Metabolic Syndrome Increases the Prevalence of Spine Osteoarthritis
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.
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.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 it