Clinical trial NCT05992506: Electroencephalographic Biomarker to Predict Postoperative Delirium
Official title: Electroencephalographic Biomarker to Predict the Development of Postoperative Delirium: a Protocol of an Observational Study in a Cohort of Patients From Five Centers
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Postoperative Delirium
Keywords: EEG
Postoperative Delirium
Risk Assessment
Anesthesia
Lead sponsor: University of Chile
Sponsor class: OTHER
Collaborators: name: Instituto Nacional del Cancer, Chile
name: Pontificia Universidad Catolica de Chile
name: Hospital Base San Jose Osorno
name: Clinica Santa Maria
First posted: 2023-08-15
Enrollment: 264
Sex: ALL
Minimum age (years): 60
Maximum age (years): 100
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients at risk of developing POD will be evaluated in the pre and postoperative period for cognitive dysfunction and the appearance of POD. In the intraoperative period, an EEG-based monitorization will be performed using a SedLine (Masimo, CA) Monitor.

Brief 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.

Detailed 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.

Eligibility criteria: 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

Primary outcomes:
measure: Postoperative Delirium
timeFrame: First 3 days after surgery
Secondary outcomes:
measure: Death
timeFrame: 30 days after surgery
measure: Delirium Severity
timeFrame: First 3 days after surgery
measure: Delirium Duration
timeFrame: First 3 days after surgery
measure: Need for Mechanical Ventilation
timeFrame: First 3 days after surgery
measure: Reintervention
timeFrame: First 3 days after surgery
measure: Unanticipated ICU hospitalization
timeFrame: First 3 days after surgery
Other outcomes:
Locations:
city: Santiago
country: Chile
facility: Hospital Clinico Universidad de Chile
city: Santiago
country: Chile
facility: Instituto Nacional del Cancer
Study officials:
References:
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 available.
citation: 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.2019.00056. eCollection 2019.
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;12(4):e054023. doi: 10.1136/bmjopen-2021-054023.