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Record W2410262809 · doi:10.1136/bcr-2016-215293

Successful treatment of hepatitis C, genotype 3, with sofosbuvir/ledipasvir in decompensated cirrhosis complicated by mixed cryoglobulinaemia

2016· article· en· W2410262809 on OpenAlexaff
Jennifer A. Flemming, Catherine Lowe

Bibliographic record

VenueBMJ Case Reports · 2016
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineSofosbuvirLedipasvirRibavirinInternal medicineCirrhosisHepatitis CGastroenterologyPopulationHepatitis C virusImmunologyVirus

Abstract

fetched live from OpenAlex

Advances in the treatment of chronic hepatitis C (HCV) have given HCV providers access to treatment regimens able to achieve sustained virological response (SVR or 'cure') in the majority of patients. There are, however, groups of patients in whom HCV treatment outcomes with direct acting antivirals (DAAs) are suboptimal (genotype (GT) 3 patients, decompensated cirrhosis, renal failure) or have not been studied in large cohorts (patients with cryoglobulinaemia (CG)). This case outlines the successful eradication of GT-3 hepatitis C (HCV) in a patient with decompensated cirrhosis and renal failure secondary to mixed CG with DAA failure, using a 12-week course of sofosbuvir, ledipasvir and ribavirin. The achievement of SVR in this patient resulted in significant improvement in hepatic and renal function. Patients with decompensated cirrhosis and GT-3 disease remain a difficult to treat population, and the safety and efficacy of sofosbuvir, ledipasvir and ribavirin in this cohort require further study.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
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 head0.032
GPT teacher head0.336
Teacher spread0.304 · 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 designCase report
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

Citations7
Published2016
Admission routes1
Has abstractyes

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