Hypotension During SurgeryEHPI-PanNCT06097052
Hypotension Predictive Index Effect on Intraoperative Hypotension During Pancreatic Surgery.
An observational study of Hypotension During Surgery and Perioperative Complication, run by Istituto Clinico Humanitas at 1 site in Italy.
Trial summary
Intraoperative hypotension (IOH) is a sudden clinical phenomenon that occurs frequently during general anesthesia. Prevention of IOH has been linked to reduced postoperative organ damage and decreased incidence of perioperative complications. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Hypotension During Surgery, Perioperative Complication
- What is being tested?
- Hypotension Predictive Index
- Type of treatment
- Medical device
- How many people
- 48 participants
- Where
- 1 siteItaly
- Study dates
- 23 May 2023to 31 Jan 2024
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Subjects undergoing general anesthesia for elective pancreatic surgery consecutively recruited before and after the introduction of Hypotension Predictive Index technology.
Who may be able to join
- Subjects aged 18 years or older.
- Subjects scheduled for major open pancreatic surgery.
- Subjects monitored with FloTrac or HPI invasive arterial blood pressure monitoring.
- Total surgical time > 360min.
Who cannot join
- Subjects aged 90 years or older
- Subjects classified as ASA IV/V/VI
- Subjects undergoing urgent or emergency surgery
Trial locations and contacts
1 site in 1 country.
About this study
Official title: The Effect of Hypotension Predictive Index on Intraoperative Hypotension Events and Duration During Pancreatic Surgery. A Retrospective Pre-post Observational Study.
Intraoperative hypotension (IOH) is a sudden clinical phenomenon that occurs frequently during general anesthesia. Prevention of IOH has been linked to reduced postoperative organ damage and decreased incidence of perioperative complications. Oncological patients with reduced preoperative physiological reserves may be especially vulnerable to IOH deleterious effects, especially when exposed to prolonged surgical time increase, as it is the case for patients undergoing pancreatic surgery.
The investigators aim to study introduction of a new technology able to predict hypotensive events (Hypotension Predictive Index, HPI Acumen™) in terms of its effects on IOH occurrence and burden in patients undergoing pancreatic surgery. The investigators will enroll patients before and after the introduction of HPI monitoring. Further, differences in postoperative outcomes and perioperative complications between before and after populations will be investigated.
Read the detailed description
Intraoperative hypotension (IOH) is a relatively common event during surgery, occurring suddenly and often without any warning sign. Predicting IOH would help clinicians to set up a rapid response, reducing the number of hypotensive events and overall time of hypotension.
Historically the management of IOH has been reactive, despite the introduction of advanced arterial waveform analysis systems providing a number of cardiovascular parameters (arterial pressure, cardiac output, dynamic indices) which allow advanced intraoperative hemodynamic monitoring (FloTrac™, Edwards Lifesciences Corp., Irvine, USA). This changed when continuous blood pressure wave static and dynamic features extraction combined with Machine-Learning approach proved informative in identifying specific signatures associated with impending exhaustion of compensatory mechanisms. By fitting these features in a mathematical model it became available an easy-to-interpret Hypotension Predictive Index (Acumen™ HPI - Edwards Lifesciences, Irvine, CA), which can predict IOH up to 15 minutes prior to the clinical event. The HPI is expressed in a range from 0 to 100, the higher the number, the higher the probability and the shorter the time of occurrence of the hypotensive event. Therefore, combining arterial waveform analysis and HPI may provide timely prediction and goal-directed treatment plans based on the specific mechanism underlying IOH, such as relative hypovolemia, temporary vasoplegia or decreased inotropism.
Several studies have shown that IOH has a great impact on postoperative outcomes and tight control of blood pressure may be important especially in patients undergoing major surgery. These patients are often frail and bear greater risks of developing organ dysfunction, mainly renal insufficiency and myocardial injury. Futier et al. reported a 25% risk reduction of postoperative organ dysfunction when IOH is properly treated during surgery. Further, prospective studies showed that the use of HPI both decreased the total time of hypotension in non-cardiac surgery and reduced post-operative complications and hospital length-of-stay.
