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Machine learning model for predicting and grading malnutrition in critically ill patients

Machine learning model for predicting and grading malnutrition in critically ill patients

Status
Active, not recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200058286
Enrollment
Unknown
Registered
2022-04-04
Start date
2022-03-20
Completion date
Unknown
Last updated
2023-12-19

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

Conditions

Malnutrition

Interventions

case series:None

Sponsors

Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital, the Affiliated Hospital of University of Electronic Science and Technology of China
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Adult ICU patients aged 18 years or older; 2. Expected to stay in ICU for more than 24 hours; 3. Informed patient or family member and signed consent form.

Exclusion criteria

Exclusion criteria: 1. Patients diagnosed with brain death within 24 hours of admission; 2. Pregnant or lactating patients; 3. Patients with mental illness; 4. Patients with cardiopulmonary failure who were treated by ECMO Extracorporeal Membrane Oxygenation; 5. Patients who used renal replacement therapy in their treatment; 6. Those who do not want to accept the survey and quit midway.

Design outcomes

Primary

MeasureTime frame
28-day mortality;Length of stay;Hospitalization expenses;

Countries

China

Contacts

Public ContactXie Caixia
xiecaixia1999@163.com+86 17708130861

Outcome results

None listed

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