The effect of adherence on the association between depressive symptoms and mortality among HIV-infected individuals first initiating HAART
Bibliographic record
Abstract
OBJECTIVE: To determine the impact of depressive symptoms on mortality among HIV/AIDS patients first initiating HAART and the potential role of patient adherence as a confounder and effect modifier in this association. METHODS: The study comprised HIV-positive individuals who were first prescribed HAART between August 1996 and June 2002. Depressive symptoms were assessed using the Center for Epidemiologic Studies Depression Scale. Cox proportional hazards models were used to determine the association between depressive symptoms, adherence and all-cause mortality while controlling for several baseline confounding factors. RESULTS: A total of 563 participants met the study inclusion criteria. Of these subjects, 51% had depressive symptoms at baseline and 23% of participants were less than 95% adherent in the first year of follow-up. The overall all-cause mortality rate was 10%. Multivariate analysis showed that individuals with depressive symptoms and adherence < 95% were 5.90 times (95% confidence interval, 2.55-13.68) more likely to die than adherent patients with no depressive symptoms. The estimated median model-based survival probabilities stratified by adherence and depressive symptoms levels ranged from 81% (interquartile range, 72-89%) for depressive symptoms and adherence < 95% to 97% (interquartile range, 94-98%) for no depressive symptoms and adherence > or = 95%. CONCLUSION: The results indicate that both depressive symptoms and adherence were associated with shorter survival among individuals with HIV accessing HAART. Given the high prevalence of depressive symptoms in HIV-positive patients and a strong association with adherence, the findings support improvement in the diagnosis and treatment of depression as well as adherence in order to maximize the effectiveness of HAART.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".