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Metabolic Subtypes of Non-Alcoholic Fatty Liver Disease

NCT05560997 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 1000

Last updated 2024-06-21

No results posted yet for this study

Summary

The purpose of this study was to use machine learning to explore a more precise classification of NAFLD subgroups towards informing individualized therapy.

Conditions

  • Non-Alcoholic Fatty Liver Disease
  • Machine Learning

Interventions

DIAGNOSTIC_TEST

10-year ASCVD risk estimation

High CVD risk was defined as a history of CVD or a 10-year ASCVD risk ≥10%. The 10-year ASCVD risk estimation was carried out according to 2016 Chinese guidelines for the management of dyslipidemia in adults.

Sponsors & Collaborators

  • Yan Bi

    lead OTHER

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2016-01-05
Primary Completion
2024-10-30
Completion
2025-06-01

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT05560997 on ClinicalTrials.gov