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Enregistrement W4214861650 · doi:10.1101/2022.02.28.22271643

Myocarditis and Pericarditis following COVID-19 Vaccination: Evidence Syntheses on Incidence, Risk Factors, Natural History, and Hypothesized Mechanisms

2022· preprint· en· W4214861650 sur OpenAlexafffundabout
Jennifer Pillay, L. Gaudet, Aireen Wingert, Liza Bialy, Andrew S. Mackie, D. Ian Paterson, Lisa Hartling

Notice bibliographique

RevuemedRxiv · 2022
Typepreprint
Langueen
DomaineMedicine
ThématiqueViral Infections and Immunology Research
Établissements canadiensUniversity of Alberta
Organismes subventionnairesCanadian Institutes of Health ResearchCanada Research ChairsPublic Health AgencyPublic Health Agency of CanadaStollery Children’s Hospital FoundationChildren's Hospital FoundationMcMaster University
Mots-clésMedicineIncidence (geometry)VaccinationMyocarditisPopulationObservational studyPericarditisCochrane LibraryEpidemiologyPediatricsImmunologyInternal medicineMeta-analysisEnvironmental health

Résumé

récupéré en direct d'OpenAlex

Abstract Objectives Myocarditis and pericarditis are adverse events of special interest after vaccination for COVID-19. Evidence syntheses were conducted on incidence rates, risk factors for myocarditis and pericarditis after COVID-19 mRNA vaccination, clinical presentation and short- and longer-term outcomes of cases, and proposed mechanisms and their supporting evidence. Design Systematic reviews and evidence reviews. Data sources Medline, Embase and the Cochrane Library were searched from October 2020 to January 10, 2022; reference lists and grey literature (to January 13, 2021). Review methods Large (>10,000) or population-based/multisite observational studies and surveillance data (incidence and risk factors) reporting on confirmed myocarditis or pericarditis after COVID-19 vaccination; case series (n≥5, presentation, short-term clinical course and longer-term outcomes); opinions/letters/reviews/primary studies focused on describing or supporting hypothesized mechanisms. A single reviewer completed screening and another verified 50% of exclusions, using a machine-learning program to prioritize records. A second reviewer verified all exclusions at full text, extracted data, and (for incidence and risk factors) risk of bias assessments using modified Joanna Briggs Institute tools. Team consensus determined certainty of evidence ratings for incidence and risk factors using GRADE. Results 46 studies were included (14 on incidence, 7 on risk factors, 11 on characteristics and short-term course, 3 on longer term outcomes, and 21 on mechanisms). Incidence of myocarditis after mRNA vaccines is highest in male adolescents and young adults (12-17y: range 50-139 cases per million [low certainty] and 18-29y: range 28-147 per million [moderate certainty]). For 5-11 year-old males and females and females 18-29 years of age, incidence of myocarditis after vaccination with Pfizer may be fewer than 20 cases per million (low certainty). There was very low certainty evidence for incidence after a third dose of an mRNA vaccine. For 18-29 year-old males and females, incidence of myocarditis is probably higher after vaccination with Moderna compared to Pfizer (moderate certainty). Among 12-17, 18-29 and 18-39 year-olds, incidence of myocarditis/pericarditis after dose 2 of an mRNA vaccine may be lower when administered ≥31 days compared to ≤30 days after dose 1 (low certainty). Data specific to males aged 18-29 indicated that the dosing interval may need to increase to ≥56 days to substantially drop incidence. For clinical course and short-term outcomes only one small series (n=8) was found for 5-11 year olds. In cases of adolescents and adults, the majority (>90%) of myocarditis cases involved 20-30 year-old males with symptom onset 2 to 4 days after second dose (71-100%). Most cases were hospitalized (≥84%) for a short duration (2-4 d). For pericarditis, data is limited but more variation has been reported in patient age, sex, onset timing and rate of hospitalization. Case series with longer-term (3 mo; n=38) follow-up suggest persistent ECG abnormalities, as well as ongoing symptoms and/or a need for medications or restriction from activities in >50% of patients. 16 hypothesized mechanisms are described, with little direct supporting or refuting evidence. Conclusions Adolescent and young adult males are at the highest risk of myocarditis after mRNA vaccination. Pfizer over Moderna and waiting more than 30 days between doses may be preferred for this population. Incidence of myocarditis in children aged 5-11 may be very rare but certainty was low. Data on clinical risk factors was very limited. Clinical course of mRNA related myocarditis appears to be benign although longer term follow-up data is limited. Prospective studies with appropriate testing (e.g., biopsy, tissue morphology) will enhance understanding of mechanism(s). Funding and Registration no This project was funded in part by the Canadian Institutes of Health Research (CIHR) through the COVID-19 Evidence Network to support Decision-making (COVID-END) at McMaster University. Not registered. Summary box What is already known about this topic? Case reports and surveillance signals of myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the two-layered sac surrounding the heart) after COVID-19 vaccination appeared as early as April 2021. These have prompted ongoing surveillance and research of these complications to investigate their incidence, possible attribution to the vaccines, and clinical course. What this study adds This review critically appraises and synthesizes the available evidence to-date on the incidence of and risk factors for myocarditis and pericarditis after COVID-19 vaccination in multiple countries. It summarizes the presentation and clinical course of over 8000 reported cases and describes some initial reports of longer term outcomes. Further, many possible mechanisms are outlined and discussed. Though low, the incidence of myocarditis is probably the highest in young males aged 12-29 years and is probably higher with Moderna than Pfizer mRNA vaccines. Longer dosing intervals may be beneficial. Most cases are mild and self-limiting, though data in 5-11 year-olds is very limited. Continued active surveillance with longer term follow-up is warranted.

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,027
score de la tête « metaresearch » (Gemma)0,161
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,027
Score d'incertitude au seuil0,141

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0270,161
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0070,008
Bibliométrie0,0120,010
Études des sciences et des technologies0,0010,001
Communication savante0,0050,004
Science ouverte0,0020,002
Intégrité de la recherche0,0030,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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 Opus0,073
Tête enseignante GPT0,336
Écart entre enseignants0,263 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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

En bref

Citations1
Publié2022
Routes d'admission3
Résumé présentoui

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