Determinants of metabolic acidosis among hemodialysis patients
Bibliographic record
Abstract
Metabolic acidosis is frequently present, poorly controlled, and associated with adverse effects among hemodialysis patients. Potential determinants of metabolic acidosis include endogenous acid production, administration of alkali, neutralization of acid by buffers, dilution of serum bicarbonate by interdialytic fluid gain, and loss of bicarbonate in stool. Understanding the relative importance of these determinants may help guide efforts to manage metabolic acidosis. We used chart abstraction, patient interviews, and laboratory testing to assess variables related to acid production (protein breakdown), alkali administration (dialysis dose, missed treatments, dialysate bicarbonate concentration, oral bicarbonate supplements), acid buffering (phosphorus binders), dilution of bicarbonate (interdialytic weight gain), and loss of bicarbonate in stool (diarrhea) for 190 randomly selected patients from 44 hemodialysis facilities. We used multivariate analyses to determine which potential determinants were independently associated with predialysis serum bicarbonate levels. Of all patients, 30% had metabolic acidosis (serum bicarbonate level <22 mEq/L). On multivariate analysis, metabolic acidosis was more likely with increased protein nitrogen appearance (odds ratio [OR] 1.60 per 0.2 g/kg/day, p=0.001) and less likely with increased Kt/V (OR 0.61 per 0.20 increase in Kt/V, p<0.001) and with increased calcium carbonate use (OR 0.38 per 2 g/day, p=0.003). Key determinants of metabolic acidosis among hemodialysis patients are protein breakdown, dialysis dose, and specific phosphorus binders. Further work is needed to develop interventions to address these determinants.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".