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| Name | Class |
|---|---|
| Attikon Hospital | OTHER |
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This study investigates if the Hypotension Prediction Index (HPI) combined with the Assisted Fluid Management (AFM) software can improve perioperative hemodynamic management in adult patients undergoing general anesthesia. The main question is :
Does the HPI and AFM software reduce the incidence and duration of intraoperative hypotension? Does the HPI and AFM software optimize fluid and vasopressor administration? Does the HPI and AFM software improve perioperative outcomes? Participants will be randomly allocated to either an experimental group receiving goal directed hemodynamic therapy guided by HPI and AFM or a control group receiving conventional hemodynamic management.
Intraoperative hypotension is a common complication during general anesthesia and is associated with an increased risk of postoperative organ dysfunction (acute kidney injury, myocardial ischemia). Even short episodes of mean arterial pressure (MAP) below accepted thresholds have been shown to adversely affect patient outcomes.
The Hypotension Prediction Index , (HPI)is a software that predicts the likelihood of hypotension minutes before it occurs, based on the arterial waveform. Thus clinicians have the opportunity to identify patients at risk of hypotension and intervene early.
The Assisted Fluid Management (AFM) software is designed to optimize perioperative fluid administration based on the Frank-Starling curve. The AFM provides guidance on crystalloid admininistration only when it is expected to increase stroke volume and cardiac output.
This prospective , randomized study evaluates whether the use of HPI coupled with AFM within a goal directed hemodynamic protocol improves perioperative hemodynamic management and reduces the incidence and duration of adult patients undergoing surgery under general anesthesia.
A total of 100 adult patients will be enrolled , for elective surgery with invasive blood pressure monitoring and intraoperative mean arterial pressure target of at least 65 mm Hg.
Patients in the intervention group will undergo goal directed hemodynamic management guided by HPI and AFM algorithms via the Hemosphere monitor and Acumen IQ sensor. The AFM software will determine the timing of fluid administration. Elevated HPI values indicating impending hypotension will be managed in a targeted manner with fluids, vasopressors or inotropes.
Patients in the control group will receive conventional hemodynamic management , based on clinical judgement, in accordance with international guidelines. Although an Acumen IQ sensor will be placed, HPI and AFM indications will not be visible to the attending anesthesiologist and will not influence clinical decision making.
Intraoperative hemodynamic data will be continuously recorded in both groups. A member of the research team will be present to supervise the procedure. The primary outcome is the time-weighted average of hypotension, defined as MAP below 65 mm Hg for at least one minute. Secondary outcomes include the incidence and duration of hypotension, type and dose of administered therapies and protocol adherence.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| HPI/AFM - Goal- Directed Hemodynamic Therapy | Experimental | Participants will receive goal-directed hemodynamic therapy guided by the Hypotension Prediction Index and Assisted Fluid Management software, using the Hemosphere monitor. Interventions include protocol-guided fluid and vasopressors to prevent or treat intraoperative hypotension. |
|
| Conventional therapy | Active Comparator | Participants will receive conventional hemodynamic intraoperative management based on anesthesiologist's clinical judgement. The Acumen IQ sensor will be placed but Hypotension Prediction Index and Assisted Fluid Management outputs will not be visible to the anesthesiologist. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Acumen IQ sensor with Hypotension Prediction Index (HPI) and Assisted Fluid Management (AFM) software | Device | The Acumen IQ sensor will be used with the Hemosphere monitor to guide goal-directed hemodynamic therapy. HPI predicts impending hypotension and AFM guides fluid administration. Clinicians will follow a protocol algorithm to prevent or treat intraoperative hypotension with fluids, vasopressors or inotropes. |
| Measure | Description | Time Frame |
|---|---|---|
| Time-weighted average of intraoperative hypotension | Time weighted average spent in hypotension, defined as mean arterial pressure (MAP) <65mmHg for ≥ 1min, measures using the Acumen IQ sensor and Hemosphere monitor. | Intraoperatively, starting 10 minutes after anesthesia induction or start of sedation |
| Measure | Description | Time Frame |
|---|---|---|
| Incidence of hypotension | Incidence of hypotension, defined as MAP <65mmHg for ≥ 1min. | Intraoperatively, starting 10 minutes after anesthesia induction or start of sedation |
| Time spent in hypotension |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Georgia Ntalamagka, MD | Contact | +306978210163 | geo.dalamaga@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Georgia Ntalamagka, MD | Attikon Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| 2nd University Department of Anesthesiology, Attikon University Hospital | Recruiting | Athens | Attica | 12462 | Greece |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| Result | 20. Pinsky MR. Protocolized cardiovascular management based on ventricular-arterial coupling. In: Functional Hemodynamic Monitoring. Update in Intensive Care and Emergency Medicine. 2004, Springer-Verlag, Berlin, 381 - 395. ISBN 3540223495 | ||
| 25524443 | Result | Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014 Dec 19;14:135. doi: 10.1186/1471-2288-14-135. | |
| 27683581 |
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Participants will be randomly assigned in a 1:1 ratio to one of two study groups. One group will receive goal-directed hemodynamic therapy using the Hypotension Prediction Index and Assisted Fluid Management software. The control group will receive conventional intraoperative hemodynamic management. Each participant will remain in the assigned group for the duration of the study without crossover.
