Acumen Hypotension Prediction Index software
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The Acumen Hypotension Prediction Index (HPI) software is a first-of-its-kind technology that provides you with information regarding the likelihood of a patient trending toward a hypotensive event*
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*A hypotensive event is defined as MAP <65 mmHg for a duration of at least one minute.
Predict hypotension sooner. Act ahead of time.
In a two-center retrospective analysis of patients undergoing major surgery, the Hypotension Prediction Index software demonstrated superior predictive ability than the commonly measured perioperative haemodynamic variables.²
Risks of hypotension
Managing hypotension
Relate products
Clinical evidence
Medical device for professional use. For a listing of indications, contraindications, precautions, warnings, and potential adverse events, please refer to the Instructions for Use (consult eifu.edwards.com where applicable).
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*Predictive performance of HPI is superior to that of CO, SV, MAP, PP, HR, SVV and Shock Index
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How many non-cardiac surgical patients have a dangerous drop in pressure?
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In a systematic review of 42 papers,† elevated risk of postoperative myocardial injury, acute kidney injury, and mortality was reported when IOH dropped lower than 65 mmHg. Risk increased as blood pressure became progressively lower. Risk of overall organ injury‡ under IOH MAP thresholds:
In a systematic review of 42 papers,† elevated risk of post-operative myocardial infarction (MI), acute kidney injury (AKI), and mortality was reported when IOH dropped lower than 65 mmHg. Risk increased as blood pressure became progressively lower. Risk of overall organ injury‡ under IOH MAP thresholds:
Managing perfusion
* From a retrospective multicentre observational study that evaluated moderate-to-high risk (ASA status of 3 or 4) noncardiac surgery patients monitored for hypotension at hospitals that used an invasive arterial line ≥75% of the time. ^ Hypotension/hypotensive event was defined as MAP <65mmHg for at least one minute. † 19,446 /22,109 noncardiac surgery patients.
Numerous studies show IOH is strongly associated with risk, especially:
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† Studies evaluated the associations between IOH and at least one of 6 identified adverse outcomes among noncardiac surgery patients. ‡ Defined as the combined outcomes of mortality, acute kidney injury, myocardial infarction, stroke, and delirium.
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of patients experienced intraoperative hypotension (IOH)^ during non-cardiac surgery*
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Acute kidney injury
Myocardial injury
Mortality
‡ Defined as the combined outcomes of mortality, acute kidney injury, myocardial infarction, stroke, and delirium.
<65 mmHg
Longer periods
Moderately or highly elevated risk
<55 mmHg
Any amount of time
MAP
Organ Injury
Duration
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† Studies evaluated the associations between IOH and at least one of 6 identified adverse outcomes among noncardiac surgery patients.
A recent study demonstrated a 57% reduction in duration of intraoperative hypotension.*
Acumen HPI reduced the duration of hypotension by over 50%
Unlock this first-of-its-kind technology with the noninvasive Acumen IQ cuff. Also available with the minimally-invasive Acumen IQ sensor that connects to any existing radial arterial line.
Hypotension Prediction Index (HPI) Dynamic arterial elastance (Ea ) Systolic Slope (dP/dt) Cardiac output (CO) Cardiac index (CI) Stroke volume (SV) Stroke volume index (SVI)
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Manage variability in volume administration
Acumen HPI software delivers a range of advanced haemodynamic pressure and flow parameters:
Alerting you when a patient is trending toward hypotension
Advanced hemodynamic parameters provided by the Acumen IQ sensor may be used in perioperative goal-directed therapy (PGDT) protocols
PGDT is a treatment protocol using dynamic, flow-based parameters with the objective of making the appropriate volume management decisions. PGDT can be implemented in a single procedure or as part of a larger initiative such as Enhanced Recovery After Surgery pathways.
Acumen HPI software combined with a treatment protocol achieved statistically significant reduction in hypotension vs. standard of care
Two randomized controlled trials have shown that using Acumen HPI software in combination with a hemodynamic treatment protocol significantly reduced the incidence and duration of hypotensive events in patients undergoing noncardiac surgery.
