A link between hypercholesterolemia and chronic lymphocytic leukemia
Bibliographic record
Abstract
The incidence of hypercholesterolemia and its possible relationship with clinical course were determined by reviewing the records of 231 consecutive patients presenting to a specialized Chronic Lymphocytic Leukemia (CLL) clinic. Evidence for elevated cholesterol was found in up to 174/231 patients (75%) based on existing use of statins (107 patients) or non-fasting low-density lipoprotein cholesterol levels greater than 2.5 mM. Excluding patients with 17p deletions, time to first treatment (TFT) was prolonged if patients were taking cholesterol-lowering statins (57.5 (IQR = 32, 77) vs 36 (IQR = 11, 100) months, p < 0.02). If patients were prescribed statins after being diagnosed with CLL, TFT was longer than if they were taking statins before the diagnosis. These observations suggest there is a high incidence of hypercholesterolemia in CLL patients and cholesterol-lowering may impact the disease course.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".