Condition‐related predictors of successful transition from paediatric to adult care among adolescents with Type 1 diabetes
Bibliographic record
Abstract
AIMS: To describe patient attendance for adult treatment after completion by young people of a structured Diabetes Transition Clinic and to identify the predictors of non-attendance at adult clinics by young people with Type 1 diabetes transitioning from paediatric care. METHODS: Young people with Type 1 diabetes were consecutively enrolled on a Diabetes Transition Clinic programme at a Canadian paediatric teaching hospital, beginning in December 2007. Data from clinical interviews completed by an adolescent medicine specialist and an adult endocrinologist were prospectively collected at the Diabetes Transition Clinic visit in the patient's 18(th) year, before he/she was transferred at age 18 years to the adult clinic and at the first adult clinic visit. RESULTS: As of June 2011, 136 young people participating in the Diabetes Transition Clinic programme had been discharged from paediatric care at least 1 year earlier. Of these, 43 participants were lost to follow-up. Loss to follow-up was more frequent among: those who were diagnosed with diabetes before the age of 12 years; those who were taking insulin twice or three times daily rather than by pump or multiple daily injections; those who had higher HbA1c levels; those who had fewer diabetes physician visits in the year preceding the Diabetes Transition Clinic visit; and those who did not ask questions at the Diabetes Transition Clinic visit. CONCLUSIONS: Several factors easily ascertained at a clinical encounter before transition can predict the likelihood of attendance in adult care, including age at diagnosis, mode of insulin administration, frequency of physician visits, and questions asked by patients during a transition visit.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".