Erythropoietin Hyporesponsiveness in Dialysis Patients: Possible Role of Statins
Bibliographic record
Abstract
BACKGROUND: Hypothesizing that statins may be useful as adjuvant treatment for renal anemia, we examined the association between statin prescription (Rx) and erythropoiesis-stimulating agent (ESA) hyporesponsiveness in Japanese hemodialysis (HD) patients prescribed ESAs. METHODS: We examined 3,602 patients in 60 HD facilities dialyzed 3 times/week for ≥4 months from the Japan Dialysis Outcomes and Practice Patterns Study phases 3-5 (2005-2015). Statin Rx was reported at the end of a 4-month interval (baseline) for each patient. ESA hyporesponsiveness in the subsequent 4 months was then defined as a binary indicator (mean hemoglobin [Hgb] level <10 g/dL and mean ESA dose >6,000 units/week) and separately as the ESA resistance index (ERI; mean ESA dose/[dry weight × mean Hgb]). We used adjusted logistic and linear regressions to evaluate the associations between statin Rx and ESA hyporesponsiveness. RESULTS: At baseline, 16.2% of patients reported statin Rx; 12.8% were classified as having ESA hyporesponsiveness during 4 months of follow-up. Compared to patients without statin Rx, patients with statin Rx had lower odds of ESA hyporesponsiveness (OR 0.87; 95% CI 0.66-1.15). Similarly, the ERI was lower for those with statin Rx than without (ratio of means, 0.94; 95% CI 0.89-0.99) after adjustment for possible confounders. CONCLUSIONS: Our results suggest that statins may slightly reduce ESA hyporesponsiveness in HD patients. However, any causal inference is limited by the observational study design and unmeasured compliance with statin Rx.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".