ODP206 High Burden of Chronic Kidney Disease in Young Adults with Type 1 Diabetes
Bibliographic record
Abstract
Abstract Background Type 1 diabetes (T1D) increases the risk of chronic kidney disease (CKD). We sought to assess the burden of CKD and albuminuria, and risk factors contributing to CKD development. Methods This retrospective cohort study (1996-2020) involved Canadian adults diagnosed with T1D before 30 years of age, followed in a sub-speciality clinic in British Columbia. CKD was defined as an estimated GFR <60 ml/min/1.73 m 2 and persistent albuminuria was defined as a urine albumin-to-creatinine ratio (ACR) ≥2 mg/mmol (≥2 measurements over 6 months). Logistic regression was used to describe the relationship between CKD and diabetes-related risk factors. Results Of the 268 adults followed in the clinic, 63.4% were male, and the median age at diagnosis of T1D was 13.7 years (IQR 11.9 years). Over a median duration of T1D of 27.1 years (IQR 21.2 years), 8.2% of the adults developed CKD and 32.5% developed albuminuria (19.8% ACR 2-20 mg/mmol, 12.7%≥20 mg/mmol). Five adults went on to develop end-stage renal disease within the follow-up period. A longer duration of T1D (≥30 years) was associated with 4-fold increase in the odds of developing CKD (odds ratio 4. 09, 95% CI 1.37-15.10). History of medical and psychiatric comorbidities, A1C≥7%, systolic blood pressure ≥130 mmHg, and ACR ≥2 mg/mmol were also associated with greater odds of developing CKD. Conclusion In this contemporary Canadian cohort of young adults with T1D, CKD and albuminuria are common. Contributing risk factors include comorbid medical and psychiatric conditions, suboptimal glycemic control, systolic hypertension, and albuminuria. Presentation: No date and time listed
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".