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Record W2159829581 · doi:10.1086/382753

Absence of Cytomegalovirus‐Resistance Mutations after Valganciclovir Prophylaxis, in a Prospective Multicenter Study of Solid‐Organ Transplant Recipients

2004· article· en· W2159829581 on OpenAlexaff
Guy Boivin, Nathalie Goyette, Christian Gilbert, Noel A. Roberts, Katherine Macey, Carlos V. Payá, Mark D. Pescovitz, Atul Humar, Ed Dominguez, Kenneth Washburn, Emily A. Blumberg, Barbara D. Alexander, Richard B. Freeman, Nigel Heaton, Emma Covington

Bibliographic record

VenueThe Journal of Infectious Diseases · 2004
Typearticle
Languageen
FieldMedicine
TopicCytomegalovirus and herpesvirus research
Canadian institutionsUniversity Health NetworkUniversité LavalToronto General HospitalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsValganciclovirGanciclovirCytomegalovirusBetaherpesvirinaeMedicineInternal medicineTransplantationHuman cytomegalovirusOrgan transplantationGastroenterologyImmunologyVirologyHerpesviridaeVirusViral disease

Abstract

fetched live from OpenAlex

We investigated the emergence of cytomegalovirus (CMV) ganciclovir-resistance mutations in 301 high-risk solid-organ transplant (SOT) recipients after oral prophylaxis, for 100 days, with either valganciclovir or ganciclovir. For patients treated with ganciclovir, the incidence of CMV UL97 mutations was 1.9% (2/103) at the end of prophylaxis and 6.1% (2/33) for patients with suspected CMV disease up to 1 year after transplantation. No resistance mutations were detected in samples from valganciclovir-treated patients. Dual polymerase (UL54) and UL97 resistance mutations were not seen. Valganciclovir was associated with negligible risk of resistance and thus constitutes a useful alternative to ganciclovir prophylaxis for CMV in high-risk SOT recipients.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.294
Teacher spread0.283 · 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 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

Citations165
Published2004
Admission routes1
Has abstractyes

Explore more

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