Effect of Liposomal Lidocaine and Sucrose Alone and in Combination for Venipuncture Pain in Newborns
Bibliographic record
Abstract
OBJECTIVE: To determine the relative effectiveness of liposomal lidocaine, sucrose, and their combination for reducing pain in term newborns. METHODS: Ours was a double-blind, randomized, controlled, double-dummy trial of 330 healthy term newborns. Before venipuncture for the newborn screening test, neonates received (1) 1 g of liposomal lidocaine cream topically, (2) 2 mL of 24% sucrose solution orally, or (3) sucrose and liposomal lidocaine. The facial grimacing score (0-100) was used to assess pain. Adverse events and lidocaine levels were used to assess safety. RESULTS: Infant characteristics did not differ among groups. Facial grimacing scores were lower in the sucrose group compared with those in the liposomal lidocaine group (mean difference: -27 [95% confidence interval (CI): -36 to -19; P < .001) and for the sucrose plus liposomal lidocaine group compared with those in the liposomal lidocaine group (mean difference: -23 [95% CI: -31 to -14]; P < .001). The sucrose and sucrose plus liposomal lidocaine groups did not differ (mean difference: -5 [95% CI: -13 to 4]; P = .3). Local skin reactions were not observed, and the incidence of spitting up did not differ between sucrose-exposed and non-sucrose-exposed infants (1.4% vs 2.7%, respectively; P = .22). The mean (SD) plasma lidocaine level was 44.6 (55.3) ng/mL. CONCLUSIONS: Sucrose was more effective than liposomal lidocaine for reducing pain during venipuncture in newborns. The addition of liposomal lidocaine to sucrose did not confer any additional benefit to sucrose alone. There was no evidence of harm from liposomal lidocaine or sucrose.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".