Hemoglobin Targets and Blood Transfusions in Hemodialysis Patients without Symptomatic Cardiac Disease Receiving Erythropoietin Therapy
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: Optimal hemoglobin targets for chronic kidney disease patients receiving erythropoiesis-stimulating agents remain controversial. The effects of different hemoglobin targets on blood transfusion requirements have not been well characterized, despite their relevance to clinical decision-making. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: Five hundred ninety-six incident hemodialysis patients without symptomatic cardiac disease were randomly assigned to hemoglobin targets of 9.5 to 11.5 g/dl or 13.5 to 14.5 g/dl for 96 wk using epoetin alfa as primary therapy and changes in left ventricular structure as the primary outcome (previously reported). Patients were masked to treatment assignment. Blood transfusion data were prospectively collected at 4-wk intervals. RESULTS: The mean age and prior duration of dialysis therapy of the study population were 50.8 and 0.8 yr, respectively. Previously reported mortality was similar in low and high-target subjects, at 4.7 (95% confidence interval 3.0, 7.3) and 3.1 (1.8, 5.4) per hundred patient years, respectively. Transfusion rates were 0.66 (0.59, 0.74) units of blood per year in low and 0.26 (0.22, 0.32) in high-target subjects (P < 0.0001). Hemoglobin level at transfusion (7.7 [7.5, 7.9]) versus 8.1 [7.6, 8.5] g/dl) were similar with both groups. High hemoglobin target was a significant predictor of time to first transfusion independent of baseline associations (hazard ratio = 0.42; 95% confidence interval = 0.26-0.67). CONCLUSIONS: In hemodialysis patients with comparatively low mortality risks, normal hemoglobin targets may reduce the need for transfusions.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".