FindTrial
Sign In

Development of artificial intelligence model for the prediction of total days of requirement of artificial breathing machine support in critically ill patients admitted to a tertiary care hospital of india.

Duration of mechanical ventilation prediction in critically ill patients: Development and validation of an AI model

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
CTRI
Registry ID
CTRI/2023/10/058972
Enrollment
2200
Registered
2023-10-20
Start date
Unknown
Completion date
Unknown
Last updated
2024-06-24

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Health Condition 1: Z518- Encounter for other specified aftercare

Interventions

Intervention1: NOT APPLICABLE: NOT APPLICABLE

Sponsors

AIIMS
Lead Sponsor

Eligibility

Inclusion criteria

Inclusion criteria: Derivation and Validation Cohort Inclusion: We will include all critically ill adult patients, who were requiring mechanical ventilation at the time of ICU admission.

Exclusion criteria

Exclusion criteria: Derivation cohort Exclusion: 1. Patients with age 2. Patients on home ventilation 3. Extubation planned on the day of prediction. 4. Patients advised imminent withdrawal of care. Validation Cohort Exclusion: 1. Patients with age 2. Patients on home ventilation 3. Extubation planned on the day of prediction. 4. Patients advised imminent withdrawal of care. 5. Tracheostamised patients.

Design outcomes

Primary

MeasureTime frame
Primary objective: Development and validation of an AI model, able to predict the Duration of mechanical ventilation incritically ill patients admitted to surgical and medical intensive care units. Timepoint: 60DAYS—

Secondary

MeasureTime frame
Secondary Objectives: 1. Extract the variables that will be showing a high contribution to predicting the Duration of mechanical ventilation. 2. Selection of Variables for the development of the AI model 3. Development of AImodel from selected variables. 4. Validation of the developed AImodel. 5. Determining the predictive accuracy of the algorithm. Timepoint: 24HOURS OF ICU ADMISSION—

Countries

India

Contacts

Public ContactMUKKELLI VINAY GANDHI

AIIMS

k.punit@yahoo.com9873106516

Outcome results

None listed

Source: CTRI (via WHO ICTRP) · Data processed: Feb 4, 2026