Hypotension Prediction Index Based Perioperative Protocolized Hemodynamic Management in Geriatric Orthopedic Surgery
NCT ID: NCT05274412
Last Updated: 2023-03-29
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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UNKNOWN
NA
280 participants
INTERVENTIONAL
2022-03-23
2024-04-30
Brief Summary
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Hypotension prediction index (HPI) is an novel machine-learning derived parameters, and was developed to predict the risk of future hypotension.Series of clinical studies have verified its clinical efficacy in avoiding perioperative hypotension.
Major orthopedic surgeries, such as spine surgery, joint surgery, long bone fracture surgery, are quite common in elder people, who are vulnerable to perioperative adverse outcomes.Thus the investigator design this study to testify the clinical efficacy of implementing HPI in perioperative goal-directed hemodynamic therapy in elder patients receiving major orthopedic surgery.
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
PREVENTION
TRIPLE
Study Groups
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Control group
Participants in this group will receive protocolized hemodynamic management based on advanced hemodynamic monitoring and dynamic parameters.Keep pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
ordinary goal-directed hemodynamic therapy
Keep pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
HPI group
Participants in this group will receive protocolized hemodynamic management based on advanced hemodynamic monitoring, hypotension prediction index (HPI), and dynamic parameters.Keep HPI \<85; pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
hypotension prediction index(HPI)
Implementing hypotension prediction index (HPI) in perioperative goal-directed hemodynamic therapy. Keep HPI \< 85; pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
Interventions
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hypotension prediction index(HPI)
Implementing hypotension prediction index (HPI) in perioperative goal-directed hemodynamic therapy. Keep HPI \< 85; pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
ordinary goal-directed hemodynamic therapy
Keep pulse pressure variation \>12%; keep cardiac index \>2L/min/cm\^2; keep mean arterial pressure \> 65mmHg.
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
60 Years
ALL
No
Sponsors
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National Taiwan University Hospital
OTHER
Responsible Party
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Principal Investigators
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Chen-Tse Lee, MD
Role: PRINCIPAL_INVESTIGATOR
National Taiwan University Hospital
Locations
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National Taiwan University Hospital
Taipei, , Taiwan
Countries
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Central Contacts
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Facility Contacts
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References
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Monk TG, Bronsert MR, Henderson WG, Mangione MP, Sum-Ping ST, Bentt DR, Nguyen JD, Richman JS, Meguid RA, Hammermeister KE. Association between Intraoperative Hypotension and Hypertension and 30-day Postoperative Mortality in Noncardiac Surgery. Anesthesiology. 2015 Aug;123(2):307-19. doi: 10.1097/ALN.0000000000000756.
Wesselink EM, Kappen TH, Torn HM, Slooter AJC, van Klei WA. Intraoperative hypotension and the risk of postoperative adverse outcomes: a systematic review. Br J Anaesth. 2018 Oct;121(4):706-721. doi: 10.1016/j.bja.2018.04.036. Epub 2018 Jun 20.
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.
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.
Other Identifiers
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202112163RIND
Identifier Type: -
Identifier Source: org_study_id
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