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Record W2141817010 · doi:10.3109/10428194.2013.850685

Early deaths in pediatric acute leukemia: a population-based study

2013· article· en· W2141817010 on OpenAlexafffundabout
Sylvia Cheng, Jason D. Pole, Lillian Sung

Bibliographic record

VenueLeukemia & lymphoma/Leukemia and lymphoma · 2013
Typearticle
Languageen
FieldMedicine
TopicAcute Lymphoblastic Leukemia research
Canadian institutionsInstitute for Clinical Evaluative SciencesHospital for Sick ChildrenPediatric Oncology GroupUniversity of Toronto
FundersCanadian Institutes of Health ResearchMcMaster University
KeywordsMedicineMyeloid leukemiaIncidence (geometry)PediatricsRetrospective cohort studyPopulationAcute leukemiaLeukemiaLymphoblastic LeukemiaCohortInternal medicine

Abstract

fetched live from OpenAlex

The purpose was to describe the incidence and risk factors associated with early deaths (≤ 42 days from diagnosis) among children with acute lymphoblastic leukemia (ALL) and acute myeloid leukemia (AML) in Ontario, Canada. The data source for this population-based, retrospective cohort study was the Pediatric Oncology Group of Ontario Networked Information System (POGONIS). Patients with acute leukemia aged ≤ 18 years diagnosed between 1990 and 2010 were included. The study population consisted of 1954 children with ALL and 403 with AML. The early death rate was 40/2357 (1.7%), with 1.1% of patients with ALL and 4.7% of patients with AML dying early. Among all 442 deaths recorded, 9.0% occurred early. Twelve/40 (30.0%) early deaths were attributed to infection. Factors associated with early deaths were AML (p < 0.0001) and age ≥ 10 years at diagnosis (p = 0.038). Future interventions to improve survival may consider focusing on the early treatment period and may target AML and older patients.

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 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), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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.

Opus teacher head0.010
GPT teacher head0.258
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

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

Citations25
Published2013
Admission routes3
Has abstractyes

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