Obesity-Related Glomerulopathy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Obesity-related glomerulopathy (ORG) is an increasing cause of end-stage renal disease, but evidence concerning the effects of treatments is rather limited. This study was aimed at exploring the renoprotective effects of weight loss on patients with ORG. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A total of 63 patients with renal biopsy-proven ORG had food and exercise intervention in the physician-supervised weight loss program and were divided into three groups on the basis of the percentage of weight change from baseline to follow-up: significant weight loss (>3% reduction in body mass index [BMI]), stable weight, or significant weight gain (>3% increase). Metabolic parameters and renal lesions were evaluated regularly for 2 years. RESULTS: After 6 months, 27 patients lost weight by 8.29 +/- 4.00%, with a mean decrease in proteinuria of 35.3%, whereas 24 months later, 27 patients achieved a 9.20 +/- 3.78% reduction in BMI and a 51.33% reduction in urine protein secretion. The levels of serum triglyceride, serum uric acid, and BP were also decreased. Contrarily, in patients with increased BMI, urine protein was increased by 28.78%. Correlation analysis showed proteinuria was associated with BMI, serum triglyceride, and uric acid, and multivariate regression analysis indicated the changes in BMI were the only predictor of proteinuria (P < 0.01). CONCLUSIONS: Weight loss intervention benefited remission of proteinuria in patients with ORG, whose function could not be replaced by conventional pharmacotherapy.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".