Effect of frequency of clinic visits and medication pick‐up on antiretroviral treatment outcomes: a systematic literature review and meta‐analysis
Bibliographic record
Abstract
Abstract Introduction: Expanding and sustaining antiretroviral therapy (ART) coverage may require simplified HIV service delivery strategies that concomitantly reduce the burden of care on the health system and patients while ensuring optimal outcomes. We conducted a systematic review to assess the impact of reduced frequency of clinic visits and drug dispensing on patient outcomes. Methods: As part of the development process of the World Health Organization antiretroviral (ARV) guidelines, we systematically searched medical literature databases for publications up to 30 August 2016. Information was extracted on trial characteristics, patient characteristics and the following outcomes: mortality, morbidity, treatment adherence, retention, patient and provider acceptability, cost and patients exiting the programme. When feasible, conventional pairwise meta‐analyses were conducted. Results and discussion: Of 6443 identified citations, 21 papers, pertaining to 16 studies, were included in this review, with 11 studies contributing to analyses. Although analyses were feasible, they were limited by the sparse evidence base, despite the importance of the research area, and relatively low quality. Comparative analyses of eight studies reporting on frequency of clinic visits showed that less frequent clinic visits led to higher odds of being retained in care (odds ratio [OR]: 1.90; 95% CI: 1.21–2.99). No differences were found with respect to viral failure, morbidity or mortality; however, most estimates were favourable to reduced clinic visits. Reduced frequency of ARVs pick‐ups showed a trend towards better retention (OR: 1.93; 95% CI: 0.62–6.04). Strategies using community support tended to have better outcomes; however, their implementation varied, particularly by location. External validity may be questionable. Conclusions: Our systematic review suggests that reduction of clinical visits (and likely ARVs pick‐ups) may improve clinical outcomes, and that they are a viable option to relieve health systems and reduce burden of care for PLHIV. Strategies aimed at reducing clinic visits or drug refill services should focus on stable patients who are virally suppressed, tolerant to their drug regimen and fully adherent. These strategies may be critical to the current changes taking place in HIV treatment policy; thus, due to the data limitations, further high quality research is needed to inform policy and programmatic interventions.
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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 | 0.017 | 0.046 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.044 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".