ACE inhibitors or angiotensin II receptor blockers in dialysed patients and erythropoietin resistance
Bibliographic record
Abstract
BACKGROUND: To examine whether angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin II receptor blockers (ARBs) are associated with a state of recombinant human erythropoietin (rHuEPO) resistance in hemodialyzed patients. METHODS: Cross-sectional study involving all dialysis facilities in French-speaking Switzerland. All patients treated with rHuEPO in March 2001 were included. Demographic, clinical and laboratory data were collected in 515 patients treated with chronic hemodialysis (HD) and rHuEPO. Patients were classified into five groups according to their antihypertensive treatment. The main outcomes of the study were the mean rHuEPO dosage and the prevalence of erythropoietin EPO resistance among the groups. Erythropoietin resistance was defined as a weekly rHuEPO dosage >300 units/kg/wk. RESULTS: The mean rHuEPO dosage and the prevalence of EPO resistance were similar in patients treated with ACEIs (n = 138, mean EPO dosage 109 units/kg/wk, EPO resistance 12%), ARBs (n = 59, mean EPO dosage 120 units/kg/wk, EPO resistance 7%), both (n = 10, mean EPO dosage 109 units/kg/wk, EPO resistance 10%), other drugs (n = 137, mean EPO dosage 110 units/kg/wk, EPO resistance 10%) and no antihypertensive treatment (n = 171, mean EPO dosage 90 units/kg/wk, EPO resistance 9%). Differences were not statistically significant. Patients with rHuEPO resistance were characterized by a higher frequency of hospitalization and a more pronounced inflammatory state. There was no difference in the use of ACEIs and ARBs between patients with and without EPO resistance (37 vs. 41%, ns). CONCLUSIONS: Neither the use of ACEIs nor ARBs is associated with a state of rHuEPO resistance among hemodialyzed patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".