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Record W4328049031 · doi:10.1097/ana.0000000000000911

Regional Anesthesia Techniques in Modern Neuroanesthesia Practice: A Narrative Review of the Clinical Evidence

2023· review· en· W4328049031 on OpenAlexaff
Kan Ma, Jamie L. Uejima, John F. Bebawy

Bibliographic record

VenueJournal of Neurosurgical Anesthesiology · 2023
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsMedicineNarrative reviewAnestheticIntensive care medicineAnesthesiaClinical PracticeAnalgesicRegional anesthesiaPhysical therapy

Abstract

fetched live from OpenAlex

Neurosurgical procedures are often associated with significant postoperative pain that is both underrecognized and undertreated. Given the potentially undesirable side effects associated with general anesthesia and with various pharmacological analgesic regimens, regional anesthetic techniques have gained in popularity as alternatives for providing both anesthesia and analgesia for the neurosurgical patient. The aim of this narrative review is to present an overview of the regional techniques that have been incorporated and continue to be incorporated into modern neuroanesthesia practice, presenting in a comprehensive way the evidence, where available, in support of such practice for the neurosurgical patient.

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)0.007
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.713
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
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 head0.191
GPT teacher head0.456
Teacher spread0.264 · 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
Published2023
Admission routes1
Has abstractyes

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