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Record W1902656250 · doi:10.3109/10428194.2015.1088651

A link between hypercholesterolemia and chronic lymphocytic leukemia

2015· article· en· W1902656250 on OpenAlexafffund
Signy Chow, Rena Buckstein, David Spaner

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2015
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsUniversity of TorontoHealth Sciences CentreSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsChronic lymphocytic leukemiaMedicineIncidence (geometry)Internal medicineCholesterolLeukemiaGastroenterology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.033
GPT teacher head0.289
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations33
Published2015
Admission routes2
Has abstractyes

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