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Predict hypotension sooner. Act ahead of time1

acumen
Developed with machine learning1 and powered by a first-of-its-kind algorithm,1,2 Acumen HPI software accurately predicts hypotension 10 minutes before it occurs.1


Multiple studies have shown:

Incidence, duration, and severity of IOH* during noncardiac surgery were significantly reduced vs standard of care.3,4

Acumen HPI software was highly accurate in predicting hypotension*.1,5

Acumen HPI software was highly accurate in identifying hemodynamic instabilities.6

Key elements of the Acumen HPI software

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HPI Parameter
HPI high alert popup
Relationship View screen
Preload
Contractility
Afterload
HPI Parameter
HPI high alert popup
Relationship View screen
Preload
Contractility
Afterload

HPI Parameter

The HPI parameter displays as a value ranging from 0 to 100, with higher values indicating higher likelihood of a hypotensive event.*

The HPI parameter value is updated every 20 seconds, providing continuous predictive insights into developing hypotension.

HPI high alert popup

The HPI high alert popup alerts you when your patient is trending towards or experiencing a hypotensive event.*

If the HPI parameter value exceeds 85 for two consecutive 20-second updates or reaches 100 at any time, the HPI high alert popup window will appear, prompting you to review the patient hemodynamics using the HPI secondary screen.

HPI Secondary Screen

The secondary screen provides you insights into the cause of hypotension, and hemodynamic parameters are arranged visually by preload, afterload and contractility. 

It provides a complete haemodynamic picture of your patient. Parameters displayed include MAP, CO, CI, SVR, PR, SV and SVV/PPV, as well as HPI, dP/dt, and Eadyn.

Preload

Stroke volume variation (SVV) or pulse pressure variation (PPV)

The percent difference between minimum and maximum stroke volume (SV) or pulse pressure (PP) during a respiratory cycle.

Contractility

Systolic slope (dP/dt)

Maximal upslope of the arterial pressure waveform from a peripheral artery.

Case study: Clinical utility of dP/dt

Afterload

Dynamic arterial elastance (Eadyn)

The ratio of pulse pressure variation to stroke volume variation.

Watch Eadyn explained


* A hypotensive event is defined as MAP <65 mmHg for a duration of at least one minute.

Clinical evidence

Reductions in incidence, duration, and severity of IOH3,4

Highlights from Wijnberge M, et al. 2020

From the HYPE trial, elective noncardiac surgery patients monitored with Acumen HPI software had a median duration of IOH per patient of 8 minutes compared to 32.7 minutes in a control group; p<0.001.3

Intervention (n=31), control (n=29)

See full study

Highlights from Schneck E, et al. 2020

Incidence of IOH (events per hour) in total hip arthroplasty patients monitored with Acumen HPI software was 0 events compared to 5 events in a prospective control and 2 events in a historical control; p<0.001.4

Intervention (n=25), prospective control (n=24), historical control (n=50)

See full study

Accurate prediction of IOH1,6

Highlights from Davies SJ, et al. 2020

Acumen HPI software had superior ability to predict IOH 5 and 10 minutes before an event vs. all other measured hemodynamic parameters.6

See full study

Highlights from Hatib F, et al. 2018

At 10 minutes before an event, Acumen HPI software predicted IOH with a specificity of 89%, a sensitivity of 90% and an AUC of 0.95.1

See full study

Edwards clinical education

Hemodynamic education empowering clinical advancement

With a long-term commitment to improving the quality of care for surgical and critical care patients through education, Edwards clinical education meets you no matter where you are in the learning process — with a continuum of resources and tools that continuously support you as you solve the clinical challenges facing you today, and in the future.

TopMedTalk podcasts on Intraoperative Hypotension (IOH)

The TopMedTalk podcast is a leading source of high value medical discussion and education in Anaesthesia, Perioperative Care and Enhanced Recovery. We've featured interviews with key opinion leaders, academics, medical practitioners and policy makers.  

Listen below to podcasts on hypotension and Acumen Hypotension Prediction Index (HPI) software. You can also find these episodes of TopMedTalk through wherever you get your podcasts.

Avoiding the hypotension hazard

The Acumen Hypotension Prediction Index (HPI) software takes 2.6 million features from a single waveform which it then applies to 133 million different wave forms looking for factors which can predict hypotension. It's the first fully approved foray into predictive analytics for the world of anaesthesia.

This conversation looks at how it works and how it is being adopted in detail.

Presented by Desiree Chappell with Monty Mythen and Feras Hatib PhD, Director, Research and Development, Algorithms and Signal Processing at Edwards Lifesciences and Dr Simon Davies, Consultant Anaesthetist at York Teaching Hospital NHS Foundation Trust.

References

  1. Hatib, F., Zhongping, J., Buddi, S., Lee, C., Settels, J., Sibert, K., Rinehart, J., Cannesson, M. (2018). Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis. Anesthesiology 129, 663-674.
  2. Edwards Lifesciences data on file [US Food and Drug Administration. Acumen HPI Software De Novo clearance].
  3. Wijnberge, M., Geerts, B., Hol, L., Lemmers, N., Mulder, M., Berge, P., Schenk, J., Terwindt, L., Hollman, M., Vlaar, A., Veelo, D. (2020) 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 Online, February 17, 2020.
  4. Schneck E, Schulte D, Habig L, 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;34(6):1149-1158.
  5. Davies SJ, Vistisen ST, Jian Z, et al. Ability of an arterial waveform analysis-derived hypotension prediction index to predict future hypotensive events in surgical patients. Anesth Analg 2019.
  6. Davies SJ, Mythen M. Hemodynamic and intestinal microcirculatory changes in a phenylephrine corrected porcine model of hemorrhage. Anesth Analg. 2021 March 23. doi: 10.1213/ANE.0000000000005388. Online ahead of print.
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