Liver biochemistry abnormalities in a quaternary care lipid clinic database
Bibliographic record
Abstract
BACKGROUND: The metabolic syndrome and non-alcoholic fatty liver disease are increasing at alarming rates. AIMS: To determine the effect of HMG-CoA reductase inhibitors (statins) on elevated liver enzymes in patients with hyperlipidemia. PATIENTS: Patients with AST above 60 U/L prior to or during treatment with statin therapy at a quaternary care lipid clinic were reviewed. METHODS: A retrospective analysis was conducted. Patients were separated into two groups: Group 1--elevated AST prior to statin therapy; and Group 2--elevated AST during statin therapy. RESULTS: Forty six patients with one or more measurements of AST >60 U/L remained after exclusion criteria were applied. Ten of 13 (77%) group 1 patients had reduced AST levels after initiation of statin therapy. Thirty two of 33 patients (97%) in group 2 had transient AST elevations while on statin therapy; one patient had persistently elevated AST after initiation of treatment. There were no significant adverse events reported. CONCLUSION: Use of HMG-CoA reductase inhibitors in patients with elevated AST resulted in normalization of AST levels. HMG-CoA reductase inhibitors were safe in patients with mildly elevated AST. This may translate to use of HMG-CoA reductase inhibitors in diseases such as non-alcoholic fatty liver disease and non-alcoholic steatohepatitis.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".