Predicting blood pressure change caused by rapid injection of propofol during anesthesia induction with a logistic regression model

Ruey Horng Rau, Yu Chuan Li, Jen Kun Cheng, Chien Chuan Chen, Yuan Pi Ko, Chun Jen Huang

研究成果: 雜誌貢獻文章

2 引文 (Scopus)

摘要

Background: Propofol is a common intravenous agent for induction and maintenance of anesthesia. The advantage of propofol is rapid recovery of consciousness when the continuous infusion is stopped. Additionally, it has antiemetic effect of reducing postoperative nausea and vomiting. On the other hand, rapid infusion of propofol is painful and may cause hypotension. In this study, we aimed to develop a logistic regression model to accurately predict blood pressure change caused by rapid infusion of propofol. Methods: Seventeen variables (including demographic data, past medical history, laboratory data, and blood pressure before induction) were assessed in 200 patients who received propofol for induction of anesthesia for routine surgery. A logistic regression model was derived using these values as independent variables to predict whether a patient would suffer a significant blood pressure change (> 30% decrease from baseline) Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of our prediction model. Results: A cut-off value of 0.17 in the logistic regression model predicted decreased blood pressure with 90.0% sensitivity and, 67.3% specificity. The area under the receiver operating characteristic curve was 0.855. Conclusions: Our prediction model predicts propofol-induced hypotension with acceptable accuracy. Because of the straightforward mathematic formula used, our model can be integrated effortlessly into a hospital information system, providing a reliable and useful decision support for clinical anesthesia staff.

原文英語
頁(從 - 到)81-86
頁數6
期刊Acta Anaesthesiologica Taiwanica
42
發行號2
出版狀態已發佈 - 六月 2004

指紋

Propofol
Anesthesia
Logistic Models
Blood Pressure
Injections
ROC Curve
Clinical Decision Support Systems
Controlled Hypotension
Hospital Information Systems
Sensitivity and Specificity
Postoperative Nausea and Vomiting
Antiemetics
Mathematics
Consciousness
Hypotension
Area Under Curve
Maintenance
Demography

ASJC Scopus subject areas

  • Anesthesiology and Pain Medicine

引用此文

Predicting blood pressure change caused by rapid injection of propofol during anesthesia induction with a logistic regression model. / Rau, Ruey Horng; Li, Yu Chuan; Cheng, Jen Kun; Chen, Chien Chuan; Ko, Yuan Pi; Huang, Chun Jen.

於: Acta Anaesthesiologica Taiwanica, 卷 42, 編號 2, 06.2004, p. 81-86.

研究成果: 雜誌貢獻文章

Rau, Ruey Horng ; Li, Yu Chuan ; Cheng, Jen Kun ; Chen, Chien Chuan ; Ko, Yuan Pi ; Huang, Chun Jen. / Predicting blood pressure change caused by rapid injection of propofol during anesthesia induction with a logistic regression model. 於: Acta Anaesthesiologica Taiwanica. 2004 ; 卷 42, 編號 2. 頁 81-86.
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abstract = "Background: Propofol is a common intravenous agent for induction and maintenance of anesthesia. The advantage of propofol is rapid recovery of consciousness when the continuous infusion is stopped. Additionally, it has antiemetic effect of reducing postoperative nausea and vomiting. On the other hand, rapid infusion of propofol is painful and may cause hypotension. In this study, we aimed to develop a logistic regression model to accurately predict blood pressure change caused by rapid infusion of propofol. Methods: Seventeen variables (including demographic data, past medical history, laboratory data, and blood pressure before induction) were assessed in 200 patients who received propofol for induction of anesthesia for routine surgery. A logistic regression model was derived using these values as independent variables to predict whether a patient would suffer a significant blood pressure change (> 30{\%} decrease from baseline) Sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the performance of our prediction model. Results: A cut-off value of 0.17 in the logistic regression model predicted decreased blood pressure with 90.0{\%} sensitivity and, 67.3{\%} specificity. The area under the receiver operating characteristic curve was 0.855. Conclusions: Our prediction model predicts propofol-induced hypotension with acceptable accuracy. Because of the straightforward mathematic formula used, our model can be integrated effortlessly into a hospital information system, providing a reliable and useful decision support for clinical anesthesia staff.",
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