Aetiological role of common respiratory viruses in acute lower respiratory infections in children under five years: A systematic review and meta–analysis
Bibliographic record
Abstract
BACKGROUND: Acute lower respiratory infection (ALRI) remains a major cause of childhood hospitalization and mortality in young children and the causal attribution of respiratory viruses in the aetiology of ALRI is unclear. We aimed to quantify the absolute effects of these viral exposures. METHODS: We conducted a systematic literature review (across 7 databases) of case-control studies published from 1990 to 2014 which investigated the viral profile of 18592 children under 5 years with and without ALRI. We then computed a pooled odds ratio and virus-specific attributable fraction among the exposed of 8 common viruses - respiratory syncytial virus (RSV), influenza (IFV), parainfluenza (PIV), human metapneumovirus (MPV), adenovirus (AdV), rhinovirus (RV), bocavirus (BoV), and coronavirus (CoV). FINDINGS: From the 23 studies included, there was strong evidence for causal attribution of RSV (OR 9.79; AFE 90%), IFV (OR 5.10; AFE 80%), PIV (OR 3.37; AFE 70%) and MPV (OR 3.76; AFE 73%), and less strong evidence for RV (OR 1.43; AFE 30%) in young children presenting with ALRI compared to those without respiratory symptoms (asymptomatic) or healthy children. However, there was no significant difference in the detection of AdV, BoV, or CoV in cases and controls. CONCLUSIONS: This review supports RSV, IFV, PIV, MPV and RV as important causes of ALRI in young children, and provides quantitative estimates of the absolute proportion of virus-associated ALRI cases to which a viral cause can be attributed.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.016 | 0.039 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".