MétaCan
Menu
Back to cohort

Early Retropulsion of Titanium-Threaded Cages After Posterior Lumbar Interbody Fusion

2001· article· en· W2020117308 on OpenAlexaff
Eshkenazi A. Uzi, Dan Dabby, Emmanuel Tolessa, Joel Finkelstein

Bibliographic record

VenueSpine · 2001
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsNorth York General HospitalSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineLumbarSpinal fusionArthrodesisSurgery

Abstract

fetched live from OpenAlex

STUDY DESIGN: Two patients had postoperative posterior migration of titanium fusion cages after posterior lumbar interbody fusion. They underwent a repeat posterior procedure and posterior fusion with pedicle screws. OBJECTIVE: To suggest a treatment for posterior migration of titanium-threaded cages causing spinal stenosis after posterior lumbar interbody fusion. SUMMARY OF BACKGROUND DATA: The use of titanium fusion cages in posterior lumbar interbody fusion is gaining popularity as a technique for arthrodesis. The literature contains only a few reports concerning complications associated with their use. METHODS: Two patients had retropulsion of titanium threaded cages, ten days and 2 months after posterior lumbar interbody fusion. The retropulsed cages compressing the dura, caused sudden onset of back pain and radiating pain to the lower extremities. Both patients underwent repeat posterior procedure that included repositioning of the cages and posterior fusion with pedicle screws. RESULTS: Symptoms of back and leg pain subsided after repositioning of the cages and application of the pedicle screws. CONCLUSIONS: A repeat posterior approach and repositioning of the retropulsed titanium fusion cages in addition to posterior fusion with pedicle screws successfully managed this complication.

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)0.003
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 score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.283
Teacher spread0.269 · 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

Citations48
Published2001
Admission routes1
Has abstractyes

Explore more

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