Impact of Thrombophilia On Arterial Ischemic Stroke or Cerebral Venous Sinus Thromboses in Children: A Systematic Review & Meta-Analysis of Observational Studies.
Notice bibliographique
Résumé
Abstract Abstract 3993 Poster Board III-929 Background The incidence of stroke in children is estimated at about 2.6 per 100,000 per year. Risk factors include congenital heart malformations, trauma, hemolytic anemias, collagen tissue diseases, inborn metabolic disorders, and infectious diseases. Apart from acquired thrombophilic risk factors, such as the presence of antiphospholipid antibodies, inherited thrombophilias (IT) have been found to be associated with stroke in infants and children. However, results of single studies on the risk of stroke onset associated with IT have been contradictory or inconclusive, mainly due to lack of statistical power. The aim of this study was to estimate the impact of thrombophilia (IT) on risk of childhood stroke via meta-analysis of published observational studies. Methods and Results A systematic search of electronic databases (Medline, EMBASE, OVID, Web of Science, The Cochrane Library) for studies published from 1970 to 2009 was conducted using key words in combination both as MeSH terms and text words. Citations were independently screened by two authors and those meeting the a priori defined inclusion criteria were retained. Data on year of publication, study design, country of origin, number of patients/controls, ethnicity, stroke type (arterial ischemic stroke [AIS]; cerebral venous sinus thrombosis [CSVT]) were abstracted. Publication bias indicator and heterogeneity across studies were evaluated, and summary odds ratios (ORs) and 95% confidence intervals (CIs) were calculated using both fixed-effects and random-effects models. Twenty-one of 185 references found met inclusion criteria. 1698 patients (AIS: 1291; CSVT: 407) and 2913 controls aged neonate to 18 years were enrolled. No significant heterogeneity was discerned across studies, and no publication bias was detected. A statistically significant association with stroke onset was demonstrated for each IT trait evaluated, with no difference found between AIS (table) and CSVT. Summary ORs/CIs (random-effects model) for AIS & CSVT cohorts were as follows: Protein C-deficiency (8.76/4.53-16.96), FV G1691A (3.34/2.66-4.26), FII G20210A (2.50/1.67-3.74), MTHFR T677T (1.61/1.21-2.14), antiphospholipid antibodies (5.84/3.06-11.18), elevated lipoprotein (a) (6.24/4.51-8.64), and combined ITs (8.85/3.32-23.57). Carrier rates reported for antithrombin- or protein S deficiency among patients were 1.5% and 1.6% as compared with 0.06% (p<0.001) and 0.4% (p=0.003) in healthy controls. Conclusions The present meta-analysis indicates that IT serve as risk factors for incident stroke. However, the impact of IT upon outcome and recurrence risk needs to be further investigated. Disclosures: Manco-Johnson: Baxter BioScience: Honoraria; Bayer HealthCare: Honoraria; CSL Behring: Honoraria; NovoNordisk: Honoraria; Octapharma: Honoraria. Off Label Use: Enoxaparin (LMWH) is used off-label in children to prevent symptomatic thromboembolism.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,045 |
| Méta-épidémiologie (sens strict) | 0,003 | 0,002 |
| Méta-épidémiologie (sens large) | 0,019 | 0,040 |
| Bibliométrie | 0,008 | 0,010 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,002 |
| Science ouverte | 0,002 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».