THU129 Age At Last Pediatric Type 1 Diabetes Visit Predicts A Successful Transition To Adult Diabetes Care
Notice bibliographique
Résumé
Abstract Disclosure: J.M. Leung: None. L. Chen: None. J. Bone: None. D.A. Fox: None. Q. Zhang: None. S. Amed: None. Introduction: Adolescents with type 1 diabetes are known to experience a substantial gap when transitioning from pediatric to adult care.1 We have previously validated a pediatric diabetes case definition and differentiating algorithm to create an administrative cohort of individuals diagnosed with type 1 diabetes using linked provincial administrative health data (physician billing, hospital discharge abstracts, and pharmacy dispensations) from British Columbia, Canada. 2 The objective of this study was to identify predictors of successful transition from pediatric to adult diabetes care within this cohort. Methods: Using our administrative cohort, we isolated adolescents who were diagnosed with type 1 diabetes between the ages of 0.5 to 18 years in 1992-2020. We excluded individuals whose last healthcare encounter was at age <14 years (i.e. individuals who had not yet reached adolescence) at the time of data acquisition (2020). Last pediatric visit before transition (LPVBT) was defined as the date of last billing by a pediatrician. First adult visit after transition (FAVAT) was defined as the date of first billing by an adult medicine specialist. We determined age at LPVBT and we calculated duration between LPVBT and FAVAT. ‘Successful transition’ was defined as ≤1 year between LPVBT and FAVAT. We fit logistic regression models to determine predictors of successful transition. Results: We identified 3660 adolescents who were diagnosed with type 1 diabetes in pediatric care. 1615 (44.1%) did not have any adult diabetes visits, while 2045 (55.9%) had one or more adult diabetes visits. Of these, 1405 (38.4%) had FAVAT >1 year after LPVBT and only 640 (17.5%) had a duration between LPVBT and FAVAT of ≤1 year (i.e. successful transition). The mean duration between LPVBT and FAVAT was 3.70 years (median 2.46, IQR = 0.68-5.45). For every 1-year increase in the age at LPVBT, there was an increased odds of successful transition in both the unadjusted analysis (OR 1.809, 95% confidence interval (CI) 1.704-1.925, p<0.001) and when adjusted for sex, age at diagnosis, and urban-rural residency (OR 1.816, 95% CI 1.709-1.933, p<0.001). Those who successfully transitioned were older at their LPVBT (17.74 years, 95% CI 17.62-17.85) compared to those who did not successfully transition (15.10 years, 95% CI 14.99-15.21). Conclusion: Adolescents with type 1 diabetes who remain in pediatric care until at least age 17 are more likely to transition successfully to adult care. Conversely, those who leave pediatric care prematurely are less likely to experience a successful transition. These findings suggest that a key area of focus to improve the transition from pediatric to adult diabetes care is ensuring that youth remain engaged in pediatric care as close to the age of transition as possible. References: 1. Garvey et al. Endocr Pract. 2013;19(6):946-52. 2. Vanderloo et al. Pediatr Diabetes. 2012;13(3):229-34. Presentation: Thursday, June 15, 2023
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 | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,009 | 0,001 |
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.
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 ».