These studies addressed application of HPI in mixed cohorts of the population (orthopedic surgery, neurosurgery, general and vascular surgery, ENT surgery), but the duration and type of surgery are certainly two major factors affecting the occurrence and the severity of IOH. Among non-cardiac operations, major pancreatic surgery is generally complex and long-lasting. In our center roughly 180 patients undergo major pancreatic surgery every year and in our experience these patients are often debilitated and have reduced physiological reserve at the time of surgery. In addition, post-operative complications including bleeding, sepsis, bilio-digestive fistulas, acute kidney injury are common in this setting. For these reasons, the investigators believe that patients undergoing major pancreatic surgery represent an excellent model to evaluate the efficacy of HPI compared to the FloTrac™ alone as they can benefit from advanced hemodynamic monitoring and IOH prediction tools.
The aim of this study is to assess whether patients undergoing pancreatic surgery benefit from early prediction and goal-directed treatment of IOH using the HPI software compared to a goal-directed hemodynamic approach using the FloTrac™ monitoring system. The investigators plan to study the occurrence of IOH with and without the use of HPI in comparison with a FloTrac™ monitoring system. Furthermore, the study aims to evaluate if HPI software inclusion in an intraoperative hemodynamic management protocol leads to improved intraoperative cardiovascular stability and better clinical outcomes. Finally, the investigators want to explore whether the improved clinical experience using HPI predictive model correlates with the degree of IOH by analyzing data from patients managed only with this technology over time.
STUDY DESIGN AND POPULATION
This is a retrospective observational before-and-after study planned to analyze data from about 60 elective patients undergoing major open pancreatic surgery. Only patients that already signed an informed consent including perioperative data utilization for previous ongoing clinical studies will be considered for the analysis.
Continuous blood pressure waveform after the insertion of an arterial line (radial artery was the preferred choice) was monitored in all patients after anesthesia induction. Until March 2022 patients were monitored using the FloTracTM waveform analysis alone, while from April 2022 to present, patients' hemodynamics were managed using the HPI software. The investigators will compare two cohorts (Flotrac group vs. HPI group) to evaluate the impact of the latter technology on IOH. Mean arterial pressure will be defined as the main variable describing the perfusion pressure, while the cardiac index will be considered as an index of oxygen delivery (assuming hemoglobin and pulmonary gas-exchange in normal ranges).
PRIMARY OUTCOME
The primary outcome will be a significant difference in the time-weighted average (TWA) of MAP < 65mmHg between the two groups. TWA calculation will be made according to the following formula: TWA = (depth of hypotension (mmHg) below a MAP of 65 mmHg × time in minutes spent below a MAP of 65 mmHg) / (total duration of surgery expressed in minutes).
SAMPLE SIZE CALCULATION \& STATISTICAL ANALYSIS
In line with the published literature, the investigators hypothesized that the HPI software-based strategy could reduce the mean TWA-MAP < 65mmHg by approximately 50%. For sample size calculation, the investigators considered 1 mmHg as the reference value of TWA-MAP < 65mmHg for patients managed with the FlotracTM system (unpublished raw data extrapolated from a cohort of 10 patients). To detect a significant difference in TWA-MAP <65 mmHg between the HPI and the Flotrac group of 0.5 mmHg with a standard deviation of 0.4 mmHg, the study requires a sample size of 14 cases for each group to achieve a 90% power and 5% significance level (two-tailed). The sample size calculation was performed with Statulator statistical calculator. Due to the observational nature of the study, the protocol plans to enroll more patients if available.
Descriptive statistics of baseline demographic and clinical data will be carried out as follows: continuous variables will be expressed as mean ± SD or median and IQR depending on the respective normality of distribution. Categorical variables will be expressed as absolute value and percentage.
Statistical differences in primary and secondary outcomes will be analyzed using unpaired Student's t-test or Mann-Whitney test, depending on the respective normality of distribution. Chi-square or Fisher exact tests will be used for the comparison of discrete variables. A multivariate analysis will be conducted utilizing regression models. The P critical value will be set at 0.05. Statistical analysis will be performed with Stata and SPSS softwares. Graphs will be drawn with Prism Graphpad software.
- Being tested
- Hypotension Predictive Index
- Keywords
- hypotension, perioperative, complications, hemodynamic
- Medical subject headings
- Hypotension
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Hypotension Predictive IndexDevice
Introduction of Hypotension Predictive index and transition from a reactive to a proactive approach of intraoperative hypotension treatment.
| Study group | Role | What they receive |
|---|---|---|
| FloTrac | Subject received standard advanced hemodynamic monitoring. Hypotensive episodes were treated using a reactive approach. | |
| HPI | Subject were monitored using the hypotension predictive index coupled with standard advanced hemodynamic monitoring. Hypotensive episodes were treated using a proactive approach. Receives: Device: Hypotension Predictive Index |
What is being measured
The primary outcome is the main question the study is designed to answer.
