13-LB: Measured vs. Estimated GFR in Young Adults with Uncomplicated T1D
Bibliographic record
Abstract
Background: eGFR equations are used to monitor progression of kidney disease, but their performance is incompletely understood in young adults with T1D and preserved GFR. To address this deficit, we compared two eGFR equations (creatinine-based CKD-EPI and modified Schwartz) to mGFR in this population.Methods: GFR based on plasma iohexol clearance was measured in 53 patients (24 males) with T1D, as part of the CAN-SOLVE CKD studyResults: Mean age was 20.6±2.1 yrs with mean diabetes duration of 13.1±3.3 yrs. Mean HbA1c and ACR were 8.1±1.3 and 1.6±1.9 mg/mmol, respectively. Mean mGFR was 107.6±15.9 ml/min/1.73 m2. The Schwartz eGFR had a smaller mean bias (5.6 vs. 27.4 ml/min/1.73m2), better accuracy, and overall correlation compared to the CKD-EPI eGFR, while the latter had slightly superior precision. However, both equations were in poor agreement with mGFR. Examination of the Bland Altman plots reveals that, in the lower normal range, the CKD-EPI equation overestimated mGFR. The modified Schwartz equation showed no discernible tendencies.Conclusion: In young adults with T1D and preserved GFR, the modified Schwartz eGFR performed slightly better than CKD-EPI eGFR. Overall, however, both were in poor agreement with mGFR suggesting caution about the use of eGFR as a surrogate outcome in longitudinal studies and emphasizing the need to develop novel equations for this population.View largeDownload slideView largeDownload slide DisclosureK. Gaebe: None. C. A. White: None. F. H. Mahmud: Advisory Panel; Self; Insulet Corporation, Lilly Diabetes. J. W. Scholey: None. L. Motran: None. M. Palaganas: None. Y. T. Elia: None. D. Cherney: Other Relationship; Self; AbbVie Inc., AstraZeneca, Bayer AG, Boehringer Ingelheim International GmbH, Janssen Scientific Affairs, LLC., Lilly Diabetes, Merck & Co., Inc., Mitsubishi-Tanabe, Maze Inc, Prometic, Novo Nordisk, Sanofi. E. B. Sochett: None.FundingCanadian Institutes of Health Research (20R26070); JDRF
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".