Inflammatory mediators and lung abnormalities in HIV: A systematic review
Bibliographic record
Abstract
HIV and pneumonia infections have both been shown to negatively impact lung function. However, evidence of the role of inflammation on lung dysfunction in HIV and pneumonia co-infected individuals remains limited. We aimed to systematically review the association of inflammatory markers and lung abnormalities in HIV and pneumonia co-infected individuals. This systematic review was registered with the International Prospective Register of Systematic Reviews on August 15, 2017 (registration number CRD42017069254) and used 4 databases (Cochrane Central Register of Controlled Trials, PubMed Central, Clinical Trials.gov and Google Scholar). All clinical trial, observational, and comparative studies targeting adult (> 18 years old) populations with HIV, pneumonia, or both, that report on immune response (cytokine, chemokine, or biomarker), and lung abnormality as an outcome were eligible. Data selection, risk of bias and extraction were performed independently by 2 blinded reviewers. Due to heterogeneity among the articles, a qualitative synthesis was performed. Our search strategy identified 4454 articles of which, 7 met our inclusion criteria. All of the studies investigated the ability of circulating biomarkers to predict lung damage in HIV. None of the articles included patients with both HIV and pneumonia, nor pneumonia alone. Markers of inflammation (IL-6, TNF-α, CRP), innate defense (cathelicidin), monocyte and macrophage activation (sCD14, sCD163 and, IL-2sRα), endothelial dysfunction (ET-1) and general immune health (CD4/CD8 ratio) were associated with lung abnormalities in HIV. This review highlights the lack of available information regarding the impact of inflammatory mediators on lung function in HIV and pneumonia populations, therefore opportunities to prevent lung damage with available anti-inflammatory treatment or to investigate new ones still remain.
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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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.007 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".