Time-weighted average of Mean Arterial Pressure < 65mmHg
Area under the threshold of MAP 65mmHg normalized for the total duration of surgery in minutes
Measured: intraoperative
Secondary outcomes (11)
Average intraoperative Mean Arterial Pressure
Mean intraoperative MAP
Measured: intraoperative
Frequency of hypotensive events
Number of hypotensive events (MAP < 65mmHg for more than 1 min) per hour of surgery
Measured: intraoperative
Average absolute time spent during Mean Arterial Pressure < 65mmHg
Time spent in hypotension (MAP < 65mmHg for more than 1 min)
Measured: intraoperative
Time-weighted average of Mean Arterial Pressure < 55mmHg
Area under the threshold of MAP 55mmHg normalized for the total duration of surgery in minutes
Measured: intraoperative
Time-weighted average of Mean Arterial Pressure > 100mmHg
Area above the threshold of MAP 100mmHg normalized for the total duration of surgery in minutes
Measured: intraoperative
Frequency of Stroke Volume Index < 35ml/m2 events
Number of SVI < 35ml/m2 events (SVI < 35ml/m2 for more than 1 min) per hour
Measured: intraoperative
Average absolute time during Stroke Volume Index < 35ml/m2
Time spent in SVI < 35ml/m2 events (SVI < 35ml/m2 for more than 1 min)
Measured: intraoperative
Average generalized real variability of Mean Arterial Pressure
Sum of the absolute value of all changes across Mean Arterial Pressure measurements divided by total surgical time
Measured: intraoperative
Postoperative ICU admission frequency
Postoperative ICU admission frequency
Measured: Up to 30 days after operation
Length of hospital stay
Length of hospital stay
Measured: Up to 30 days after operation
Postoperative complication rate
Incidence of complications and burden according to Calvin-Dindo classification
Measured: Up to 30 days after operation
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Oct 2023
- Study start23 May 2023
- Primary completion1 Dec 2023
- Study completion31 Jan 2024
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (11)Papers the sponsor has linked to this study.
- Other trials for Hypotension During SurgeryStudies of the same condition, open and under way.
- More trials run by Istituto Clinico HumanitasThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 48 participants (actual)
Sponsor and investigators
- Lead sponsor
- Istituto Clinico Humanitas
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Federico Piccioni, Istituto Clinico Humanitas
- Investigators
- Federico Piccioni, Principal investigator, Istituto Clinico Humanitas
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06097052
- Sponsor's protocol ID
- EHPI-Pan-15/23
- Acronym
- EHPI-Pan
- Status last verified
- Mar 2024
- First submitted
- 17 Oct 2023
- Last updated
- 6 Mar 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- Yes
Publications
Augustin T, Burstein MD, Schneider EB, Morris-Stiff G, Wey J, Chalikonda S, Walsh RM. Frailty predicts risk of life-threatening complications and mortality after pancreatic resections. Surgery. 2016 Oct;160(4):987-996. doi: 10.1016/j.surg.2016.07.010. Epub 2016 Aug 18.
PubMed 27545992Frassanito L, Giuri PP, Vassalli F, Piersanti A, Longo A, Zanfini BA, Catarci S, Fagotti A, Scambia G, Draisci G. Hypotension Prediction Index with non-invasive continuous arterial pressure waveforms (ClearSight): clinical performance in Gynaecologic Oncologic Surgery. J Clin Monit Comput. 2022 Oct;36(5):1325-1332. doi: 10.1007/s10877-021-00763-4. Epub 2021 Oct 7.
PubMed 34618291Futier 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.
PubMed 28973220Hatib 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.
PubMed 29894315Pecorelli N, Capretti G, Sandini M, Damascelli A, Cristel G, De Cobelli F, Gianotti L, Zerbi A, Braga M. Impact of Sarcopenic Obesity on Failure to Rescue from Major Complications Following Pancreaticoduodenectomy for Cancer: Results from a Multicenter Study. Ann Surg Oncol. 2018 Jan;25(1):308-317. doi: 10.1245/s10434-017-6216-5. Epub 2017 Nov 7.
PubMed 29116490Salmasi 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.
PubMed 27792044Schneck 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.
