Prevalence of metabolic dysfunction-associated fatty liver disease & its association with physical function in patients with acute coronary syndrome
Bibliographic record
Abstract
Abstract Background and Aims: It is widely known that patients with acute coronary syndrome (ACS) are at increased risk of nonalcoholic fatty liver disease (NAFLD), which is linked to sarcopenia and physical dysfunction. However, the relationship between metabolic dysfunction-associated fatty liver disease (MAFLD) and physical dysfunction remains unclear. The purpose of this study was to investigate the prevalence of MAFLD in patients with ACS to assess the relationship between MAFLD and muscle strength, walking speed, and 6-minute walking distance (6 MWD).Methods and Results: We reviewed patients with ACS who were assessed for hepatic steatosis using the fatty liver index, and the results were further assessed to determine the presence of MAFLD. Multiple regression analysis was used to examine the association between MAFLD and physical function. Among 479 enrolled hospitalized patients, MAFLD was identified in 234 (48.9%) patients. We conducted a multiple regression analysis in which MAFLD was independently associated with lower leg strength, gait speed, and 6 MWD (leg strength, P = 0.023; gait speed, P = 0.002 and 6 MWD, P = 0.017). Furthermore, having more metabolic impairment was still associated with lower physical function decline (leg strength, P for trend = 0.002; gait speed, P for trend = 0.019 and 6 MWD, P for trend = 0.003).Conclusions: MAFLD is common in hospitalized patients with ACS, and most patients with MAFLD have many overlapping metabolic abnormalities. MAFLD is associated with impaired physical function, and the greater the number of overlapping metabolic abnormalities, the worse the motor function.Registration number: KMEO B18-075
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".