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Record W2102814989 · doi:10.4021/gr246w

Clinical Benefits of Biochemical Markers of Fibrosis in Egyptian Children With Chronic Liver Diseases

2011· article· en· W2102814989 on OpenAlexvenueno aff
Tawhida Yassin Abdel-Ghaffar

Bibliographic record

VenueGastroenterology Research · 2011
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCirrhosisLiver biopsyLamininFibrosisGastroenterologyBiopsyInternal medicineChronic liver diseaseLiver diseaseType IV collagenHepatic fibrosisPathologyExtracellular matrixBiology

Abstract

fetched live from OpenAlex

BACKGROUND: The need for repetition of liver biopsy, especially in assessing the degree of fibrosis and follow-up of treatment protocols, justifies an intensive search for non-invasive alternatives. We attempted to investigate the clinical usefulness of serum fibrogenesis markers in pediatric chronic liver diseases. METHODS: We measured serum levels of TGF-β1, collagen IV, laminin, MMP-2 and EGF-R, in 50 children with chronic liver disease (HBV, HCV and Bilharziasis) and 30 healthy controls, and determined their relationship to frequently used liver function tests and liver biopsy findings in patients. RESULTS: TGF-β1, collagen IV, laminin and MMP-2, but not EGF-R, were significantly higher in patients than in controls (P < 0.01). None of these markers correlated with the histological fibrosis stage, whereas laminin correlated with necroinflammatory activity (P < 0.01). TGF-β1, collagen IV, laminin and MMP-2 had the ability to discriminate patients with significant fibrosis, while only collagen IV and laminin were able to discriminate those with cirrhosis. Among these markers, collagen IV had the best predictive accuracy for significant fibrosis (AUROC 0.94; PPV 91.5%) and cirrhosis (AUROC 0.85; PPV 80%). CONCLUSIONS: In conclusion, these markers may be useful in reducing but not replacing the need for liver biopsy in the monitoring of disease progression and treatment effectiveness and might be an inseparable part of assessment of chronic hepatopathies.

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 score0.005
Threshold uncertainty score0.376

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 studies0.0000.001
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 head0.061
GPT teacher head0.342
Teacher spread0.281 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

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