Prescribing Practices of Erythropoiesis-Stimulating Agents in Dialysis-Dependent and Nondialysis-Dependent CKD
Bibliographic record
Abstract
Background: Anemia is a common complication of CKD. Erythropoiesis-stimulating agents (ESAs) have been used to treat CKD-associated anemia but are associated with increased risk of stroke, cancer progression and recurrence. There are no clear guidelines on ESA use for CKD patients with stroke, active or prior malignancy. Our objective was to assess the practice patterns and hemoglobin targets of Canadian Nephrologists and other Nephrology prescribers for ESA use in CKD patients with stroke or malignancy. Methods: We developed a cross-sectional, online survey to assess the anemia practice patterns of Canadian nephrologists, nephrology trainees, pharmacists and nurse practitioners. Survey design was done using a modified-Delphi process. The survey was nationally disseminated to members of the Canadian Society of Nephrology from March to May, 2024. Descriptive statistics were used to characterize hemoglobin targets and perceptions of “comfort” in prescribing across practitioners. Results: Survey response rate is 16.3% (88/540). In general CKD patients, a hemoglobin target of 95-115 g/L was most common (50.0%). In CKD patients with history of stroke, 90-105 g/L and 95-115 g/L were the most common targets (both 27.3%). In CKD patients with active or previous malignancy, 90-105 g/L was the most common target (27.3% and 25.0%, respectively). Figure-1 shows Likert scale ratings for ESA prescribing comfort in different CKD populations. Differences were observed for comfort in prescribing. Final survey results will be available in June 2024. Conclusion: This study highlights that there are a wide range of hemoglobin targets that are used, especially among those with active or prior malignancy and informs the need for better evidence for hemoglobin targets among CKD patients with malignancy or stroke.Figure-1: Likert Scale Ratings for ESA Prescriber Comfort in CKD Populations. Likert Rating: 1-Strongly Disagree, 2-Disagree, 3-Neither Agree nor Disagree, 4-Agree, 5-Strongly Agree. Comfort levels between general CKD patients versus other populations were compared.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".