Ignite Creation Date:
2024-05-05 @ 6:31 PM
Last Modification Date:
2024-10-26 @ 9:34 AM
Study NCT ID:
NCT00497640
Status:
WITHDRAWN
Last Update Posted:
2020-11-25
First Post:
2007-07-05
Brief Title:
CPAP Titration Using an Artificial Neural Network A Randomized Controlled Study
Sponsor:
State University of New York at Buffalo
Organization:
State University of New York at Buffalo
Study Overview
Official Title:
CPAP Titration Using an Artificial Neural Network A Randomized Controlled Study
Status:
WITHDRAWN
Status Verified Date:
2009-09
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Study was terminated due to lack of interest from subjects and no funding only 1 subject signed consent but did not participate
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
The purpose of the study is to determine the validity of the prediction model in reducing the rate of CPAP titration failure and in achieving a shorter time to optimal pressure
Detailed Description:
In order to derive the most effective pressure CPAP titration is performed in the sleep laboratory during which the pressure is gradually increased until apneas and hypopneas are abolished in all sleep stages and in all body positions The technique is however time consuming and labor intensive Furthermore the duration of the study may not be sufficient to attain this goal because of patients poor ability to sleep in this environment or due to difficulty in attaining an appropriate pressure A predictive algorithm based on demographic anthropometric and polysomnographic data was developed to facilitate the selection of a starting pressure during the overnight titration study Yet the performance of this model was inconsistent when validated by other centers One of the potential reasons for the lack of reproducibility is the complex relation of behavioral processes with nonlinear attributes In areas of complex interactions the artificial neural network ANN has been found to be a more appropriate alternative to linear parametric statistical tools due to its inherent property of seeking information embedded in relations among variables thought to be independent
Comparison time to achieve optimal pressure in the conventional technique versus the intervention model
Comparison time to achieve optimal pressure in the conventional technique versus the intervention model
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
None
Is a FDA Regulated Device?:
None
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None