Inflamation and EPO Therapy in HD Patients
Bibliographic record
Abstract
Some authors suggest that inflammation can be one of the reasons of erythropoietin (EPO) resistance. The purpose of the study was to follow‐up some laboratory markers of inflammation in 21 dialysis patients, all treated with adequate anaemia doses EPO, divided in 2 groups: first one adequately responding to EPO treatment (with Hb higher than 9 g/L) and second one resistant to it (with Hb lower than 9 g/L). Some acute phase proteins and markers of inflammation were measured as follow: C‐reactive protein (CRP), α1‐AGT, α1‐antitrypsine, and haptoglobine (HP), as some anti‐acute phase proteins, transferrin (TF). WBC count, some enzymes: ASAT, ALAT, and substrates: urea, creatinine, albumins (Albs), lipid profile, glucose, phosphate, iron, electrolytes, and parathyroid hormone were tested as well. The study found significant higher CRP, HP, Tg, P, and Alb in the second group than in the first. TF was lower in all patients, which may be connected to the chronic inflammatory status (uremia), and there was no iron deficit or severe parathyroid hyperfunction to be convinced for EPO resistance. The study suggests that EPO resistance may be related to some inflammatory factors and treatment of the inflammation possibly will overcome the problem.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".