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Record W4292451654 · doi:10.1097/aco.0000000000001181

Erector spinae block: beyond the torso

2022· review· en· W4292451654 on OpenAlexaff
Sinead Campbell, Ki Jinn Chin

Bibliographic record

VenueCurrent Opinion in Anaesthesiology · 2022
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsToronto Western HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineLumbar plexusAnesthesiaLumbarLocal anestheticErector spinae musclesNerve blockBrachial plexusArthroplastyBrachial plexus blockSurgery

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: This article aims to summarize the current literature describing the application of erector spinae plane (ESP) blocks for regional anesthesia of upper and lower limbs and to discuss the advantages and limitations. RECENT FINDINGS: Investigations are still at an early stage but results are promising. High thoracic ESP blockade can relieve acute and chronic shoulder pain through local anesthetic diffusion to cervical nerve roots, although it may not be as effective as direct local anesthetic injection around the brachial plexus. It does, however, preserve motor and phrenic nerve function to a greater extent. It will also block the T2 innervation of the axilla which can be a source of pain in complex arthroscopic shoulder surgery. Lumbar ESP blocks provide effective analgesia following hip arthroplasty and arthroscopy, and appear comparable to lumbar plexus, quadratus lumborum, and fascia iliaca blocks. Unlike the latter, they are motor-sparing and are associated with improved postoperative ambulation. SUMMARY: High thoracic and lumbar ESP blocks have the potential to provide adequate analgesia of the upper and lower limbs respectively, without causing significant motor block. They are thus alternative methods of regional anesthesia when other techniques are not feasible or have undesirable adverse effects.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.962
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.139
GPT teacher head0.401
Teacher spread0.262 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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