MétaCan
Menu
Back to cohort
Record W4255844266 · doi:10.14341/probl201763146-50

Thyrotoxic hepatitis

2017· article· en· W4255844266 on OpenAlexaff
Dmitrij V. Pikulev, А.В. Клеменов

Bibliographic record

VenueProblems of Endocrinology · 2017
Typearticle
Languageen
FieldMedicine
TopicThyroid Disorders and Treatments
Canadian institutionsVétoquinol (Canada)
Fundersnot available
KeywordsMedicineVirology

Abstract

fetched live from OpenAlex

In most cases, liver pathology in hyperthyroidism is confined to asymptomatic changes in laboratory indices, while clinical signs are much rarer. Three clinical variants of liver pathology in patients with hyperthyroidism can be differentiated: drug-induced hepatitis that develop in response to administration of thyrostatic agents (mainly propylthiouracil); concomitant autoimmune liver diseases (autoimmune hepatitis, primary biliary cirrhosis), and hepatopathies as a direct manifestation of thyrotoxicosis (thyrotoxic hepatitis). Thyrotoxic hepatitis is a rare condition difficult to diagnose. The variety of etiological factor of liver pathology in hyperthyroidism, universal clinical symptoms, and the lack of specific histological markers make it difficult to make a correct diagnosis. A clinical case of Graves’ disease complicated with severe thyrotoxic hepatitis, the edema-ascites syndrome and hyperbilirubinemia is reported. The patient was diagnosed with thyrotoxic hepatitis after all other reasons for liver pathology have been ruled out. The concomitant thyrogenic myocardiodystrophy, cardiomegaly and atrial fibrillation required ruling out the diagnosis of cardiogenic liver injury and made diagnosing more difficult. Normalization of the thyroid status in patients receiving mercazolyl therapy was accompanied by alleviation of clinical symptoms of hepatitis and the positive dynamics of the indices of liver function tests. A brief review of the data on clinical variants and mechanisms of liver injury in patients with thyrotoxicosis is presented.

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 score0.060
Threshold uncertainty score0.305

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 head0.026
GPT teacher head0.299
Teacher spread0.273 · 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

Citations3
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProblems of EndocrinologySame topicThyroid Disorders and TreatmentsFrench-language works237,207