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Record W3132871788 · doi:10.1080/16078454.2021.1880762

Anticoagulation and bone marrow biopsy: is it safe to proceed?

2021· review· en· W3132871788 on OpenAlexaff
Cameron Moore, Rouslan Kotchetkov

Bibliographic record

VenueHematology · 2021
Typereview
Languageen
FieldMedicine
TopicHematological disorders and diagnostics
Canadian institutionsRoyal Victoria Regional Health Centre
Fundersnot available
KeywordsMedicineBiopsyBone marrowClinical judgementSurgeryIntensive care medicineRadiologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Bone marrow (BM) biopsy is the most common diagnostic procedure in hematology. Bleeding is an expected complication, and its risk is assumed to be increased in patients on anticoagulants. However, the effect of anticoagulation on BM biopsy safety is unclear and guidelines are lacking robust data in this regard. As such, physicians use their clinical judgement to guide periprocedural management of anticoagulation. OBJECTIVE: To provide the best available evidence regarding management of anticoagulation in patients who need BM biopsy. METHODS: We reviewed and summarized available guidelines directing management of periprocedural anticoagulation for BM biopsy, and share our experience and practices with BM biopsy at our institution. RESULTS: The incidence of significant hemorrhage after BM biopsy is very low (0.007-1.1%). BM biopsy is classified as having a low to moderate bleeding risk. Interrupting anticoagulation is not consistently recommended. Strategies exist to minimize bleeding risk for anticoagulated patients. Patients with myeloproliferative neoplasms can develop an acquired von Willebrand syndrome which increases their risk for bleeding and therefore require extra vigilance to ensure appropriate hemostasis. CONCLUSION: Withholding anticoagulation prior to BM biopsy is not routinely recommended. Instead, assessment and optimization of bleeding risk factors should be done on a patient by patient basis.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.801
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.088
GPT teacher head0.388
Teacher spread0.300 · 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 teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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

Citations4
Published2021
Admission routes1
Has abstractyes

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