Non-invasive Measurement of the Hypotension Prediction Index for the Reduction of Intraoperative Hypotension

NCT ID: NCT06291714

Last Updated: 2025-04-03

Basic Information

• Recruitment Status: RECRUITING
• Clinical Phase: NA
• Total Enrollment: 150 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2024-08-01
• Study Completion Date: 2026-03-31

Brief Summary

In order to reduce the incidence of IOH, various goal-directed therapy (GDT) protocols have already been introduced with success regarding the reduction of postoperative AKI and MINS. However, these studies used an invasive hemodynamic monitoring which offered a continuous surveillance of the blood pressure. In contrast, standard non-invasive blood pressure monitoring results in a blind gap between two measurements (mostly three or five minutes). In order to address this limitation, different continuous non-invasive blood pressure monitoring devices have been introduced. The next evolutional step of non-invasive cardiac output monitoring was to prevent IOH before their onset by using the Hypotension Prediction Index (HPI). Based on the Edward ́s monitoring platform, HPI is a monitoring tool which aims to predict IOH (defined as MAP<65 mmHg for at least one minute) up to 15 min before its onset. The underlying machine learning based algorithm uses analyses features from the pressure waveform and was first calculated from a large retrospective data set of surgical patients and subsequently validated in a prospective cohort. In this study HPI showed a sensitivity of 88% and specificity of 87% for predicting IOH 15 min before its onset. Since then, own and studies of other working groups confirmed the effective prevention of IOH by the use of HPI-based GDT. Until today the arterial waveform analysis was dependent on invasive arterial measurement but since Edwards Lifesciences already promoted the start of the HPI on the ClearSight platform a non-invasive measurement will soon be possible.

Further, until now it has not yet been proven that the perioperative use of a continuous non-invasive blood pressure monitoring has a beneficial effect on the patient´s outcome.

Study objectives The aim of the study is to investigate whether a hemodynamic protocol based on continuous non-invasive cardiac output monitoring (ClearSight system) compared to standard care can reduce the incidence of IOH, postoperative AKI, and MINS in patients undergoing major trauma and orthopedic surgery.

Detailed Description

Complications related to intraoperative hypotension (IOH) can be detected in most organ systems of which renal failure poses a relevant complication in the perioperative phase. Acute kidney injury (AKI) affects up to 25 % of patients attending the intensive care unit (ICU). Currently, serum creatinine and urea display the most common parameters used to detect AKI, but it may take a day or more for serum creatinine levels to accumulate in the blood of a patient with an AKI. For this reason, it may not reflect real time kidney damage or loss of function. To overcome this limitation, the cell cycle arrest biomarkers TIMP-2- and IGFBP7-quantification (Nephrocheck) has been successfully evaluated for the detection of AKI. The main advantage of both parameters is the opportunity of early detection of AKI and its point-of-care design, which makes them especially for the use on the ICU valuable.

Myocardial injury after non-cardiac surgery (MINS) displays another adverse outcome associated to IOH and endangers particularly patients with an age of 45 years and older and approximately 1% of all patients suffering of MINS die within 30 days after non-cardiac surgery.

In order to reduce the incidence of IOH, various goal-directed therapy (GDT) protocols have already been introduced with success regarding the reduction of postoperative AKI and MINS. However, these studies used an invasive hemodynamic monitoring which offered a continuous surveillance of the blood pressure. In contrast, standard non-invasive blood pressure monitoring results in a blind gap between two measurements (mostly three or five minutes). In order to address this limitation, different continuous non-invasive blood pressure monitoring devices have been introduced. The next evolutional step of non-invasive cardiac output monitoring was to prevent IOH before their onset by using the Hypotension Prediction Index (HPI). Based on the Edward ́s monitoring platform, HPI is a monitoring tool which aims to predict IOH (defined as MAP<65 mmHg for at least one minute) up to 15 min before its onset. Until today the arterial waveform analysis was dependent on invasive arterial measurement but since Edwards Lifesciences already promoted the start of the HPI on the ClearSight platform a non-invasive measurement will soon be possible.

Further, until now it has not yet been proven that the perioperative use of a continuous non-invasive blood pressure monitoring has a beneficial effect on the patient´s outcome. Especially, a GDT based on non-invasive blood pressure monitoring might not only be able to reduce the incidence of IOH but also of the occurrence of postoperative renal failure.

