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Record W2022565011 · doi:10.4103/0019-5049.135050

Ultrasound guided selective cervical nerve root block and superficial cervical plexus block for surgeries on the clavicle

2014· article· en· W2022565011 on OpenAlexaff
Harsha Shanthanna

Bibliographic record

VenueIndian Journal of Anaesthesia · 2014
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsMcMaster UniversityHealth Sciences Centre
Fundersnot available
KeywordsMedicineHydromorphoneAnesthesiaClavicleCervical NerveSurgeryNerve blockInterventional pain managementBlockadeOpioidNerve rootPain managementInternal medicine

Abstract

fetched live from OpenAlex

We report the anaesthetic management of two cases involving surgeries on the clavicle, performed under superficial cervical plexus block and selective C5 nerve root block under ultrasound (US) guidance, along with general anaesthesia. Regional analgesia for clavicular surgeries is challenging. Our patients also had significant comorbidities necessitating individualised approach. The first patient had a history of emphysema, obesity, and was allergic to morphine and hydromorphone. The second patient had clavicular arthritis and pain due to previous surgeries. He had a history of smoking, Stevens-Johnson syndrome, along with daily marijuana and prescription opioid use. Both patients had an effective regional block and required minimal supplementation of analgesia, both being discharged on the same day. Interscalene block with its associated risks and complications may not be suitable for every patient. This report highlights the importance of selective regional blockade and also the use of US guidance for an effective and safe block.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.259
Teacher spread0.242 · 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 designObservational
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

Citations40
Published2014
Admission routes1
Has abstractyes

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