Stenosis of the Glomerulotubular Neck Is Associated with Progressive CKD
Bibliographic record
Abstract
Background: Histopathologic evaluation can clarify the pathophysiology of chronic kidney disease (CKD). We tested whether the occurrence of glomerulotubular neck stenoses associates with progressive CKD. Methods: We evaluated the non-cancerous parenchyma from radical nephrectomies for tumor between 2000 and 2021 and analyzed the cortex for stenoses of the glomerulotubular neck. Stenosis was defined as a focal narrowing at the neck for which the draining tubule had a greater diameter than at the neck (Figure 1B). Progressive CKD was defined as dialysis, kidney transplantation, sustained eGFR <10 ml/min per 1.73m2 or sustained 40% decline from the post-nephrectomy eGFR during follow-up. Each case of progressive CKD was age-sex-matched to 2 controls without progressive CKD. Logistic regression models assessed the risk of progressive CKD with stenotic necks adjusting for other histological features, kidney function, and CKD risk factors. Results: There were 65 cases with a mean of 255 glomeruli and 130 controls with a mean of 329 glomeruli. Among both cases and controls, 5% of glomeruli showed visible glomerulotubular necks. The proportion of necks that were stenotic was higher in cases than controls (35% vs. 11%, p<0.0001). Stenotic necks associated with progressive CKD independent of other histologic and clinical characteristics. ROC curvesfor histological morphometric measures showed that the proportion of stenotic necks was superior to glomerular volume, %GSG, and % IFTA as a classifier for predicting progressive CKD (Figure 1C). Conclusion: Glomerulotubular neck stenosis predicts progressive CKD. Funding: NIDDK Support, Veterans Affairs SupportRepresentative images of glomerulotubular necks that are A) normal (non-stenotic), and B) stenotic. C) ROC curves for histological pathology by morphometry as a classifier for subsequent progressive CKD among patients who underwent radical nephrectomy for tumor. The area under the curve (AUC) was 0.847 (95%CI: 0.776 to 0.917) for % stenotic glomerulotubular necks, 0.715 (95%CI: 0.638 to 0.793) for glomerular volume, 0.707 (95%CI: 0.623 to 0.790) for % globally sclerotic glomeruli (%GSG), and 0.695 (95%CI: 0.617 to 0.772) for % interstitial fibrosis and tubular atrophy (%IFTA).
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".