Association between serum bicarbonate and death in hemodialysis patients: Is it better to be acidotic or alkalotic?
Bibliographic record
Abstract
The optimal acid base status for survival in maintenance hemo‐dialysis (MHD) patients (pts) remains controversial. According to some reports acidosis is associated with improved survival in MHD pts, i.e., reverse epidemiology. We examined associations between baseline (first 3‐month averaged) serum bicarbonate (HCO3), divided into 12 categories, and 2‐yr mortality in 56,376 MHD pts across the US after controlling for confounding effects of malnutrition‐inflammation complex syndrome (MICS). Three sets of Cox regression models were evaluated to estimate hazard ratios (HR) of death and 95% confidence intervals (CI): (1) Unadjusted; (2) Multivariate adjusted for case‐mix (age, gender, diabetes, race, insurance, marital status, vintage, standardized mortality ratio, residual renal function, dialysate HCO3, and Kt/V); and (3) Additional adjustments for 8 markers of MICS (body mass index, serum albumin, creatinine, ferritin, TIBC, dietary protein intake, WBC and lymphocyte counts). See Figure for HR and 95% CI: We conclude that, although high HCO3 levels appear to be associated with increased mortality in MHD pts, this paradoxical effect is almost entirely due to the overwhelming impact of MICS on survival.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 | 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".