Machine learning analysis of factors contributing to hypotension after lumbosacral epidural anaesthesia in dogs undergoing abdominal surgery

利用机器学习分析犬腹部手术后腰骶部硬膜外麻醉导致低血压的因素

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Abstract

The incidence of hypotension after a lumbosacral epidural in dogs depends on the volume of local anaesthetic administered. So far, there are no reports comparing both methods used to calculate this volume-body weight (BW) and occipito-coccygeal length (OCL)-in veterinary medicine. In this study, we evaluated the effect of these two common dosing strategies on risk of intraoperative hypotension in dogs undergoing abdominal surgery. Data were collected retrospectively from 210 dogs in a veterinary specialist hospital, with 110 receiving OCL-based dosing and 100 receiving BW-based dosing. Comparing logistic regression and ExtraTrees machine learning models (both demonstrating strong predictive performance, with AUROC 0.78 and 0.79, respectively, and supported by external validation on an independent dataset), we identified additional factors associated with post-epidural hypotension, including body temperature, minimum alveolar concentration, sex, and premedication. Our findings revealed that post-epidural hypotension occurred more frequently in the OCL group compared to the BW group (49.1% vs. 33%, respectively, p = 0.025). Despite both dosing strategies being considered effective, the OCL method resulted in a greater incidence of post-epidural hypotension. Our findings highlight the importance of careful individualized risk-benefit analyses for epidural dosing strategy.

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