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Blood pressure optimization has been considered as a crucial factor to avoid perioperative vital organ hypoperfusion, and perioperative hypotension has been addressed as a risk factor for complications and adverse clinical outcomes.
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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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Control group | Active Comparator | 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. |
|
| HPI group | Experimental | 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. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| hypotension prediction index(HPI) | Other | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| Perioperative acute kidney injury | Acute kidney injury will be assessed according to the KDIGO guideline. Serum creatinine will be examined on the day before surgery and postoperative day 1. | 24 hours |
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| Measure | Description | Time Frame |
|---|---|---|
| perioperative neurocognitive disorder | Taiwan version of quick mild cognitive impairment(Qmci) test will be used to identify perioperative neurocognitive disorder | 30 day |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Chen-Tse Lee, MD | Contact | 0972653169 | lctbrian314@gmail.com |
| Name | Affiliation | Role |
|---|---|---|
| Chen-Tse Lee, MD | National Taiwan University Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Taiwan University Hospital | Recruiting | Taipei | Taiwan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26083768 | Background | 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. | |
| 30236233 |
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| ordinary goal-directed hemodynamic therapy | Other | Keep pulse pressure variation >12%; keep cardiac index >2L/min/cm^2; keep mean arterial pressure > 65mmHg. |
|
| 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. |
| 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. |
| 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. |
| ID | Term |
|---|---|
| D009140 | Musculoskeletal Diseases |
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