Weight loss and proteinuria: systematic review of clinical trials and comparative cohorts
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Obesity is a risk factor for the progression of chronic kidney disease (CKD). The impact of weight loss on proteinuria and renal function is less clear. We aimed to determine the effect of intentional weight loss on proteinuria and kidney function. METHODS: Three bibliographic databases including Medline, Cochrane and SCUPOS as well as reference list of articles were searched. We included randomized and non-randomized controlled trials as well as single-arm trials published in English through May 2009 which examined urinary protein among obese or overweight adults before and after weight loss interventions including dietary restriction, exercise, anti-obesity medications and bariatric surgery. Study characteristics and methodological quality of trials were assessed. RESULTS: Five hundred twenty-two subjects from five controlled and eight uncontrolled trials were included. Weight loss interventions were associated with decreased proteinuria and microalbuminuria by 1.7 g [95% confidence interval (95% CI), 0.7 to 2.6 g] and 14 mg (95% CI, 11 to 17 mg), respectively (P < 0.05). Meta-regression showed that, independent of decline in mean arterial pressure, each 1 kg weight loss was associated with 110 mg (95% CI, 60 to 160 mg, P < 0.001) decrease in proteinuria and 1.1 mg (95% CI, 0.5 to 2.4 mg, P = 0.011) decrease in microalbuminuria, respectively. The decrease was observed across different designs and methods of weight loss. Only bariatric surgery resulted in a significant decrease in creatinine clearance. CONCLUSIONS: Weight loss is associated with decreased proteinuria and microalbuminuria. There were no data evaluating the durability of this decrease or the effect of weight loss on CKD progression.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it