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A dynamic prediction model for the optimal intake of energy and protein in sepsis patients based on deep learning

A dynamic prediction model for the optimal intake of energy and protein in sepsis patients based on deep learning

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200056316
Enrollment
Unknown
Registered
2022-02-03
Start date
2022-02-08
Completion date
Unknown
Last updated
2024-09-23

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

Conditions

Sepsis

Interventions

Sepsis patient group receiving nutritional support:None

Sponsors

Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital (SAMSPH)
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1. Adult patients (Age >= 18 years); 2. Definitely diagnosed sepsis patients (according to Sepsis 3.0); 3. APACHE II score >= 10 points; 4. Can continuously tolerate enteral or parenteral nutrition support treatment, and nutrition support treatment time >= 5 days.

Exclusion criteria

Exclusion criteria: 1. Patients with cardiopulmonary failure who used ECMO Extracorporeal Membrane Oxygenation during treatment; 2. Patients who used renal replacement therapy during treatment; 3. Women during pregnancy or lactation; 4. Patients participating in other clinical trials.

Design outcomes

Primary

MeasureTime frame
Intake of energy;Intake of protein;

Countries

China

Contacts

Public ContactZeng Jun

Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital (SAMSPH)

18981838988@qq.com+86 18981838988

Outcome results

None listed

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