Modic Changes in the Lumbar Spine are Common Aging-related Degenerative Findings that Parallel With Disk Degeneration
Bibliographic record
Abstract
STUDY DESIGN: This is a cross-sectional study. OBJECTIVE: To determine the prevalence and distribution patterns of Modic changes (MCs) in the lumbar spine and their associations with disk degeneration in mainland Chinese using a sample of general population. SUMMARY OF BACKGROUND DATA: Previous studies reported that the prevalence of MCs in Hong Kong Chinese was much lower than in other populations. Moreover, their associations with disk degeneration need further study. MATERIALS AND METHODS: The study sample consisted of 442 subjects (53.6±14.9 y; range, 20-88 y) randomly selected from a typical Chinese community. Lumbar spines were imaged using a 3.0 T magnetic resonance scanner. Eleven endplates (L1-S1) in the lumbar spine were evaluated for the presence of MCs, type, location, and size to determine MCs prevalence and distribution patterns. Disk degeneration was graded using a Pfirrmann scale. RESULTS: MCs were present in 209 (47.3%) subjects and 593 (12.2%) endplates. Among these endplates, 84.1% (499) were type II, 9.1% (54) were type I, and 6.4% (38) were mixed MCs. Approximately 2/3 MCs were present in the lower lumbar spine and 44.9% of MCs were at the L5/S1 disk level. Most MCs (73.9%) involved both endplates of a disk. Greater age [odds ratio (OR)=2.44 for each 10-year increase, P<0.001] and body mass index (OR=1.07, P=0.016) were associated with the presence of MCs, as was adjacent disk degeneration (OR=6.00, P<0.001), controlling for age and other covariates. Greater age, body mass index, and adjacent disk degeneration were also associated with greater MCs size. CONCLUSIONS: MCs are common in mainland Chinese, with type II predominating. MCs mainly present in the lower lumbar region and tend to occur in pairs. MCs were strongly associated with age and disk degeneration, suggesting MCs may be aging-related degenerative findings that parallel disk degeneration. LEVEL OF EVIDENCE: Level II.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".