Effect of Choice of Measles-Mumps-Rubella Vaccine on Immediate Vaccination Pain in Infants
Bibliographic record
Abstract
OBJECTIVE: To compare acute pain response to 2 measles-mumps-rubella vaccines. DESIGN: Double-blind clinical trial. SETTING: Hospital for Sick Children, Toronto, Ontario. Patients Forty-nine infants 12 months of age receiving their first measles-mumps-rubella vaccination. INTERVENTIONS: Random allocation to receive Priorix or M-M-R II. MAIN OUTCOME MEASURES: Pain responses before (baseline) and after (within 15 seconds) vaccination were quantified by visual analog scale (VAS; range, 0-100), completed by the parent and independently by the pediatrician, and the Modified Behavioral Pain Scale (range, 0-10), scored by a coder blinded to the vaccine allocation. Crying (yes or no) and latency to the first cry after injection were also measured. RESULTS: Twenty-six infants received Priorix and 23 received M-M-R II. There were no differences between the 2 groups in baseline characteristics or prevaccination baseline pain scores. Median pain scores after vaccination (Priorix vs M-M-R II) were as follows: pediatrician VAS, 15 vs 58 (P =.001); parent VAS, 22 vs 53 (P =.007); and Modified Behavioral Pain Scale, 6 vs 8 (P =.02). Median difference in pain scores (after minus before) for Priorix vs M-M-R II were as follows: pediatrician VAS, 15 vs 53 (P =.003); parent VAS, 22 vs 47 (P =.008); and Modified Behavioral Pain Scale, 3 vs 5 (P =.03). The median latency to first cry was 1.5 seconds in the Priorix group compared with 1 second in the M-M-R II group (P =.26). CONCLUSIONS: Priorix vaccine causes significantly less pain than M-M-R II at the time of injection for 12-month-old infants receiving their first measles-mumps-rubella vaccination.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".