Does undernutrition increase the risk of lost to follow-up in adults living with HIV in sub-Saharan Africa? Protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction Undernutrition is considered a marker for poor prognosis among people living with HIV (PLHIV), particularly in sub-Saharan Africa (SSA), where undernutrition and HIV are both highly prevalent. Evidence suggests that undernutrition (body mass index <18.5 kg/m 2 ) is one of the main factors that significantly increases the risk of lost to follow-up (LTFU) in PLHIV. However, primary studies in SSA have reported inconsistent findings on the relationship between undernutrition and LTFU among adults living with HIV. To the best of our knowledge, no systematic review which aimed to summarise the available evidence. Hence, this review aims to determine the pooled effect of undernutrition on LTFU among adults living with HIV in SSA. Methods and analysis PubMed, EMBASE, Web of Science, Scopus, and, for grey literature, Google Scholar will be systematically searched to include relevant articles published since 2005. Studies reporting the effect of undernutrition on LTFU in adults living with HIV in SSA will be included. The Newcastle-Ottawa Scale will be used for quality assessment. Data from eligible studies will be extracted using a standardised data extraction tool. Heterogeneity between included studies will be assessed using Cochrane Q-test and I 2 statistics. The Egger’s and Begg’s tests at a 5% significance level will be used to evaluate publication bias. As heterogeneity is anticipated, the pooled effect size will be estimated using a random-effects model. The final effect size will be reported using the adjusted HR with a 95% CI. Ethics and dissemination Ethical approval is not required for a protocol for a systematic review. The results of this systematic review will be published in a peer-reviewed journal and will be publicly available. PROSPERO registration number CRD42021277741.
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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 | 0.079 | 0.091 |
| Meta-epidemiology (narrow) | 0.008 | 0.006 |
| Meta-epidemiology (broad) | 0.032 | 0.049 |
| Bibliometrics | 0.013 | 0.010 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.006 | 0.006 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.050 | 0.005 |
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".