Relationship between<i>JAK2V617F</i>mutation, allele burden and coagulation function in Ph-negative myeloproliferative neoplasms
Bibliographic record
Abstract
OBJECTIVES: Our aim was to explore the relationship between JAK2V617F mutation allele burden and hematological parameters especially in coagulation function in Chinese population. METHODS: This study included 133 Ph-negative myeloproliferative neoplasms (MPNs) patients between 2013 and 2016. All the clinical and experimental data of patients were collected at the time of the diagnosis without any prior treatment, including blood parameters, coagulation function, splenomegaly, vascular events and chromosome karyotype. PCR and qPCR were used to detect JAK2V617F mutation and JAK2V617F mutation allele burden. RESULTS: In polycythemia vera patients, a positive correlation between the allele burden of JAK2V617F mutation and PLT counts was found; in essential thrombocythemia (ET) patients, WBC counts, RBC counts, HB, and HCT were higher in mutated patients than in wild-type patients. Furthermore, PT-INR was higher in ET and PMF mutated patients. In addition, a positive correlation between the allele burden of JAK2V617F mutation and activated partial thromboplastin time (APTT) was observed in JAK2V617F mutated ET patients. CONCLUSIONS: Higher hematologic parameters including counts of WBC, RBC, and PLT are closely associated with JAK2V617F mutation and its burden in Ph-negative MPNs; importantly, PT-INR, APTT are also related to JAK2V617F mutation and allele burden. Thus, our data indicate that JAK2V617F mutation allele burden might not only represent the burden of MPN but also alter the coagulation function.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".