65 XyloFUNS: Xylocaine to Freeze during Unpleasant Nasopharyngeal Swabs in Children – A Randomized Controlled Trial
Bibliographic record
Abstract
Abstract Background Nasopharyngeal (NP) swabs have been recommended to detect SARS-CoV-2 since the beginning of the COVID-19 pandemic, but are reported to be at least moderately painful. Objectives To evaluate the efficacy of intranasal vaporized lidocaine compared to a sham treatment in reducing pain in children undergoing a NP swab in the Emergency Department (ED). Design/Methods A randomized double-blinded clinical trial was conducted in a pediatric ED. Both participants and the researcher evaluating the primary outcome were blinded. Children 6 to 17 years old requiring a NP swab were eligible. Participants were randomly allocated to receive intranasal lidocaine or a sham treatment prior to their NP swab. The primary outcome measure was pain during the swab as assessed by the visual analog scale. Secondary outcome measures were pain using the verbal numeric rating scale, fear using the children fear scale, and side effects of the intervention. Results Eighty-eight participants were enrolled: 45 to the lidocaine group and 43 to the control group. The mean visual analog scale scores for pain were 46 mm in the lidocaine group and 53 mm in the control group (mean difference 7 mm; 95%CI -5 to 19 mm). The numeric rating scale and children fear scale were not statistically different between groups. No serious adverse events were observed. Fear prior to the test and younger age were associated with higher pain scores. Conclusion Intranasal lidocaine administered prior to NP swabs in the ED did not lower pain scores for school-aged children and youth.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".