Acumen Analytics software offers you retrospective data analysis and hemodynamic insights into patient perfusion.
Acumen Analytics software allows you to retrospectively view and analyze monitored hemodynamic parameters from the Acumen IQ sensor, FloTrac sensor, or ClearSight finger cuff, highlighting key events including:
How Acumen Analytics software works
Acumen Analytics software reviews retrospective hemodynamic parameter data from the Acumen IQ sensor, FloTrac sensor, or ClearSight finger cuff.
Please note that not all sensors may be used with all monitoring platforms.
Monitoring sessions, including demographic data, can be downloaded from the HemoSphere advanced monitoring platform or EV1000 clinical platform into Acumen Analytics software for organization and analysis. Patient identifiers are omitted from the collection of data.
The Acumen Analytics software primary screen allows you to retrospectively analyze data within and between cohorts or on individual patients.
Main viewing pane
With a streamlined tile layout, the main viewing page organizes a list of all cases, cohort summaries, and cohort comparison for convenient overviews.
This case summary list provides statistics on key hypotensive calculations such as average number of hypotensive events, duration of each event, number of patients in a cohort that experienced a hypotensive event.
The cohort comparison screen allows you to retrospectively compare data from two cohorts. Hypotension data includes duration of hypotension and mean arterial pressure (MAP) events under 65 mmHg. The customizable cohort summary screen displays a summary of the data collected for the chosen patient or patient group.
At the core of Acumen Analytics software is advanced hemodynamic parameter data. You can review recorded data on a number of valuable pressure and flow parameters involved in clinical decision making. See chart below for available parameters.
|Cardiac output (CO)||Continuous measurement of the volume of blood pumped by the heart measured in liters per minute|
|Cardiac index (CI)||Cardiac output relative to body surface area (BSA)|
|Diastolic pressure (DIA)||Diastolic blood pressure|
|Mean arterial pressure (MAP)||Averaged systemic blood pressure over one cardiac cycle|
|Pulse rate (PR)||Number of ventricular contractions per minute|
|Stroke volume (SV)||Volume of blood pumped with each heart beat|
|Stroke volume index (SVI)||Stroke volume relative to body surface area (BSA)|
|Systemic vascular resistance (SVR)||The resistance that the left ventricle must overcome to eject stroke volume with each beat|
|Systemic vascular resistance index (SVRI)||SVR relative to body surface area|
|Stroke volume variation (SVV)||The percent difference between SVmin, max and mean|
|Central venous oximetry (ScvO2)||Venous oxygen saturation as measured in the superior vena cava|
|Mixed venous oximetry (SvO2)||Venous oxygen saturation as measured in the pulmonary artery|
|Systolic pressure (SYS)||Systolic blood pressure|
Intraoperative hypotension is common.
In noncardiac surgery patients, research findings have revealed strong associations between intraoperative hypotension and elevated risk of both acute kidney injury (AKI) and myocardial injury after noncardiac surgery (MINS).1,2,3
MINS — the most common cardiovascular complication that occurs after noncardiac surgery — is the leading cause of mortality within one month following surgery.1,4
More than 1 in 12 patients (8 million people globally) over 45 years old experience MINS each year after non-cardiac surgery.4,5,6
- Once a patient's mean arterial pressure (MAP) drops below 65 mmHg, it takes just 10 minutes of exposure to see higher associations between intraoperative hypotension and MINS.1
- Once a patient's MAP drops below 50 mmHg, it takes only one minute for the risk of MINS to increase significantly, making early identification of a hypotensive event critical.1
Adequate perfusion requires adequate arterial pressure and cardiac output (CO)
Cardiac Output (CO) = Stroke Volume x Heart Rate
Preload: the tension of myocardial fibers at the end of diastole, as a result of volume in the ventricle
Stroke Volume (SV): volume of blood pumped from the left ventricle per heartbeat
When managing volume, stroke volume variation (SVV) has been proven to be a highly sensitive and specific indicator for preload responsiveness. SVV has also been shown to be an accurate predictor of fluid responsiveness in loading conditions induced by mechanical ventilation.7-10
Hypotension Prediction Index
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* and provides you with insights to understand the root cause and inform a potential course of action for your patient.
