Alexithymia in HIV, HCV and coinfections.
Bibliographic record
Abstract
Recent studies show that alexithymia, an impairment of emotional processing, plays a role in HIV and HCV infections, although little is known about about alexithymia in HIV/HCV coinfection. This study aimed to assess alexithymia in patients suffering from HIV, HCV or HIV/HCV coinfection and observe major differences. We selected 153 subjects, excluding those with psychiatric diagnosis, cognitive impairment or opportunistic diseases, of whom 70 (46%) had HIV infection, 57 (37%) HCV infection and 26 (17%) HIV/HCV coinfection. For the evaluation of alexithymia, we used the Toronto Alexithymia Scale (TAS-20), a self-report questionnaire which allows the results to be assessed both on a dimensional level and on defined cutoff scores. Data analysis showed significant differences between monoinfected and coinfected subjects. The coinfected group had a mean score of 54.00 ±13.43, higher than HIV (48.11 ± 12.38) and HCV (48.28 ± 10.71) (p <0.05). Furthermore, we found clinically relevant scores (≥51) in 65.38% of coinfected subjects, in 42.85% of HIV and in 40.35% of HCV (p <0.05). Given the medical and behavioral correlates of alexithymia highlighted in the literature, we suggest that further investigations are needed to clarify the relationship between alexithymia and HIV/HCV coinfection.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".