Metabolic Syndrome Increases the Prevalence of Spine Osteoarthritis
Bibliographic record
Abstract
OBJECTIVE: To determine whether the prevalence of severe spinal osteoarthritis (OA) increases with the number of metabolic syndrome (MetS) risk factors. METHODS: Data from a single surgeon's high volume, spine surgery practice were reviewed. Severe OA was defined as degenerative spondylolisthesis or cervical or lumbar stenosis causing neurologically based symptoms and early OA as lumbar and cervical spondylosis causing axial pain only. Logistic regression modeling was used to determine the odds (adjusted for age and sex) of having severe spine OA with more numerous MetS risk factors. RESULTS: Severe spinal OA was identified in 839/1502 patients (55.9%) and early OA in the remaining 663 individuals (44.1%). The overall prevalence of MetS was 30/1502 (2.0%): 26/839 (3.1%) in the severe OA group and 4/663 (0.6%) in the early OA group (P = 0.001). Presence of all four MetS risk factors was associated with almost quadruple the odds of having severe OA as compared with absence of risk factors (OR 3.9 [1.4-11.6], P < 0.01). CONCLUSION: The components of MetS are more prevalent in subjects with severe spinal OA than in those with spondylosis causing axial pain. Future study of the association between MetS and the incidence of OA is required.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".