Association of kidney function with anemia: the Third National Health and Nutrition Examination Survey (1988-1994).
Bibliographic record
Abstract
BACKGROUND: Kidney failure is known to cause anemia, which is associated with a higher risk of cardiac failure and mortality. The impact of milder decreases in kidney function on hemoglobin levels and anemia in the US population, however, is unknown. METHODS: We analyzed a population-based sample of 15419 participants 20 years and older in the Third National Health and Nutrition Examination Survey, conducted from 1988 to 1994. RESULTS: Lower kidney function was associated with a lower hemoglobin level and a higher prevalence and severity of anemia below, but not above, an estimated glomerular filtration rate (GFR) of 60 mL/min per 1.73 m(2). Adjusted to the age of 60 years, the predicted median hemoglobin level among men (women) decreased from 14.9 (13.5) g/dL at an estimated GFR of 60 mL/min per 1.73 m(2) to 13.8 (12.2) g/dL at an estimated GFR of 30 mL/min per 1.73 m(2) and to 12.0 (10.3) g/dL at an estimated GFR of 15 mL/min per 1.73 m(2). The prevalence of anemia (hemoglobin level <12 g/dL in men and <11 g/dL in women) increased from 1% (95% confidence interval, 0.7%-2%) at an estimated GFR of 60 mL/min per 1.73 m(2) to 9% (95% confidence interval, 4%-19%) at an estimated GFR of 30 mL/min per 1.73 m(2) and to 33% (95% confidence interval, 11%-67%) at an estimated GFR of 15 mL/min per 1.73 m(2) among men and to 67% (95% confidence interval, 30%-90%) at an estimated GFR of 15 mL/min per 1.73 m(2) among women. An estimated GFR of 15 to 60 mL/min per 1.73 m(2) was present in 4% of the entire population and in 17% of the individuals with anemia. CONCLUSION: Below an estimated GFR of 60 mL/min per 1.73 m(2), lower kidney function is strongly associated with a higher prevalence of anemia among the US adult population.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".