Estimated Net Endogenous Acid Production and Serum Bicarbonate in African Americans with Chronic Kidney Disease
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Metabolic acidosis may contribute to morbidity and disease progression in patients with chronic kidney disease (CKD). The ratio of dietary protein, the major source of nonvolatile acid, to dietary potassium, which is naturally bound to alkali precursors, can be used to estimate net endogenous acid production (NEAP). We tested the association between estimated NEAP and serum bicarbonate in patients with CKD. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: NEAP was estimated among 462 African American adults with hypertensive CKD using published equations: NEAP (mEq/d) = -10.2 + 54.5 (protein [g/d]/potassium [mEq/d]). Dietary protein and potassium intake were estimated from 24-hour urinary excretion of urea nitrogen and potassium, respectively. All of the eligible measurements during follow-up were modeled using generalized linear regression clustered by participant and adjusted for demographics, 24-hour urinary sodium, kidney function, and selected medications. RESULTS: Higher NEAP was associated with lower serum bicarbonate in a graded fashion (P trend < 0.001). Serum bicarbonate was 1.27 mEq/L lower among those in the highest compared with the lowest quartile of NEAP (P < 0.001). There was a greater difference in serum bicarbonate between the highest and lowest quartiles of NEAP among patients with stage 4/5 CKD (-2.43 mEq/L, P < 0.001) compared with those with stage 2/3 disease (-0.77 mEq/L, P = 0.01; P-interaction = 0.02). CONCLUSIONS: Reducing NEAP, through reduction of dietary protein and increased intake of fruits and vegetables, may prevent metabolic acidosis in patients with CKD.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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