Pure Red Cell Aplasia and Mature-cell Directed Immune-Mediated Anemia in a Golden Retriever
Bibliographic record
Abstract
A 4 year old female spayed Golden Retriever dog was presented with acute collapse following a 2 day history of lethargy and hematochezia. On presentation, the patient was dyspneic with severely icteric and pale mucous membranes and sclera. Point-of-care blood work revealed a severe anemia with spherocytes and icteric plasma. A saline slide agglutination test was positive for macroaggluti-nation. The dog was given a transfusion of packed red blood cells (RBCs) and subsequently devel-oped central vestibular disease with vestibular ataxia and nystagmus. A complete blood count revealed a severe non-regenerative anemia with marked spherocytosis and ghost cells, an inflammatory leukogram (neutrophilia with a left shift and toxic change and a mono-cytosis) and moderate thrombocytopenia. A biochemistry panel revealed evidence of hypovolemia and hypoxic injury, as a consequence of the immune-mediated hemolytic anemia (IMHA). Coagu-lation testing revealed evidence of hypercoagulability. Tests for infectious diseases (Babesia PCR, 4DX Snap test) were negative and zinc concentrations were low. Abdominal ultrasonographic and thoracic radiographic examination revealed no underlying cause for the anemia. Due to the lack of an appropriate regenerative response to the patient’s anemia, a bone marrow aspirate was per-formed, which revealed marked erythroid hypoplasia, with <5% erythroid precursors. The dog was diagnosed with pure red cell aplasia (PRCA) with a concurrent peripheral IMHA. The dog was treated aggressively with multiple transfusions of packed RBCs, immunosuppressive medications, antithrombotic drugs, anti-nausea and gastroprotectant medications, and an antibiotic. Over the following months, the patient’s hematocrit steadily increased and the immune-mediated anemia entered remission.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| 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) | 0.002 | 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".