Epidemiology of metabolic dysfunction-associated steatotic liver disease and association with kidney transplant outcomes
Bibliographic record
Abstract
Background: The metabolic syndrome is highly prevalent among kidney transplant candidates and recipients.The hepatic manifestation of the metabolic syndrome, metabolic dysfunctionassociated steatotic liver disease (MASLD), is the most common chronic liver disease globally.However, it has not been studied thoroughly among kidney transplant recipients (KTR).Objectives: We sought to describe the burden of MASLD in a KTR population, and to investigate its potential association with transplant outcomes, including advanced graft dysfunction, graft failure, and death. Methods:We conducted a retrospective cohort study in consecutive first-time KTR (2008-2020) with pre-transplant abdominal ultrasound, and without history of other chronic liver diseases including liver disease related to alcohol consumption.MASLD was defined as the presence of hepatic steatosis on abdominal ultrasound and presence of at least one of the adult cardiometabolic criteria, including obesity, insulin resistance, hypertension, and dyslipidemia.We assessed the prevalence of MASLD at transplantation and at 1-, 3-, and 5-years posttransplant.In KTR without MASLD at baseline, we determined an incidence rate of MASLD and estimated its cumulative incidence function (CIF) when considering graft failure and death as competing risks.We further assessed the association of MASLD with the composite endpoint of advanced graft dysfunction (defined as eGFR < 30 mL/min/1.73m 2 sustained for a period of ≥ 3 months), death-censored graft failure (DCGF, defined as return to dialysis or retransplantation), and death with graft function (DWGF).We fit time-dependent Cox regression models adjusted for recipient, donor, and transplant characteristics for both composite and each of the distinct endpoints (i.e., advanced graft dysfunction, DCGF and DWGF).Results: We included 650 KTR (median age 57.2 years [IQR 45.0, 66.0], 34% female) with a median follow up of 5.0 years post-transplant.Prevalence of MASLD at transplantation was
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".