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Record W1825572972 · doi:10.1155/2014/496196

Out with the Old and in with the New: Hepatic Fibrosis Assessment in Canada

2014· letter· en· W1825572972 on OpenAlexaffabout
Natasha Chandok

Bibliographic record

VenueCanadian Journal of Gastroenterology and Hepatology · 2014
Typeletter
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsWilliam Osler Health SystemWestern University
Fundersnot available
KeywordsMedicineHepatic fibrosisFibrosisInternal medicinePathologyIntensive care medicine

Abstract

fetched live from OpenAlex

A rapid, reliable test, also acceptable to patients for the assessment of liver fibrosis, has long been the 'holy grail' of hepatology.The now dusty liver textbooks of yesteryear described percutaneous liver biopsy (PLB) -an ancient procedure that must seem archaic to patients.Although PLB remains germane to the artful management and careful diagnosis of particular diseases, its role in certain entities, such as viral hepatitis, is now questionable at best since FibroTest (LabCorp, USA) and FibroScan (Echosens, France) have become available in Canada.Even among common conditions such as steatohepatitis, liver biopsy may not exceed the minimum threshold of 'changing the patient's management' to justify its execution and cost and, as such, there appears to be increasingly fewer reasons to perform it.In fact, an entire generation of hepatologists have graduated their fellowship programs of late with ineptness in PLB, and I maintain that they are none the lesser for it.Of the gold standards, PLB is a flawed one for (at least) three reasons: most liver biopsies are inadequate in size and, thus, carry an inherent risk of inaccuracy (1); studies show a concerning interobserver variation among the pathologists who read them (1); and even if the specimen is of adequate size, diseases of the liver are all too often patchy, creating an intrinsic uncertainty in staging (2).Moreover, as a medical test, patients are, at the very least, highly inconvenienced by it, and while the majority sail through without major complications, a sufficiently high proportion of patients experience significant pain, not infrequently requiring admission to hospital or extended time away from work.Although also imperfect in head-to-head comparison studies with liver biopsy for accuracy, FibroScan and FibroTest have high F-statistics, and address many of the particular pitfalls of PLB, namely that of morbidity risk (3).As such, FibroTest and FibroScan have a primary, indisputable role to play in fibrosis assessment.Current trends in Canadian physician practice patterns regarding PLB are well-reflected in a study published by Sebastiani et al (4) (pages 23-30) in the current issue of the Journal.They surveyed a collection of 104 physicians who are members of the Canadian Association of Gastroenterology and/or the Canadian HIV Trials Network caring for patients with liver disease; their results are both informative and largely unsurprising.The majority of survey participants, nearly twothirds of whom were gastroenterologists, required assessment of disease stage, and the greatest demand for fibrosis assessment was for patients with hepatitis C (76.9%).The authors found that noninvasive fibrosis assessment was ordered more frequently in patients with viral hepatitis than autoimmune hepatitis, likely reflecting that necroinflammatory activity of the latter is crucial information by which to guide immunosuppression.Similar to our recent study involving hepatologists who are members of the Canadian Association for the Study of the Liver (5), noninvasive modalities of fibrosis evaluation had an approximate 50% perceived reduction in the need for PLB.When one considers

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.361
Threshold uncertainty score0.727

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.002
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0150.014
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.008
GPT teacher head0.207
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2014
Admission routes2
Has abstractyes

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