MétaCan
Menu
← Back to cohort
Record W4291018460 · doi:10.1136/rapm-2022-esra.338

B264 Do tarlov cysts usually cause back pain?

2022· article· en· W4291018460 on OpenAlexaff
A Ghidan, A Bhatia, P Kumar

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsToronto Western Hospital
Fundersnot available
KeywordsMedicineNerve rootMagnetic resonance imagingBack painWeaknessThighSurgeryPosterior compartment of thighGanglion cystAnatomyRadiology

Abstract

fetched live from OpenAlex

Background and Aims 61-year-old lady case of Complex Regional Pain Syndrome involving the left foot and ankle due to Left foot crush injury (3-foot fractures/first proximal phalanx and first metatarsal). Her pain has been refractory to pharmacotherapy and SCS trial then she developed new symptoms and changes in the pain character as lower back and the left buttock radiating in the outer aspect of the left posterior thigh and radiating down the calf into the outer aspect of the foot and the sole of the foot. Urgent MRI showed: Multiple prominent bilateral perineural nerve root sleeve cysts that are Tarlov cysts within the sacral spinal canal tracking along with the proximal exiting nerve roots. Methods Results Tarlov cysts are an uncommon cause of back pain.Tarlov cysts are fluid-filled sacs that most often affect nerve roots at the lower end of the spine. Such cysts typically cause no symptoms and are found incidentally in magnetic resonance imaging (MRI) studies done for other reasons. (1) Conclusions in some cases, the cysts expand, putting pressure on the affected nerve root. The results may include sharp, burning pain in the hip and down the back of the thigh, possibly with weakness and reduced sensation all along the affected leg and foot. Tarlov cysts sometimes enlarge enough to cause erosion of the surrounding bone, which is another way they may cause back pain. In most cases, Tarlov cysts require no treatment. For those that do, some surgical treatments — such as draining the cyst, have had promising results. (1)

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 score0.008
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0080.003

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 head0.029
GPT teacher head0.295
Teacher spread0.266 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

Explore more

Same topicSpine and Intervertebral Disc Pathology→French-language works237,207→