2.1 Study hypothesis 2.1.1 Primary study hypothesis The perioperative use of non-invasive HPI-guided GDT reduces the incidence of IOH in patients undergoing major trauma and orthopedic surgery.

2.1.2 Secondary study hypothesis

• The perioperative use of non-invasive HPI-guided GDT reduces the occurrence of postoperative renal failure in patients undergoing major trauma and orthopedic surgery.
• The perioperative use of non-invasive HPI-guided GDT reduces the occurrence of postoperative MINS in patients undergoing major trauma and orthopedic surgery.

2.2 Study objectives The aim of the study is to investigate whether a hemodynamic protocol based on continuous non-invasive cardiac output monitoring (ClearSight system) compared to standard care can reduce the incidence of IOH, postoperative AKI, and MINS in patients undergoing major trauma and orthopedic surgery.

3 Methodology 3.1 Study design The study is designed as a monocentric randomized prospective interventional trial comparing goal directed hemodynamic management using continuous non-invasive cardiac output monitoring (ClearSight system) to standard care.

3.2 Study centers University Hospital Giessen, Department of Anesthesiology and Intensive Care Medicine

3.3 Study Population 3.3.1 Study groups Major Trauma and Orthopedic Surgery

3.4 Working plan 3.4.1 Preoperative Assessment

Patients are recruited before surgery after checking inclusion and exclusion criteria. Informed consent is obtained at this time. Patients will be randomized 1:1 to the two groups after achieving the patient´s informed consent. Further, the following basic characteristics are obtained:

• Age, sex, height, weight, ASA score
• Pre-existing conditions (hypertension, coronary heart disease with and without history of myocardial infarction, peripheral arterial disease, renal failure, chronic obstructive pulmonary disease, diabetes)
• Previous major surgeries
• Current prescription of medication

Furthermore, the following laboratory results will be gained:

• Blood cell count
• Global coagulatory function (Internationalized Ratio, thromboplastine time, fibrinogen levels)
• Parameters of renal function (Creatinine, urea, Nephrocheck, blood and urinary mitochondrial DNA)
• Parameters of cardiac function (Troponin I, Creatinine kinase, Myoglobin, Brain Natriuretic Peptide)
• Inflammatory Parameters (C-Reactive Protein, Procalcitonin)
• Parameters of endothelial function (Angiopoietins 1 and 2, Syndecan-1 and intercellular adhesion molecule-1 (ICAM-1)), Bio-ADM

3.4.2 Time Points The study time points are defined as followed: prior to surgery as well as immediately, 24, 72, and 168 hours after surgery (depending on the duration of hospital stay). At any time point clinical data, blood and urine will be collected (depending on the duration of hospital stay).

3.4.3 Perioperative Management 3.4.3.1 Induction and Maintenance of anesthesia All patients receive the standard hemodynamic monitoring (electrocardiogram, non-invasive blood pressure, and plethysmography). Non-invasive blood pressure will be measured every three minutes.

Independently of the randomized study group, induction of anesthesia will be performed with fentanyl, propofol, and cis-atracurium. Dosages will be chosen according to the patient´s age and body weight as well as pre-existing diseases according to the assessment of the attending physician. After intubation, all patients are ventilated with a tidal volume of 8 ml/kg ideal bodyweight and with regard to the capnography (target end-tidal CO2 of 35-40 mmHg). The control group will be managed according to the investigators´ SOP with the aim of an MAD &amp;gt; 65mmHg.

3.4.3.2 Management of interventional group patients Prior to the surgery the rest cardiac index and contractility (dp/dt) must be quantified. For this purpose, the cardiac index will be measured in the preoperative night by applicating the HPI ClearSight system through a study team member. A nighttime cardiac index is accepted when more than three reliable measurements were recorded in rest over a time period of 60 minutes. If the rest cardiac index is not available throughout the night because the patient´s sleep is altered by the measurements, the awake cardiac index will be quantified until the monitoring is stopped for the night sleep of the patient. This mean baseline measurements (CI and dp/dt) will then be the target cardiac index throughout the study algorithm (figure 1). In case no sleep measurement was achievable, the awake measurement will be accounted as baseline value. The perioperative study intervention period starts with the beginning of anesthesia and ends at the end of surgery. Intraoperative mean arterial pressure will be maintained at least at 65 mmHg and cardiac index and dp/dt will be individually optimized according to the GDT algorithm.

