Polymyalgia Rheumatica After Influenza Vaccine
Bibliographic record
Abstract
Influenza is an acute upper respiratory tract infection that occurs in epidemics almost every year, and is caused by influenza A and B viruses. It can cause serious complications including death especially in older adults and individuals with underlying health problems. Influenza vaccination is a very effective way of preventing influenza and is recommended by CDC. The common side effects of the vaccine vary from mild injection site reactions, to rhinorrhea, nasal congestion, headache and sore throat. On the other hand, there have been very rare reports of Guillain-Barre’s syndrome and also some cases of polymyalgia rheumatica (PMR) after influenza vaccine. Our patient, an 86-year-old female, presented with bilateral shoulder and hip pain, and stiffness 2 weeks after she received her influenza vaccine, and both the patient and family were very adamant and upset that the problem was caused by the vaccination. Patient’s erythrocyte sedimentation rate and C-reactive protein were elevated, a clinical diagnosis of PMR was made, and she was started on steroids to which she had a dramatic response. While we strongly recommend the administration of influenza vaccination, we also want to create awareness among the clinicians of this possibility, and proper education of the patients regarding this existence and the fact that if it happens at all, there is a treatment for it, and it should not discourage the patients from getting the vaccine in future. Also this association would need more studies in future. J Med Cases. 2017;8(4):117-118 doi: https://doi.org/10.14740/jmc2788w
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".