MétaCan
Menu
Back to cohort
Record W2140042090 · doi:10.1016/j.clpt.2003.12.008

Use of population modeling to define rational monitoring of amiodarone hepatic effects*1

2004· article· en· W2140042090 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueClinical Pharmacology & Therapeutics · 2004
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicDrug-Induced Hepatotoxicity and Protection
Canadian institutionsDalhousie UniversityQueen Elizabeth II Health Sciences Centre
Fundersnot available
KeywordsAmiodaroneMedicineInternal medicineAlbuminLactate dehydrogenaseGastroenterologyNONMEMPopulationBilirubinPharmacologyEndocrinologyPharmacokineticsChemistryEnzymeAtrial fibrillationBiochemistry

Abstract

fetched live from OpenAlex

BACKGROUND: Amiodarone causes hepatotoxicity in experimental models, but in humans, the relationships between drug administration, serum concentrations, markers of liver function, and how to monitor for hepatotoxicity have not been well characterized. METHODS: An open-dose, prospective study collected serum amiodarone, desethylamiodarone, ALT, AST, lactate dehydrogenase (LDH), alkaline phosphatase, total bilirubin, and albumin concentrations over a 5-year period from 125 patients. Nonlinear mixed-effects modeling (NONMEM) was used to explore the relationship between markers of hepatotoxicity and concentrations of amiodarone and desethylamiodarone. RESULTS: No patients had clinical symptoms of hepatotoxicity during follow-up. The natural history of changes in hepatic makers showed ALT to have the strongest independent relationship to changes in serum amiodarone (r = 0.32, P <.001). An ALT greater than 3 times the upper limit of normal developed in only 8 patients (7%), with the earliest occurrence at 55 days of therapy. A mixed-effects model relating ALT elevation to serum amiodarone was improved by the addition of an effect compartment having an equilibration half-time of 87 days (r = 0.81, P <.001). The model predicts that 6% of patients will have an ALT greater than 3 times the upper limit of normal if amiodarone concentrations are maintained at less than 2.5 mg/L, and virtually no patients will have such ALT elevations if amiodarone concentrations are maintained at less than 1.5 mg/L. CONCLUSIONS: Concentrations of amiodarone below a threshold of 1.5 mg/L are associated with a minimal risk of hepatotoxicity, whereas concentrations greater than 2.5 mg/L are associated with a greater than 6% risk of hepatotoxicity. There is significant hysteresis between changes in amiodarone concentration and the resulting change in ALT. The model suggests that monitoring ALT at baseline, 1, 3, and 6 months, and then semiannually would be an efficient strategy to detect amiodarone-induced hepatotoxicity.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.302
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.400
GPT teacher head0.520
Teacher spread0.120 · 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