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Enregistrement W2605986624 · doi:10.1182/blood.v128.22.4752.4752

Comparison of Bleeding Tools in a Cohort of Pediatric Patients with ITP: Data from the Pediatric ITP Consortium of North America ICON1 Study

2016· article· en· W2605986624 sur OpenAlexaff
Breakey R. Vicky, Rachael F. Grace, Carolyn M. Bennett, Jenny M. Despotovic, Jennifer Rothman, Yves Pastore, Ellis J. Neufeld, Robert J. Klaassen, Michele P. Lambert, James B. Bussel, George R. Buchanan, Melissa J. Rose, Amy E. Geddis, Kristin A. Shimano, Kerry Hege, Kristina M. Haley, Adonis Lorenzana, Alexis A. Thompson, Michael Jeng, Shelley E. Crary, Michelle Neier, Travis Brown, Peter Forbes, Cindy Neunert

Notice bibliographique

RevueBlood · 2016
Typearticle
Langueen
DomaineMedicine
ThématiquePlatelet Disorders and Treatments
Établissements canadiensChildren's Hospital of Eastern OntarioCentre Hospitalier Universitaire Sainte-JustineMcMaster University
Organismes subventionnairesnon disponible
Mots-clésMedicineCohortImmune thrombocytopeniaPediatricsCohort studyObservational studyPlateletInternal medicine

Résumé

récupéré en direct d'OpenAlex

Abstract Background: The indications for treating children with immune thrombocytopenia (ITP) remain controversial. A valid and reliable bleeding assessment tool could assist in objectively quantifying bleeding and influence treatment decisions. Both the ITP Bleeding Score (IBLS) and the ITP-Bleeding Assessment Tool (BAT) have been developed to assess bleeding severity in ITP. The IBLS scores bleeding severity using an 11-item tool with grading from 0 to 2 and the 18-item BAT grades from 0 to 3 or 4. The BAT includes some types of bleeding not represented on the IBLS, such has intramuscular hematomas. To date, no data describe how these two measures compare when measuring bleeding associated with ITP. Objective: To describe and compare bleeding as assessed by both the IBLS and BAT and to correlate bleeding severity with platelet counts in a cohort of children with ITP. Methods: A longitudinal observational cohort of children ages >1 and < 18 years with ITP, were enrolled from 2013-2015 in the Pediatric ITP Consortium of North America ICON1 trial. All children were enrolled prior to starting a new second line monotherapy (not IVIG, steroids or anti-D). At enrollment, bleeding was assessed using the IBLS in all children. A subset of children also underwent a BAT assessment. Grades of bleeding were described and compared between tools and agreement in grading was assessed. Severity was correlated with platelet count using Spearman's correlation calculation. Results: 118 children were enrolled from 21 ICON centers. 54% had chronic ITP and the median age was 11.4y (range 1.2-17.8). The mean platelet count was 28 x 109/l (SD 57) and 88% had a baseline platelet count of <30 x 109/l. The burden of skin and oral bleeding was high. Table 1 compares bleeding scores for the 78 patients with both measures. Agreement for grades 0, 1, and 2 between the measures was highest for urinary bleeding (97%), gastrointestinal (95%), subconjunctival (95%), and epistaxis (91%). Agreement between IBLS oral bleeding by historyand BAT gum bleeding was 78% and with BAT oral cavity bleeding was 79%. IBLS oral bleeding by physical examination and BAT gum bleeding was 73% and BAT oral cavity bleeding was 79%. The lowest agreement was seen for skin manifestations. IBLS skin bleeding by history showed only 54% and 62% agreement with the BAT ecchymoses and petechiae items respectively. IBLS skin bleeding by physical examination showed 59% agreement with both the BAT ecchymoses and petechiae items. Grades 3 and 4 scores from the BAT did not provide additional information beyond the IBLS for most sites of bleeding. For sites included on the BAT but not represented on the IBLS, only 1 child had an intramuscular hematoma, 1 suffered an ocular bleed, and none experienced hemarthrosis. Bleeding from minor wounds and bleeding with tooth loss captured additional bleeding symptoms in 9 and 4 children, respectively. There were no episodes of pulmonary or intracranial hemorrhage in the cohort. Table 2 shows the correlation between bleeding severity and platelet count for all items on each measure. Conclusion: The IBLS and BAT were similarly effective at identifying bleeding symptoms, although neither tool showed strong correlation with the platelet count. There were moderate correlations noted between skin bleeding scores and platelet counts for both tools. A major limitation of this comparison is the different definitions of bleeding severity between the two measures. For sites where the items were more detailed, agreement declined (i.e. adding specificity reduced generalizability). While no patients in our cohort exhibited significant grade 3 or 4 bleeding outside of skin findings, we conclude that in the setting of clinical trials, the ability to capture very severe bleeding might be an important distinction that supports using the more complicated BAT, but for clinical practice, a simplified assessment such as the IBLS may suffice. Disclosures Grace: Agios Pharmaceuticals: Other: Scientific Advisor, Research Funding. Neufeld:Novartis: Consultancy. Bussel:Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; UpToDate: Patents & Royalties; Protalex: Membership on an entity's Board of Directors or advisory committees, Research Funding; Genzyme: Research Funding; Ligand: Membership on an entity's Board of Directors or advisory committees, Research Funding; Symphogen: Membership on an entity's Board of Directors or advisory committees; Rigel Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Shionogi: Membership on an entity's Board of Directors or advisory committees; Sysmex: Research Funding; Momenta Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees; Immunomedics: Research Funding; Eisai: Membership on an entity's Board of Directors or advisory committees, Research Funding; Boehringer Ingelheim: Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Cangene: Research Funding; Prophylix Pharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Physicians Education Resource: Speakers Bureau; BiologicTx: Research Funding. Haley:CSL Behring: Honoraria; Baxalta: Membership on an entity's Board of Directors or advisory committees. Thompson:Celgene: Research Funding; ApoPharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Mast: Research Funding; Amgen: Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding; Amgen: Research Funding; Baxalta (now part of Shire): Research Funding; bluebird bio: Consultancy, Research Funding; Baxalta (now part of Shire): Research Funding; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; bluebird bio: Consultancy, Research Funding; Mast: Research Funding; ApoPharma: Consultancy, Membership on an entity's Board of Directors or advisory committees; Eli Lily: Research Funding; Eli Lily: Research Funding.

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)0,002
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
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 enseignants0,012
Score d'incertitude au seuil0,023

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,003
Études des sciences et des technologies0,0000,000
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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 Opus0,039
Tête enseignante GPT0,294
Écart entre enseignants0,254 · 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'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
Publié2016
Routes d'admission1
Résumé présentoui

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