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Clinicians managing patients are aware of group assignment, as treatment decisions depend on the intervention. Outcome assessors collect data but do not influence group allocation.
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|
| Conventional Intraoperative Hemodynamic management | Other | Participants receive hemodynamic management based on the anesthesiologist's clinical judgement. The Acumen IQ sensor will be placed , but HPI and AFM outputs are not visible to the clinician. |
|
Time spent in hypotension, in minutes, defined as MAP <65mmHg for ≥ 1min
| Intraoperatively, starting 10 minutes after anesthesia induction or start of sedation |
| Choice of therapy (fluids/medications) | Medication used to prevent/treat hypotension. A study member is present at the OR to make notes. | Intraoperatively, starting 10 minutes after anesthesia induction or start of sedation |
| Dose of therapy (fluids/medications) | Dose of medication used to prevent/treat hypotension. | Intraoperatively, starting 15 minutes after anesthesia induction. |
| Protocol deviations | Diagnostic guidance protocol deviations, a study member is present at the OR to make notes of any protocol deviations. | Intraoperatively, starting 15 minutes after anesthesia induction |
| Result |
| Luo D, Wan X, Liu J, Tong T. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 2018 Jun;27(6):1785-1805. doi: 10.1177/0962280216669183. Epub 2016 Sep 27. |
| 39052844 | Result | Coeckelenbergh S, Soucy-Proulx M, Van der Linden P, Roullet S, Moussa M, Kato H, Toubal L, Naili S, Rinehart J, Grogan T, Cannesson M, Duranteau J, Joosten A. Restrictive versus Decision Support Guided Fluid Therapy during Major Hepatic Resection Surgery: A Randomized Controlled Trial. Anesthesiology. 2024 Nov 1;141(5):881-890. doi: 10.1097/ALN.0000000000005175. |
| 39116013 | Result | Coeckelenbergh S, Entzeroth M, Van der Linden P, Flick M, Soucy-Proulx M, Alexander B, Rinehart J, Grogan T, Cannesson M, Vincent JL, Vicaut E, Duranteau J, Joosten A. Assisted Fluid Management and Sublingual Microvascular Flow During High-Risk Abdominal Surgery: A Randomized Controlled Trial. Anesth Analg. 2025 May 1;140(5):1149-1158. doi: 10.1213/ANE.0000000000007097. |
| 29750699 | Result | Joosten A, Coeckelenbergh S, Delaporte A, Ickx B, Closset J, Roumeguere T, Barvais L, Van Obbergh L, Cannesson M, Rinehart J, Van der Linden P. Implementation of closed-loop-assisted intra-operative goal-directed fluid therapy during major abdominal surgery: A case-control study with propensity matching. Eur J Anaesthesiol. 2018 Sep;35(9):650-658. doi: 10.1097/EJA.0000000000000827. |
| 26578397 | Result | Joosten A, Alexander B, Delaporte A, Lilot M, Rinehart J, Cannesson M. Perioperative goal directed therapy using automated closed-loop fluid management: the future? Anaesthesiol Intensive Ther. 2015;47(5):517-23. doi: 10.5603/AIT.a2015.0069. Epub 2015 Nov 18. |
| 33901281 | Result | Maheshwari K, Malhotra G, Bao X, Lahsaei P, Hand WR, Fleming NW, Ramsingh D, Treggiari MM, Sessler DI, Miller TE; Assisted Fluid Management Study Team. Assisted Fluid Management Software Guidance for Intraoperative Fluid Administration. Anesthesiology. 2021 Aug 1;135(2):273-283. doi: 10.1097/ALN.0000000000003790. |
| 29779129 | Result | Joosten A, Hafiane R, Pustetto M, Van Obbergh L, Quackels T, Buggenhout A, Vincent JL, Ickx B, Rinehart J. Practical impact of a decision support for goal-directed fluid therapy on protocol adherence: a clinical implementation study in patients undergoing major abdominal surgery. J Clin Monit Comput. 2019 Feb;33(1):15-24. doi: 10.1007/s10877-018-0156-x. Epub 2018 May 19. |