3.5 Data Processing Data collection is carried out consistently on pre-defined time-points in the investigators´ electronic patient data management system into a separate study database (Microsoft Excel).

The collected data is pseudonymised in the database based on a random key method. The chart with the patient data and decrypting keys is kept in the study center for at least 15 years after the end of the study (publication). Data anonymization is intentionally not performed to give patients the option for data insight or deletion of their data in the future.

Data management and evaluation is performed by the study team.

3.6 Patient number and Biometrics The aim of the study is to show the impact of non-invasive cardiac output monitoring on the incidence of IOH in a cohort of trauma and orthopedic surgery. Sample size calculation was performed with regard to a recent study by Maheshwari et al. who investigated the effect of HPI on the prevention of hypotension. This study was chosen because the primary endpoint, respectively the definition of hypotension (MAP<65 mmHg), was identical to the investigators´ study and they investigated also non-cardiac surgical patients. In this study, the mean number of hypotensive periods (given as an area under the curve of MAP ≤65 mmHg) of patients without hemodynamic management accounted to 34.2 [8,5-112.7] compared to 32.7 [6.3-102] in patients with hemodynamic measurement. Aiming for an alpha of 0.05 and power of 0.95, the sample size calculation resulted in 66 patients per study group (total 132 patients, based on the use of the Wilcoxon test). In order to address potential dropouts (estimated drop-out rate 10-20%) the investigators chose to increase the patients numbers to 75 patients in each study group.

Next to the target parameters, data of the hemodynamic and respiratory function will be achieved as well as of the anesthetic and hemodynamic management (please see CRF). Furthermore, general characteristics such as age, gender, body mass index, as well as pre-existing conditions and prescriptions will be assessed.

For the target variables, the results will be investigated and analyzed descriptively (e.g., checked for distribution). Metric characteristics (mean and standard deviation) as well as median and interquartile difference and achieved frequencies (with a percentage specification) will be determined. As part of the exploratory analysis, the structural equilibrium (homogeneity) of the treatment groups will also be checked.

Depending on the distribution of the observation values, appropriate test methods are used.

The outcome of the statistical testing will be controlled for influence of secondary parameters, as there are suspected reasons for hypotension, type and dosage of vasopressors used during the procedure, as well as type and dosage of inotropic medication.

All analysis will be done using R-Plus scripting (R Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, http://www.R-project.org/).

3.7 Benefit - Risk assessment 3.7.1 Potential benefit Based on a continuous monitoring by additional monitoring system an early detection of potential life-threatening events and acute kidney injury is possible. This can result in an optimization of the patients' therapy and a better outcome.

3.7.2 Potential Risks The presented study is an interventional study. The potential risks are marginal. The usage of an additional non-invasive cardiac output monitoring is minimal.

The time points of blood samples for the study are in line with routine sampling. Based on this, there is no additional risk for the patient.

3.7.3 Benefit/ Risk analysis The benefit for the patients is additional monitoring, based on an additional monitoring device and the supervising study doctor, who can support the treating anesthesiologist with information in potentially critical situations. Thereby, it is possible to treat early goal-directed and possibly improve the patient´s outcome. Considering the potential benefits of the generated information for the patient in comparison to the expected risks, the beneficial effect is overbalanced.

The expected gain in knowledge from this study could be used for optimizing perioperative care.

Conditions

Intraoperative Hypotension; Acute Kidney Injury; Myocardial Injury After Non-cardiac Surgery

Study Design

• Allocation Method: RANDOMIZED
• Intervention Model: PARALLEL
• Primary Study Purpose: PREVENTION
• Blinding Strategy: DOUBLE

Study Groups

Interventional group

GDT-therapy guided hemodynamic management based on Clearsight system

Group Type: ACTIVE_COMPARATOR

GDT-based hemodynamic management based on Clearsight device

Intervention Type: DEVICE

Intraoperative use of a HPI-guided hemodynamic goal-directed protocol based on the non-invasive measurement of HPI (Clearsight system)

Control group

Clearsight-monitor is blinded but records standard hemodynamic care

Group Type: NO_INTERVENTION

No interventions assigned to this group

Interventions

GDT-based hemodynamic management based on Clearsight device

Intraoperative use of a HPI-guided hemodynamic goal-directed protocol based on the non-invasive measurement of HPI (Clearsight system)

