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Record W2162141964 · doi:10.1016/s1665-2681(19)31889-7

Liver biochemistry abnormalities in a quaternary care lipid clinic database

2008· article· en· W2162141964 on OpenAlexaff
H Wiesinger, Justin A. Shah, A. Clinton White, Eric M. Yoshida, J. Frohlich, Sandra Sirrs, Sharlene Gill, Michael F. Byrne

Bibliographic record

VenueAnnals of Hepatology · 2008
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineInternal medicineHyperlipidemiaReductaseFatty liverStatinHMG-CoA reductaseGastroenterologyAtorvastatinSteatohepatitisAdverse effectDiseaseEndocrinologyEnzymeBiochemistryDiabetes mellitus

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.416

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.086
GPT teacher head0.348
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2008
Admission routes1
Has abstractyes

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