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Enregistrement W4387568102 · doi:10.1093/ajcp/aqad118

Reply to “Kikuchi disease and COVID-19 vaccination”

2023· article· en· W4387568102 sur OpenAlexaff
Jeffrey W. Craig, Pedro Farinha, Aixiang Jiang, Brian Skinnider, Graham W. Slack, Andrew Lytle

Notice bibliographique

RevueAmerican Journal of Clinical Pathology · 2023
Typearticle
Langueen
DomaineMedicine
ThématiqueLymphadenopathy Diagnosis and Analysis
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesnon disponible
Mots-clésLibrary scienceColumbia universityHistoryClassicsMedicineGerontologyMedia studiesSociologyComputer science

Résumé

récupéré en direct d'OpenAlex

We are grateful for Dr Yu’s interest in our recent report of an association between Kikuchi-Fujimoto disease (KFD) and antecedent COVID-19 vaccine administration in British Columbia.1 It was our hope to inspire other groups to come forward with their own data, and the preliminary analysis of axillary KFD cases from a KFD-endemic region of the world provides welcome fuel for discussion. The neck, and especially the posterior cervical triangle, is unquestionably the most common site of nodal involvement by idiopathic KFD, present in the vast majority of cases.2 Meanwhile, axillary lymphadenopathy, occurring with or without concurrent cervical lymphadenopathy, has been reported in just 13% of KFD cases worldwide.3 Within our COVID-19 vaccine–associated KFD cohort, 6 of 8 patients had clinical or radiographic evidence of axillary lymphadenopathy (compared with 5 of 8 patients with cervical lymphadenopathy). Further, KFD diagnoses were based on axillary lymph node biopsy in 5 of these patients (vs just 2 patients diagnosed by cervical lymph node biopsy). Our data are consistent with previous case reports of COVID-19 vaccine–associated KFD, in which at least 8 of 11 patients were documented as having axillary lymph node enlargement.4–7 These individuals hail from all over the world, and just like those in our cohort, all received messenger RNA (mRNA)–based vaccines. The apparent excess of axillary lymph node involvement in published cases of COVID-19 vaccine–associated KFD strengthens the argument for causality and provides ample justification for the exploratory investigation performed by Dr Yu, which did not reveal a significant increase in axillary KFD diagnoses during the COVID-19 pandemic in the local population. To understand the relevance of this result, we must first acknowledge the intricacies of comparing studies across diverse populations. There are several potential reasons why an association, if one were truly present, may not have been observed. For example, KFD may manifest differently in different communities, regardless of vaccine influence. In endemic regions, KFD exhibits near-universal cervical involvement and is rarely diagnosed by axillary lymph node biopsy,8,9 whereas axillary lymphadenopathy can be found in nearly 40% of patients with KFD from Western populations of mixed racial/ethnic composition.10 The frequency of KFD-associated HLA risk alleles differs significantly between Asiatic peoples and Europeans and Africans,11 and clinical and serologic differences have been found between patients with KFD from Asia and those from Europe.3 It is therefore plausible that other important differences may exist, including variation in biological or other factors that could contribute to the degree of vaccine-induced KFD risk elevation. Differences in regional vaccine supply, especially the use of non–messenger RNA vaccines, may be particularly significant in this regard. Clinical practice habits must also be considered. It is currently unclear whether the axillary KFD cases Dr Yu identified represent all patients with axillary lymph node enlargement (which would require radiographic imaging of the axillae) or whether axillary KFD cases were simply those diagnosed by axillary lymph node biopsy. If the latter is true, local preference for targeting cervical lymph nodes over axillary lymph nodes may be a factor. Further, global awareness of the high incidence of conventional COVID-19 vaccine–associated lymphadenopathy would likely dissuade from axillary lymph node sampling because of the high probability of finding only common benign/reactive histology.12 Finally, the pandemic introduced a multitude of clinical practice changes that make direct comparisons with prepandemic statistics extremely challenging. Data from surveillance programs such as the European adverse events database (EudraVigilance) suggest that the number of COVID-19 vaccine–associated KFD cases is potentially much higher than currently appreciated.13 These tools have also captured instances of KFD occurring in the setting of other antecedent vaccinations (eg, human papillomavirus; tetanus, diphtheria, pertussis, and polio [Tdap-IPV]; influenza), and in this regard, we find the mild increase in axillary KFD cases following expanded influenza vaccine coverage in Taiwan in 2016 to be particularly intriguing. We eagerly await future studies addressing this topic and appreciate the opportunity for open scientific discourse.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,002
score de la tête « metaresearch » (Gemma)0,013
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMétarecherche
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,165
Score d'incertitude au seuil0,995

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0020,013
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,058
Tête enseignante GPT0,447
Écart entre enseignants0,389 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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