Sweet Solutions for Analgesia in Neonates in China: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
INTRODUCTION: High-quality synthesized evidence of sweet taste analgesia in neonates exists. However, Chinese databases have never been included in previous systematic reviews of sweet solutions for procedural pain. OBJECTIVE: To conduct a systematic review of Chinese literature evaluating analgesic effects of sweet solutions for neonates. Data sources: Wang Fang, China National Knowledge Infrastructure and Chinese Biomedical Literature Database. Data extraction and analysis: Two authors screened studies for inclusion and conducted risk of bias ratings and data extraction. A third author resolved any conflicts. Meta-analyses were performed using RevMan 5.2 software, on mean differences in pain outcomes using random effects models. RESULTS: Thirty-one trials (4999 neonates) were included; 26 trials used glucose, 4 used sucrose, and 1 trial evaluated both solutions. Sweet solutions reduced standardized mean pain scores (n = 21 studies; -1.68, 95% confidence interval -2.08, -1.27) and cry duration (n = 6 studies; -25.60, 95% confidence interval -36.47, -14.72 s) but not heart rate change (n = 7 studies; -17.64, 95% confidence interval -52.71, 17.43). No included studies cited the previously published systematic reviews of sweet solutions. CONCLUSIONS: This systematic review of Chinese databases showed the same results as previously published systematic reviews. No trials included in this review cited the English systematic reviews, highlighting a parallel research agenda.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".