Artificial Neural Network Directed Therapy of Severe Obst... | NCT01286636

Studies
Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea

NCT01286636

Sponsor

State University of New York at Buffalo

Status

Withdrawn

Last Update Posted

Jan 13, 2016Estimated

Enrollment

0Actual

Phase

Phase 3

Conditions

Sleep Apnea

Interventions

computer model
Polysomnogram

Countries

United States

Protocol Section

Identification Module Status Module Sponsor/Collaborators Module Oversight Module Description Module Conditions Module Design Module Arms/Interventions Module Outcomes Module Eligibility Module Contacts/Locations Module References Module IPD Sharing Statement Module

Results Section

Participant Flow Module Baseline Characteristics Module Outcome Measures Module Adverse Events Module More Info Module

Annotation Section

Annotation Module

Document Section

Large Document Module

Derived Section

Miscellaneous Info Module Condition Browse Module Intervention Browse Module

Protocol Section

Identification Module

NCT ID

Results Section

No data available

No data is available for this block.

Annotation Section

No data available

No data is available for this block.

Document Section

No data available

No data is available for this block.

Derived Section

Miscellaneous Info Module

Version Holder

Status Module

Record Verification Date

Jan 2016

Overall Recruitment Status or Expanded Access Status

Withdrawn

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Jan 2011

Primary Completion Date

Mar 2015Actual

Completion Date

Jun 2015Actual

First Submitted Date

Jan 27, 2011

First Submission Date that Met QC Criteria

Jan 28, 2011

First Posted Date

Jan 31, 2011Estimated

Results Waived

Not provided

Results First Submitted Date

Not provided

Results First Submitted that Met QC Criteria

Not provided

Results First Posted Date

Not provided

Certification/Extension (aka Delayed Results) First Submitted Date

Not provided

Certification/Extension First Submitted that Passed QC Review

Not provided

Certification/Extension First Posted Date

Not provided

Last Update Submitted Date

Jan 12, 2016

Last Update Posted Date

Jan 13, 2016Estimated

Name	Class
VA Office of Research and Development	FED

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Not provided

Is FDA Regulated Device

Not provided

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

Not provided

FDAAA801 Violation

Not provided

Description Module

Brief Summary

The investigators have developed a simple, accurate, and a point-of-care, computer-based clinical decision support system (CDSS) not only to detect the presence of sleep apnea but also to predict its severity. The CDSS is based on deploying an artificial neural network (ANN) derived from anthropomorphic and clinical characteristics.

The investigators hypothesize that patients with severe OSA defined as AHI≥30 can be diagnosed with the use of ANN without undergoing a sleep study, and that empiric management with auto-CPAP has similar outcomes to those who undergo a formal sleep study.

Detailed Description

Not provided

Design Module

Study Type

Interventional

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Not provided

Target Follow-Up Duration

Not provided

Phases

Phase 3

Interventional Study Design

Allocation

Biospecimen

No data available

No data is available for this block.

Enrollment

0Actual

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
artificial neural network	Experimental		Other: computer model
Polysomnogram	Active Comparator		Other: Polysomnogram

Interventions

Name	Type	Description	Arm Group Labels	Other Names
computer model	Other	Diagnosis of Sleep apnea and treatment guidance will rely on a computer model prediction.	artificial neural network

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
To demonstrate that using an ANN directed management of OSA is not inferior to PSG directed management of OSA in terms of sleepiness related functional outcome		6 weeks

Secondary Outcomes

Not provided

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

Must be an adult (≥18 years old)
Must have symptoms suggestive of OSA, and be considered for sleep study by the sleep specialist provider.

Exclusion Criteria:

Pregnancy or breast feeding
Patients with severe congestive heart failure (eg, NYHA Class IV, ejection fraction < 35%).
Patients with end-stage renal disease on hemodialysis
Patients with CVA, Parkinson, neuromuscular degenerative disease.
Patient on narcotics.
Patients with severe lung disease requiring oxygen at night and/or during the day.
Patient with predominant insomnia or sleep hygiene problems, and who are not considered for PSG by the sleep specialist.

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

75 Years

Standard Ages

AdultOlder Adult

Study Population

Not provided

Sampling Method

Not provided

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
Ali El-Solh, MD, MPH	State University of New York at Buffalo	Principal Investigator

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Veterans Affairs Medical Center in Buffalo		Buffalo	New York	14215	United States

Condition Browse Module

MeSH Terms

ID	Term
D012891	Sleep Apnea Syndromes

Ancestor Terms

ID	Term
D001049	Apnea
D012120	Respiration Disorders
D012140	Respiratory Tract Diseases
D020919	Sleep Disorders, Intrinsic

Browse Leaves

Not provided

Browse Branches

Not provided