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| Name | Class |
|---|---|
| Edwards Lifesciences | INDUSTRY |
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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.
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
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:
Furthermore, the following laboratory results will be gained:
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 &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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Interventional group | Active Comparator | GDT-therapy guided hemodynamic management based on Clearsight system |
|
| Control group | No Intervention | Clearsight-monitor is blinded but records standard hemodynamic care |
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| GDT-based hemodynamic management based on Clearsight device | Device | Intraoperative use of a HPI-guided hemodynamic goal-directed protocol based on the non-invasive measurement of HPI (Clearsight system) |
| Measure | Description | Time Frame |
|---|---|---|
| Change of the frequency of intraoperative hypotension | Change of the frequency of intraoperative hypotension (defined as MAP below 65mmHg, frequency ((n)/h) | through study completion, an average of 1 year |
| Change of the absolute duration of of intraoperative hypotension | Change of the absolute duration of intraoperative hypotension (defined as MAP below 65mmHg, unit: minutes) | through study completion, an average of 1 year |
| Change of the relative duration of intraoperative hypotension | Change of the relative duration of intraoperative hypotension (defined as MAP below 65mmHg, unit: percentage of total anesthesia time) | through study completion, an average of 1 year |
| Measure | Description | Time Frame |
|---|---|---|
| AKI | Occurrence of an AKI (according to the KDIGO criteria or an increase of Nephrocheck > 0.3 (ng/ml)^2/1000; both parameters will be presented in the results for AKI) | through study completion, an average of 1 year |
| MINS |
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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
Exclusion Criteria:
- Predefined exclusion criteria are:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Emmanuel Schneck, M.D. | Contact | 0049 641 985 44401 | emmanuel.schneck@chiru.med.uni-giessen.de | |
| Michael Sander, Prof. | Contact | 0049 641 985 44401 | michael.sander@chiru.med.uni-giessen.de |
| Name | Affiliation | Role |
|---|---|---|
| Michael Sander, Prof. | Justus-Liebig-University of Giessen | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Justus-Liebig-University of Giessen | Recruiting | Giessen | 35392 | Germany |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33384395 | Background | 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. | |
| 17667564 | Background |
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The study data can be checked on reasonable request by contact the PI.
The study data can be checked on reasonable request by contact the PI after the end of the analysis (appr. after 06/2025). The study protocol, SAP, ICF can been assessed after the start of the study.
The data can be accessed by writing an email to the PI. He checks the if the request is reasonable (e.g., for review purpose) and will then provide the information per mail.
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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. 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
Not provided
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All patients are connected to the Clearsight device but the interface is masked in the control group.
Occurrence of MINS (TNI exceeding the 99th percentile of the normal population)
| through study completion, an average of 1 year |
| 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. |
| 26540148 | Background | 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. |
| 15616043 | Background | 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. |
| 23835589 | Background | 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. |
| 15933284 | Background | 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. |
| 16115962 | Background | 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. |
| 10990106 | Background | 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. |
| 18768582 | Background | 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. |
| 22158679 | Background | 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. |
| 23394211 | Background | 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. |
| 21765352 | Background | 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. |
| 23048068 | Background | 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. |
| 16177006 | Background | 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. |
| 23388612 | Background | 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. |
| 26948834 | Background | 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. |
| 28030663 | Background | 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. |
| 28444280 | Background | 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. |
| 27792044 | Background | 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. |
| 31095334 | Background | 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. |
| 26001837 | Background | 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. |
| 23558909 | Background | 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. |
| 28602158 | Background | 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. |
| 22833509 | Background | 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. |
| 21624138 | Background | 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. |
| 24413429 | Background | 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. |
| 27999663 | Background | 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. |
| 24010849 | Background | 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. |
| 29916861 | Background | 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. |
| 22382920 | Background | 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. |
| 22415387 | Background | 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. |
| 28922340 | Background | 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. |
| 28973220 | Background | 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. |
| 29894315 | Background | 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. |
| 30896602 | Background | 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. |
| 31784852 | Background | 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 | Background | 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. |
| 29132579 | Background | 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. |
| 28291129 | Background | Shem Tov L, Matot I. Frailty and anesthesia. Curr Opin Anaesthesiol. 2017 Jun;30(3):409-417. doi: 10.1097/ACO.0000000000000456. |
| 28958363 | Background | 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. |
| 32960954 | Background | 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. |
| 41168839 | Derived | Habicher M, Kleymann R, Shakkour K, Holstein N, Koch C, Markmann M, Schneck E, Sander M. AI-supported non-invasive measurement for intraoperative hypotension reduction in major Orthopedic and trauma surgery-study protocol for a randomized clinical trial. Trials. 2025 Oct 30;26(1):455. doi: 10.1186/s13063-025-09194-x. |
| ID | Term |
|---|---|
| D058186 | Acute Kidney Injury |
| ID | Term |
|---|---|
| D051437 | Renal Insufficiency |
| D007674 | Kidney Diseases |
| D014570 | Urologic Diseases |
| D052776 | Female Urogenital Diseases |
| D005261 | Female Urogenital Diseases and Pregnancy Complications |
| D000091642 | Urogenital Diseases |
| D052801 | Male Urogenital Diseases |
Not provided
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