Intervention Type: DEVICE

Eligibility Criteria

Inclusion Criteria

• Patients undergoing major trauma or orthopedic surgery in supine position, which is defined as:

• Reconstructive Surgery of the pelvis (e.g., stabilization of fractures)
• Total hip arthroplasty
• Surgery of the proximal femur (e.g., stabilization of fractures)
• Total knee arthroplasty
• Surgery of the spine

• Performance of general anesthesia with planned duration of &gt;90min
• Age ≥ 45 years

Exclusion Criteria

• Planned invasive blood pressure monitoring
• Participation in another interventional study
• Pregnancy and nursing mothers
• Surgery without controlled mechanical ventilation
• ASA I or IV
• Arterial Fibrillation
• Allergy against gelantine

• Minimum Eligible Age: 45 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Edwards Lifesciences

INDUSTRY

Sponsor Role: collaborator

University of Giessen

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Michael Sander, Prof.

Role: PRINCIPAL_INVESTIGATOR

Justus-Liebig-University of Giessen

Locations

Justus-Liebig-University of Giessen

Giessen, , Germany

Site Status: RECRUITING

Countries

Germany

Central Contacts

Emmanuel Schneck, M.D.

Role: CONTACT

emmanuel.schneck@chiru.med.uni-giessen.de

0049 641 985 44401

Michael Sander, Prof.

Role: CONTACT

michael.sander@chiru.med.uni-giessen.de

0049 641 985 44401

Facility Contacts

Emmanuel Schneck, M.D.

Role: primary

emmanuel.schneck@chiru.med.uni-giessen.de

004964198544401

Michael Sander, Prof.

Role: backup

michael.sander@chiru.med.uni-giessen.de

004964198544401

References

Cecconi M, Fasano N, Langiano N, Divella M, Costa MG, Rhodes A, Della Rocca G. Goal-directed haemodynamic therapy during elective total hip arthroplasty under regional anaesthesia. Crit Care. 2011;15(3):R132. doi: 10.1186/cc10246. Epub 2011 May 30.

Reference Type: BACKGROUND

PMID: 21624138 (View on PubMed)

Alyabsi M, Gaid R, Alqunaibet A, Alaskar A, Mahmud A, Alghamdi J. Impact of the 2017 ACC/AHA guideline on the prevalence of elevated blood pressure and hypertension: a cross-sectional analysis of 10 799 individuals. BMJ Open. 2020 Dec 31;10(12):e041973. doi: 10.1136/bmjopen-2020-041973.

Reference Type: BACKGROUND

PMID: 33384395 (View on PubMed)

Bijker JB, van Klei WA, Kappen TH, van Wolfswinkel L, Moons KG, Kalkman CJ. Incidence of intraoperative hypotension as a function of the chosen definition: literature definitions applied to a retrospective cohort using automated data collection. Anesthesiology. 2007 Aug;107(2):213-20. doi: 10.1097/01.anes.0000270724.40897.8e.

Reference Type: BACKGROUND

PMID: 17667564 (View on PubMed)

van Waes JA, van Klei WA, Wijeysundera DN, van Wolfswinkel L, Lindsay TF, Beattie WS. Association between Intraoperative Hypotension and Myocardial Injury after Vascular Surgery. Anesthesiology. 2016 Jan;124(1):35-44. doi: 10.1097/ALN.0000000000000922.

Reference Type: BACKGROUND

PMID: 26540148 (View on PubMed)

Monk TG, Saini V, Weldon BC, Sigl JC. Anesthetic management and one-year mortality after noncardiac surgery. Anesth Analg. 2005 Jan;100(1):4-10. doi: 10.1213/01.ANE.0000147519.82841.5E.

Reference Type: BACKGROUND

PMID: 15616043 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 23835589 (View on PubMed)

Morris RW, Watterson LM, Westhorpe RN, Webb RK. Crisis management during anaesthesia: hypotension. Qual Saf Health Care. 2005 Jun;14(3):e11. doi: 10.1136/qshc.2002.004440.

Reference Type: BACKGROUND

PMID: 15933284 (View on PubMed)

Reich DL, Hossain S, Krol M, Baez B, Patel P, Bernstein A, Bodian CA. Predictors of hypotension after induction of general anesthesia. Anesth Analg. 2005 Sep;101(3):622-628. doi: 10.1213/01.ANE.0000175214.38450.91.

