of postanaesthesia care unit (PACU) hypotension is not routine in anaesthesiology workflow. Although machine learning models may support clinician prediction of PACU hypotension, clinician acceptance of prediction models is poorly understood. ⋯ The ability of anaesthesiologists to predict PACU hypotension was improved by exposure to machine learning model predictions. Clinicians acknowledged value and trust in machine learning technology. Increasing familiarity with clinical use of model predictions is needed for effective integration into perioperative workflows.
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The impact of opioid analgesic use before cancer diagnosis on survival in patients with chronic pain is unclear. Therefore, we designed a propensity score-matched population-based cohort study to compare overall and cancer-related survival of patients with chronic pain who received long-term opioid analgesic treatment with that of those who did not receive such treatment. ⋯ Long-term opioid analgesic use before cancer diagnosis might be associated with poor overall survival in patients with chronic pain compared with such patients who did not receive long-term opioid analgesics.
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Workplace-based assessment (WBA) is key to a competency-based assessment strategy. Concomitantly with our programme's launch of competency-based medical education, we developed an entrustment-based WBA, the Anesthesia Clinical Encounter Assessment (ACEA), to assess readiness for independent practice of competencies essential to perioperative patient care. This study aimed to examine validity evidence of the ACEA during postgraduate anaesthesiology training. ⋯ This study supports the validity of the ACEA for assessing the competence of residents performing perioperative care and supports its use in competency-based anaesthesiology training.