Objective Measurement of Pain in Individuals With Cognitive Deterioration Utilizing Electroencephalography

Exploring Objective Pain Assessment in Individuals With Cognitive Deterioration: Electroencephalographic Markers and Machine Learning Analysis

This research addresses the challenge of pain assessment in individuals with cognitive deterioration (CD), a common aspect of aging and various neurological conditions. Due to difficulties in self-reporting, especially in severe cases, accurate pain diagnosis and management are hindered. The study explores the use of electroencephalography (EEG) and machine learning techniques to objectively measure pain in CD patients. Utilizing a BIS device, the research aims to identify EEG markers associated with pain, comparing them with an objective PANAID scale. The study targets patients in surgical departments, providing valuable insights into enhancing pain assessment for those unable to express pain through traditional subjective scales.

Study Overview

• Status: Not yet recruiting
• Conditions: Cognitive Deterioration
• Intervention / Treatment: Device: BIS Quantitative EEG

Detailed Description

Cognitive deterioration (CD) may develop during the aging process and is a characteristic feature of various neurological and neurodegenerative diseases. Individuals with CD often face significant, prolonged, and intricate healthcare needs, frequently involving pain. However, effectively communicating pain characteristics becomes a challenge for individuals with CD, presenting a substantial obstacle to the accurate diagnosis and treatment of pain. CD affects various patient groups, although current data predominantly focus on dementia patients, revealing pain prevalence ranging from 40% to over 80%, depending on the context .

Due to its subjective nature, pain assessment relies predominantly on self-reporting. Individuals with CD often encounter difficulties in verbally expressing their pain due to limited intellectual and communicative abilities. Even when verbal skills are present, they may not guarantee valid pain reports. Consequently, pain assessment poses challenges for individuals with CD, particularly those with severe CD, elevating the risk of delayed or inaccurate pain diagnoses. Self-assessments or patient-reported measures are considered the gold standard in clinical pain assessment.

For individuals with compromised cognitive or linguistic abilities, or when self-assessment is impractical or invalid, behavioral measures can be employed. These tools capture facial expressions, vocalizations, or body movements as indicators of pain from an external observer's perspective, such as nurses, physicians, or healthcare providers. However, these parameters rely entirely on others being attentive to non-verbal pain signals, presenting a challenge as trained observers must reliably distinguish pain from various other facial and bodily expressions.

Developing objective measures reflecting the presence of painful states appears crucial to improving pain management in various clinical situations. In this regard, electroencephalographic (EEG) activation has been described as a cortical correlate of pain processing. Encouraging results have led researchers to consider increased gamma band activity as a potential indicator of pain presence applicable in clinical conditions.

This study employs a commonly used BIS device in hospitals to objectively measure pain levels in subjects with cognitive deterioration. Quantitative electroencephalography (qEEG) data will be obtained, and machine learning techniques will be applied for data analysis. Thirty patients experiencing cognitive decline, admitted to the general surgery and orthopedics departments at Volterra Hospital for significant surgical interventions, will be enrolled in the study. Concurrently, pain will be assessed using an objective PANAID scale and, if applicable, the NRS. The study aims to identify electroencephalographic markers of pain through machine learning techniques and establish correlations with pain levels obtained from the use of both subjective and objective scales

• Study Type: Observational
• Enrollment (Estimated): 30

Contacts and Locations

• Study Contact: Name: Alessandro Tani, MD; Phone Number: 039 058891706; Email: alessandro.tani113@gmail.com

Study Locations

• Italy
  • Pisa
    • Volterra, Pisa, Italy, 56048
      • Santa Maria Maddalena Hospital

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

Patients admitted to general surgery and orthopedics, departments at Volterra Hospital with cognitive deterioration, undergoing major surgery.

Description

Inclusion Criteria:

• Subjects exhibiting at least moderate cognitive impairment as assessed by the Pfeiffer scale.

Exclusion Criteria:

• lack of consent

Study Plan

How is the study designed?

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Utilization of the BIS device for the objective quantification of pain levels in patients with cognitive deterioration.	The outlined study aims to investigate and address the challenges associated with pain assessment in individuals with cognitive deterioration (CD), particularly focusing on hospidalized subjects admitted to general surgery, and orthopedics . The primary objective is to employ a commonly used BIS device in hospitals for the objective measurement of pain levels in these patients.	20 minutes

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Correlation between the identified electroencephalographic markers and a specific behavioral indicators of pain	The study may also investigate the correlation between the identified electroencephalographic markers and specific behavioral indicators of pain. By examining the concordance between EEG data and observable behaviors captured by external observers, such as nurses or physicians, the research could provide additional insights into the validity and comprehensiveness of EEG-based pain assessments.	20 minutes

Collaborators and Investigators

• Sponsor: Azienda USL Toscana Nord Ovest
• Collaborators: Istituto per la Ricerca e l'Innovazione Biomedica
• Investigators: Principal Investigator: Alessandro Tani, MD, Azienda Usl Toscana Nord Ovest

Publications and helpful links

General Publications

• Kimura A, Mitsukura Y, Oya A, Matsumoto M, Nakamura M, Kanaji A, Miyamoto T. Objective characterization of hip pain levels during walking by combining quantitative electroencephalography with machine learning. Sci Rep. 2021 Feb 4;11(1):3192. doi: 10.1038/s41598-021-82696-1.

Study record dates

Study Major Dates

• Study Start (Estimated): April 15, 2024
• Primary Completion (Estimated): December 1, 2024
• Study Completion (Estimated): January 15, 2025

Study Registration Dates

• First Submitted: February 3, 2024
• First Submitted That Met QC Criteria: February 3, 2024
• First Posted (Actual): February 13, 2024

Study Record Updates

• Last Update Posted (Actual): March 26, 2024
• Last Update Submitted That Met QC Criteria: March 24, 2024
• Last Verified: March 1, 2024

More Information

Terms related to this study

• Keywords: Pain assessment; Quantitative electroencephalography; Cognitive deterioration
• Additional Relevant MeSH Terms: Mental Disorders; Neurocognitive Disorders; Cognition Disorders
• Other Study ID Numbers: AUSLNordOvest 2024

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No