Reference: 1. Cannesson, M. (2010) Arterial pressure variation and goal-directed fluid therapy. Journal of Cardiothoracic and Vascular Anesthesia, 24(3), 487-97.
dyn
Systolic blood pressure (SYS ) Diastolic blood pressure (DIA ) Mean arterial pressure (MAP) Systemic vascular resistance (SVR) Systemic vascular resistance Index (SVRI) Stroke volume variation (SVV) Pulse pressure variation (PPV)
ART
Hypotension prediction index (HPI) Stroke volume (SV) Stroke volume variation (SVV) Mean arterial pressure (MAP) Cardiac index (CI) Systolic slope (dP/dt) Dynamic arterial elastance (Ea )
Perfusion management
*†
•
Allowing you to investigate and understand the root cause, and to determine the best course of action
Potentially avoiding hypotension and its associated risks
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* Single arm, multicenter, prospective-to-historical control where non-cardiac surgical patients received arterial line monitoring. † Data on File.
Acumen Hypotension Prediction Index software provides continuous insights into potential hypotension
The HPI parameter displays as a value ranging from 0 to 100, with higher values indicating higher likelihood of a hypotensive event.*
Key elements of the Acumen Hypotension Prediction Index software
HPI parameter
HPI high alert pop-up
HPI secondary screen
The HPI high alert pop-up alerts you when your patient is trending toward 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 pop-up window will appear, prompting you to review the patient haemodynamics using the HPI secondary screen.
The advanced haemodynamic pressure and flow parameters on the HPI secondary screen provides information to investigate and identify the root causes of potentially developing hypotensive events*
The HPI parameter value is updated every 20 seconds, providing continuous predictive insights into developing hypotensive events.*
Educational resources
Case study: Clinical utility of dP/dt
HPI high alert popup
Hypotension Prediction Index (HPI) Parameter
Acumen HPI software – which is powered by a first-of-its-kind algorithm that was developed with machine learning – can predict the onset of hypotension.
The advanced haemodynamic parameters on the secondary screen are arranged visually by:
Preload Contractility Afterload
• • •
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 It may be used as an indicator of fluid responsiveness.
Contractility
Systolic slope (dP/dt) Maximum upslope of the arterial pressure waveform from a peripheral artery. Changes from baseline or trend values of arterial dP/dt are more useful than absolute values, and may be an indicator of increasing or decreasing contractility
Afterload
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Dynamic arterial elastance (Ea ) The ratio of pulse pressure variation to stroke volume variation
Alerting you when a patient is trending toward hypotension Allowing you to investigate and understand the root cause, and to determine the best course of action Potentially avoiding hypotension and its associated risks
In this case example, you see that the HPI alarm alerted 10 minutes before the patient's MAP dropped below 65 mmHg giving you more time to investigate the root cause.
Example from case data
* A hypotensive event is defined as MAP <65 mmHg for a duration of at least one minute.
^ The HPI parameter information provided in this chart is presented as general guidance and may not be representative of individual experience. A review of the patient's haemodynamics is recommended prior to initiating treatment.
Ea explained
Watch video
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Acumen Hypotension Prediction Index software is part of the Acumen intelligent decision support suite
Acumen IQ sensor +
Acumen Analytics software +
HemoSphere advanced monitoring platform +
Acumen IQ sensor
Features
Model Numbers
Advanced haemodynamic parameters provided by the Acumen IQ sensor offer you continuous insight into your patient’s haemodynamic status.
Unlocks the Acumen Hypotension Prediction Index software. Connects to any existing radial arterial line. Automatically updates advanced parameters every 20 seconds, reflecting rapid physiological changes in moderate- to high-risk surgery.
