British journal of anaesthesia
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Randomized Controlled Trial
Effect of machine learning models on clinician prediction of postoperative complications: the Perioperative ORACLE randomised clinical trial.
Anaesthesiologists might be able to mitigate risk if they know which patients are at greatest risk for postoperative complications. This trial examined the impact of machine learning models on clinician risk assessment. ⋯ NCT05042804.
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Randomized Controlled Trial Multicenter Study
From pain level to pain experience: redefining acute pain assessment to enhance understanding of chronic postsurgical pain.
Chronic postsurgical pain (CPSP) significantly impairs quality of life and poses a substantial healthcare burden, affecting up to a quarter of patients undergoing surgery. Although acute pain is recognised as a predictor for CPSP development, the role of patient experience remains underexplored. This study examines the predictive value of patient experience alongside traditional risk factors for CPSP after orthopaedic surgery. ⋯ This study underscores the role of patient-reported outcomes, specifically the pain experience dimension captured by the EVAN-G scale, in prediction of CPSP 90 days after surgery. It suggests a shift from conventional assessments of pain intensity to a comprehensive understanding of pain experience, advocating for tailored pain management approaches that could reduce chronic pain, thereby improving patient quality of life and functional recovery.