Atypical complications and co-morbidities of type 1 diabetes in young adults
Bibliographic record
Abstract
AIMS: Our review aimed to determine the prevalence of - and factors associated with - hearing loss, oral and olfactory disease, frozen shoulder, trigger finger, and hair loss in young adults with type 1 diabetes. These conditions were selected based on research team interests, existing literature, and group discussion. METHODS: We conducted a quantitative narrative review using a systematic process to identify cohort and cross-sectional studies involving young adults with type 1 diabetes (mean age 18-30 years). PubMed, CINAHL, and Cochrane were searched (January 2000-February 2024). Grey literature was not restricted, and quality appraisal was undertaken. Extracted data were synthesised and summarised narratively. RESULTS: The initial search found 3924 records and after title, abstract and full-text review, 19 records met inclusion criteria. Hearing loss prevalence ranged from 22.6 to 48.0 %, with age, diabetes duration, and systolic blood pressure identified as prominent associated features. For oral disease, peridontitis prevalence was 4.7 %, while alveolar bone loss ranged from 24.6 to 43.9 %; age was the primary associated factor. No eligible data were identified regarding frozen shoulder, trigger finger, or hair loss. CONCLUSIONS: Further research is needed to characterize the prevalence and risk factors of atypical complications in type 1 diabetes. Clinical care should be guided by a robust understanding of these under-recognised comorbidities.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".