Can a liver risk score predict early death from routine checkups?
NCT ID NCT07816211
First seen Sep 11, 2026 · Last updated Sep 18, 2026 · Updated 2 times
Summary
Researchers at Anhui Provincial Hospital are checking whether an existing risk model can predict five-year death risk in adults with fatty liver disease. The study uses health examination records from nearly 270,000 people seen between 2018 and 2024, including liver ultrasound, elastography, and lab results. The team links these records to mortality and hospitalization data to see how well the model performs outside the datasets it was built on. No new tests or visits are involved, and the model is used for research only, not for making treatment decisions.
What this could mean
Our plain-language read of the trial. This is informational only, not medical advice or a prediction.
- What this could lead to
- If the model holds up, doctors could one day use routine health-check data to flag people with fatty liver disease who face a higher risk of dying and need closer follow-up.
- What could go wrong
- This is a single-center look back at old records, so the model may not work as well in other hospitals or in people whose data was incomplete. It cannot prove that acting on the model's predictions saves lives.
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Study facts
What this study's own registry entry says, in plain language.
- Participants
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269,901 people
The number who actually took part.
- Started
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Jan 2018
- Finished
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Jan 2026
- Lead sponsor
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A government agency
The lead sponsor is a government body.
Who can take part
This study's own entry requirements. Only the study team can say for certain whether you qualify.
Who is studied
The study population comprised adult participants who underwent health examinations at our hospital's health examination center between January 1, 2018, and December 31, 2024, and who possessed documented records of fatty liver disease, liver attenuation, controlled attenuation parameter (CAP), liver stiffness measurement (LSM), liver ultrasound, or related metabolic/liver function tests.For participants with multiple health examination records, the index visit was determined based on pre-specified rules. The primary definition targeted the date of the first visit where fatty liver-related examinations were available and critical variables were substantially complete. Sensitivity definitions for the index visit included: (1) the very first recorded visit, (2) the most recent recorded visit, (3) the visit with the most complete CAP/LSM data, or (4) the visit with the highest completeness of model-specific predictor variables.
- Ages
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18 years and older
- Sex
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Anyone
Show the full entry requirements Hide the full entry requirements
Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.
Inclusion Criteria: 1. Age ≥ 18 years at the time of the health examination. 2. Presence of health examination records at our hospital's health examination center between January 1, 2018, and December 31, 2024. 3. Availability of fatty liver-related records, including hepatic steatosis indicated by liver ultrasound, controlled attenuation parameter (CAP), liver stiffness measurement (LSM), or screening-related checkup items. 4. Complete documentation of essential baseline characteristics, minimally including age, sex, and the exact date of the physical examination. 5. Possession of a unique in-hospital patient identifier or a study-specific identification code generated by the data management department to enable reliable deduplication and outcome linkage. Exclusion Criteria: 1. Age \< 18 years. 2. Absence of critical data fields required to establish basic eligibility, such as missing records for age, sex, or the date of the health examination. 3. Presence of duplicate records that cannot be reliably resolved, or irresolvable conflicts during participant identity mapping. 4. Physiologically implausible data without a verifiable audit trail for correction, such as anthropometric indices, CAP, LSM, or liver enzymes falling outside biologically reasonable ranges. 5. Explicit prior refusal by the participant (opt-out) to allow their medical or health examination data to be utilized for clinical research. 6. Any other conditions or restrictions stipulated by the Institutional Review Board (IRB) or the hospital's data management department that preclude inclusion.
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Conditions
The condition(s) this trial relates to.
As listed by the trial registrant
The condition terms exactly as the trial's registrant entered them.
Contacts and locations
Locations
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The First Affiliated Hospital of University of Science and Technology of China
Hefei, Anhui, 230001, China
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Other studies related to the condition(s) this trial covers.
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