PubMed 31784852Solares GJ, Garcia D, Monge Garcia MI, Crespo C, Rabago JL, Iglesias F, Larraz E, Zubizarreta I, Rabanal JM. Real-world outcomes of the hypotension prediction index in the management of intraoperative hypotension during non-cardiac surgery: a retrospective clinical study. J Clin Monit Comput. 2023 Feb;37(1):211-220. doi: 10.1007/s10877-022-00881-7. Epub 2022 Jun 2.
PubMed 35653007van der Ven WH, Veelo DP, Wijnberge M, van der Ster BJP, Vlaar APJ, Geerts BF. One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making. Surgery. 2021 Jun;169(6):1300-1303. doi: 10.1016/j.surg.2020.09.041. Epub 2020 Dec 11.
PubMed 33309616Wesselink 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.
PubMed 30236233Wijnberge 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.
PubMed 32065827
Study at a glance
From the registry record, last updated by the sponsor on 6 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Effect of Hypotension Predictive Index on Intraoperative Hypotension Events and Duration During Pancreatic Surgery. A Retrospective Pre-post Observational Study.
- ClinicalTrials.gov ID
- NCT06097052
- Acronym / sponsor ID
- EHPI-Pan / EHPI-Pan-15/23
- Keywords
- hypotension, perioperative, complications, hemodynamic
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 48 participants (actual)
- Lead sponsor
- Istituto Clinico HumanitasUniversity, hospital or other
- Study start
- 23 May 2023 (actual)
- Primary completion
- 1 Dec 2023 (actual)
- Study completion
- 31 Jan 2024 (actual)
- First posted
- 24 Oct 2023 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Intraoperative hypotension (IOH) is a sudden clinical phenomenon that occurs frequently during general anesthesia. Prevention of IOH has been linked to reduced postoperative organ damage and decreased incidence of perioperative complications. Oncological patients with reduced preoperative physiological reserves may be especially vulnerable to IOH deleterious effects, especially when exposed to prolonged surgical time increase, as it is the case for patients undergoing pancreatic surgery.
The investigators aim to study introduction of a new technology able to predict hypotensive events (Hypotension Predictive Index, HPI Acumen™) in terms of its effects on IOH occurrence and burden in patients undergoing pancreatic surgery. The investigators will enroll patients before and after the introduction of HPI monitoring. Further, differences in postoperative outcomes and perioperative complications between before and after populations will be investigated.
Detailed description
Intraoperative hypotension (IOH) is a relatively common event during surgery, occurring suddenly and often without any warning sign. Predicting IOH would help clinicians to set up a rapid response, reducing the number of hypotensive events and overall time of hypotension.
Historically the management of IOH has been reactive, despite the introduction of advanced arterial waveform analysis systems providing a number of cardiovascular parameters (arterial pressure, cardiac output, dynamic indices) which allow advanced intraoperative hemodynamic monitoring (FloTrac™, Edwards Lifesciences Corp., Irvine, USA). This changed when continuous blood pressure wave static and dynamic features extraction combined with Machine-Learning approach proved informative in identifying specific signatures associated with impending exhaustion of compensatory mechanisms. By fitting these features in a mathematical model it became available an easy-to-interpret Hypotension Predictive Index (Acumen™ HPI - Edwards Lifesciences, Irvine, CA), which can predict IOH up to 15 minutes prior to the clinical event. The HPI is expressed in a range from 0 to 100, the higher the number, the higher the probability and the shorter the time of occurrence of the hypotensive event. Therefore, combining arterial waveform analysis and HPI may provide timely prediction and goal-directed treatment plans based on the specific mechanism underlying IOH, such as relative hypovolemia, temporary vasoplegia or decreased inotropism.
Several studies have shown that IOH has a great impact on postoperative outcomes and tight control of blood pressure may be important especially in patients undergoing major surgery. These patients are often frail and bear greater risks of developing organ dysfunction, mainly renal insufficiency and myocardial injury. Futier et al. reported a 25% risk reduction of postoperative organ dysfunction when IOH is properly treated during surgery. Further, prospective studies showed that the use of HPI both decreased the total time of hypotension in non-cardiac surgery and reduced post-operative complications and hospital length-of-stay.
