Adherence rates to ferric citrate as compared to active control in patients with end stage kidney disease on dialysis
Bibliographic record
Abstract
INTRODUCTION: Oral phosphate binders are the main stay of treatment of hyperphosphatemia. Adherence rates to ferric citrate, a recently approved phosphate binder, are unknown. METHODS: We conducted a post-hoc analysis to evaluate whether adherence rates were different for ferric citrate vs. active control in 412 subjects with end stage kidney disease (ESKD) who were randomized to ferric citrate vs. active control (sevelamer carbonate and/or calcium acetate). Adherence was defined as percent of actual number of pills taken to total number of pills prescribed. FINDINGS: There were no significant differences in baseline characteristics including gender, race/ethnicity, and age between the ferric citrate and active control groups. Baseline phosphorus, calcium, and parathyroid hormone levels were similar. Mean (SD) adherence was 81.4% (17.4) and 81.7% (15.9) in the ferric citrate and active control groups, respectively (P = 0.88). Adherence remained similar between both groups after adjusting for gender, race/ethnicity, age, cardiovascular disease (CVD), and diabetic nephropathy (mean [95% CI]: 81.4% [78.2, 84.6] and 81.5% [77.7, 85.2] for ferric citrate and active control, respectively). Gender, race/ethnicity, age, and diagnosis of diabetic nephropathy did not influence adherence to the prescribed phosphate binder. Subjects with CVD had lower adherence rates to phosphate binder; this was significant only in the active control group. DISCUSSION: Adherence rates to the phosphate binder, ferric citrate, were similar to adherence rates to active control. Similar adherence rates to ferric citrate are notable since tolerance to active control was an entry criteria and the study was open label. Gender, race/ethnicity, nor age influenced adherence.
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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 | 0.002 | 0.004 |
| 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 | 0.001 | 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".