Changing HCV patient profiles: insights from a large multinational real-world sofosbuvir/velpatasvir (SOF/VEL) dataset
Bibliographic record
Abstract
Background and Aims More HCV-patients (pts) being started on direct-acting antivirals (DAAs) are belonging to vulnerable populations. This real-world analysis describes the profiles of these populations. Method HCV-pts (18+years [y]) from 37 clinical cohorts across nine countries treated with SOF/VEL for 12 weeks without ribavirin were included. Those with a history of decompensation or prior NS5A-inhibitor exposure were excluded. This descriptive analysis evaluated patient characteristics, time to treatment (TT [time from HCV-RNA diagnosis to DAA-initiation]), and sustained virological response≥12 weeks after end of treatment (SVR), stratified by age and sex. Results Among 6356 pts, 2274 were aged<50y, 2568: 50−65y, and 1514>65y. The percentage of male was decreasing with age. Approx. 20% of all pts had past IV drug use. Irrespective of age, male pts were more likely to have compensated cirrhosis and HCV genotype (GT) 3 infection. Results in vulnerable male patients: Higher likelihood of incarceration in age-group≤65y, significantly fewer mental health disorders and median TT was shorter.. Use of antipsychotics appeared similar, irrespective of sex.. In 5845 pts with valid result, SVR was high across age ranges, independent of sex (<50y: female 98.7%, male 99.2%; 50−65y: female 98.7%, male 98.1%;>65y: female 99.3%, male 98.3%). 475 pts did not achieve SVR for a non-virological reason; mostly loss to follow-up, independent of gender. Conclusion Independent of gender, SOF/VEL results in high SVR rates. Significantly fewer mental health disorders were observed in male pts and TT was shorter. Publication History Article published online: 18 January 2023 © 2023. Thieme. All rights reserved. Georg Thieme Verlag Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".