利用电子麻醉记录避免诱导后低血压的麻醉剂量预测模型的提出

Nanaka Asai, Chiaki Doi, Koki Iwai, S. Ideno, H. Seki, Jungo Kato, Takashige Yamada, H. Morisaki, H. Shigeno
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引用次数: 2

摘要

诱导后低血压常发生在麻醉诱导后。避免诱导后低血压很重要,因为它与术后不良后果有关。相关研究表明,麻醉诱导药物的剂量对诱导后低血压有影响。本研究的目的是根据患者的情况提出一种不会引起诱导后低血压的麻醉剂量。以电子麻醉记录为研究对象,采用机器学习方法中的回归模型,建立了麻醉诱导药物的最佳剂量预测模型。通过调整解释变量和参数,采用岭回归,确定预测系数为0.5008。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proposal of Anesthetic Dose Prediction Model to Avoid Post-induction Hypotension Using Electronic Anesthesia Records
Post-induction hypotension frequently occurred after anesthesia induction. Avoiding post-induction hypotension is important as it is associated with postoperative adverse outcomes. Related studies have shown that the dose of anesthetic induction drugs affects the post-induction hypotension. The purpose of this study is to propose an anesthetic dose that does not cause post-induction hypotension according to the patient's condition. A model for predicting the optimal dose of an anesthetic induction drug is constructed using a regression model which is one of machine learning methods by focusing on electronic anesthesia records. The prediction coefficient of determination 0.5008 was achieved by adjusting the explanatory variables and parameters and using ridge regression.
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