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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05992506
Other study ID # IT21I0041
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date September 1, 2023
Est. completion date June 30, 2026

Study information

Verified date August 2023
Source University of Chile
Contact Jose I Egana, MD, PhD
Phone +56 2 2978 8209
Email jiegana@uchile.cl
Is FDA regulated No
Health authority
Study type Observational [Patient Registry]

Clinical Trial Summary

Acute post-operatory cognitive dysfunction states are one of the most important complications in older patients that underwent surgery. Among them postoperative delirium (POD) is the the most studied. Patients who develop delirium have poorer long-term outcomes, such as longer length of hospital stay, institutionalization at discharge, and even higher mortality, and consequently, the human and economic costs significantly increase for the health system. Here the research team will use an observational cohort, investigator blinded in five-center with a primary endpoint to validate intraoperative EEG analysis as a reliable biomarker of postoperative delirium.


Description:

Acute post-operatory cognitive dysfunction states are one of the most frequent complications in older patients after surgery, being POD the most important. Previous studies have shown than the incidence of POD in older patients range between 10-50%. Patients who develop POD have poorer long-term outcomes, such as longer length of hospital stay, institutionalization at discharge, and even higher mortality. Consequently, the human and economic costs associated to POD represents an important issue for health systems worldwide. A key element to diminish POD and its burden on healthcare is early diagnostic. Current risk assessment tools are centered on clinical approaches based on cognitive tests (i.e., MoCA) and/or prediction models that uses patients' clinical variables (i.e., DELPHI score). We have developed a strategy that uses intraoperative EEG features as building blocks for a new POD risk assessment predictive model. This system, called PEUMA, uses data obtained from 95 patients from a previous study (NCT04214496). This will be a multicenter (five-centers), observational study and its primary outcome will be PEUMA's ability to predict POD. To calculate the sample size, the methodology described by Riley et al was used. This method is specially designed for clinical prediction models. Such a tool is available online (https://mvansmeden.shinyapps.io/BeyondEPV/). The parameters used were the following: - Number of predictor candidates: 4 - Fraction of events: 0.22. 22% was used because it is the incidence of POD in the analysis of the preliminary data of the first stage and these are in the reporting range common worldwide. - Estimation error of the classifier: 0.06. The authors suggest prediction errors small when evaluating binary outcomes (Yes POD/No POD) The calculation indicates a sample size of 240 patients. Considering a loss of 10% (in the preliminary results of the first stage the loss was 8%), the sample size is 264 patients.


Recruitment information / eligibility

Status Recruiting
Enrollment 264
Est. completion date June 30, 2026
Est. primary completion date December 31, 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 60 Years to 100 Years
Eligibility Inclusion Criteria: - Age = 60 years old - Scheduled for high-risk elective surgery - Need for at least 3 days of hospital stay after surgery - Surgery performed under general anesthesia - Written informed consent for participation in the trial Exclusion Criteria: - Patients with preoperative delirium or dementia - Patients using neuroleptics drug during the past 6 months - Patients with a history of encephalopathy, psychosis, stroke or brain trauma with neurologic sequels - The use of ketamine or dexmedetomidine during surgery - Emergency surgery - Mechanical ventilation during the 72 after surgery - Analphabetism - Patients who do not talk Spanish - Patients included in another clinical trial

Study Design


Related Conditions & MeSH terms


Intervention

Diagnostic Test:
POD risk estimation using PEUMA
A software will analyze intraoperative EEG recording for the estimation of a POD Risk Index

Locations

Country Name City State
Chile Hospital Clinico Universidad de Chile Santiago
Chile Instituto Nacional del Cancer Santiago

Sponsors (5)

Lead Sponsor Collaborator
University of Chile Clinica Santa Maria, Hospital Base San Jose Osorno, Instituto Nacional del Cancer, Chile, Pontificia Universidad Catolica de Chile

Country where clinical trial is conducted

Chile, 

References & Publications (3)

Gutierrez R, Egana JI, Saez I, Reyes F, Briceno C, Venegas M, Lavado I, Penna A. Intraoperative Low Alpha Power in the Electroencephalogram Is Associated With Postoperative Subsyndromal Delirium. Front Syst Neurosci. 2019 Oct 18;13:56. doi: 10.3389/fnsys. — View Citation

Riley RD, Ensor J, Snell KIE, Harrell FE Jr, Martin GP, Reitsma JB, Moons KGM, Collins G, van Smeden M. Calculating the sample size required for developing a clinical prediction model. BMJ. 2020 Mar 18;368:m441. doi: 10.1136/bmj.m441. No abstract availabl — View Citation

Wong CK, van Munster BC, Hatseras A, Huis In 't Veld E, van Leeuwen BL, de Rooij SE, Pleijhuis RG. Head-to-head comparison of 14 prediction models for postoperative delirium in elderly non-ICU patients: an external validation study. BMJ Open. 2022 Apr 8;1 — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Postoperative Delirium Incidence of POD in the cohort diagnosed using the Confusion Assessment Method (CAM) twice/day First 3 days after surgery
Secondary Death Number of deceased patients 30 days after surgery
Secondary Delirium Severity Delirium severity assessed by Cognitive Assessment Method - Severity (CAM-S) First 3 days after surgery
Secondary Delirium Duration Duration of delirium during the postoperative period First 3 days after surgery
Secondary Need for Mechanical Ventilation Number of patients that needed mechanical ventilation First 3 days after surgery
Secondary Reintervention Number of patients who required other unanticipated surgery after the primary intervention First 3 days after surgery
Secondary Unanticipated ICU hospitalization Number of patients that needed unanticipated intensive care unit (ICU) care First 3 days after surgery
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