Ignite Creation Date:
2024-05-06 @ 6:54 PM
Last Modification Date:
2024-10-26 @ 2:56 PM
Study NCT ID:
NCT05825261
Status:
RECRUITING
Last Update Posted:
2023-11-24
First Post:
2023-03-09
Brief Title:
Exploring Novel Biomarkers for Emphysema Detection
Sponsor:
Maastricht University
Organization:
Maastricht University
Study Overview
Official Title:
Exploring Novel Biomarkers for Emphysema Detection the ENBED Study
Status:
RECRUITING
Status Verified Date:
2023-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
ENBED
Brief Summary:
The goal of this clinical trial is to evaluate whether voice or capnometry alone or in combination with other non invasive biomarkers can be used to detect emphysema on chest CT-scan in people with chronic obstructive pulmonary disease COPD The main question it aims to answer is
Can a machine-learning based algorithm be developed that can classify the extent of emphysema on chest CT scan from patients with COPD based on voice andor capnometry
Participants will
perform different voice-related tasks
perform capnometry twice beforeafter exercise
perform a light exercise task between tasks 5-sit-to-stand test
undergo one venipuncture
Can a machine-learning based algorithm be developed that can classify the extent of emphysema on chest CT scan from patients with COPD based on voice andor capnometry
Participants will
perform different voice-related tasks
perform capnometry twice beforeafter exercise
perform a light exercise task between tasks 5-sit-to-stand test
undergo one venipuncture
Detailed Description:
This is a cross sectional single center study At the clinic patients with COPD will be invited to perform several voice related tasks paced reading sustained vowels cough quiet breathing and will be instructed to perform capnometry measurements These measurements will be performed before and after a light exercise task 5-STS 5-sit-to-stand test
Clinical characterisation of patients including pulmonary function tests spirometry body plethysmography diffusion capacity and CT scans have been performed in all patients as a part of routine workup in the COPD care pathway Emphysema will be quantified as low attenuation areas with a density below -950 Hounsfield units HU using Syngovia Siemens Erlangen Germany
The primary outcome will fit a simple machine learning classification model eg using logistic regression support vector machines random forests andor decision tree to classify logistic regression model for the outcome of emphysema 25 vs 25 from speech features and capnometry with explanatory variables of speech features Similar classification methods with incremental models using capnography features will be explored Prior to carrying out the above analyses data has to be pre-processed including merging data quality control handling of missing data and feature extraction
Clinical characterisation of patients including pulmonary function tests spirometry body plethysmography diffusion capacity and CT scans have been performed in all patients as a part of routine workup in the COPD care pathway Emphysema will be quantified as low attenuation areas with a density below -950 Hounsfield units HU using Syngovia Siemens Erlangen Germany
The primary outcome will fit a simple machine learning classification model eg using logistic regression support vector machines random forests andor decision tree to classify logistic regression model for the outcome of emphysema 25 vs 25 from speech features and capnometry with explanatory variables of speech features Similar classification methods with incremental models using capnography features will be explored Prior to carrying out the above analyses data has to be pre-processed including merging data quality control handling of missing data and feature extraction
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None