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Hypotension Prediction Index Is Equally Effective in Predicting Intraoperative Hypotension during Noncardiac Surgery Compared to a Mean Arterial Pressure Threshold: A Prospective Observational Study.
Mulder, Marijn P; Harmannij-Markusse, Mirjam; Fresiello, Libera; Donker, Dirk W; Potters, Jan-Willem.
Affiliation
  • Mulder MP; Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, Enschede, The Netherlands.
  • Harmannij-Markusse M; Technical Medicine, University of Twente, Enschede, The Netherlands.
  • Fresiello L; Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, Enschede, The Netherlands.
  • Donker DW; Cardiovascular and Respiratory Physiology, TechMed Centre, University of Twente, Enschede, The Netherlands; and Intensive Care Center, University Medical Center Utrecht, Utrecht, The Netherlands.
  • Potters JW; Department of Anesthesiology, Medisch Spectrum Twente, Enschede, The Netherlands.
Anesthesiology ; 141(3): 453-462, 2024 Sep 01.
Article in En | MEDLINE | ID: mdl-38558038
ABSTRACT

BACKGROUND:

The Hypotension Prediction Index is designed to predict intraoperative hypotension in a timely manner and is based on arterial waveform analysis using machine learning. It has recently been suggested that this algorithm is highly correlated with the mean arterial pressure itself. Therefore, the aim of this study was to compare the index with mean arterial pressure-based prediction methods, and it is hypothesized that their ability to predict hypotension is comparable.

METHODS:

In this observational study, the Hypotension Prediction Index was used in addition to routine intraoperative monitoring during moderate- to high-risk elective noncardiac surgery. The agreement in time between the default Hypotension Prediction Index alarm (greater than 85) and different concurrent mean arterial pressure thresholds was evaluated. Additionally, the predictive performance of the index and different mean arterial pressure-based methods were assessed within 5, 10, and 15 min before hypotension occurred.

RESULTS:

A total of 100 patients were included. A mean arterial pressure threshold of 73 mmHg agreed 97% of the time with the default index alarm, whereas a mean arterial pressure threshold of 72 mmHg had the most comparable predictive performance. The areas under the receiver operating characteristic curve of the Hypotension Prediction Index (0.89 [0.88 to 0.89]) and concurrent mean arterial pressure (0.88 [0.88 to 0.89]) were almost identical for predicting hypotension within 5 min, outperforming both linearly extrapolated mean arterial pressure (0.85 [0.84 to 0.85]) and delta mean arterial pressure (0.66 [0.65 to 0.67]). The positive predictive value was 31.9 (31.3 to 32.6)% for the default index alarm and 32.9 (32.2 to 33.6)% for a mean arterial pressure threshold of 72 mmHg.

CONCLUSIONS:

In clinical practice, the Hypotension Prediction Index alarms are highly similar to those derived from mean arterial pressure, which implies that the machine learning algorithm could be substituted by an alarm based on a mean arterial pressure threshold set at 72 or 73 mmHg. Further research on intraoperative hypotension prediction should therefore include comparison with mean arterial pressure-based alarms and related effects on patient outcome.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Predictive Value of Tests / Monitoring, Intraoperative / Arterial Pressure / Hypotension / Intraoperative Complications Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Anesthesiology Year: 2024 Document type: Article Affiliation country: Países Bajos Country of publication: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Predictive Value of Tests / Monitoring, Intraoperative / Arterial Pressure / Hypotension / Intraoperative Complications Limits: Aged / Female / Humans / Male / Middle aged Language: En Journal: Anesthesiology Year: 2024 Document type: Article Affiliation country: Países Bajos Country of publication: Estados Unidos