Development of a Scoring and Prediction Model for Weaning... | NCT06751693

Studies
Development of a Scoring and Prediction Model for Weaning Success in ARDS Patients Using Ventilation Parameters Combined with Artificial Intelligence and Deep Learning Techniques

NCT06751693

Sponsor

Bakirkoy Dr. Sadi Konuk Research and Training Hospital

Status

Completed

Last Update Posted

Dec 30, 2024Actual

Enrollment

25,000Actual

Phase

Not provided

Conditions

Deep Learning
Artificial Intelegence
ARDS (Acute Respiratory Distress Syndrome)

Interventions

Not provided

Countries

Turkey (Türkiye)

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

Status Module

Record Verification Date

Dec 2024

Overall Recruitment Status or Expanded Access Status

Completed

Last Known Status

Not provided

Delayed Posting

Not provided

Why Stopped

Not provided

Expanded Access Info

Start Date

Dec 10, 2024Actual

Primary Completion Date

Dec 24, 2024Actual

Completion Date

Dec 24, 2024Actual

First Submitted Date

Dec 11, 2024

First Submission Date that Met QC Criteria

Dec 26, 2024

First Posted Date

Dec 30, 2024Actual

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

Dec 26, 2024

Last Update Posted Date

Dec 30, 2024Actual

Oversight Module

Has Data Monitoring Committee (DMC)

Is FDA Regulated Drug

Is FDA Regulated Device

Is Unapproved Device

Not provided

Pediatric Postmarket Surveillance of a Device Product

Not provided

Product Exported from US

FDAAA801 Violation

Not provided

Description Module

Brief Summary

This study aims to develop an AI-supported scoring model to optimize the weaning processes of ARDS patients from mechanical ventilation. Retrospective analysis will be conducted on the data of 25,000 patients, focusing on ventilator parameters and hemodynamic variables. The model will be designed to contribute to clinical decision support systems.

Detailed Description

The aim of this study is to develop an artificial intelligence and deep learning-supported scoring system using ventilator parameters obtained during the mechanical ventilation process in patients diagnosed with ARDS. This system seeks to predict and optimize the weaning process, facilitating successful liberation from mechanical ventilation.

In this context, our study will analyze data from 25,000 patients obtained from the Metavision system. From this data pool, ARDS patients will be filtered and divided into two groups: those successfully weaned from mechanical ventilation (weaned) and those who were not (non-weaned). The ventilator parameters of both groups, including oxygenation indices, driving pressure, and total mechanical power, will be examined in detail.

The collected data will be analyzed using artificial intelligence and deep learning algorithms to develop a scoring system capable of predicting patients' weaning processes. This system is designed to guide clinicians in patient management and enhance the success of weaning procedures.

The results of this study aim to contribute to more efficient and safer management of the weaning process for ARDS patients. Furthermore, the implementation of AI-supported scoring systems in intensive care units is expected to promote widespread adoption and improve the quality of patient care.

Design Module

Study Type

Observational

Number of References to an Expanded Access Study

Not provided

Expanded Access Types

Not provided

Patient Registry

Target Follow-Up Duration

Not provided

Phases

Not provided

Interventional Study Design

Allocation

Not provided

Intervention Model

Biospecimen

No data available

No data is available for this block.

Enrollment

25,000Actual

Arms/Interventions Module

Arm Groups

Label	Type	Description	Intervention Names
Weaned		Those successfully weaned from mechanical ventilation
Non-weaned		Those who not weaned from mechanical ventilation

Interventions

Not provided

Outcomes Module

Primary Outcomes

Measure	Description	Time Frame
Successful Weaning	The primary outcome of this study will be the successful weaning from mechanical ventilation.	48 hours

Secondary Outcomes

Measure	Description	Time Frame
Mechanical Ventilatory Parameters	Determining the impact of mechanical power on patient outcomes.	48 hours

Other Outcomes

Not provided

Eligibility Module

Eligibility Criteria

Inclusion Criteria:

ARDS diagnosis
Aged 18 years and older
Intubated and followed by Mechanical ventilation
Admission on Intensive care unit
Complete data on clinical support and desicion system

Exclusion Criteria:

Missing data
Under 18 years of age
Followed by non-ARDS conditions
Terminal status

Accepts Healthy Volunteers

Sex

All

Sex/Gender Based

Not provided

Sex/Gender Description

Not provided

Minimum Age

18 Years

Maximum Age

Not provided

Standard Ages

AdultOlder Adult

Study Population

Intubated patients which diagnosed with ARDS and followed up in the ICU for more than 48 hours.

Sampling Method

Non-Probability Sample

Contacts/Locations Module

Central Contacts

Not provided

Overall Officials

Name	Affiliation	Role
Zafer Cukurova, M.D	Bakirkoy Dr. Sadi Konuk Research and Training Hospital	Study Chair

Locations

Facility	Status	City	State	ZIP	Country	Contacts
Bakirkoy Dr Sadi Konuk Research and Training Hospital		Istanbul			Turkey (Türkiye)

IPD Sharing Statement Module

Plan to Share IPD

Description

Not provided

Types

Not provided

Time Frame

Not provided

Access Criteria

Not provided

URL

Not provided

Derived Section

Miscellaneous Info Module

Version Holder

Jul 10, 2026

Removed Countries

Not provided

Submission Tracking

No data available

No data is available for this block.

Condition Browse Module

MeSH Terms

Intervention Browse Module

No data available

No data is available for this block.

ID	Term
D055370	Lung Injury
D008171	Lung Diseases
D012140	Respiratory Tract Diseases