MétaCan
Menu
Back to cohort

Lumbar Neuraxial Ultrasound for Spinal and Epidural Anesthesia: A Systematic Review and Meta-Analysis

2017· review· en· W4239453972 on OpenAlex
Anahi Perlas, Luis Enrique Chaparro, Ki Jinn Chin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueObstetric Anesthesia Digest · 2017
Typereview
Languageen
FieldMedicine
TopicAnesthesia and Pain Management
Canadian institutionsToronto Western HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineAnesthesiaLumbarNeuraxial blockadeAnestheticEpidural hematomaSurgeryHematomaSpinal anesthesia

Abstract

fetched live from OpenAlex

( Reg Anesth Pain Med . 2016;41:251–260) Spinal anesthesia and lumbar epidural anesthesia are safe and effective anesthetic techniques. However, neuraxial blocks can sometimes be difficult to perform especially when the spinal anatomy is altered. This technical challenge poses a potential risk of procedural failure and consequent complications including postdural puncture headache and backache, epidural hematoma, and spinal cord injury. A neuraxial ultrasound of the spine delineates its anatomy precisely, thus facilitating successful insertion of a spinal or epidural needle. This study aimed to assess the evidence favoring the use of preprocedural neuraxial ultrasound for spinal or lumbar epidural anesthesia and to put forward recommendations for practice.

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.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.906
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0180.005
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
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 head0.134
GPT teacher head0.369
Teacher spread0.234 · 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