Protocol adherence and the ability to achieve target haemoglobin levels in haemodialysis patients
Bibliographic record
Abstract
BACKGROUND: Anemia management remains complicated in patients with endstage renal disease on hemodialysis. We wished to evaluate the effect of protocol adherence to EPO and intravenous iron dosing on achieving the desired range of hemoglobin levels. METHODS: A cohort of hemodialysis patients was studied to evaluate the rate of adherence to EPO and iron dosing protocols over a 5 month period. A database was completed to evaluate all known comorbidities, demographic factors, and facility issues that might affect hemoglobin levels. A logistic regression model was employed to evaluate the effect of adherence to the anemia protocols on the probability of achieving a hemoglobin level below, within or above the targeted range of 11-12.5 g/dl. RESULTS: Among 2114 patients, we found that adherence to both the EPO and iron dosing protocol resulted in the greatest probability of achieving the target hemoglobin range (56 +/- 5% in anemia protocol adherent patients versus 42 +/- 7% in non adherent patients). This was predominantly due to a lowered risk of having above target hemoglobin levels rather than below. The use of the anemia protocols was associated with lower rates of hospitalization (9 +/- 0.7 visits/100 months in adherent group vs 15 +/- 2 in non adherent group) and lower utilization of both EPO and intravenous iron. Furthermore, patients in the adherent groups had less variability of their hemoglobin levels month by month, at least as judged by standard deviation. CONCLUSION: Adherence to anemia protocols, as practiced in the dialysis units included in this cohort, may improve hemodialysis patients' ability to achieve target hemoglobin levels, and by avoiding above target hemoglobin values, lower drug utilization and reduce variability of hemoglobin levels.
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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 | 0.005 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".