AIQS8
84 in / 213 cm
Model
Description
Length
Unit of measure
Acumen IQ sensor standalone
Acumen IQ sensor standalone (5-pack)
60 in / 152 cm
EA
Acumen Analytics software
Acumen Analytics software enables you to analyse parameters from the HemoSphere monitoring platform providing insights into haemodynamic management of individual patients, as well as groups of patients. The view of specific pressure and flow parameters allow you to analyse:
Hypotension frequency Hypotension duration Hypotension prevalence
More on HemoSphere advanced monitoring platform
HemoSphere advanced monitoring platform
HemoSphere advanced monitoring platform offers advanced haemodynamic parameters that can help guide you with proactive decision support in a range of clinical situations and settings so you can maintain optimal patient perfusion.
AIQS85
AIQS6
AIQS65
AIQS6AZ
Acumen IQ sensor with VAMP adult system
AIQS6AZ5
Acumen IQ cuff +
Acumen IQ cuff
Acumen IQ cuff unlocks Acumen HPI software and provides continuous blood pressure and advanced haemodynamic parameters from a noninvasive finger cuff. Continuous data offered by the Acumen IQ cuff enables you to proactively optimise perfusion through haemodynamic management and provides more accurate systolic, diastolic and MAP values than a brachial cuff.
Gives you noninvasive access to automatically calculate beat-to-beat haemodynamic information for a broad patient population, including patients in who an arterial line would not be typically placed. The easy to use self-coiling mechanism within the interior of the cuff wraps snugly around the patient’s finger and offers improved cuff placement, consistent snugness, and usability.
AIQCL
Large
AIQCM
Medium
AIQCS
Small
Pack size
Acumen IQ cuff unlocks Acumen HPI software and provides continuous blood pressure and advanced haemodynamic parameters from a noninvasive finger cuff. Continuous data offered by the Acumen IQ cuff enables you to proactively optimize perfusion through haemodynamic management and provides more accurate systolic, diastolic and MAP values than a brachial cuff.
Pack Size
21-23
Some studies have shown reduced incidence, duration and severity of IOH* during noncardiac surgery guided by an Acumen HPI software protocol vs. standard of care.
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Highlights from Winjberge M, et al. 2020
Learn more +
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Highlights from Schneck E, et al. 2020
Highlights from Hatib F, et al. 2018
Highlights from Davies SJ, et al. 2020
Incidence, duration, and severity of IOH* during noncardiac surgery were significantly reduced vs standard of care²
Highlights from 2020 Wijnberge, et al. 2020
From HYPE, a preliminary single-centre randomised trial that evaluated the use of Acumen HPI software in 68 patients undergoing elective noncardiac surgery²
Incidence and duration of IOH* during noncardiac surgery were significantly reduced vs standard of care⁸
From a single-centre feasibility randomised blinded prospective interventional trial that evaluated protocolised care according to HPI monitoring among 99 patients undergoing total hip arthroplasty⁸
Acumen HPI software was highly accurate in predicting hypotension*¹
Acumen HPI software was highly accurate in predicting hypotension*¹³
From a 2-center retrospective analysis of 255 patients undergoing major surgery
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Prediction of hypotension at 10 minutes before an event
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From the HYPE trial, patients undergoing elective noncardiac surgery guided by an Acumen HPI software protocol had a median duration of IOH per patient of 8 minutes compared to 32.7 minutes in a control group; p<0.00116 Wijnberge cohort was 68 adult patients undergoing noncardiac surgery (Intervention (n=31), control (n=29))
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.
Acumen HPI software had superior ability to predict IOH 5 and 10 minutes before an event vs all other measured haemodynamic parameters.
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)
Clinical studies
IOH=Intraoperative hypotension.
*Hypotension was defined as MAP <65 mmHg for ≥1 minute.² †Corrected for the total time of surgery.² IOH=Intraoperative hypotension
*Hypotension was defined as MAP <65 mmHg for ≥1 minute.⁸ IOH=Intraoperative hypotension.
Hypotension was defined as a MAP <65 mmHg for at least 1 minute.¹
Additional evidence
Acumen HPI software detected haemodynamic instabilities during early haemorrhage From an experimental study of 8 anesthetised, mechanically ventilated pigs that lost blood due to graded haemorrhage.
