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Record W2064949271 · doi:10.1136/rapm-2018-000019

Lower extremity regional anesthesia: essentials of our current understanding

2019· article· en· W2064949271 on OpenAlexaff
De Q.H. Tran, Francis V. Salinas, Honorio T. Benzon, Joseph M. Neal

Bibliographic record

VenueRegional Anesthesia & Pain Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcGill University
FundersUniversidad de Chile
KeywordsMedicineRegional anesthesiaWarrantPeripheral nervePeripheral nerve stimulationLumbarNerve blockAnesthesiaPhysical medicine and rehabilitationSurgeryAnatomy

Abstract

fetched live from OpenAlex

The advent of ultrasound guidance has led to a renewed interest in regional anesthesia of the lower limb. In keeping with the American Society of Regional Anesthesia and Pain Medicine's ongoing commitment to provide intensive evidence-based education, this article presents a complete update of the 2005 comprehensive review on lower extremity peripheral nerve blocks. The current review article strives to (1) summarize the pertinent anatomy of the lumbar and sacral plexuses, (2) discuss the optimal approaches and techniques for lower limb regional anesthesia, (3) present evidence to guide the selection of pharmacological agents and adjuvants, (4) describe potential complications associated with lower extremity nerve blocks, and (5) identify informational gaps pertaining to outcomes, which warrant further investigation.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.015
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.002
Science and technology studies0.0010.009
Scholarly communication0.0060.015
Open science0.0030.003
Research integrity0.0060.015
Insufficient payload (model declined to judge)0.0030.002

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 head0.063
GPT teacher head0.300
Teacher spread0.236 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations317
Published2019
Admission routes1
Has abstractyes

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