Effect of exercise on albuminuria in people with diabetes
Bibliographic record
Abstract
Aim: Spot urine measurement of albumin is now the most commonly accepted approach to screening for proteinuria. Exertion prior to the collection may potentially influence the result of spot urine albumin estimation. We aim to evaluate the effect of exercise on albuminuria in subjects at various stages of diabetic nephropathy in comparison with healthy control volunteers. Methods: Thirty-five people with diabetes (19 with normoalbuminuria (NA), nine with microalbuminuria (MA) and seven with overt proteinuria (OP)) and nine control subjects were assessed. A 1 km treadmill walk was performed. Four spot urine specimens were collected: first morning void, immediately prior to exercise, and 1 h and 2 h after exercise. A random effects linear regression mixed model was used to assess the effect of exercise on albumin/creatinine ratio (uACR). Results are presented separately for male and female subjects with diabetes due to a significant exercise/ gender interaction (P < 0.05). Results: No significant effect of exercise on uACR was seen in control subjects. In NA males with diabetes no effect of exercise was seen, while in females uACR 1 h after exercise was significantly higher than the early morning sample (3.55 mg/mmol (96% confidence interval 0.27‐6.83). Both female and male diabetes subjects with MA have increase in uACR 1 h after exercise (87.8, -24.3‐199.4 and 6.7, 2.1‐11.3). For both males and females with OP, uACR was significantly increased 1 h post exercise (67.5, 22‐113 and 21.6, 8.4‐34.8, respectively). In all groups uACR at 2 h after exercise was not significantly different to the early morning sample. Conclusions: Exercise increased uACR estimation in normoalbuminuric subjects with diabetes with a larger effect in females. Whether exercise unmasks early diabetic nephropathy in NA subjects requires further study.
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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 | 0.001 |
| 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) | 0.001 | 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".