The Acumen IQ sensor
The Acumen IQ sensor — part of the minimally-invasive family of hemodynamic sensors — unlocks the Acumen Hypotension Prediction Index software. The Acumen IQ system* automatically updates advanced parameters every 20 seconds, reflecting rapid physiological changes in moderate- to high-risk surgery.
Acumen Analytics softwareAcumen Analytics is a software that provides you with retrospective hemodynamic insights into patient perfusion when managing patients with pressure and flow parameters. Acumen Analytics software allows you to view and analyze monitored hemodynamic parameters from the Acumen IQ sensor, FloTrac sensor, or ClearSight finger cuff, highlighting key events including hypotension frequency, duration, and prevalence.
To request a download of the Acumen Analytics software, please submit your contact information below, and our representative will contact you shortly.
HemoSphere advanced monitoring platform
The HemoSphere advanced monitoring platform allows you to see, experience and interact with hemodynamic parameters. Compatible with the Acumen IQ sensor and the FloTrac sensor, you can see your patient’s physiologic status and analyze trends with exceptional clarity that you can intuitively navigate with a simple-to-use touchscreen.
The EV1000 clinical platform
The EV1000 clinical platform from Edwards Lifesciences presents the physiologic status of the patient in an intuitive and meaningful way. The EV1000 clinical platform enables you to choose the parameters needed to monitor your patients and is compatible with a number of Edwards advanced hemodynamic monitoring solutions.
To request your unique download key for Acumen Analytics software, please submit your contact information below and an Edwards representative will email you shortly.
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- Minimum 32GB hard drive with 2GB available
- Memory: 4GB
- Compatible with Windows 7, 8 and 10 (32 & 64 bit)
- Data download from monitoring platform must be in 20-second increments
- 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. Anesthesiology, 126(1), 47- 65.
- Sun, L.Y., Wijeysundera, D.N., Tait, G.A., & Beattie, W.S. (2015). Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery and myocardial injury. Anesthesiology, 123(3), 515-523.
- Walsh, M., Devereaux, P.J., Garg, A.X., Kurz, A., Turan, A., Rodseth, R.N., Cywinski, J., Thabane, L., & Sessler, D.I. (2013). Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac surgery. Anesthesiology, 119(3), 507-515.
- Khan, J., Alonso-Coello, P., Devereaux, P.J., Myocardial injury after noncardiac surgery, Curr Opin Cardiol, 2014, 29: 307-311.
- Sellers, D., Srinivas, C., Djaiani, G. (2018). Cardiovascular complications after noncardiac surgery. Anaesthesia, 73 (Suppl. 1), 34 - 42.
- van Waes, J., Nathoe, H., Graa, J., Kemperman, H., de Borst, G., Peelen, L., van Klei, W. (2013). Myocardial injury after noncardiac surgery and its association with short-term mortality. Circulation, 127, 2264 – 2271.
- Berkenstadt, H., et al. (2001). Stroke volume variation as a predictor of fluid responsiveness in patients undergoing brain surgery. Anesthesia & Analgesia, 92, 984-9.
- McGee, W.T. (2009). A simple physiologic algorithm for managing hemodynamics using stroke volume and stroke volume variation: physiologic optimization program. Journal of Intensive Care Medicine, 24(6), 352-360.
- Peng, K., Li, J., Cheng, H., Ji, FH. (2014) Goal-directed fluid therapy based on stroke volume variations improves fluid management and gastrointestinal perfusion in patients undergoing major orthopedic surgery. Medical Principles and Practice, 23(5), 413-20.
- Li, C., Lin, F.Q., Fu, S. K., Chen, G. Q., Yang, X. H., Zhu, C. Y., Zhang, L. J., & Li, Q. (2013). Stroke volume variation for prediction of fluid responsiveness in patients undergoing gastrointestinal surgery. International Journal of Medical Sciences, 10(2), 148.