Degenerative Marrow (Modic) Changes on Cervical Spine Magnetic Resonance Imaging Scans
Bibliographic record
Abstract
STUDY DESIGN: A prevalence and reliability study of Modic changes (MCs) in the cervical spine. OBJECTIVE: To assess the prevalence and reliability of diagnosing and classifying MCs and their relationship to disc herniations (DHs) in the cervical spine. SUMMARY OF BACKGROUND DATA: Degenerative marrow (Modic) changes in the spine can be seen on MRI with some evidence linking them to pain. Many studies have been published on MCs in the lumbar spine, but only one small prevalence study focusing on MCs in the cervical spine has been reported. METHODS: The cervical magnetic resonance imaging (MRI) scans of 500 patients over the age of 50 were retrospectively evaluated for the prevalence, type, and location of MCs and DHs. Two hundred of these same scans were independently analyzed by a second observer to evaluate interobserver reliability of diagnosis with 100 re-evaluated by the same observer 1 month later to assess intraobserver reliability. The SPSS program and Kappa statistics were used to assess prevalence and reliability. The risk ratio comparison of DH and MC was calculated. RESULTS: Four hundred and twenty-six patients (85.2%) met the inclusion criteria. MCs were observed in 40.4% of patients (14.4% of all motion segments). A 4.3% were type 1 and 10.1% were type 2. DH were seen in 78.2% of patients (13.3% of motion segments). Both MC and DH were most frequently observed at C5/6 and C6/7. Disc extrusions were positively associated with MC (RR=2.4). The reliability showed an upper moderate interobserver (k=0.54) and an almost perfect intraobserver agreement (k=0.82). CONCLUSION: A high prevalence of MCs was observed with type 2 predominating. The C5/6 and C6/7 levels are most effected. Patients with MC are more likely to have a DH at the same level. MC type 2 predominates. The classification is reliable.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.003 | 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 teacher head, 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".