Metabolic Acidosis Is a Predictive Factor for All-Cause Mortality in Patients with CKD
Bibliographic record
Abstract
Background: The consequences of metabolic acidosis are wide-ranging, consistent with the fact that many critical cell functions require physiologic pH (Salameh AI, Am J Physiol Regul Integr Comp Physiol. 2014). The extent to which metabolic acidosis contributes to mortality in patients with chronic kidney disease (CKD) is unknown. Methods: Optum® de-identified Electronic Health Records dataset 2007 to 2017 was queried to identify patients with non-dialysis CKD Stages 3-5 with ≥2 consistent 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 baseline serum bicarbonate (12 to < 22 mEq/L or 22 - 29 mEq/L). All-cause mortality was measured at 2 years in patients with metabolic acidosis vs. normal serum bicarbonate at baseline. The impact of baseline serum bicarbonate on 2-year mortality, 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) was evaluated using logistic regression models. Results: 51,558 patients qualified for analysis; 17,350 with metabolic acidosis, 34,208 with normal serum bicarbonate at baseline. Unadjusted rates of mortality within 2 years were higher among patients with metabolic acidosis vs. normal serum bicarbonate (30.9% vs. 10.2%, respectively, P< 0.0001) and within all CKD stages (P< 0.001). Each 1 mEq/L lower serum bicarbonate value was independently associated with a 15% higher risk of all-cause mortality, OR: 0.853, 95% CI: 0.846-0.861. These findings were consistent in subgroup and sensitivity analyses. Conclusions: The presence of metabolic acidosis was associated with a high 2-year risk of all-cause death in patients with CKD. 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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".