Depressive Symptoms Decline Among Persons on HIV Protease Inhibitors
Bibliographic record
Abstract
OBJECTIVE: To ascertain whether initiation of protease inhibitors was associated with a change in depressive symptoms among persons infected with HIV. METHODS: Study subjects included men and women who were enrolled in the HIV/AIDS Drug Treatment Program and who had completed an annual participant survey before and after initiating triple combination therapy with a protease inhibitor. Depressive symptoms were assessed using the Centre for Epidemiologic Studies-Depression scale (CES-D). Statistical analyses to determine the change in CES-D total and subscale scores before and after protease inhibitor use were conducted using parametric and multivariate methods. RESULTS: Our analysis was restricted to 453 participants. Of these 234 (52%) were depressed at baseline (CES-D score > or = 16). Compared with nondepressed participants, depressed participants were slightly younger (p = .048), less likely to be employed (p < .001) and more likely to have an annual income less than $10,000 per annum (p < .001). After adjusting for CD4 count, employment status, income, age, and CES-D total or subscale score at baseline, we found a significant improvement in total scale score (p = .001) and depressive mood (p = .002), positive affects (p = .005), and somatic symptoms (p = .011) subscale scores at follow-up. There was no significant change in the interpersonal relations score over the study period. CONCLUSION: Our findings indicate that in addition to conferring impressive clinical benefits, protease inhibitor use is associated with a significant improvement in HIV-positive individuals' mental health.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".