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Record W4310335490 · doi:10.2106/jbjs.oa.22.00052

Evaluating Instability in Degenerative Lumbar Spondylolisthesis

2022· article· en· W4310335490 on OpenAlex

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

VenueJBJS Open Access · 2022
Typearticle
Languageen
FieldMedicine
TopicSpine and Intervertebral Disc Pathology
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaWestern UniversitySaint John Regional HospitalDalhousie University
Fundersnot available
KeywordsMedicineSpondylolisthesisInstabilityLumbarLow back painSurgery

Abstract

fetched live from OpenAlex

The subjective degenerative spondylolisthesis instability classification (S-DSIC) system attempts to define preoperative instability associated with degenerative lumbar spondylolisthesis (DLS). The system guides surgical decision-making based on numerous indicators of instability that surgeons subjectively assess and incorporate. A more objective classification is warranted in order to decrease variation among surgeons. In this study, our objectives included (1) proposing an objective version of the DSIC system (O-DSIC) based on the best available clinical and biomechanical data and (2) comparing subjective surgeon perceptions (S-DSIC) with an objective measure (O-DSIC) of instability related to DLS. Methods: In this multicenter cohort study, we prospectively enrolled 408 consecutive adult patients who received surgery for symptomatic DLS. Surgeons prospectively categorized preoperative instability using the existing S-DSIC system. Subsequently, an O-DSIC system was created. Variables selected for inclusion were assigned point values based on previously determined evidence quality. DSIC types were derived by point summation: 0 to 2 points was considered stable, Type I); 3 points, potentially unstable, Type II; and 4 to 5 points, unstable, Type III. Surgeons' subjective perceptions of instability (S-DSIC) were retrospectively compared with O-DSIC types. Results: The O-DSIC system includes 5 variables: presence of facet effusion, disc height preservation (≥6.5 mm), translation (≥4 mm), a kyphotic or neutral disc angle in flexion, and low back pain (≥5 of 10 intensity). Type I (n = 176, 57.0%) and Type II (n = 164, 53.0%) were the most common DSIC types according to the O-DSIC and S-DSIC systems, respectively. Surgeons categorized higher degrees of instability with the S-DSIC than the O-DSIC system in 130 patients (42%) (p < 0.001). The assignment of DSIC types was not influenced by demographic variables with either system. Conclusions: The O-DSIC system facilitates objective assessment of preoperative instability related to DLS. Surgeons assigned higher degrees of instability with the S-DSIC than the O-DSIC system in 42% of cases. Level of Evidence: Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.204
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.000

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 head0.297
GPT teacher head0.546
Teacher spread0.248 · 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