MétaCan
Menu
Back to cohort
Record W2166696993 · doi:10.1148/radiol.2211010213

Lumbar Facet Joint Synovial Cyst: Percutaneous Treatment with Steroid Injections and Distention—Clinical and Imaging Follow-up in 12 Patients

2001· article· en· W2166696993 on OpenAlexaff
Nathalie J. Bureau, P A Kaplan, Robert G. Dussault

Bibliographic record

VenueRadiology · 2001
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsHôpital Saint-LucCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicinePercutaneousCystLumbarFacet jointSurgeryFacet (psychology)AsymptomaticRadiologyLow back painSynovial cystPathology

Abstract

fetched live from OpenAlex

PURPOSE: To determine the imaging characteristics of lumbar facet joint synovial cysts after percutaneous treatment with steroid injections and distention of the cyst and to correlate these findings with the clinical outcome. MATERIALS AND METHODS: Clinical outcome and imaging findings were retrospectively studied in 12 patients (four men, eight women) aged 45-79 years (mean, 60 years) with a symptomatic lumbar facet joint synovial cyst treated with percutaneous steroid injections. At varying times after the procedure, patients were contacted for clinical follow-up, and repeat imaging was performed to verify the status of the cyst. RESULTS: Excellent pain relief was achieved in nine (75%) of 12 patients. At follow-up imaging, the cyst completely regressed in six (67%) of these nine patients, partially regressed in two (22%) patients, and was unchanged in one (11%) patient. One (8%) of the 12 patients had transient pain relief, with recurrence of symptoms at short intervals after each of three injections. No pain relief was achieved in two (17%) of 12 patients. CONCLUSION: Image-guided percutaneous steroid injections are often effective in the treatment of lumbar facet joint synovial cysts and may result in complete regression of the cyst.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.028
GPT teacher head0.293
Teacher spread0.264 · 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.

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

Citations102
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueRadiologySame topicSpine and Intervertebral Disc PathologyFrench-language works237,207