Clinical evidence: Acumen Hypotension Prediction Index (HPI) Software
The EU HYPROTECT study demonstrated that patients monitored with Acumen HPI software experienced a low incidence, duration and severity of intraoperative hypotension*1
The multicenter, prospective, observational study of over 700 noncardiac surgery patients demonstrated:
- Low incidence of hypotension
41% of patients avoided hypotension when monitored with Acumen HPI software, compared to 12% of patients in another large multicenter study where Acumen HPI software was not used.*1,2 - Brief duration of hypotension
Patients in this study experienced approximately 2 minutes of hypotension, or 1% of surgery time, compared with 28 minutes in another large multicenter study where Acumen HPI software was not used.*1,2 - Low severity of hypotension
Patients monitored with Acumen HPI software experienced a very low TWA MAP <65 mmHg at 0.03. The TWA MAP <60 mmHg was 0.*1
Read the results from Kouz et al, 2023 (British Journal of Anaesthesia Open):
Intraoperative hypotension when using hypotension prediction index software during major noncardiac surgery: a European multicentre prospective observational registry (EU HYPROTECT)
*Multicenter, prospective, observational study of patients across 5 EU countries monitored with Acumen IQ arterial line sensor where hypotension was defined as > 1 min below MAP 65 mmHg
Highlighted clinical evidence for Acumen HPI software
Wijnberge et al, 2020 - Journal of the American Medical Association
Effect of a Machine Learning–Derived Early Warning System for Intraoperative Hypotension vs Standard Care on Depth and Duration of Intraoperative Hypotension During Elective Noncardiac Surgery: The HYPE Randomized Clinical Trial*
This study demonstrated that Acumen HPI software combined with a treatment protocol achieved statistically significant reduction in hypotension vs. standard of care. Elective, noncardiac surgery patients monitored with Acumen HPI had a median time of hypotension per patient of 8 minutes compared to 32.7 minutes in the control group.2
Schneck et al, 2019 - Journal of Clinical Monitoring and Computing
Hypotension Prediction Index Based Protocolized Haemodynamic Management Reduces the Incidence and Duration of Intraoperative Hypotension in Primary Total Hip Arthroplasty: a Single Centre Feasibility Randomised Blinded Prospective Interventional Trial*
In this single center feasibility study, Acumen HPI software combined with protocolized treatment was shown to reduce the relative and absolute duration of hypotension in total hip arthroplasty patients, in comparison to a historical and prospective control group.6
*Studies conducted with arterial line monitoring
Highlighted validation studies for Acumen HPI software
Ability of an Arterial Waveform Analysis–Derived Hypotension Prediction Index to Predict Future Hypotensive Events in Surgical Patients*
In this 255 patient, 2-center retrospective analysis study, when compared with hemodynamic parameters such as SV, CO, SVV, and MAP, Acumen HPI software showed a higher predictive performance at 5 and 10 minutes before hypotension.8
Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis*
An internal validation of 350 patient records demonstrated that 10 minutes before an event, Acumen HPI software predicted hypotension with a specificity and sensitivity of 89% and 90% respectively, and with an AUC of 0.95 (CI 95%).9
*Studies conducted with arterial line monitoring.
Read the full list of clinical evidence and validation studies about Acumen HPI software
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Acumen HPI software
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References
- Kouz K, Garcia MIM, Cerutti E, Lisanti I, Draisci G, Frassanito L, et al. Intraoperative hypotension when using hypotension prediction index software during major noncardiac surgery: a European multicentre prospective observational registry (EU HYPROTECT). BJA Open. 2023 May 4;6:100140.
- Shah, N., Mentz, G., Kheterpal, S. The incidence of intraoperative hypotension in moderate to high risk patients undergoing non-cardiac surgery: A retrospective multicenter observational analysis. Journal of Clinical Anesthesia. 2020: 66; 1-12.
- Wijnberge M, Geerts BF, Hol L, Lemmers N, Mulder MP, Berge P, et al. Effect of a machine learning-derived early warning system for intraoperative hypotension vs standard care on depth and duration of intraoperative hypotension during elective noncardiac surgery: The HYPE Randomized Clinical Trial. JAMA. 2020 Mar 17;323(11):1052-1060.
- Maheshwari K, Shimada T, Yang D, Khanna S, Cywinski JB, Irefin SA, et al. Hypotension Prediction Index for prevention of hypotension during moderate- to high-risk noncardiac surgery. Anesthesiology. 2020 Dec 1;133(6):1214-1222.
- Tsoumpa M, Kyttari A, Matiatou S, Tzoufi M, Griva P, Pikoulis E, Riga M, Matsota P, Sidiropoulou T. The use of the Hypotension Prediction Index integrated in an algorithm of goal directed hemodynamic treatment during moderate and high-risk surgery. J Clin Med. 2021 Dec 15;10(24):5884.
- Grundmann CD, Wischermann JM, Fassbender P, Bischoff P, Frey UH. Hemodynamic monitoring with Hypotension Prediction Index versus arterial waveform analysis alone and incidence of perioperative hypotension. Acta Anaesthesiol Scand. 2021 Nov;65(10):1404-1412. Epub 2021 Aug 31.
- Schneck E, Schulte D, Habig L, Ruhrmann S, Edinger F, Markmann M, et al. Hypotension Prediction Index based protocolized haemodynamic management reduces the incidence and duration of intraoperative hypotension in primary total hip arthroplasty: a single centre feasibility randomised blinded prospective interventional trial. J Clin Monit Comput. 2020 Dec;34(6):1149-1158. Epub 2019 Nov 29.
- Davies SJ, Vistisen ST, Jian Z, Hatib F, Scheeren TWL. Ability of an arterial waveform analysis-derived hypotension prediction index to predict future hypotensive events in surgical patients. Anesth Analg. 2020 Feb;130(2):352-359.
- Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K, et al. Machine-learning algorithm to predict hypotension based on high-fidelity arterial pressure waveform analysis. Anesthesiology. 2018 Oct;129(4):663-674.
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