Reference Type: BACKGROUND

PMID: 16115962 (View on PubMed)

de Mendonca A, Vincent JL, Suter PM, Moreno R, Dearden NM, Antonelli M, Takala J, Sprung C, Cantraine F. Acute renal failure in the ICU: risk factors and outcome evaluated by the SOFA score. Intensive Care Med. 2000 Jul;26(7):915-21. doi: 10.1007/s001340051281.

Reference Type: BACKGROUND

PMID: 10990106 (View on PubMed)

Liu YL, Prowle J, Licari E, Uchino S, Bellomo R. Changes in blood pressure before the development of nosocomial acute kidney injury. Nephrol Dial Transplant. 2009 Feb;24(2):504-11. doi: 10.1093/ndt/gfn490. Epub 2008 Sep 3.

Reference Type: BACKGROUND

PMID: 18768582 (View on PubMed)

Lehman LW, Saeed M, Moody G, Mark R. Hypotension as a Risk Factor for Acute Kidney Injury in ICU Patients. Comput Cardiol (2010). 2010;37:1095-1098.

Reference Type: BACKGROUND

PMID: 22158679 (View on PubMed)

Kellum JA, Lameire N; KDIGO AKI Guideline Work Group. Diagnosis, evaluation, and management of acute kidney injury: a KDIGO summary (Part 1). Crit Care. 2013 Feb 4;17(1):204. doi: 10.1186/cc11454.

Reference Type: BACKGROUND

PMID: 23394211 (View on PubMed)

Mandelbaum T, Scott DJ, Lee J, Mark RG, Malhotra A, Waikar SS, Howell MD, Talmor D. Outcome of critically ill patients with acute kidney injury using the Acute Kidney Injury Network criteria. Crit Care Med. 2011 Dec;39(12):2659-64. doi: 10.1097/CCM.0b013e3182281f1b.

Reference Type: BACKGROUND

PMID: 21765352 (View on PubMed)

Martensson J, Martling CR, Bell M. Novel biomarkers of acute kidney injury and failure: clinical applicability. Br J Anaesth. 2012 Dec;109(6):843-50. doi: 10.1093/bja/aes357. Epub 2012 Oct 9.

Reference Type: BACKGROUND

PMID: 23048068 (View on PubMed)

Chertow GM, Burdick E, Honour M, Bonventre JV, Bates DW. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005 Nov;16(11):3365-70. doi: 10.1681/ASN.2004090740. Epub 2005 Sep 21.

Reference Type: BACKGROUND

PMID: 16177006 (View on PubMed)

Kashani K, Al-Khafaji A, Ardiles T, Artigas A, Bagshaw SM, Bell M, Bihorac A, Birkhahn R, Cely CM, Chawla LS, Davison DL, Feldkamp T, Forni LG, Gong MN, Gunnerson KJ, Haase M, Hackett J, Honore PM, Hoste EA, Joannes-Boyau O, Joannidis M, Kim P, Koyner JL, Laskowitz DT, Lissauer ME, Marx G, McCullough PA, Mullaney S, Ostermann M, Rimmele T, Shapiro NI, Shaw AD, Shi J, Sprague AM, Vincent JL, Vinsonneau C, Wagner L, Walker MG, Wilkerson RG, Zacharowski K, Kellum JA. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013 Feb 6;17(1):R25. doi: 10.1186/cc12503.

Reference Type: BACKGROUND

PMID: 23388612 (View on PubMed)

Vijayan A, Faubel S, Askenazi DJ, Cerda J, Fissell WH, Heung M, Humphreys BD, Koyner JL, Liu KD, Mour G, Nolin TD, Bihorac A; American Society of Nephrology Acute Kidney Injury Advisory Group. Clinical Use of the Urine Biomarker [TIMP-2] x [IGFBP7] for Acute Kidney Injury Risk Assessment. Am J Kidney Dis. 2016 Jul;68(1):19-28. doi: 10.1053/j.ajkd.2015.12.033. Epub 2016 Mar 4.

Reference Type: BACKGROUND

PMID: 26948834 (View on PubMed)

Smilowitz NR, Gupta N, Ramakrishna H, Guo Y, Berger JS, Bangalore S. Perioperative Major Adverse Cardiovascular and Cerebrovascular Events Associated With Noncardiac Surgery. JAMA Cardiol. 2017 Feb 1;2(2):181-187. doi: 10.1001/jamacardio.2016.4792.

