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Record W3141634248 · doi:10.1213/xaa.0000000000001427

Cryoneurolysis of Innervation to Sacroiliac Joints: Technical Description and Initial Results—A Case Series

2021· article· en· W3141634248 on OpenAlexaff
Rajendra Kumar Sahoo, Gautam Das, Laxmi Pathak, Debjyoti Dutta, Chinmoy Roy, Anuj Bhatia

Bibliographic record

VenueA&A Practice · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsSacroiliac jointMedicineAnalgesicLow back painRadiofrequency ablationPhysical therapySurgeryAnesthesiaAblationInternal medicineAlternative medicine

Abstract

fetched live from OpenAlex

The sacroiliac joint (SIJ) is a common source of pain in patients with low back pain. Untreated pain from the SIJ can lead to prolonged discomfort and financial burden. Interventional treatments for SIJ-related pain include intraarticular steroid injection and radiofrequency ablation but both procedures provide pain relief for a limited duration. Cryoneurolysis is another neuroablative technique that is effective in various chronic pain conditions. However, there is no clear description of SIJ cryoneurolysis in the published literature. In this report, we present 5 patients with SIJ-related pain and we describe the ultrasound-guided SIJ cryoneurolysis technique and its analgesic efficacy.

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)0.017
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.753
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.334
Teacher spread0.307 · 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 designBench or experimental
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

Citations8
Published2021
Admission routes1
Has abstractyes

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