| 39576150 | Result | Schuurmans J, Rellum SR, Schenk J, van der Ster BJP, van der Ven WH, Geerts BF, Hollmann MW, Cherpanath TGV, Lagrand WK, Wynandts PR, Paulus F, Driessen AHG, Terwindt LE, Eberl S, Hermanns H, Veelo DP, Vlaar APJ. Effect of a Machine Learning-Derived Early Warning Tool With Treatment Protocol on Hypotension During Cardiac Surgery and ICU Stay: The Hypotension Prediction 2 (HYPE-2) Randomized Clinical Trial. Crit Care Med. 2025 Feb 1;53(2):e328-e340. doi: 10.1097/CCM.0000000000006518. Epub 2024 Nov 22. |
| 33446404 | Result | Shin B, Maler SA, Reddy K, Fleming NW. Use of the Hypotension Prediction Index During Cardiac Surgery. J Cardiothorac Vasc Anesth. 2021 Jun;35(6):1769-1775. doi: 10.1053/j.jvca.2020.12.025. Epub 2020 Dec 21. |
| 34775533 | Result | van der Ven WH, Terwindt LE, Risvanoglu N, Ie ELK, Wijnberge M, Veelo DP, Geerts BF, Vlaar APJ, van der Ster BJP. Performance of a machine-learning algorithm to predict hypotension in mechanically ventilated patients with COVID-19 admitted to the intensive care unit: a cohort study. J Clin Monit Comput. 2022 Oct;36(5):1397-1405. doi: 10.1007/s10877-021-00778-x. Epub 2021 Nov 13. |
| 32960954 | Result | Maheshwari K, Shimada T, Yang D, Khanna S, Cywinski JB, Irefin SA, Ayad S, Turan A, Ruetzler K, Qiu Y, Saha P, Mascha EJ, Sessler DI. Hypotension Prediction Index for Prevention of Hypotension during Moderate- to High-risk Noncardiac Surgery. Anesthesiology. 2020 Dec 1;133(6):1214-1222. doi: 10.1097/ALN.0000000000003557. |
| 35054083 | Result | Murabito P, Astuto M, Sanfilippo F, La Via L, Vasile F, Basile F, Cappellani A, Longhitano L, Distefano A, Li Volti G. Proactive Management of Intraoperative Hypotension Reduces Biomarkers of Organ Injury and Oxidative Stress during Elective Non-Cardiac Surgery: A Pilot Randomized Controlled Trial. J Clin Med. 2022 Jan 13;11(2):392. doi: 10.3390/jcm11020392. |
| 34945177 | Result | 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. doi: 10.3390/jcm10245884. |
| 31784852 | Result | Schneck E, Schulte D, Habig L, Ruhrmann S, Edinger F, Markmann M, Habicher M, Rickert M, Koch C, Sander M. 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. doi: 10.1007/s10877-019-00433-6. Epub 2019 Nov 29. |
| 32065827 | Result | Wijnberge M, Geerts BF, Hol L, Lemmers N, Mulder MP, Berge P, Schenk J, Terwindt LE, Hollmann MW, Vlaar AP, Veelo DP. 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. doi: 10.1001/jama.2020.0592. |
| 30896602 | Result | 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. doi: 10.1213/ANE.0000000000004121. |
| 29894315 | Result | Hatib F, Jian Z, Buddi S, Lee C, Settels J, Sibert K, Rinehart J, Cannesson M. Machine-learning Algorithm to Predict Hypotension Based on High-fidelity Arterial Pressure Waveform Analysis. Anesthesiology. 2018 Oct;129(4):663-674. doi: 10.1097/ALN.0000000000002300. |
| 26181335 | Result | 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. doi: 10.1097/ALN.0000000000000765. |
| 27792044 | Result | Salmasi V, Maheshwari K, Yang D, Mascha EJ, Singh A, Sessler DI, Kurz A. Relationship between Intraoperative Hypotension, Defined by Either Reduction from Baseline or Absolute Thresholds, and Acute Kidney and Myocardial Injury after Noncardiac Surgery: A Retrospective Cohort Analysis. Anesthesiology. 2017 Jan;126(1):47-65. doi: 10.1097/ALN.0000000000001432. |
| 23835589 | Result | 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. doi: 10.1097/ALN.0b013e3182a10e26. |
| ID | Term |
|---|---|
| D055991 | Health Records, Personal |
| D018625 | Microscopy, Atomic Force |
| ID | Term |
|---|---|
| D008499 | Medical Records |
| D011996 | Records |
| D003625 | Data Collection |
| D004812 | Epidemiologic Methods |
| D008919 | Investigative Techniques |
| D020527 | Microscopy, Scanning Probe |
| D008853 | Microscopy |
| D003952 | Diagnostic Imaging |
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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