Metabolic Acidosis and Progression to Renal Replacement Therapy
Bibliographic record
Abstract
Background: Metabolic acidosis is common in advanced chronic kidney disease (CKD) and is associated with its progression (Kraut J, Adv Chronic Kidney Dis. 2017). Methods: De-identified electronic health records (Optum® EHR), 2007 to 2017 were queried to identify patients with non-dialysis CKD Stages 3-5 with ≥2 serum bicarbonate tests 28-365 days apart, ≥3 eGFR values <60 mL/min/1.73 m2 and ≥2 years of post-index data or who died during that period. Cohorts with metabolic acidosis and normal serum bicarbonate were established based on the index serum bicarbonate (< 22 mEq/L or 22 - 29 mEq/L). Progression to RRT was defined as initiation of dialysis or kidney transplantation, identified in EHR data by diagnosis or procedure codes, or eGFR ≤ 9 mL/min/1.73 m2. We evaluated the impact of baseline serum bicarbonate on RRT initiation, adjusted for age, sex, race, diabetes, hypertension, heart failure, Charlson Comorbidity Score (index of comorbidity burden), and baseline eGFR and log albumin-to-creatinine ratio (ACR) using logistic regression models (2-year outcome period) and Cox proportional hazards models (up to 10 years). Results: 51,558 patients qualified for analysis; 17,350 with metabolic acidosis, 34,208 with normal serum bicarbonate at baseline. Unadjusted rates of progression to RRT within 2 years were higher among patients with metabolic acidosis vs. normal serum bicarbonate overall (19.6% vs. 5.5%, respectively, p< 0.001) and at all baseline CKD stages (p< 0.001) except stage 5 (p=0.4). Each 1 mEq/L increase in serum bicarbonate between 12 and 29 mEq/L was associated with a 2.5% decrease in the 2-year risk of initiating RRT, (OR: 0.975, 95% CI: 0.965, 0.985), and a 4.5% decrease in risk up to 10 years (HR: 0.955, 95% CI: 0.948, 0.963). Conclusions: The presence of metabolic acidosis was associated with an increased risk of CKD progression to dialysis or kidney transplantation. This finding was independent of age, sex, race, pre-existing comorbidities, and baseline eGFR and ACR. Funding: Commercial Support - Tricida, Inc.
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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 | 0.007 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".