Reference Type: BACKGROUND

PMID: 28030663 (View on PubMed)

Writing Committee for the VISION Study Investigators; Devereaux PJ, Biccard BM, Sigamani A, Xavier D, Chan MTV, Srinathan SK, Walsh M, Abraham V, Pearse R, Wang CY, Sessler DI, Kurz A, Szczeklik W, Berwanger O, Villar JC, Malaga G, Garg AX, Chow CK, Ackland G, Patel A, Borges FK, Belley-Cote EP, Duceppe E, Spence J, Tandon V, Williams C, Sapsford RJ, Polanczyk CA, Tiboni M, Alonso-Coello P, Faruqui A, Heels-Ansdell D, Lamy A, Whitlock R, LeManach Y, Roshanov PS, McGillion M, Kavsak P, McQueen MJ, Thabane L, Rodseth RN, Buse GAL, Bhandari M, Garutti I, Jacka MJ, Schunemann HJ, Cortes OL, Coriat P, Dvirnik N, Botto F, Pettit S, Jaffe AS, Guyatt GH. Association of Postoperative High-Sensitivity Troponin Levels With Myocardial Injury and 30-Day Mortality Among Patients Undergoing Noncardiac Surgery. JAMA. 2017 Apr 25;317(16):1642-1651. doi: 10.1001/jama.2017.4360.

Reference Type: BACKGROUND

PMID: 28444280 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 27792044 (View on PubMed)

Devereaux PJ, Szczeklik W. Myocardial injury after non-cardiac surgery: diagnosis and management. Eur Heart J. 2020 May 1;41(32):3083-3091. doi: 10.1093/eurheartj/ehz301.

Reference Type: BACKGROUND

PMID: 31095334 (View on PubMed)

Gillies MA, Shah AS, Mullenheim J, Tricklebank S, Owen T, Antonelli J, Strachan F, Mills NL, Pearse RM. Perioperative myocardial injury in patients receiving cardiac output-guided haemodynamic therapy: a substudy of the OPTIMISE Trial. Br J Anaesth. 2015 Aug;115(2):227-33. doi: 10.1093/bja/aev137. Epub 2015 May 21.

Reference Type: BACKGROUND

PMID: 26001837 (View on PubMed)

Scheeren TW, Wiesenack C, Gerlach H, Marx G. Goal-directed intraoperative fluid therapy guided by stroke volume and its variation in high-risk surgical patients: a prospective randomized multicentre study. J Clin Monit Comput. 2013 Jun;27(3):225-33. doi: 10.1007/s10877-013-9461-6. Epub 2013 Apr 5.

Reference Type: BACKGROUND

PMID: 23558909 (View on PubMed)

Sun Y, Chai F, Pan C, Romeiser JL, Gan TJ. Effect of perioperative goal-directed hemodynamic therapy on postoperative recovery following major abdominal surgery-a systematic review and meta-analysis of randomized controlled trials. Crit Care. 2017 Jun 12;21(1):141. doi: 10.1186/s13054-017-1728-8.

Reference Type: BACKGROUND

PMID: 28602158 (View on PubMed)

Giglio M, Dalfino L, Puntillo F, Rubino G, Marucci M, Brienza N. Haemodynamic goal-directed therapy in cardiac and vascular surgery. A systematic review and meta-analysis. Interact Cardiovasc Thorac Surg. 2012 Nov;15(5):878-87. doi: 10.1093/icvts/ivs323. Epub 2012 Jul 24.

Reference Type: BACKGROUND

PMID: 22833509 (View on PubMed)

Arulkumaran N, Corredor C, Hamilton MA, Ball J, Grounds RM, Rhodes A, Cecconi M. Cardiac complications associated with goal-directed therapy in high-risk surgical patients: a meta-analysis. Br J Anaesth. 2014 Apr;112(4):648-59. doi: 10.1093/bja/aet466. Epub 2014 Jan 10.

Reference Type: BACKGROUND

PMID: 24413429 (View on PubMed)

Habicher M, Balzer F, Mezger V, Niclas J, Muller M, Perka C, Kramer M, Sander M. Implementation of goal-directed fluid therapy during hip revision arthroplasty: a matched cohort study. Perioper Med (Lond). 2016 Dec 13;5:31. doi: 10.1186/s13741-016-0056-x. eCollection 2016.

