Poor treatment outcomes of children on highly active antiretroviral therapy: protocol for a systematic review and meta-analysis
Bibliographic record
Abstract
Introduction While access to highly active antiretroviral therapy (HAART) for children with HIV has expanded and the use of HAART has substantially reduced the morbidity and mortality of children due to HIV, poor treatment outcomes among children with HIV are still a major public health problem globally. The aim of this systematic review and meta-analysis is to quantify treatment outcomes among children with HIV. Methods and analysis Systematic searches will be conducted in three electronic databases (PubMed, SCOPUS and Web of Science) for recent studies published from 01 Jan 2000 up to 28 October 2020, without geographical restriction. The primary outcomes of the study will be poor treatment outcomes, which include death, treatment failure and loss to follow-up. We will include quantitative studies that report treatment outcomes among children under the age of 18 years with HIV. Studies will be excluded if they are case report, case series, conducted among adults only or do not provide data on treatment outcomes for children. Two researchers will screen the titles and abstracts of all citations identified in our search, then review the full text of the remaining papers to identify those that meet the inclusion criteria. The Newcastle–Ottawa Scale will be used for quality assessment. A random-effects meta-analysis will be used to obtain pooled estimates of the proportion of poor treatment outcomes. The heterogeneity between studies will be checked visually by using forest plots and quantitatively measured by the index of heterogeneity (I 2 ). Pooled estimates of poor treatment outcomes will be calculated with a random-effects model. Subgroup analysis will be conducted by study settings, treatment regimen, comorbidity (such as tuberculosis), study period and HIV type (HIV-1 and HIV-2). Ethics and dissemination Ethical approval will not be required for this study as it will be based on published papers. The final report of this review will be published in a peer-reviewed scientific journal.
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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 | 0.077 | 0.108 |
| Meta-epidemiology (narrow) | 0.008 | 0.005 |
| Meta-epidemiology (broad) | 0.023 | 0.038 |
| Bibliometrics | 0.014 | 0.012 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.007 | 0.008 |
| Insufficient payload (model declined to judge) | 0.056 | 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".