An algorithm for assessing intraoperative mean arterial pressure lability

David L. Reich, Todd K. Osinski, Carol Bodian, Marina Krol, Kaya Sarier, Ram Roth, Steven N. Konstadt

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Background: Intraoperative blood pressure liability may be related to risk factors, hypovolemia, light anesthesia, and morbid outcomes, but the measurements of lability in previous studies have been limited by imprecise and infrequent data collection methods. Computerized intraoperative data acquisition systems have provided an opportunity to readdress the issue of intraoperative blood pressure lability with more abundant and precise data. This study sought to derive and validate an algorithm (expert system) to measure mean arterial pressure (MAP) lability. Methods: Two hundred thirty- nine computerized anesthesia records were reviewed retrospectively. Three anesthesiologists separately rated MAP as very stable, average, or very labile. The parameters of a computer algorithm that measured the change of median MAP between consecutive 2-min epochs were optimized to achieve the best possible agreement among the anesthesiologists. The algorithm was then validated on 229 additional anesthesia records. Results: The proportion of consecutive 2-min epochs in which the absolute value of the fractional change of median MAP exceeded 0.06 (i.e., 6%) correlated strongly with the anesthesiologists' ratings (r = 0.78; P < 0.0001). The optimal sensitivity and specificity of the algorithm for detecting MAP lability were 98% and 59%, respectively. Conclusions: One potential application of expert systems to anesthesia practice is a 'smart alarm' to detect blood pressure lability. It may also provide a better tool to assess the relation between lability and outcome than has been available previously.

Original languageEnglish
Pages (from-to)156-161
Number of pages6
JournalAnesthesiology
Volume87
Issue number1
DOIs
StatePublished - 1997

Keywords

  • Blood pressure
  • Computers: expert systems monitoring, hemodynamic
  • Surgery, cardiac: coronary artery bypass grafting

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