Second-dose mRNA COVID-19 vaccine safety in patients with immediate reactions after the first dose: A case series
Bibliographic record
Abstract
Background: The rates of suspected allergic reactions to the first dose of the coronavirus disease 2019 (COVID-19) mRNA vaccines have been reported to be as high as 2%, with an anaphylaxis incidence up to 2.5 per 10,000 individuals. Anaphylaxis in response to the first dose may be considered a contraindication to administration of the second dose, even though the second dose is necessary for optimal protection against severe disease. Many individuals with anaphylactic reactions to the first dose still want to receive a second dose. However, there are few published data to support the safety of administration of a second dose in this population. Objective: The primary objective of this study was to determine the percentage of patients tolerating a second COVID-19 mRNA vaccine dose after an immediate reaction to the first dose. Methods: This was a retrospective chart review of 47 patients at a Canadian hospital who had immediate, suspected allergic reactions following their first COVID-19 mRNA vaccine dose and received a second dose within our allergy clinic. Results: Of 47 patients, 46 tolerated the second dose; 43% of patients developed mild, transient symptoms. There were no patients who developed anaphylaxis or needed epinephrine after the second dose. Conclusion: Our case series adds to current evidence that administration of a second COVID-19 mRNA vaccine dose has a good safety profile in patients with a history of immediate reactions after the first dose, including those with a history of anaphylaxis in response to the first dose.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".