The Association of Metabolic Acidosis with AKI in Patients with CKD: A Retrospective Cohort Study in Two Cohorts
Bibliographic record
Abstract
Background: Metabolic acidosis in patients with chronic kidney disease (CKD) results from a loss of kidney function. It has been associated with more rapid CKD progression, all-cause mortality, and other adverse outcomes. Whether metabolic acidosis is associated with a higher risk of acute kidney injury (AKI) remains unknown. Methods: We conducted a retrospective cohort study in 2 North American cohorts (US EMR cohort and Manitoba Claims cohort) using electronic health records and administrative data of patients with CKD Stages G3-G5. The primary exposure was metabolic acidosis (serum bicarbonate between 12 and <22 mEq/L), and the primary outcome of interest was the development of AKI (defined using ICD-9 and 10 codes at hospital admission or a laboratory-based definition based on KDIGO guidelines). We applied Cox proportional hazards regression models adjusting for common demographic and clinical characteristics. Results: In both cohorts, metabolic acidosis was associated with AKI: HR 1.565 (95% CI 1.518 - 1.613) in the US EMR cohort and HR 1.652 (95% CI 1.578 - 1.729) in the Manitoba Claims cohort. The association was consistent when serum bicarbonate was treated as a continuous variable, and in multiple subgroup and sensitivity analyses including those adjusting for albuminuria. Conclusions: Metabolic acidosis is associated with a higher risk of AKI in patients with CKD. AKI should be considered as a safety outcome in studies of treatments for patients with metabolic acidosis. 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 | 0.001 | 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 | 0.000 |
| 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".