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Record W4411292903 · doi:10.2337/db25-1220-p

1220-P: Bridge Into Adulthood—Global Practice on Transitioning Youth with Type 1 Diabetes from Pediatric to Adult Care—Findings from SWEET Database and Center Survey

2025· article· en· W4411292903 on OpenAlexaboutno aff
Barbara Piccini, Reinhard W. Holl, FAISAL MALIK, Carine de Beaufort, Nancy Samir Elbarbary, Violeta Iotova, Christina Kanaka‐Gantenbein, Joseph Leung, Jawad Mirza, Lukana Preechasuk, Sonia Toni

Bibliographic record

VenueDiabetes · 2025
Typearticle
Languageen
FieldHealth Professions
TopicAdolescent and Pediatric Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)Center (category theory)Type 1 diabetesMedicinePediatricsFamily medicineDiabetes mellitusEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

Introduction and Objective: The transition process from pediatric to adult type 1 diabetes (T1D) care is poorly explored. We aimed to assess transition for youth living with T1D worldwide. Methods: SWEET (Better control in Pediatric and Adolescent diabeteS: Working to crEate CEnTers of Reference) database was analyzed (2016-2023, centers >20 patients, > 5-year data). Transfer was assumed in T1D patients 14-24 years with no visits for ≥2 years. Age at transfer was evaluated across regions. A survey developed by pediatric and adult diabetologists was distributed to all SWEET centers. Results: Among 33,418 transferred patients (104 centers, 51% male), age at T1D transfer was 18.7 years in Asia/Middle East/Africa, 18.4 in North America/Canada, 18.0 in Europe, 17.2 in Australia/New Zealand and 17.0 in South America (p <0.0001). Female gender and higher HbA1c were associated with earlier transfer (- 0.1 year, p <0.0002; - 0.08, p <0.0001), longer duration and larger centers with later transfer (p <0.0001). Of 160 surveyed centers, 79 responded: 43 in Europe, 20 Asia/Middle East/Africa, 8 North America, 6 South America, 2 Australia/New Zealand, 87% academic, 74% exclusively pediatric, 57% with age limit for pediatric care reimbursement. Annually, 80% of centers transferred <50 patients; 13% of centers transferred at 20+ years, 41% at 18-20, 27% at 16-18 and 9% at 14-16 years (no transfer: 6%). Structured transition was absent in 34% of centers. Key drivers for transfer included age (83% of centers), reimbursement policies (8%) and patient request (4%). Metabolic control (60%), psychiatric comorbidity (63%) and teen pregnancy (59%) influenced transfer, while technology use and T1D complications did not. Conclusion: This study highlights the global variability in T1D transition and the lack of structured transition in many centers. More efforts are needed to enhance transition preparation and a successful transfer for youth with T1D. Disclosure B. Piccini: Advisory Panel; Sanofi. R.W. Holl: None. F. Malik: None. C. de Beaufort: None. N.S. Elbarbary: None. V. Iotova: Other Relationship; Pfizer Inc, Novo Nordisk, AstraZeneca, Rezolute Bio, Medtronic, Novartis Pharmaceuticals Corporation, Novo Nordisk. C. Kanaka-Gantenbein: Research Support; Abbott, Amgen Inc. Advisory Panel; Kyowa Kirin Co., Ltd. Research Support; Novo Nordisk. Advisory Panel; Pfizer Inc, Sanofi. H. Kim: None. J.M. Leung: None. J. Mirza: None. L. Preechasuk: None. S. Toni: Consultant; Abbott. Advisory Panel; Sanofi.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.005
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.034
GPT teacher head0.367
Teacher spread0.332 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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