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Current understanding of bleeding with ibrutinib use: a systematic review and meta-analysis

2017· review· en· W2613723809 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBlood Advances · 2017
Typereview
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsHamilton Health SciencesMcMaster UniversityPopulation Health Research Institute
FundersMcMaster UniversityCanadian Institutes of Health ResearchHamilton Health Sciences
KeywordsIbrutinibMeta-analysisMedicineConfidence intervalInternal medicineRelative riskClinical trialLeukemia

Abstract

fetched live from OpenAlex

Ibrutinib therapy was associated with an increased risk of bleeding in previous trials. In this systematic review and meta-analysis of published trials including patients treated with ibrutinib, the relative risk (95% confidence interval [CI]) of overall bleeding was significantly higher in ibrutinib recipients (2.72 [1.62-6.58]), but major bleeding did not show a significant difference (1.66 [0.96-2.85]). The incidences (95% CI) of major bleeding and any bleeding were 3.0 (2.3-3.7) and 20.8 (19.1-22.1) per 100 patient-years, respectively. This analysis is limited by reporting bias from variable ascertainment of bleeding and lack of allocation concealment in some studies and differing exposures between groups, leading to potential overestimation of event rates in the ibrutinib group.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.574
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.002
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.389
GPT teacher head0.468
Teacher spread0.079 · 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