Identifying a retrospective cohort of adolescents with chronic health conditions from a paediatric hospital prior to transfer to adult care: the Calgary Transition Cohort
Bibliographic record
Abstract
PURPOSE: The Calgary Transition Cohort was created to examine health service utilisation by adolescents affected by chronic health conditions seen in a tertiary paediatric hospital in the province of Alberta, Canada. The cohort includes adolescents who received care before the implementation of a hospital-wide intervention to improve transitions to adult care. PARTICIPANTS: Using hospital records, a stepwise methodology involving a series of algorithms based on adolescents' visit frequency to a hospital ambulatory chronic care clinic (CCC) was used to identify the cohort. A visit frequency of ≥4 visits in any 24-month window, during the ages of 12-17 years old, was used to identify eligible adolescents, as agreed on by key stakeholders and chronic disease clinical providers, and reflects the usual practice at the hospital for routine care of children with chronic disease. FINDINGS TO DATE: Adolescents with ≥4 visits to the same CCC in any 2-year period (n=1344) with a median of 8.7 years of follow-up data collected (range 1.4-9.1). The median age at study entry was 14 years (range 12-17) and 22 years (range 14-24) at study exit. The cohort was linked (97% successful match proportion) to their population-level health records that allowed for examination of occurrence of chronic disease codes in health utilisation encounters (ie, physician claims, hospital admissions and emergency room visits). At least one encounter with a chronic disease code (International Classification of Diseases, 9th/10th Revisions) was observed during the entire study window in 87.9% of the cohort. FUTURE PLANS: The Calgary Transition Cohort will be used to address existing knowledge gaps about health service utilisation by adolescents, seen at a tertiary care hospital, affected by a broad group of chronic health conditions. These adolescents will require transition to adult-oriented care. Longitudinal analysis of health service use patterns over a 9-year window (2008-2016) will be conducted.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".