Erythropoietic effects of vadadustat in patients with anemia associated with chronic kidney disease
Bibliographic record
Abstract
Patients with chronic kidney disease (CKD) develop anemia largely because of inappropriately low erythropoietin (EPO) production and insufficient iron available to erythroid precursors. In four phase 3, randomized, open-label, clinical trials in dialysis-dependent and non-dialysis-dependent patients with CKD and anemia, the hypoxia-inducible factor prolyl hydroxylase inhibitor, vadadustat, was noninferior to the erythropoiesis-stimulating agent, darbepoetin alfa, in increasing and maintaining target hemoglobin concentrations. In these trials, vadadustat increased the concentrations of serum EPO, the numbers of circulating erythrocytes, and the numbers of circulating reticulocytes. Achieved hemoglobin concentrations were similar in patients treated with either vadadustat or darbepoetin alfa, but compared with patients receiving darbepoetin alfa, those receiving vadadustat had erythrocytes with increased mean corpuscular volume and mean corpuscular hemoglobin, while the red cell distribution width was decreased. Increased serum transferrin concentrations, as measured by total iron-binding capacity, combined with stable serum iron concentrations, resulted in decreased transferrin saturation in patients randomized to vadadustat compared with patients randomized to darbepoetin alfa. The decreases in transferrin saturation were associated with relatively greater declines in serum hepcidin and ferritin in patients receiving vadadustat compared with those receiving darbepoetin alfa. These results for serum transferrin saturation, hepcidin, ferritin, and erythrocyte indices were consistent with improved iron availability in the patients receiving vadadustat. Thus, overall, vadadustat had beneficial effects on three aspects of erythropoiesis in patients with anemia associated with CKD: increased endogenous EPO production, improved iron availability to erythroid cells, and increased reticulocytes in the circulation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".