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Record W4366085187 · doi:10.1093/ajcp/aqad032

Kikuchi-Fujimoto Disease Following COVID-19 Vaccination: Experience at a Population-Based Referral Center

2023· article· en· W4366085187 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2023
Typearticle
Languageen
FieldMedicine
TopicLymphadenopathy Diagnosis and Analysis
Canadian institutionsSpinal Cord Injury BCUniversity of British Columbia
Fundersnot available
KeywordsCoronavirus disease 2019 (COVID-19)MedicineVaccination2019-20 coronavirus outbreakReferralSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Center (category theory)PopulationDiseaseFamily medicinePediatricsVirologyOutbreakPathologyInfectious disease (medical specialty)Environmental health

Abstract

fetched live from OpenAlex

OBJECTIVES: Multiple case reports describe Kikuchi-Fujimoto disease (KFD) following COVID-19 vaccination, but the true nature of this phenomenon is unknown. The purpose of this study was to further assess the relationship between KFD and COVID-19 vaccination at the population level. METHODS: Confirmed KFD cases from January 2018 to April 2022 were identified from provincial pathology archives and analyzed in the context of vaccination statistics from public health resources. RESULTS: Our statistical models provide evidence of a temporal association between KFD and both antecedent COVID-19 vaccine administration as well as age-stratified vaccination rates. Eight new cases of plausible COVID-19 vaccine-associated KFD are presented, collectively exhibiting clinical and pathologic features that overlap substantially with those of idiopathic KFD. CONCLUSIONS: Our findings indicate that KFD is observed in association with COVID-19 vaccination and suggest that mechanistic studies are warranted.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.749

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.084
GPT teacher head0.463
Teacher spread0.379 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it