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Enregistrement W2988955792 · doi:10.1182/blood-2019-125686

The Effect of "Pathway" to Diagnosis for Childhood ITP on Caregiver Quality of Life at Time of Diagnosis

2019· article· en· W2988955792 sur OpenAlexaff
Michelle Neier, Michele P. Lambert, Rachael F. Grace, Kerry Hege, Stephanie Chiu, Julianne Thompson, Robert J. Klaassen

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineMedicine
ThématiquePlatelet Disorders and Treatments
Établissements canadiensChildren's Hospital of Eastern Ontario
Organismes subventionnairesnon disponible
Mots-clésMedicineQuality of life (healthcare)PediatricsObservational studyAsymptomaticProspective cohort studyImmune thrombocytopeniaSpecialtyDiseaseFamily medicineInternal medicine

Résumé

récupéré en direct d'OpenAlex

Background: Immune thrombocytopenia (ITP) is an immune mediated bleeding disorder characterized by isolated thrombocytopenia. ITP can have a variety of presentations from asymptomatic to life threatening bleeding. Although childhood ITP is most often a self-resolving illness which can be closely observed without intervention, it can be associated with significant impact on quality of life (QoL). Prospective studies of QoL in ITP patients show that there is not always a correlation with treatment or disease severity. The pathway from initial presentation to final diagnosis varies and may include encounters with emergency room, primary care or specialty providers. There have been no published studies to date showing the impact of factors prior to the diagnosis of ITP on treatment decision making and QoL. Objective: To identify the role of physician-patient and physician-caregiver interactions on the QoL and emotional well-being of patients and their families. Ascertaining the impact of pre-diagnosis factors may provide an opportunity to improve access and quality of care provided. Methods: The ITP Consortium of North America (ICON) "Pathways" study was a multicenter observational prospective cohort study focused on the pathways to diagnosis of ITP. The study was supported by a Foundation for Morristown Medical Center Research Fund Grant. Subjects were included if they had presumed primary ITP and were age >12 months to <18 years. Subjects were excluded if they had secondary ITP, including Evans syndrome. Treatment was determined by the physician. Subjects were consented and presented with questionnaires to be completed at the conclusion of the initial hematology visit. The hematologist also completed survey data at that time. Survey data forms included demographic form, physician form, Peds QL Family Impact Questionnaire, Kids ITP tools (KIT) Parent Impact Report and parent proxy report, and child (patient) KIT self-report. There was a parent questionnaire which included a question about worry with a scale from 0 to 10. Study data were collected and managed using REDCap electronic data capture tools hosted at Atlantic Health System. Correlation between variables were calculated using Pearson coefficient or Spearman's rho depending on the distribution of the data variables. Results: Sixty subjects and caregivers were enrolled at 6 ICON centers; 52 were eligible for inclusion. The majority (40%) had Grade 1 bleeding. Most patients (82%) were seen in outpatient hematology clinic by the hematologist and had been referred by the emergency room (73%). The median time to consultation with a hematologist from onset of symptoms was 7 days (1-199) and the median time to diagnosis by hematologist from initial contact with a health care provider was 5 days (0-154). Most subjects had seen 2 health care providers prior to the hematologist. KIT proxy report cumulative scores were a mean of 76.03 (SD 14.72). There was no significant difference between the time to diagnosis or the time from initial encounter with health care provider to hematologist and initial level of worry (p=0.70 and 0.90, respectively). There was also no significant difference between the time to diagnosis or the time from initial encounter with health care provider to hematologist and KIT proxy scores (p=0.96 and 0.50, respectively). However, there was a significant decline in level of worry (scale 0-10) prior to the hematologist visit (median 8, range 1-10) to after the visit (median 4, range 1-10). The association between number of medical providers encountered prior to diagnosis and KIT proxy scores was not significant (p=0.45) (Table). Conclusions: In this study at 6 teaching institutions, we were unable to detect a significant difference in proxy-reported KIT scores relative to the number of health care providers seen or time from diagnosis until the first encounter with the hematologist. We were, however, able to detect a significant change in the level of caregiver worry pre- and post- visit with the pediatric hematologist, supporting a benefit of specialist care to the caregivers of children with ITP. This study was limited by its small sample size and retrospective design. ITP is considered a benign disease but is associated with a significant amount of worry and impact on QoL for patients and caregivers which warrants further investigation. Disclosures Lambert: CSL Behring: Consultancy; Amgen: Consultancy, Other; Bayer: Other: Ad boards; Novartis: Other: Ad boards, Research Funding; Shionogi: Consultancy; Kedrion: Consultancy; Sysmex: Consultancy; AstraZeneca: Research Funding; PDSA: Research Funding. Grace:Agios Pharmaceuticals, Inc: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: 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)0,001
score de la tête « metaresearch » (Gemma)0,011
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 enseignants0,014
Score d'incertitude au seuil0,028

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,011
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,000
Communication savante0,0010,000
Science ouverte0,0000,001
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

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 Opus0,009
Tête enseignante GPT0,259
Écart entre enseignants0,250 · 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

Citations1
Publié2019
Routes d'admission1
Résumé présentoui

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