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Comparison of differences in cohort (forwards) and case control (backwards) methodological approaches for validation of the Hypotension Prediction Index.
Davies, Simon J; Sessler, Daniel I; Jian, Zhongping; Fleming, Neal W; Mythen, Monty; Maheshwari, Kamal; Veelo, Denise P; Vlaar, Alexander Pj; Settels, Jos; Scheeren, Thomas; van der Ster, Bjp; Sander, Michael; Cannesson, Maxime; Hatib, Feras.
Afiliación
  • Davies SJ; Department of Anaesthesia, Critical Care and Perioperative Medicine, York and Scarborough Teaching Hospitals NHS foundation Trust, York, UK.
  • Sessler DI; Centre for Health and Population Science, Hull York Medical School, York, UK.
  • Jian Z; Department of Outcomes Research, Cleveland Clinic, Ohia, USA.
  • Fleming NW; Edwards Lifesciences, Irvine, California, USA.
  • Mythen M; UC Davis School of Medicine, California, USA.
  • Maheshwari K; Edwards Lifesciences, Irvine, California, USA.
  • Veelo DP; UCL/UCLH National Institute of Health Research Biomedical Research Centre, London, UK.
  • Vlaar AP; Department of Outcomes Research, Cleveland Clinic, Ohia, USA.
  • Settels J; Departments of Anaesthesia and Intensive Care, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • Scheeren T; Departments of Anaesthesia and Intensive Care, Amsterdam University Medical Center, Amsterdam, The Netherlands.
  • van der Ster B; Edwards Lifesciences, Irvine, California, USA.
  • Sander M; Edwards Lifesciences, Irvine, California, USA.
  • Cannesson M; Department of Anesthesiology, University Medical Centre Groningen, The Netherlands.
  • Hatib F; Departments of Anaesthesia and Intensive Care, Amsterdam University Medical Center, Amsterdam, The Netherlands.
Anesthesiology ; 2024 Apr 01.
Article en En | MEDLINE | ID: mdl-38557791
ABSTRACT

BACKGROUND:

The Hypotension Prediction Index (the index) software is a machine learning algorithm that detects physiological changes that may lead to hypotension. The original validation used a case control (backwards) analysis that has been suggested to be biased. We therefore conducted a cohort (forwards) analysis and compared this to the original validation technique.

METHODS:

We conducted a retrospective analysis of data from previously reported studies. All data were analysed identically with 2 different methodologies and receiver operating characteristic curves (ROC) constructed. Both backwards and forwards analyses were performed to examine differences in area under the ROC for HPI and other haemodynamic variables to predict a MAP < 65mmHg for at least 1 minute 5, 10 and 15 minutes in advance.

RESULTS:

Two thousand and twenty-two patients were included in the analysis, yielding 4,152,124 measurements taken at 20 second intervals. The area-under-the-curve for the index predicting hypotension analysed by backward and forward methodologies respectively was 0.957 (95% CI, 0.947-0.964) vs 0.923 (95% CI, 0.912-0.933) 5 minutes in advance, 0.933 (95% CI, 0.924-0.942) vs 0.923 (95% CI, 0.911-0.933) 10 minutes in advance , and 0.929 (95% CI, 0.918-0.938) vs. 0.926 (95% CI, 0.914-0.937) 15 minutes in advance. No other variable had an area-under-the-curve > 0.7 except for MAP. Area-under-the-curve using forward analysis for MAP predicting hypotension 5, 10, and 15 minutes in advance was 0.932 (95% CI, 0.920-0.940), 0.929 (95% CI, 0.918-0.938), and 0.932 (95% CI, 0.921-0.940). The R 2 for the variation in the index due to MAP was 0.77.

CONCLUSION:

Using an updated methodology, we found the utility of the HPI index to predict future hypotensive events is high, with an area under the receiver-operating-characteristics curve similar to that of the original validation method.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Anesthesiology Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Anesthesiology Año: 2024 Tipo del documento: Article País de afiliación: Reino Unido
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