Successful reintroduction of a different erythropoiesis-stimulating agent after pure red cell aplasia: relapse after successful therapy with prednisone
Bibliographic record
Abstract
We report a 3-year case history that describes a 78-year-old woman with recurrent transfusion-dependent pure red cell aplasia (PRCA) secondary to recombinant epoetin use that was responsive to immunosuppressant therapy. The patient had kidney disease of unknown aetiology (estimated glomerular filtration rate of 13 ml/min/1.73 m2) and was not on dialysis. After 16 months of therapy with subcutaneous Eprex, she developed anti-erythropoietin antibody-confirmed PRCA and was started on high dose prednisone (50 mg per day). Within 5 months, the patient's serum was clear of antibodies and, under the cover of low dose prednisone (5-7.5 mg per day), therapy with a different erythropoiesis-stimulating compound (Aranesp) was initiated due to persistent fatigue and anaemia. At 3 months of therapy, the serum anti-erythropoietin antibodies remained negative and, due to the patient's requests, and after discussion, prednisone therapy was discontinued. Unfortunately, 3 months after cessation of prednisone, a recurrence of PRCA was confirmed by the development of profound anaemia and reappearance of anti-erythropoietin antibodies in the patient's serum. High dose prednisone (50 mg per day) was reinstituted, whereupon, 2 months later, antibodies were again confirmed to be negative. This case report demonstrates the responsiveness of PRCA to simple immunosuppressive therapy, and the ability to introduce different erythropoiesis-stimulating agents in the presence of such therapy. It appears that there may be problems associated with discontinuation of immunosuppressive therapy in the presence of sustained erythropoiesis-stimulating agent therapy in those in whom the condition has occurred previously.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".