A Case of Evans Syndrome: A Clinical Condition With Under-Recognized Thrombotic Risk
Bibliographic record
Abstract
Evans syndrome (ES) is a rare hematologic disorder characterized by the presence of Direct Antiglobulin test (DAT) positive autoimmune hemolytic anemia (AIHA), immune thrombocytopenia (ITP), and/or immune neutropenia. The risk of thrombosis has been well established in retrospective studies for ITP and AIHA; however, the risk of thrombosis in ES has been limited to case reports and individual case series. Whether the risk of thrombosis in ITP and AIHA is additive has not been well established, but preliminary observation suggests the rate of thrombosis is higher than the rate observed in ITP or AIHA individually. Furthermore, ES appears to be an underappreciated diagnosis. Anemia in the presence of ITP is often considered to be secondary to acute blood loss and a proper workup for hemolysis is often missed. Appropriate risk stratification of these patients is hindered by this lack of workup and many patients are unfortunately not treated appropriately and/or not offered appropriate prophylaxis for their level of thrombotic risk. The purpose of this case report is to not only increase the level of awareness among clinicians to initiate an appropriate diagnostic workup in patients presenting with anemia in the setting of ITP, but also to a heightened thrombotic risk warranting an appropriate thromboprophylaxis. This case also adds to the body of evidence that a “second- hit” phenomenon is often a precipitating cause for a thrombotic event. J Hematol. 2015;4(3):205-209 doi: http://dx.doi.org/10.14740/jh222w
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| 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".