Metabolic Acidosis and Adverse Outcomes and Costs in CKD: An Observational Cohort Study
Bibliographic record
Abstract
Rationale & Objective Metabolic acidosis is a risk factor for progression of chronic kidney disease (CKD), but little is known about its effect on health care costs and resource utilization. We describe the associations between metabolic acidosis, adverse kidney outcomes, and health care costs in patients with CKD stages G3-G5 and not receiving dialysis. Study Design Retrospective cohort study. Setting & Participants An integrated claims-clinical data set of US patients with CKD stages G3-G5, with serum bicarbonate values of 12 to<22 mEq/L (metabolic acidosis group) or 22 to 29 mEq/L (normal serum bicarbonate level group). Predictor The primary exposure variable was the baseline serum bicarbonate level. Outcomes The primary clinical outcome was the composite of all-cause mortality, maintenance dialysis, kidney transplant, or a decline in the estimated glomerular filtration rate of≥40% (DD40). The primary cost outcome was all-cause predicted per-patient per-year cost, assessed over a 2-year outcome period. Analytical Approach Logistic and generalized linear regression models, adjusted for key covariates such as age, sex, race, kidney function, comorbidities, and pharmacy insurance coverage, were used to assess serum bicarbonate levels as a predictor of DD40 and health care costs, respectively. Results 51,558 patients qualified. The metabolic acidosis group experienced higher rates of DD40 (48.3% vs. 16.7%, P <0.001) and higher all-cause yearly costs ($65,172 vs. $24,681, P <0.001). Two-year adjusted odds ratio of DD40 per 1-mEq/L increase in serum bicarbonate levels was 0.873 (95% CI, 0.866-0.879); the parameter estimate (±SE) for costs was−0.070±0.0075 ( P <0.001). Limitations Possible residual confounding. Conclusions Patients with CKD and metabolic acidosis had higher costs and rates of adverse kidney outcomes compared with patients with normal serum bicarbonate levels. Each 1-mEq/L increase in serum bicarbonate levels was associated with a 13% decrease in 2-year DD40 events and a 7% decrease in per-patient per-year cost.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".