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Real‐time ultrasound‐guided spinal anesthesia in patients with a challenging spinal anatomy: two case reports

2009· article· en· W2057425440 on OpenAlexaff
Ki Jinn Chin, Vincent Chan, Reva Ramlogan, Anahi Perlas

Bibliographic record

VenueActa Anaesthesiologica Scandinavica · 2009
Typearticle
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineUltrasoundSpinal anesthesiaLumbarLumbar punctureLandmarkAnatomical landmarkSurgeryRadiologyAnesthesiaCerebrospinal fluidPathology

Abstract

fetched live from OpenAlex

Spinal anesthesia may be challenging in patients with poorly palpable surface landmarks or abnormal spinal anatomy. Pre-procedural ultrasound imaging of the lumbar spine can help by providing additional anatomical information, thus permitting a more accurate estimation of the appropriate needle insertion site and trajectory. However, actual needle insertion in the pre-puncture ultrasound-assisted technique remains a 'blind' procedure. We describe two patients with an abnormal spinal anatomy in whom ultrasound-assisted spinal anesthesia was unsuccessful. Successful dural puncture was subsequently achieved using a technique of real-time ultrasound-guided spinal anesthesia. This may be a useful option in patients in whom landmark-guided and ultrasound-assisted techniques have failed.

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)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.173
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.014
GPT teacher head0.276
Teacher spread0.263 · 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 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

Citations62
Published2009
Admission routes1
Has abstractyes

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