MétaCan
Menu
← Back to cohort
Record W2800305246 · doi:10.1111/hdi.12646

Treatment and management options for the hepatitis C virus infected kidney transplant candidate

2018· review· en· W2800305246 on OpenAlexvenueno aff
Adriana Dejman, Marco Ladino, David Roth

Bibliographic record

VenueHemodialysis International · 2018
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineContext (archaeology)PopulationIntensive care medicineKidney diseaseKidney transplantationHepatitis CTransplantationHepatitis C virusHemodialysisInternal medicineClinical trialImmunologyVirus

Abstract

fetched live from OpenAlex

A substantial body of literature has unequivocally established that prevalent hepatitis C virus infection in chronic kidney disease (CKD), end stage renal disease (ESRD) and kidney transplant recipients is associated with a negative impact on patient survival. As a consequence of remarkable work that explained the details of the hepatitis C virus (HCV) genome, a class of drugs referred to as the direct-acting antiviral (DAA) agents were developed that targeted specific key sites in viral replication. Large clinical trials in the HCV-infected general population followed soon after that demonstrated cure rates exceeding 95%. Treatment paradigms have been further refined and expanded to populations of patients that were initially excluded from the large pivotal trials. This includes the CKD and ESRD patients for whom there are now safe and effective DAAs available as well. In this context, the focus of decision making has shifted from initially demonstrating safety and efficacy to now identifying which patient should receive therapy and at what point in their CKD/ESRD journey. The specific issue of timing of treatment is particularly relevant to the HCV-infected ESRD patient who is being considered for kidney transplantation. The option of treating with DAAs prior to the transplant or alternatively delaying therapy and treating in the posttransplant period will be influenced by several factors, including patient preference, the extent of liver injury, the availability of a living or deceased donor, and more recently the option of transplanting a kidney from HCV-positive donor. The latter has been associated with the advantage of shortened waiting times and expansion of the organ donor pool. The optimal timing and choice of therapy will be the result of a decision that has been individualized for each patient as a consequence of a process of clear communication involving the patient, primary care physician, nephrologist, gastroenterologist (GI)/hepatologist, and local transplant center.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.002

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 head0.058
GPT teacher head0.376
Teacher spread0.318 · 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
GenreReview

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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueHemodialysis International→Same topicHepatitis C virus research→French-language works237,207→