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Patients’ Preference of Valacyclovir Once-Daily Suppressive Therapy Versus Twice-Daily Episodic Therapy for Recurrent Genital Herpes

2003· letter· en· W2054592903 on OpenAlexaff
Barbara Romanowski, RAYMOND B. MARINA, Jeremy Roberts

Bibliographic record

VenueSexually Transmitted Diseases · 2003
Typeletter
Languageen
FieldMedicine
TopicHerpesvirus Infections and Treatments
Canadian institutionsGlaxoSmithKline (Canada)University of Alberta
Fundersnot available
KeywordsMedicineGenital herpesQuality of life (healthcare)Internal medicineSex organPharmacotherapyPatient satisfactionSurgeryImmunology

Abstract

fetched live from OpenAlex

BACKGROUND: Valacyclovir is effective for suppressive and episodic treatment of recurrent genital herpes. Few data on patients' treatment strategy preferences are available. GOAL: The goal was to assess patients' preference, satisfaction, and quality of life with suppressive versus episodic treatment of recurrent genital herpes. STUDY DESIGN: This was a multicenter, open-label, randomized, two-arm, crossover 48-week study involving 225 patients with genital herpes. RESULTS: Suppressive valacyclovir therapy was preferred to episodic valacyclovir treatment by 72% of patients (P < 0.001). Overall treatment satisfaction and quality of life were significantly greater during suppressive therapy (P < 0.001 and P = 0.002, respectively). The risk of recurrence during the first 24 weeks was reduced by 78% with suppressive therapy (P < 0.001). Significantly fewer patients experienced recurrences during suppressive treatment than with episodic treatment (P < 0.001). Valacyclovir was well tolerated. CONCLUSIONS: Suppressive valacyclovir was preferred to episodic therapy by most patients. Suppressive therapy was associated with increased treatment satisfaction, and decreased risk and lower frequency of recurrences.

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)0.004
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.042
GPT teacher head0.291
Teacher spread0.249 · 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

Citations55
Published2003
Admission routes1
Has abstractyes

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