Seven-month persistence of COVID-19 vaccine-induced lymphadenopathy: a case report
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Lymphadenopathy is a known side effect of both messenger RNA and viral vector coronavirus disease-2019 vaccines and can cause a spectrum of findings. Coronavirus disease-2019 vaccine-associated lymphadenopathy typically resolves within 60 days after administration of the dose. CASE PRESENTATION: A 59 year old Chinese woman underwent routine mammographic screening that revealed scattered areas of fibroglandular densities in the lower-inner quadrant of the left breast and abnormal lymph nodes. A core biopsy of the breast identified ductal carcinoma in situ. A biopsy of the lymph nodes was performed, and histological findings and immunophenotype were consistent with lymphoid hyperplasia. This patient had sought medical attention after she detected swelling in her left supraclavicular fossa 7 months earlier. She had received the first dose of the Pfizer coronavirus disease-2019 vaccine in the left deltoid muscle 7 days prior to presenting with left supraclavicular fossa swelling. CONCLUSION: After reviewing the history, imaging, and pathology, it was concluded through a diagnosis of exclusion that the observed enlarged left axillary lymph nodes with reactive histology were probably related to the coronavirus disease-2019 vaccine administration and not to ductal carcinoma in situ or an undetected invasive cancer. Clinicians and radiologists need to be aware of the potential for abnormal presentations of persistent lymphadenopathy that may interfere with the diagnosis and follow-up of cancers.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it