Facility factors dominate the ability to achieve target haemoglobin levels in haemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Our objective was to determine whether patient factors, processes of care and measures of erythropoietin (EPO) responsiveness were associated with successful anemia management at the individual patient level. METHODS: We retrospectively reviewed laboratory and demographic data from 1499 patients receiving hemodialysis in 15 units operated by the same dialysis provider. We performed univariate and multivariate logistic regression analysis to determine predictors of an average 3-month hemoglobin level below or above the target interval of 11.0-12.5 g/dL. To explain the effect of facility on anemia performance, we calculated correlations between measures of EPO responsiveness and the probability of achieving the target interval by facility. RESULTS: Patients above the target hemoglobin range demonstrated an association with parathyroid hormone (PTH) (OR = 0.96 per 100 pg/mL increase), female gender (OR = 0.68), EPO protocol use (OR = 0.94 per 10% increase in use) and facility (range of OR = 0.26-2.59 for 15 participating sites). Patients below the target hemoglobin range demonstrated an association with CRP (OR = 1.10 per mg/L increase), PTH (OR = 1.07 per 100 pg/mL increase), iron deficiency (OR = 1.07 per 10% increase), EPO protocol use (OR = 0.89 per 10% increase in use), iron protocol use (OR = 0.93 per 10% increase in use) and facility (range of OR = 0.58-3.41 over 15 units). EPO index (r = 0.71), EPO dose (r = 0.73), hemoglobin (r = -0.60) and EPO per unit weight (r = 0.76) were significantly correlated with the probability of achieving the target hemoglobin by facility. CONCLUSIONS: The facility significantly influences the outcome of anemia management in patients with ESRD. In part, this is due to the patients' EPO responsiveness, which may be influenced by facility care patterns.
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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 | 0.007 |
| 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 | 0.001 | 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".