Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Dyspnea and Cerebral Cortex Activation Measured by fNIRS During Spontaneous Breathing Trial

Assistance Publique - Hôpitaux de Paris · 2024
ClinicalTrials.gov · Datasets · License: Public Domain · 2024
Open Source ↗
critical-caredyspneaelectroencephalographymechanical-ventilation
Background: In Intensive Care Unit (ICU) patients, dyspnea is frequent, severe and exerts unfavorable effects on the short, medium and long term. Detection and quantification rely on the patient's self-reporting abilities. However, more than half of the patients in the ICU are unable to report their sensations. Therefore, the risk is to miss the evaluation of dyspnea and the potential benefits associated with its control. Observational scales, based on physiological and behavioral changes related to dyspnea (such as the Mechanical Ventilation Respiratory Distress Observational Scale MV-RDOS), are promising alternative tools for the detection of dyspnea in non-communicating patients. However, their routine use is not standardized, is not supported by any recommendation, but above all, relies largely on the subjective observation of the facial expression of fear or the abdominal paradox. There is a need for alternatives to the visual analogue dyspnea scale (D-VAS) for the detection of dyspnea in non-communicating intubated patients. Analysis of brain cortical activity modifications during dyspnea could be an alternative to the dyspnea self-report (D-VAS) in the ICU and could improve the performance of observational dyspnea scales. Hypothesis: 1) dyspnea during a spontaneous breathing trial (SBT) is associated with premotor cortex activation identifiable using functional Near-Infrared Spectroscopy (fNIRS); 2) replacing the items "abdominal paradox" or "facial expression of fear" by HbO2 level could improve the performance of the MV-RDOS to predict dyspnea in non-communicating intubated patients; 3) HbO2 level change identified using fNIRS performs well in predicting SBT outcome
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1031428
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive