Hypotension Predictive Index Effect on Intraoperative Hypotension During Pancreatic Surgery. (EHPI-Pan)

March 4, 2024 updated by: Federico Piccioni, Istituto Clinico Humanitas

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.

Study Overview

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 Type

Observational

Enrollment (Actual)

48

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Lombardia
      • Rozzano, Lombardia, Italy, 20089
        • Istituto Clinico Humanitas

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

Subjects undergoing general anesthesia for elective pancreatic surgery consecutively recruited before and after the introduction of Hypotension Predictive Index technology.

Description

Inclusion Criteria:

  • 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.

Exclusion Criteria:

  • Subjects aged 90 years or older
  • Subjects classified as ASA IV/V/VI
  • Subjects undergoing urgent or emergency surgery

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
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.
Introduction of Hypotension Predictive index and transition from a reactive to a proactive approach of intraoperative hypotension treatment.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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
intraoperative

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Average intraoperative Mean Arterial Pressure
Time Frame: intraoperative
Mean intraoperative MAP
intraoperative
Frequency of hypotensive events
Time Frame: intraoperative
Number of hypotensive events (MAP < 65mmHg for more than 1 min) per hour of surgery
intraoperative
Average absolute time spent during Mean Arterial Pressure < 65mmHg
Time Frame: intraoperative
Time spent in hypotension (MAP < 65mmHg for more than 1 min)
intraoperative
Time-weighted average of Mean Arterial Pressure < 55mmHg
Time Frame: intraoperative
Area under the threshold of MAP 55mmHg normalized for the total duration of surgery in minutes
intraoperative
Time-weighted average of Mean Arterial Pressure > 100mmHg
Time Frame: intraoperative
Area above the threshold of MAP 100mmHg normalized for the total duration of surgery in minutes
intraoperative
Frequency of Stroke Volume Index < 35ml/m2 events
Time Frame: intraoperative
Number of SVI < 35ml/m2 events (SVI < 35ml/m2 for more than 1 min) per hour
intraoperative
Average absolute time during Stroke Volume Index < 35ml/m2
Time Frame: intraoperative
Time spent in SVI < 35ml/m2 events (SVI < 35ml/m2 for more than 1 min)
intraoperative
Average generalized real variability of Mean Arterial Pressure
Time Frame: intraoperative
Sum of the absolute value of all changes across Mean Arterial Pressure measurements divided by total surgical time
intraoperative
Postoperative ICU admission frequency
Time Frame: Up to 30 days after operation
Postoperative ICU admission frequency
Up to 30 days after operation
Length of hospital stay
Time Frame: Up to 30 days after operation
Length of hospital stay
Up to 30 days after operation
Postoperative complication rate
Time Frame: Up to 30 days after operation
Incidence of complications and burden according to Calvin-Dindo classification
Up to 30 days after operation

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Investigators

  • Principal Investigator: Federico Piccioni, Istituto Clinico Humanitas

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

May 23, 2023

Primary Completion (Actual)

December 1, 2023

Study Completion (Actual)

January 31, 2024

Study Registration Dates

First Submitted

October 17, 2023

First Submitted That Met QC Criteria

October 20, 2023

First Posted (Actual)

October 24, 2023

Study Record Updates

Last Update Posted (Actual)

March 6, 2024

Last Update Submitted That Met QC Criteria

March 4, 2024

Last Verified

March 1, 2024

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • EHPI-Pan-15/23

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

Yes

product manufactured in and exported from the U.S.

Yes

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