Global prevalence of depression in HIV/AIDS: a systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: The incidence of some fatal diseases, including HIV/AIDS, accompanied by depression has become a significant concern in developed, developing and underdeveloped countries. A great deal of time and money are spent on controlling and reducing the complications of this infection across the world. Accordingly, the main purpose of this study was to clarify the global prevalence rate of depression in patients living with HIV/AIDS via a systematic review and meta-analysis. METHODOLOGY: All articles in English, published between 2000 and 2018, were systematically searched from the original databases of Web of Science, PubMed, Scopus, Cochrane Library, Google Scholar and Embase. As a result, a total of 118 articles were identified. RESULTS: The total sample size in these articles was 51143 people, and the number of patients suffering from moderate and severe levels of depression was 14 942. The results of the analysis based on the random-effects (DerSimonian and Laird) model revealed that the prevalence rate of depression in patients with HIV/AIDS was 31% (95% CI 28% to 34%), with a 98% heterogeneity index which was reported significant. Meanwhile, the highest prevalence rate of depression based on continent was in South America at 44% (95% CI 35% to 53%) and the lowest rate was in Europe at 22% (95% CI 17% to 27%). CONCLUSION: In general, there was a higher prevalence rate of depression in developing and underdeveloped countries than in developed countries, which could be attributed to the advancement of science and the possibilities for early diagnosis of this syndrome. TRIAL REGISTRATION NUMBER: CRD42019119137.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".