Longitudinal Estimated Glomerular Filtration Rate Trajectories in Children with Type 1 Diabetes
Bibliographic record
Abstract
Although children with type 1 diabetes (T1D) are at risk for developing diabetic kidney disease (DKD), clinical practice guidelines do not uniformly recommend routine serum creatinine (SCr) monitoring, and data describing changes in renal function from diagnosis are lacking. As part of a quality improvement initiative, the Diabetes Clinic at British Columbia Children’s Hospital in Vancouver, Canada, implemented routine serum SCr monitoring. This study describes estimated glomerular filtration rate (eGFR) trajectories and prevalence of decreased eGFR, hypertension, and albuminuria and their relationship to patterns of nephrology referral in a cohort of children aged ≤18 years (n = 307) with T1D recruited between December 2016 and February 2019. Annualized eGFR (ml/min/1.73 m2 per year) was calculated using the CKiD U25 formula and categorized as declining (<−3), stable (−3 to +3), and inclining (>+3). eGFR was categorized as normal (≥90), mildly decreased (60 to <90), and chronic kidney disease (CKD, <60). In this cohort, 54% were male; the median age at diagnosis and duration of T1D was 6.2 years and 6.9 years, respectively. Over a median follow-up of 2.3 years, declining, stable, and inclining trajectories were observed in 33%, 32%, and 35%, respectively. During their follow-up, 32% had mildly decreased eGFR, elevated blood pressures (≥90th percentile), and/or abnormal urine albumin-creatinine ratios (≥2 mg/mmol), with <10% referred for nephrology assessment. Twenty-three percent of subjects had an eGFR <90; this subgroup was more highly represented in the declining trajectory group (vs. stable and inclining). Logistic regression analysis found female sex and higher baseline eGFR to be associated with a declining eGFR trajectory. In conclusion, these data challenge the commonly held paradigm that renal function remains stable in childhood T1D and supports systematic monitoring of renal function in children with T1D, as well as collaboration across disciplines, particularly endocrinology and nephrology, to provide evidence-based individualized care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".