Effect of depressive symptoms on health services utilization in the HIV and hepatitis C co-infected population in Canada
Bibliographic record
Abstract
Depression is common among people living with HCV and HIV, which contributes to health services utilization (HSU). It is unknown whether successful HCV treatment affects this. We examined depressive symptoms and HSU in people co-infected with HIV-HCV and their association with sustained virologic response (SVR) during the direct-acting antiviral era. We predicted depressive symptoms by a random forest classifier in the Canadian Co-infection Cohort. HSU was measured by inpatient and out-patient visits in the previous six months. We fit zero-inflated negative binomial models. Of the 1153 HCV RNA+participants, 530 were treated and of them, 95% achieved SVR. Without SVR, inpatient and out-patient visits were 17% and 5% higher among those with depressive symptoms than those without respectively; with SVR, this association disappeared. SVR was associated with 24% fewer inpatient visits. Thus, depressive symptoms were associated with a modest increase in HSU, and SVR appears to attenuate this effect.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".