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Identification of haemodynamic instabilities
In a clinical study, postoperative monitor of Ea was associated with:
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Assessment of advanced hemodynamic parameters
Predictive algorithms can be evaluated via receiver-operating characteristic (ROC) curves, with the area under the curve (AUC) showing the predictive power of an algorithm for a specific dataset An ROC curve closest to the y-axis approaches a perfect model, with fewer false-positive and false-negative values
*Hypotension was defined as MAP <65 mmHg for ≥1 minute.¹³
Acumen HPI software was highly accurate in identifying hemodynamic instabilities
Highlights from Davies SJ, et al. 2021
Assessment of advanced haemodynamic parameters – such as dynamic arterial elastance (Ea ) – can provide both clinical and economic benefits
Highlights from Guinot PG, et al. 2017
*Vasoplegic syndrome was defined as persistent hypotension (ie., a MAP below 65 mmHg) despite fluid resuscitation, and the need for norepinephrine to maintain or restore a MAP over 70 mmHG for more than 4 hours. CO=Cardiac output; ICU=Intensive care unit; MAP=Mean arterial pressure; PPV=Pulse pressure variation; SV=Stroke volume; SVR=Systemic vascular resistance; SVV=Stroke volume variation.
CVP=Central venous pressure; CO=Cardiac output; dP/dT=Arterial pressure change over time; Ea =Dynamic arterial elastance; HR=Heart rate; MAP=Mean arterial pressure; MPAP=Mean pulmonary arterial pressure; SV=Stroke volume; Svo =Mixed venous oxygen saturations; SVR=Systemic vascular resistance; SVV=Stroke volume variation.
Hemodynamic parameters provided by Acumen HPI software include CO, SV, SVR, SVV, dP/dt, and Ea
From a prospective, open-label, randomised study of 130 patients requiring norepinephrine for vasoplegic* syndrome after cardiac surgery In a clinical study, postoperative monitor of Ea was associated with:
Shorter duration/lower cumulative dose of norepinephrine treatment Shorter length of ICU stay
From an experimental study of 8 anesthetised, mechanically ventilated pigs that lost blood due to graded haemorrhage
Acumen HPI software detected hemodynamic instabilities during early haemorrhage
Outperforming all other measured parameters, including MAP, CVP, HR, and even SVV
During early haemorrhage, most parameters remained in clinically normal ranges
Created from Davies SJ, et al. 2021.
Total duration of norepinephrine treatment
Created from Guinot PG, et al. 2017
Acumen HPI software detected haemodynamic instabilities during early haemorrhage. From an experimental study of 8 anesthetised, mechanically ventilated pigs that lost blood due to graded haemorrhage.
Identification of hemodynamic instabilities
In a clinical study, postoperative monitor of Eadyn was associated with:
Acumen HPI software was highly accurate in identifying hemodyamic instabilities
*Vasoplegic syndrome was defined as persistent hypotension (ie., a MAP below 65 mmHg) despite fluid resuscitation, and the need for norepinephrine to maintain or restore a MAP over 70 mmHG for more than 4 hours. CCO=Cardiac output; ICU=Intensive care unit; MAP=Mean arterial pressure; PPV=Pulse pressure variation; SV=Stroke volume; SVR=Systemic vascular resistance; SVV=Stroke volume variation.
Created from Guinot PG, et al. 2017.
* IOH is defined as MAP <65 mmHg for at least one minute.
Reductions in incidence, duration and severity of IOH
Accurate prediction of IOH
*IOH is defined as MAP <65 mmHg for at least one minute.
