Adherence to antiretroviral therapy during and after pregnancy in low-income, middle-income, and high-income countries
Bibliographic record
Abstract
OBJECTIVE: To estimate antiretroviral therapy (ART) adherence rates during pregnancy and postpartum in high-income, middle-income, and low-income countries. DESIGN: Systematic review and meta-analysis. METHODS: MEDLINE, EMBASE, SCI Web of Science, NLM Gateway, and Google scholar databases were searched. We included all studies reporting adherence rates as a primary or secondary outcome among HIV-infected pregnant women. Two independent reviewers extracted data on adherence and study characteristics. A random-effects model was used to pool adherence rates; sensitivity, heterogeneity, and publication bias were assessed. RESULTS: Of 72 eligible articles, 51 studies involving 20 153 HIV-infected pregnant women were included. Most studies were from United States (n = 14, 27%) followed by Kenya (n = 6, 12%), South Africa (n = 5, 10%), and Zambia (n = 5, 10%). The threshold defining good adherence to ART varied across studies (>80, >90, >95, 100%). A pooled analysis of all studies indicated a pooled estimate of 73.5% [95% confidence interval (CI) 69.3-77.5%] of pregnant women who had adequate (>80%) ART adherence. The pooled proportion of women with adequate adherence levels was higher during the antepartum (75.7%, 95% CI 71.5-79.7%) than during postpartum (53.0%, 95% CI 32.8-72.7%; P = 0.005). Selected reported barriers for nonadherence included physical, economic and emotional stresses, depression (especially postdelivery), alcohol or drug use, and ART dosing frequency or pill burden. CONCLUSION: Our findings indicate that only 73.5% of pregnant women achieved optimal ART adherence. Reaching adequate ART adherence levels was a challenge in pregnancy, but especially during the postpartum period. Further research to investigate specific barriers and interventions to address them is urgently needed globally.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.018 | 0.043 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.012 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".