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Record W2942490812 · doi:10.1177/2050640619843735

Treatment of acute hepatitis C in HIV coinfection: Is this a chance for achieving microelimination?

2019· editorial· en· W2942490812 on OpenAlexaboutno aff
Jürgen K. Rockstroh, Christoph Boesecke

Bibliographic record

VenueUnited European Gastroenterology Journal · 2019
Typeeditorial
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCoinfectionMen who have sex with menTransmission (telecommunications)Sexual transmissionHepatitis CHepatitis C virusConcomitantPsychological interventionImmunologyHuman immunodeficiency virus (HIV)VirologyInternal medicineSyphilisVirusPsychiatry

Abstract

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In 2002 the first increase in sexually transmitted acute hepatitis C (HCV) was observed among human immunodeficiency virus (HIV)-positive men who have sex with men (MSM) in London.1 Subsequently, outbreaks of acute HCV have been described globally in Asia, Australia, Canada and the USA and in almost all major cities from Western Europe but more recently also from Central and Eastern Europe.2,3 Most likely transmission risk factors are traumatic sex practices with increased risk for blood-blood contacts, concomitant other sexually transmitted diseases and use of Chemsex.4,5 Moreover, rectal shedding of HCV in HIV-coinfected MSM and transmission of HCV from dendritic cells have been discussed as contributors to the spread of acute HCV.6,7 Behavioral interventions in combination with increased roll-out of direct-acting antiviral (DAA) therapy have been discussed as a potential strategy to stop the ongoing HCV epidemic in this particular patient group.8 In the current issue of the United European Gastroenterology Journal, Chromy and colleagues report on the outcome of DAA therapy in HIV-coinfected patients with acute HCV from Austria.9 Reassuringly, they can confirm 100% cure rates following DAA therapy in early HCV infection. So clearly, early treatment intervention by preventing further HCV transmissions could be very instrumental in helping to achieve microelimination in this group. At least three countries have now reported a dramatic reduction in new incident cases of acute HCV following identification of HIV-positive MSM and ongoing HCV replication after acute HCV infection.10-12 Delay of DAA therapy because of missing reimbursement for DAA therapy during acute HCV infection remains a challenge in Europe despite first cost-effectiveness studies demonstrating a cost benefit for early intervention rather than waiting six months to establish chronic HCV infection.13 As shown in the paper by Chromy et al.,9 the probability of spontaneous HCV clearance is low at only 11%, making waiting an unattractive option. Similar data are reported from the European PROBE-C cohort, in which, in a much larger cohort, a 15% spontaneous HCV clearance rate was found in HIV-coinfected individuals with an episode of acute HCV.14 Indeed, the current European AIDS Clinical Society treatment algorithm for management of acute HCV recommends a second quantitative HCV-RNA determination four weeks after initial diagnosis; in case there is no two log drop in HCV-RNA at this time, chronification of HCV infection can be expected and early DAA therapy is suggested.15 Most studies seem to suggest that shorter treatment durations needed for treatment in early chronic HCV infections such as eight weeks of sofosbuvir/ledipasvir or grazoprevir/elbasvir are sufficient, which also implies cost savings toward treatment at later stages with more advanced fibrosis.16,17 The spread of HCV to HIV-negative MSM, particularly in preexposure prophylaxis cohorts, as well as the high reinfection rate among HIV-coinfected MSM with an acute HCV episode further enhance the need for early treatment intervention to prevent further spread of this epidemic.5,18 Clearly, it is no longer a question of treatment efficacy but rather treating all individuals identified with acute HCV to prevent further its spread and to contribute toward microelimination of HCV in this particular patient population.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.346
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.312
Teacher spread0.295 · 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.

Study designNot applicable
Domainnot available
GenreEditorial

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

Citations4
Published2019
Admission routes1
Has abstractyes

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