Epidemiology of chronic obstructive pulmonary disease in the global HIV-infected population: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
Evidence suggests a relationship between human immunodeficiency virus (HIV) infection and chronic obstructive pulmonary disease (COPD). Although the high burden of COPD and the HIV disease is clearly demonstrated, to the best of our knowledge, there is a lack of summary and meta-analysis data on the epidemiology of COPD in the global HIV-infected population to date. The present protocol for a systematic review and meta-analysis intends to summarize existing data on the prevalence, incidence, and risk factors of COPD in the global HIV-infected population. The present review will include cohort, cross-sectional, and case-control studies conducted among HIV infected people, which report prevalence, incidence, and factors associated with COPD or enough data for their estimation. We will consider published and unpublished studies in English and French language, regardless of geographical location. Relevant records will be searched using PubMed/Medline, and Scopus from inception to December 31st, 2016. Reference lists of eligible papers and relevant review articles will be screened. Two investigators will independently screen, select studies, and extract data, with discrepancies resolved by consensus or arbitrarily by a third investigator. Risk of bias and methodological quality of the included studies will be assessed using the Newcastle-Ottawa Scale. Funnel-plots and Egger’s test will be used to determine publication bias. The study-specific estimates will be pooled through a random-effects meta-analysis model to obtain an overall summary estimate. To keep the effect of studies with extremely small or extremely large estimates on the overall estimate to a minimum, the variance of the study-specific prevalence/incidence will be stabilized with the Freeman-Tukey single arc-sine transformation. The heterogeneity will be evaluated by the χ2 test on Cochrane’s Q statistic. Results will be presented by geographic region and by antiretroviral therapy status. We plan to summarize data on factors associated with COPD in narrative format. This systematic review and meta-analysis will give an overview of the epidemiology of COPD in the global HIV population to inform policy-makers and to provide accurate data that can underpin effective interventions for optimizing their detection and management. PROSPERO CRD42016052639 .
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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 | 0.059 | 0.084 |
| Meta-epidemiology (narrow) | 0.007 | 0.005 |
| Meta-epidemiology (broad) | 0.022 | 0.022 |
| Bibliometrics | 0.015 | 0.013 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.072 | 0.008 |
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".