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Factors Influencing Epidural Anesthesia for Cesarean Section Outcome

机译:影响剖宫产的硬膜外麻醉的因素

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This study investigates practice variance in performing epidural anesthesia for cesarean section. Specifically, we analyze the safety and efficacy of a large-dose, needle-based epidural technique where anesthetic dose is administered through an epidural needle prior to insertion of the epidural catheter. Using a data-driven informatics and machine learning approach, our findings show that the needle-based technique is faster and more dose-effective in achieving sensory level than the catheter- based approach. We also find that injecting large doses in the epidural space through the epidural needle is safe, with complication rates similar to those reported in published literature. Further, machine learning reveals that a needle dose of at most 18 ml offers lower hypotension complication. The machine learning framework can predict hypotension incidents with 85% accuracy. The findings facilitate delivery improvement and establish an improved clinical practice guideline for training and dissemination of safe practice. Successful prediction of hypotension allows for early intervention to minimize the effects of complication. Furthermore, although almost 50% of the drug combinations used involve fentanyl, our findings show that fentanyl has little effect on the outcome and should be avoided in epidural anesthesia.
机译:本研究研究了对剖宫产表演硬膜外麻醉进行的实践差异。具体地,我们分析了大剂量,针基硬膜外技术的安全性和功效,其中在插入硬膜外导管之前通过硬膜外针给予麻醉剂量。使用数据驱动的信息和机器学习方法,我们的研究结果表明,基于针对基于导管的方法的针对基于针对的技术更快,更具剂量有效。我们还发现,通过硬膜外针在硬膜外线空间中注入大剂量是安全的,并复杂化率类似于发表文献中报告的那些。此外,机器学习表明,最多18毫升的针剂量提供较低的低血压并发症。机器学习框架可以预测高精度的低血压事件,精度为85%。调查结果促进了交付改进,并建立了改进的培训和传播安全实践的临床实践指南。成功预测低血压允许早期干预以最小化并发症的影响。此外,虽然近50%的药物组合使用涉及芬太尼,但我们的研究结果表明芬太尼对结果几乎没有影响,应该在硬膜外麻醉中避免。

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