Reference Type: BACKGROUND

PMID: 27999663 (View on PubMed)

Salzwedel C, Puig J, Carstens A, Bein B, Molnar Z, Kiss K, Hussain A, Belda J, Kirov MY, Sakka SG, Reuter DA. Perioperative goal-directed hemodynamic therapy based on radial arterial pulse pressure variation and continuous cardiac index trending reduces postoperative complications after major abdominal surgery: a multi-center, prospective, randomized study. Crit Care. 2013 Sep 8;17(5):R191. doi: 10.1186/cc12885.

Reference Type: BACKGROUND

PMID: 24010849 (View on PubMed)

Maheshwari K, Khanna S, Bajracharya GR, Makarova N, Riter Q, Raza S, Cywinski JB, Argalious M, Kurz A, Sessler DI. A Randomized Trial of Continuous Noninvasive Blood Pressure Monitoring During Noncardiac Surgery. Anesth Analg. 2018 Aug;127(2):424-431. doi: 10.1213/ANE.0000000000003482.

Reference Type: BACKGROUND

PMID: 29916861 (View on PubMed)

Chen G, Chung E, Meng L, Alexander B, Vu T, Rinehart J, Cannesson M. Impact of non invasive and beat-to-beat arterial pressure monitoring on intraoperative hemodynamic management. J Clin Monit Comput. 2012 Apr;26(2):133-40. doi: 10.1007/s10877-012-9344-2. Epub 2012 Mar 1.

Reference Type: BACKGROUND

PMID: 22382920 (View on PubMed)

Martina JR, Westerhof BE, van Goudoever J, de Beaumont EM, Truijen J, Kim YS, Immink RV, Jobsis DA, Hollmann MW, Lahpor JR, de Mol BA, van Lieshout JJ. Noninvasive continuous arterial blood pressure monitoring with Nexfin(R). Anesthesiology. 2012 May;116(5):1092-103. doi: 10.1097/ALN.0b013e31824f94ed.

Reference Type: BACKGROUND

PMID: 22415387 (View on PubMed)

Meidert AS, Nold JS, Hornung R, Paulus AC, Zwissler B, Czerner S. The impact of continuous non-invasive arterial blood pressure monitoring on blood pressure stability during general anaesthesia in orthopaedic patients: A randomised trial. Eur J Anaesthesiol. 2017 Nov;34(11):716-722. doi: 10.1097/EJA.0000000000000690.

Reference Type: BACKGROUND

PMID: 28922340 (View on PubMed)

Futier E, Lefrant JY, Guinot PG, Godet T, Lorne E, Cuvillon P, Bertran S, Leone M, Pastene B, Piriou V, Molliex S, Albanese J, Julia JM, Tavernier B, Imhoff E, Bazin JE, Constantin JM, Pereira B, Jaber S; INPRESS Study Group. Effect of Individualized vs Standard Blood Pressure Management Strategies on Postoperative Organ Dysfunction Among High-Risk Patients Undergoing Major Surgery: A Randomized Clinical Trial. JAMA. 2017 Oct 10;318(14):1346-1357. doi: 10.1001/jama.2017.14172.

Reference Type: BACKGROUND

PMID: 28973220 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 29894315 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 30896602 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 31784852 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 32065827 (View on PubMed)

Hruska K, Ruge T. The Tragically Hip: Trauma in Elderly Patients. Emerg Med Clin North Am. 2018 Feb;36(1):219-235. doi: 10.1016/j.emc.2017.08.014.

Reference Type: BACKGROUND

PMID: 29132579 (View on PubMed)

Shem Tov L, Matot I. Frailty and anesthesia. Curr Opin Anaesthesiol. 2017 Jun;30(3):409-417. doi: 10.1097/ACO.0000000000000456.

Reference Type: BACKGROUND

PMID: 28291129 (View on PubMed)

Brooks SE, Peetz AB. Evidence-Based Care of Geriatric Trauma Patients. Surg Clin North Am. 2017 Oct;97(5):1157-1174. doi: 10.1016/j.suc.2017.06.006.

Reference Type: BACKGROUND

PMID: 28958363 (View on PubMed)

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.

Reference Type: BACKGROUND

PMID: 32960954 (View on PubMed)

Other Identifiers

Clearsight

Identifier Type: -

Identifier Source: org_study_id