Impact of hypertonic saline on hospitalization rate in infants with acute bronchiolitis: A meta‐analysis
Bibliographic record
Abstract
AIM: This meta-analysis aimed to assess the efficacy of nebulized hypertonic saline (HS) on the rate of hospitalization in infants with acute bronchiolitis in the Emergency Department (ED) setting. METHOD: We searched PubMed, Virtual Health Library-BVS and Cochrane CENTRAL from inception until January 31, 2018. We selected randomized trials that compared nebulized HS with normal saline (NS) or standard care in children up to 24 months of age with acute bronchiolitis in the ED setting. We conducted random-effects meta-analyses to estimate the risk ratio (RR) and 95% confidence interval (CI). RESULTS: A total of 293 records were screened and 8 trials involving 1708 patients were included. The meta-analysis showed a 16% reduction in the risk of hospitalization among patients treated with HS compared to NS (risk ratio [RR]: 0.84, 95% confidence interval [CI]: 0.71-0.98, P = 0.03). A significant effect of HS in reducing the risk of hospitalization was found only in the subgroup analyses of trials in which HS was mixed with bronchodilators, multiple doses (≥3) were given, and risk of bias was low. CONCLUSIONS: Nebulized hypertonic saline may potentially reduce the risk of hospitalization in infants with acute bronchiolitis in the ED setting. Quality of evidence is moderate due to substantial clinical heterogeneity between studies and large multicenter trials are still warranted.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.062 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".