The Effect of Erythropoietin-Stimulating Agents on Health-Related Quality of Life in Anemia of Chronic Kidney Disease
Bibliographic record
Abstract
BACKGROUND: The efficacy of erythropoietin-stimulating agents (ESAs) for improving health-related quality of life (HRQOL) in anemia of chronic kidney disease (CKD) is unclear. PURPOSE: To determine the effect of ESAs on HRQOL at different hemoglobin targets in adults with CKD who were receiving or not receiving dialysis. DATA SOURCES: Searches of PubMed, EMBASE, the Cochrane Library, and ClinicalTrials.gov from inception to 1 November 2015, supplemented with manual screening. STUDY SELECTION: Randomized, controlled trials that evaluated the treatment of anemia with ESAs, including erythropoietin and darbepoetin, targeted higher versus lower hemoglobin levels, and used validated HRQOL metrics. DATA EXTRACTION: Study characteristics, quality, and data were assessed independently by 2 reviewers. Outcome measures were scores on the Short Form-36 Health Survey (SF-36), Kidney Dialysis Questionnaire (KDQ), and other tools. DATA SYNTHESIS: Of 17 eligible studies, 13 reported SF-36 outcomes and 4 reported KDQ outcomes. Study populations consisted of patients not undergoing dialysis (n = 12), those undergoing dialysis (n = 4), or a mixed sample (n = 1). Only 4 studies had low risk of bias. Pooled analyses showed that higher hemoglobin targets resulted in no statistically or clinically significant differences in SF-36 or KDQ domains. Differences in HRQOL were further attenuated in studies at low risk of bias and in subgroups of dialysis recipients. LIMITATION: Statistically significant heterogeneity among studies, few good-quality studies, and possible publication bias. CONCLUSION: ESA treatment of anemia to obtain higher hemoglobin targets does not result in important differences in HRQOL in patients with CKD. PRIMARY FUNDING SOURCE: KRESCENT and Manitoba Health Research Council Establishment.
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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 | 0.002 | 0.005 |
| 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".