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Record W2008241551 · doi:10.1080/10428190600572673

Leukocyte count as a predictor of death during remission induction in acute myeloid leukemia

2006· article· en· W2008241551 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2006
Typearticle
Languageen
FieldMedicine
TopicAcute Myeloid Leukemia Research
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsMedicineInduction chemotherapyMyeloid leukemiaInternal medicineCohortMyeloidImmunologyAcute leukemiaLeukemiaChemotherapyOncologyGastroenterology

Abstract

fetched live from OpenAlex

Acute myeloid leukemia (AML) presenting with a high leukocyte count has been associated with an increase in induction mortality and poor results in a number of other survival measures. However, the level at which an elevated leukocyte count has prognostic significance in AML remains unclear. In this report on a series of 375 adult (non-M3) AML patients undergoing induction chemotherapy at a single institution, leukocyte count analyzed as a continuous variable is shown to be a better predictor of induction death (ID) and overall survival (OS) than a leukocyte count of > or = 100 x 10(9)/L, a value characteristically associated with "hyperleukocytosis" (HL). In this patient cohort, a presenting leukocyte count of > or = 30 x 10(9)/L had high sensitivity and specificity for predicting ID, and both performance status (PS) and leukocyte count more accurately predicted for ID than age. Considering these parameters in newly-diagnosed AML patients may facilitate the development of strategies for reducing induction mortality.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.526
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.010
GPT teacher head0.255
Teacher spread0.245 · 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