These studies addressed application of HPI in mixed cohorts of the population (orthopedic surgery, neurosurgery, general and vascular surgery, ENT surgery), but the duration and type of surgery are certainly two major factors affecting the occurrence and the severity of IOH. Among non-cardiac operations, major pancreatic surgery is generally complex and long-lasting. In our center roughly 180 patients undergo major pancreatic surgery every year and in our experience these patients are often debilitated and have reduced physiological reserve at the time of surgery. In addition, post-operative complications including bleeding, sepsis, bilio-digestive fistulas, acute kidney injury are common in this setting. For these reasons, the investigators believe that patients undergoing major pancreatic surgery represent an excellent model to evaluate the efficacy of HPI compared to the FloTrac™ alone as they can benefit from advanced hemodynamic monitoring and IOH prediction tools.
The aim of this study is to assess whether patients undergoing pancreatic surgery benefit from early prediction and goal-directed treatment of IOH using the HPI software compared to a goal-directed hemodynamic approach using the FloTrac™ monitoring system. The investigators plan to study the occurrence of IOH with and without the use of HPI in comparison with a FloTrac™ monitoring system. Furthermore, the study aims to evaluate if HPI software inclusion in an intraoperative hemodynamic management protocol leads to improved intraoperative cardiovascular stability and better clinical outcomes. Finally, the investigators want to explore whether the improved clinical experience using HPI predictive model correlates with the degree of IOH by analyzing data from patients managed only with this technology over time.
STUDY DESIGN AND POPULATION
This is a retrospective observational before-and-after study planned to analyze data from about 60 elective patients undergoing major open pancreatic surgery. Only patients that already signed an informed consent including perioperative data utilization for previous ongoing clinical studies will be considered for the analysis.
Continuous blood pressure waveform after the insertion of an arterial line (radial artery was the preferred choice) was monitored in all patients after anesthesia induction. Until March 2022 patients were monitored using the FloTracTM waveform analysis alone, while from April 2022 to present, patients' hemodynamics were managed using the HPI software. The investigators will compare two cohorts (Flotrac group vs. HPI group) to evaluate the impact of the latter technology on IOH. Mean arterial pressure will be defined as the main variable describing the perfusion pressure, while the cardiac index will be considered as an index of oxygen delivery (assuming hemoglobin and pulmonary gas-exchange in normal ranges).
PRIMARY OUTCOME
The primary outcome will be a significant difference in the time-weighted average (TWA) of MAP < 65mmHg between the two groups. TWA calculation will be made according to the following formula: TWA = (depth of hypotension (mmHg) below a MAP of 65 mmHg × time in minutes spent below a MAP of 65 mmHg) / (total duration of surgery expressed in minutes).
SAMPLE SIZE CALCULATION \& STATISTICAL ANALYSIS
In line with the published literature, the investigators hypothesized that the HPI software-based strategy could reduce the mean TWA-MAP < 65mmHg by approximately 50%. For sample size calculation, the investigators considered 1 mmHg as the reference value of TWA-MAP < 65mmHg for patients managed with the FlotracTM system (unpublished raw data extrapolated from a cohort of 10 patients). To detect a significant difference in TWA-MAP <65 mmHg between the HPI and the Flotrac group of 0.5 mmHg with a standard deviation of 0.4 mmHg, the study requires a sample size of 14 cases for each group to achieve a 90% power and 5% significance level (two-tailed). The sample size calculation was performed with Statulator statistical calculator. Due to the observational nature of the study, the protocol plans to enroll more patients if available.
Descriptive statistics of baseline demographic and clinical data will be carried out as follows: continuous variables will be expressed as mean ± SD or median and IQR depending on the respective normality of distribution. Categorical variables will be expressed as absolute value and percentage.
Statistical differences in primary and secondary outcomes will be analyzed using unpaired Student's t-test or Mann-Whitney test, depending on the respective normality of distribution. Chi-square or Fisher exact tests will be used for the comparison of discrete variables. A multivariate analysis will be conducted utilizing regression models. The P critical value will be set at 0.05. Statistical analysis will be performed with Stata and SPSS softwares. Graphs will be drawn with Prism Graphpad software.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| FloTrac | – | –Subject received standard advanced hemodynamic monitoring. Hypotensive episodes were treated using a reactive approach. |
| HPI | – | Device: Hypotension Predictive IndexSubject were monitored using the hypotension predictive index coupled with standard advanced hemodynamic monitoring. Hypotensive episodes were treated using a proactive approach. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Subjects undergoing general anesthesia for elective pancreatic surgery consecutively recruited before and after the introduction of Hypotension Predictive Index technology.
Key inclusion criteria (4 listed)
- Subjects aged 18 years or older.
- Subjects scheduled for major open pancreatic surgery.
- Subjects monitored with FloTrac or HPI invasive arterial blood pressure monitoring.
