Factors associated with intention for revaccination among patients with adverse events following immunization
Bibliographic record
Abstract
OBJECTIVES: Individuals and healthcare providers may be uncertain about the safety of revaccination after an adverse event following immunization (AEFI). We identified factors associated with physician recommendation for revaccination and participant intention to be revaccinated among patients with adverse events following immunization (AEFIs) assessed in the Canadian Special Immunization Clinic (SIC) Network from 2013 to 2019. METHODS: This prospective observational study included patients assessed in the Canadian Special Immunization Clinic Network from 2013 to 2019 for an AEFI who required additional doses of the vaccine temporally associated with their AEFI. Participants underwent standardized assessment and data collection. Physician recommendations regarding revaccination and participant intent for revaccination were recorded. AEFI impact on daily activities and need for medical attention was captured as low, moderate, high impact and serious (e.g., requiring hospitalization). Multivariable logistic regression analysis identified factors associated with physician recommendation and participant intention for revaccination, controlling for province of assessment. RESULTS: Physician recommendation was significantly associated with the type of AEFI and AEFI impact. Compared to large local reaction, physician recommendation for revaccination was reduced for immediate hypersensitivity (aOR: 0.24 [95% CI: 0.08-0.76]) and new onset autoimmune disease (aOR: 0.16; 95% CI: 0.04-0.69). Compared to low impact AEFIs, physician recommendation was reduced for moderate (aOR: 0.22 [95% CI: 0.07-0.65]), high impact (aOR: 0.08 [95% CI: 0.02-0.30]), and serious AEFIs (aOR: 0.11 [95% CI: 0.03-0.37]). Participant intention for revaccination was significantly associated with AEFI impact, with reduced odds for high versus low impact AEFIs (aOR: 0.12 [95% CI: 0.04-0.42]). CONCLUSION: Physicians appear to use AEFI type and impact to guide recommendations while patients use primarily AEFI impact to form intentions for revaccination. The findings may help inform counselling for patients with AEFIs.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".