JAK2 unmutated erythrocytosis: current diagnostic approach and therapeutic views
Bibliographic record
Abstract
JAK2 unmutated or non-polycythemia vera (PV) erythrocytosis encompasses both hereditary and acquired conditions. A systematic diagnostic approach begins with documentation of historical hematocrit (Hct)/hemoglobin (Hgb) measurements and classification of the process as life-long/unknown duration or acquired. Further investigation in both categories is facilitated by determination of serum erythropoietin level (EPO). Workup for hereditary/congenital erythrocytosis requires documentation of family history and laboratory screening for high-oxygen affinity hemoglobin variants, 2, 3 biphosphoglycerate deficiency, and germline mutations that are known to alter cellular oxygen sensing (e.g., PHD2, HIF2A, VHL) or EPO signaling (e.g., EPOR mutations); the latter is uniquely associated with subnormal EPO. Acquired erythrocytosis is often elicited by central or peripheral hypoxia resulting from cardiopulmonary disease/high-altitude dwelling or renal artery stenosis, respectively; EPO in the former instance is often normal (compensated by negative feed-back). Other conditions associated with acquired erythrocytosis include EPO-producing tumors and the use of drugs that promote erythropoiesis (e.g., testosterone, erythropoiesis stimulating agents). "Idiopathic erythrocytosis" loosely refers to an otherwise not explained situation. Historically, management of non-PV erythrocytosis has been conflicted by unfounded concerns regarding thrombosis risk, stemming from limited phenotypic characterization, save for Chuvash polycythemia, well-known for its thrombotic tendency. In general, cytoreductive therapy should be avoided and phlebotomy is seldom warranted where frequency is determined by symptom control rather than Hct threshold. Although not supported by hard evidence, cardiovascular risk optimization and low-dose aspirin use are often advised. Application of modern genetic tests and development of controlled therapeutic intervention trials are needed to advance current clinical practice.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".