reduction in treatment duration
~55%
Hatib F et al, Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis Anesthesiology 2018, Vol.129, 663-674. 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. Shah NJ, Mentz G, Kheterpal S. The incidence of intraoperative hypotension in moderate to high risk patients undergoing non-cardiac surgery: A retrospective multicenter observational analysis. J Clin Anesth. 2020 Nov;66:109961. Salmasi, V., Maheshwari, K., Yang, G., Mascha, E.J., Singh, A., Sessler, D.I., & Kurz, A. (2017). Relationship between intraoperative hypotension, defined by either reduction from baseline or absolute thresholds, and acute kidney injury and myocardial injury after noncardiac surgery: A retrospective cohort analysis. Anesthesiology, 126(1), 47-65. Sun LY, Wijeysundera DN, Tait GA, Beattie WS. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015 Sep;123(3):515- 23. Walsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, Cywinski J, Thabane L, Sessler DI. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery: toward an empirical definition of hypotension. Anesthesiology. 2013 Sep;119(3):507-15. Sessler DI, Khanna AK. Perioperative myocardial injury and the contribution of hypotension. Intensive Care Med. 2018 Jun;44(6):811-822. doi: 10.1007/s00134-018-5224-7. Epub 2018 Jun 4. PMID: 29868971. Gregory A, Stapelfeldt WH, Khanna AK, et al. Intraoperative hypotension is associated with adverse clinical outcomes after noncardiac surgery. Anesth Analg. 2021;132(6):1654-1665. Wesselink EM, Kappen TH, Torn HM, et al. Intraoperative hypotension and the risk of postoperative adverse outcomes: a systematic review. Br J Anaesth. 2018;121(4):706-721. Monk TG, et al. Anesthetic Management and One-Year Mortality After Noncardiac Surgery. Anesth Analg 2005;100:4–10. Monk TG, et al. Association between Intraoperative Hypotension and Hypertension and 30- day Postoperative Mortality in Noncardiac Surgery. Anesthesiology 2015; 123:307-19. Hirsch J, et al. Impact of intraoperative hypotension and blood pressure fluctuations on early postoperative delirium after noncardiac surgery. British Journal of Anaesthesia, 2015:418–26. Bijker JB, et al. Intraoperative Hypotension and Perioperative Ischemic Stroke after General Surgery: A Nested Casecontrol Study. Anesthesiology, 2012;116: 658-664. Pinsky MR. Chapter 5: Overview of the circulation. In: Cannesson M, Pearse R, eds. Perioperative hemodynamic monitoring and goal directed therapy: from theory to practice. 2nd ed. Cambridge University Press;2015:29-38. 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. 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 LearningDerived 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.Mathis MR, Kheterpal SK, Najarian K. Artificial intelligence for anesthesia: what the practicing clinician needs to know. Anesthesiology. 2018;129(4):619- 622. Ward H. van der Ven, Denise P. Veelo, Marije Wijnberge, Björn J.P. van der Ster, Alexander P.J. Vlaar, Bart F. Geerts, One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making, Surgery, Volume 169, Issue 6, 2021, Pages 1300-1303, ISSN 0039-6060, https://doi.org/10.1016/j.surg.20 20.09.041. Tartiere JM, Logeart D, Beauvais F, Chavelas C, Kesri L, Tabet JY, Cohen-Solal A. Non-invasive radial pulse wave assessment for the evaluation of left ventricular systolic performance in heart failure. Eur J Heart Fail. 2007 May;9(5):477-83. Monge Garcia MI, Jian Z, Settels JJ, Hunley C, Cecconi M, Hatib F, Pinsky MR. Performance comparison of ventricular and arterial dP/dtmax for assessing left ventricular systolic function during different experimental loading and contractile conditions. Crit Care. 2018 Nov 29;22(1):325. Cannesson, M. Arterial Pressure Variation and Goal-Directed Fluid Therapy. Journal of Cardiothoracic and Vascular Anesthesia. V24, No 3, 2010. 487-497. Thacker, J. Perioperative Fluid Utilization Variability and Association with Outcomes. Annals of Surgery. 2015. 1-9. McGee, W. A Simple Physiologic Algorithm for Managing Hemodynamics Using Stroke Volume and Stroke Volume Variation: Physiologic Optimization Program. J Intensive Care Med. 2009. 352-360. 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. Guinot PG, Abou-Arab O, Guilbart M, et al. Monitoring dynamic arterial elastance as a means of decreasing the duration of norepinephrine treatment in vasoplegic syndrome following cardiac surgery: a prospective, randomized trial. Intensive Care Med. 2017;43(5):643-651.
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