Cardiovascular Disease Among Patients With AML and CHIP-Related Mutations
Why this work is in the frame
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Bibliographic record
Abstract
Clonal hematopoiesis of indeterminate potential (CHIP) is a novel cardiovascular disease (CVD) risk factor in individuals without acute myeloid leukemia (AML). The aim of this study was to examine the association between mutations associated with CHIP (CHIP-related mutations) identified in patients at AML diagnosis and the risk for cardiovascular events (CVEs). This was a retrospective cohort study of 623 patients with AML treated between 2015 and 2018 who underwent DNA analysis. Cause-specific hazard regression models were used to study the associations between pathogenic mutations in common CHIP-related genes (DNMT3A, TET2, ASXL1, JAK2, TP53, SRSF2, and SF3B1) and the rate of CVEs (heart failure hospitalization, acute coronary syndrome, coronary artery revascularization, ischemic stroke, venous thromboembolism, and CVD death) and between CVE development and all-cause mortality. Patients were 64.6 ± 15.3 years of age, 265 (42.5%) were women, and 63% had at least 1 CHIP-related mutation. Those with CHIP-related mutations were older (69.2 ± 12.3 vs 56.6 ± 16.6 years; P < 0.001) and had a greater prevalence of CVD risk factors and CVD history. In adjusted analysis, the presence of any CHIP-related mutation was associated with a higher rate of CVEs (HR: 1.74; 95% CI: 1.03-2.93; P = 0.037) among intensively treated patients (anthracycline based) but not the whole cohort (HR: 1.26; 95% CI: 0.81-1.97; P = 0.31). TP53 (HR: 4.18; 95% CI: 2.07-8.47; P < 0.001) and ASXL1 (HR: 2.37; 95% CI: 1.21-4.63; P = 0.012) mutations were associated with CVEs among intensively treated patients. Interval development of CVEs was associated with all-cause mortality (HR: 1.99; 95% CI: 1.45-2.73; P < 0.001). Among patients with AML treated with intensive chemotherapy, mutations in CHIP-related genes were associated with an increased risk for developing incident CVEs after AML diagnosis.
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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 | 0.000 |
| 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 | 0.001 |
| 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 it