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Record W3177672117 · doi:10.1007/s12630-021-02050-x

Continuous bilateral subomohyoid suprascapular nerve blocks for postoperative analgesia for bilateral rotator cuff repair: a case report

2021· article· en· W3177672117 on OpenAlexaff
Shalini Dhir, Marie‐Eve LeBel, Rosemary A. Craen

Bibliographic record

VenueCanadian Journal of Anesthesia/Journal canadien d anesthésie · 2021
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsSt Joseph's Health CareWestern University
Fundersnot available
KeywordsMedicineRopivacaineSurgerySuprascapular nerveAnesthesiaRotator cuffShoulder surgeryBrachial plexus

Abstract

fetched live from OpenAlex

Blocking the suprascapular nerve under the inferior belly of the omohyoid muscle is a novel regional anesthesia technique that has been proposed for shoulder analgesia. We describe the use of and our experience with bilateral indwelling suprascapular catheters for pain management via continuous infusions in a patient undergoing bilateral shoulder surgery. Bilateral subomohyoid suprascapular catheters were inserted prior to surgery for postoperative analgesia in a patient undergoing bilateral rotator cuff tear repair. The catheters were placed 0.5–1 cm beyond the needle tip, and low local anesthetic infusion rates (ropivacaine 0.2% at 5 mL·hr −1 on each side) were used. Judicious use of preoperatively placed bilateral suprascapular catheters added to a comprehensive multimodal analgesic regimen provided excellent analgesia without respiratory compromise throughout the perioperative course.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0030.002
Science and technology studies0.0030.003
Scholarly communication0.0020.003
Open science0.0020.002
Research integrity0.0090.005
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 head0.014
GPT teacher head0.245
Teacher spread0.231 · 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 designCase report
Domainnot available
GenreEmpirical

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
Published2021
Admission routes1
Has abstractyes

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