- Total surgical time > 360min.
Key exclusion criteria (3 listed)
- Subjects aged 90 years or older
- Subjects classified as ASA IV/V/VI
- Subjects undergoing urgent or emergency surgery
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Hypotension Predictive IndexIntroduction of Hypotension Predictive index and transition from a reactive to a proactive approach of intraoperative hypotension treatment. | Device | HPI |
Primary outcome
Time-weighted average of Mean Arterial Pressure < 65mmHg
Time frame: intraoperative
Area under the threshold of MAP 65mmHg normalized for the total duration of surgery in minutes
11 secondary outcomes
Average intraoperative Mean Arterial Pressure
Time frame: intraoperative
Frequency of hypotensive events
Time frame: intraoperative
Average absolute time spent during Mean Arterial Pressure < 65mmHg
Time frame: intraoperative
Time-weighted average of Mean Arterial Pressure < 55mmHg
Time frame: intraoperative
Time-weighted average of Mean Arterial Pressure > 100mmHg
Time frame: intraoperative
Frequency of Stroke Volume Index < 35ml/m2 events
Time frame: intraoperative
Average absolute time during Stroke Volume Index < 35ml/m2
Time frame: intraoperative
Average generalized real variability of Mean Arterial Pressure
Time frame: intraoperative
Postoperative ICU admission frequency
Time frame: Up to 30 days after operation
Length of hospital stay
Time frame: Up to 30 days after operation
Postoperative complication rate
Time frame: Up to 30 days after operation
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Mar 2024.
- Background: PubMed 27545992Augustin T, Burstein MD, Schneider EB, Morris-Stiff G, Wey J, Chalikonda S, Walsh RM. Frailty predicts risk of life-threatening complications and mortality after pancreatic resections. Surgery. 2016 Oct;160(4):987-996. doi: 10.1016/j.surg.2016.07.010. Epub 2016 Aug 18.
- Background: PubMed 34618291Frassanito L, Giuri PP, Vassalli F, Piersanti A, Longo A, Zanfini BA, Catarci S, Fagotti A, Scambia G, Draisci G. Hypotension Prediction Index with non-invasive continuous arterial pressure waveforms (ClearSight): clinical performance in Gynaecologic Oncologic Surgery. J Clin Monit Comput. 2022 Oct;36(5):1325-1332. doi: 10.1007/s10877-021-00763-4. Epub 2021 Oct 7.
- Background: PubMed 28973220Futier 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.
- Background: PubMed 29894315Hatib 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.
- Background: PubMed 29116490Pecorelli N, Capretti G, Sandini M, Damascelli A, Cristel G, De Cobelli F, Gianotti L, Zerbi A, Braga M. Impact of Sarcopenic Obesity on Failure to Rescue from Major Complications Following Pancreaticoduodenectomy for Cancer: Results from a Multicenter Study. Ann Surg Oncol. 2018 Jan;25(1):308-317. doi: 10.1245/s10434-017-6216-5. Epub 2017 Nov 7.
- Background: PubMed 27792044Salmasi 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.
- Background: PubMed 31784852Schneck 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.
- Background: PubMed 35653007Solares GJ, Garcia D, Monge Garcia MI, Crespo C, Rabago JL, Iglesias F, Larraz E, Zubizarreta I, Rabanal JM. Real-world outcomes of the hypotension prediction index in the management of intraoperative hypotension during non-cardiac surgery: a retrospective clinical study. J Clin Monit Comput. 2023 Feb;37(1):211-220. doi: 10.1007/s10877-022-00881-7. Epub 2022 Jun 2.
- Background: PubMed 33309616van der Ven WH, Veelo DP, Wijnberge M, van der Ster BJP, Vlaar APJ, Geerts BF. One of the first validations of an artificial intelligence algorithm for clinical use: The impact on intraoperative hypotension prediction and clinical decision-making. Surgery. 2021 Jun;169(6):1300-1303. doi: 10.1016/j.surg.2020.09.041. Epub 2020 Dec 11.
- Background: PubMed 30236233Wesselink 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.
- Background: PubMed 32065827Wijnberge 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Federico Piccioni principal investigator
Istituto Clinico Humanitas
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Hypotension During Surgery and Perioperative Complication, run by Istituto Clinico Humanitas at 1 site in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 6 Mar 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Time-weighted average of Mean Arterial Pressure < 65mmHg (time frame: intraoperative). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06097052, which also lists 11 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 6 Mar 2024.