Evaluation of Hepatitis C Screening and Treatment Among Psychiatry Inpatients
Bibliographic record
Abstract
To evaluate uptake of hepatitis C virus (HCV) testing and treatment among psychiatry inpatients at Canada's largest mental health institution, the Centre for Addiction and Mental Health (CAMH). We reviewed medical records for all forensic and long-stay mental health patients from January 2017 to May 2021 to examine rates of HCV testing (antibody and RNA), treatment, and follow-up and completed a logistical regression to identify predictors associated with HCV antibody (Ab) screening among inpatients. < .05). HCV Ab positivity was 4.9%, and most (84%, n = 27) HCV Ab-positive individuals had subsequent RNA testing, of whom 56% (n = 15) tested HCV RNA positive. Of 15 RNA-positive individuals, 10 initiated treatments, 7 on-site at CAMH and 3 at a local hepatology center. A total of 7 individuals (1 treated by specialists and 6 on-site) achieved sustained virological response or cure. The remaining 3 were lost to follow-up, 2 of whom were treated at the hepatology clinic. Based on the high prevalence of HCV, mental health inpatients should be included in groups for whom universal screening is recommended. Since on-site treatment was more successful than referral to external hepatology specialists, utilizing inpatient admission as an opportunity for HCV screening and treatment should receive more consideration.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".