Demographic and socioeconomic patterns in the risk of alcohol‐related hospital admission in children and young adults with childhood onset type‐1 diabetes from a record‐linked longitudinal population cohort study in Wales
Bibliographic record
Abstract
BACKGROUND: Little is known about alcohol-related harm in children and young adults with type 1 diabetes (T1D). Education on managing alcohol intake is provided to teenagers with T1D in paediatric clinics in Wales, but its effectiveness is unknown. We compared the patterns in risk of alcohol-related hospital admissions (ARHA) between individuals with and without childhood-onset T1D. METHODS: We extracted data for 1 791 577 individuals born during 1979 to 2014 with a general practitioner registration in Wales, and record-linked the demographic data to ARHA between 1998 and June 2016 within the Secure Anonymised Information Linkage Databank (SAIL). Linkage to a national T1D register (Brecon Cohort) identified 3575 children diagnosed aged <15 years since 1995. We estimated hazard ratios (HRs) with 95% confidence intervals (95% CIs) for the risk of ARHA using recurrent-event models, including interaction terms. RESULTS: Individuals with T1D had a higher riskof ARHA (HR: 1.78; 95% CI: 1.60-1.98), adjusted for age group, sex, and deprivation. The risk in people with diabetes was highest aged 14 to 17 years, around three times higher than the peak in non-T1D aged 18 to 22. Females with diabetes had a lower risk generally. The association between deprivation and ARHA was weaker in the T1D group. CONCLUSION: Young people with T1D had increased risks of ARHA, particularly at school age, and smaller socioeconomic inequalities in ARHA. A review of interventions to reduce alcohol-related harm in T1D is needed, perhaps including modification of current education and guidance for teenagers on managing alcohol consumption and reviewing criteria for hospital admission.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".