A Systematic Review and Meta‐Analyses of Nonsucrose Sweet Solutions for Pain Relief in Neonates
Bibliographic record
Abstract
BACKGROUND: Sucrose has been demonstrated to provide analgesia for minor painful procedures in infants. However, results of trials investigating other sweet solutions for neonatal pain relief have not yet been synthesized. OBJECTIVE: To establish the efficacy of nonsucrose sweet-tasting solutions for pain relief during painful procedures in neonates. METHOD: The present article is a systematic review and meta-analyses of the literature. Standard methods of the Cochrane Neonatal Collaborative Review Group were used. Literature searches were reviewed for randomized controlled trials investigating the use of sweet solutions, except sucrose, for procedural pain management in neonates. Outcomes assessed included validated pain measures and behavioural and physiological indicators. RESULTS: Thirty-eight studies (3785 neonates) were included, 35 of which investigated glucose. Heel lancing was performed in 21⁄38 studies and venipuncture in 11⁄38 studies. A 3.6-point reduction in Premature Infant Pain Profile scores during heel lances was observed in studies comparing 20% to 30% glucose with no intervention (two studies, 124 neonates; mean difference -3.6 [95% CI -4.6 to -2.6]; P<0.001; I2=54%). A significant reduction in the incidence of cry after venipuncture for infants receiving 25% to 30% glucose versus water or no intervention was observed (three studies, 130 infants; risk difference -0.18 [95% CI -0.31 to -0.05]; P=0.008, number needed to treat = 6 [95% CI 3 to 20]; I2=63%). CONCLUSIONS: The present systematic review and meta-analyses demonstrate that glucose reduces pain scores and crying during single heel lances and venipunctures. Results indicate that 20% to 30% glucose solutions have analgesic effects and can be recommended as an alternative to sucrose for procedural pain reduction in healthy term and preterm neonates.
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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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.036 |
| Bibliometrics | 0.007 | 0.008 |
| 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".