British journal of anaesthesia
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Observational Study
Endotypes of intraoperative hypotension during major abdominal surgery: a retrospective machine learning analysis of an observational cohort study.
Intraoperative hypotension is associated with myocardial injury, acute kidney injury, and death. In routine practice, specific causes of intraoperative hypotension are often unclear. A more detailed understanding of underlying haemodynamic alterations of intraoperative hypotension may identify specific treatments. We thus aimed to use machine learning - specifically, hierarchical clustering - to identify underlying haemodynamic alterations causing intraoperative hypotension in major abdominal surgery patients. Specifically, we tested the hypothesis that there are distinct endotypes of intraoperative hypotension, which may help refine therapeutic interventions. ⋯ Hierarchical clustering identified six endotypes of intraoperative hypotension. If validated, considering these intraoperative hypotension endotypes may enable causal treatment of intraoperative hypotension.
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The randomised controlled trial is the foundation of clinical research; yet there is concern that many trials have flaws in design, conduct, and reporting that undermine trustworthiness. Common flaws in trials include high risk of bias, small size, outcomes irrelevant to clinical care and patient's experience, and inability to detect efficacy even if present. These flaws carry forward into systematic reviews, which can confer the label of 'high-quality evidence' on inadequate data. ⋯ Some trials have been discovered to be fabricated, the number of which is growing. The fields of anaesthesia and pain have more fabricated trials than other clinical fields, possibly because of increased vigilance. This narrative review examines these themes in depth whilst acknowledging an inescapable conclusion: that much of our clinical evidence is in trouble, and special measures are needed to bolster quality and confidence.