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Obstetric Neuraxial Anesthesia at Low Platelet Counts in the Context of Immune Thrombocytopenia: A Systematic Review and Meta-analysis

2020· review· en· W3080777733 on OpenAlexaff
Liane J. Bailey, Nadine Shehata, Bryon De France, J.C.A. Carvalho, Ann Kinga Malinowski

Bibliographic record

VenueObstetric Anesthesia Digest · 2020
Typereview
Languageen
FieldMedicine
TopicPlatelet Disorders and Treatments
Canadian institutionsMount Sinai Hospital
Fundersnot available
KeywordsMedicineContext (archaeology)AsymptomaticPlateletPregnancyImmune thrombocytopeniaAnesthesiaNeuraxial blockadeSurgeryImmunology

Abstract

fetched live from OpenAlex

( Can J Anesth . 2019;66:1396–1414) Immune thrombocytopenia purpura (ITP) is a rare autoimmune condition marked by a low platelet count, typically <100×10 9 /L. It may initially present during the preconception or antenatal periods. Most women are asymptomatic, but some may experience epistaxis, petechiae, easy bruising, or mucosal bleeding. Consensus on a safe threshold for platelet counts for placement of neuraxial anesthesia in pregnancy is unclear. The American Society of Anesthesiologists recommends an individualized approach to determine the risk of excessive bleeding without suggesting a minimum platelet threshold. The aim of this study was to examine obstetric neuraxial anesthesia (OBNA) outcomes in patients with platelet counts <100×10 9 /L in the context of primary ITP.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0150.003
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.048
GPT teacher head0.297
Teacher spread0.249 · 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 designMeta-analysis
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

Citations1
Published2020
Admission routes1
Has abstractyes

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