Prevalence of Modic Degenerative Marrow Changes in the Cervical Spine
Bibliographic record
Abstract
OBJECTIVE: The prevalence and distribution of Modic degenerative marrow changes as seen on magnetic resonance imaging scans have been reported for the lumbar spine, and research suggests that type 1 Modic changes are linked to low back pain. The purpose of this study was to report on the prevalence, types, and distribution of the changes found for the cervical spine. METHODS: One hundred thirty-three cervical spine T1-weighted and T2-weighted sagittal magnetic resonance imaging scans were viewed retrospectively by two radiologists. Data were recorded for patient age, patient sex, and the presence or absence of Modic changes. If Modic changes were present, then the precise vertebral levels of these changes and the specific Modic type were recorded. Descriptive statistics were calculated for the prevalence of Modic changes overall, the prevalence of types 1, 2, and 3 changes, and the prevalence in male vs female patients. The frequency of these changes by spinal level was also determined. RESULTS: One hundred eighteen patients met the inclusion criteria. Modic changes were seen in 19 patients (16%), with 4 showing changes in more than one segmental level. The most common Modic change observed was type 1. Type 3 marrow changes were the second most common category to be noted. Only 3 patients had Modic type 2 marrow changes. The most common cervical spinal level to show Modic changes was C5-6. CONCLUSIONS: Modic degenerative bone marrow changes are observed in the cervical spine, with the C5-6 level being the most commonly involved. Unlike in the lumbar spine in which Modic type 2 changes predominate, type 1 marrow changes were far more common in the cervical spine. Further studies should focus on the clinical relevance of these findings.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.002 | 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".