Relationship between Glomerular Filtration Rate and the Prevalence of Metabolic Abnormalities: Results from the Third National Health and Nutrition Examination Survey (NHANES III)
Bibliographic record
Abstract
BACKGROUND AND AIMS: National Kidney Foundation Kidney Disease Outcomes Quality Initiative (KDOQI) guidelines recommend that all people with a glomerular filtration rate (GFR) <60 ml/min/1.73 m(2) undergo evaluation for anaemia and metabolic bone disease. We aim to report the prevalence of metabolic complications in adults with low GFR. METHODS: Analysis of 15,802 non-institutionalised adult participants in the Third National Health and Nutrition Survey (NHANES III), a cross-sectional population-based survey conducted in the United States between 1986 and 1994. Renal function was estimated according the modification of diet in renal disease equation 7 (MDRD GFR), the Cockcroft-Gault formula and by the serum creatinine cut-off points described by Couchoud and colleagues. Haemoglobin <110 g/l occurred in 42.2% [95% confidence interval (CI) 28.3-56.0] of patients with MDRD GFR <30 ml/min/1.73 m(2) [stage 3 chronic kidney disease (CKD)] and 3.5% (95% CI 2.4-4.7) of patients with MDRD GFR between 30 and 60 ml/min/1.73 m(2) (stage 4-5 CKD). Corresponding prevalences for calcium <2.15 mmol/l were 8.2 (95% CI 1.6-14.8) and 3.4 (95% CI 1.7-5.2); for phosphate >1.6 mmol/l, 15.1 (95% CI 5.0-25.3) and 0.3 (95% CI 0-0.6); and for bicarbonate <23 mmol/l, 32.7 (95% CI 19.6-45.9) and 5.7 (95% CI 3.3-8.2), respectively. Similar results were obtained when patients were categorised by the Cockcroft-Gault formula or Couchoud's cut-off points. CONCLUSIONS: The prevalence of complications in stage 3 CKD is low. These data do not support the recommendation for routine screening for metabolic complications of renal insufficiency in adults seen in primary care settings whose GFR exceeds 30 ml/min/1.73 m(2).
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".