British journal of anaesthesia
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Preoperative risk prediction is an important component of perioperative medicine. Machine learning is a powerful tool that could lead to increasingly complex risk prediction models with improved predictive performance. Careful consideration is required to guide the machine learning approach to ensure appropriate decisions are made with regard to what we are trying to predict, when we are trying to predict it, and what we seek to do with the results.
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Multicenter Study
Frailty and decisional regret after elective noncardiac surgery: a multicentre prospective cohort study.
Frailty is associated with patient surgical-regret at 1 year post-op among older patients, particularly for non-orthopaedic surgery.
pearl -
As the primary Ca2+ release channel in skeletal muscle sarcoplasmic reticulum (SR), mutations in type 1 ryanodine receptor (RyR1) or its binding partners underlie a constellation of muscle disorders, including malignant hyperthermia (MH). In patients with MH mutations, triggering agents including halogenated volatile anaesthetics bias RyR1 to an open state resulting in uncontrolled Ca2+ release, increased sarcomere tension, and heat production. Propofol does not trigger MH and is commonly used for patients at risk of MH. The atomic-level interactions of any anaesthetic with RyR1 are unknown. ⋯ Propofol demonstrated direct binding and inhibition of RyR1 at clinically plausible concentrations, consistent with the hypothesis that propofol partially mitigates malignant hyperthermia by inhibition of induced Ca2+ flux through RyR1.