Injury of the Posterior Ligamentous Complex of the Thoracolumbar Spine
Bibliographic record
Abstract
STUDY DESIGN: Prospective diagnostic imaging study. OBJECTIVE: To determine the accuracy of magnetic resonance imaging (MRI) in diagnosing injury of the posterior ligamentous complex (PLC) in patients with thoracolumbar trauma. SUMMARY OF BACKGROUND DATA: Treatment decisions in thoracolumbar injury patients are currently based on the status of the PLC. It is, therefore, important to understand the accuracy of MRI in diagnosing varying degrees of PLC injury. Prior studies report that MRI is up to 100% sensitive for diagnosing PCL injury. METHODS: Patients with an acute injury from T1 to L3 who required posterior surgery were prospectively studied. A musculoskeletal radiologist, based on the preoperative MRI findings, characterized each of the 6 components of the PLC as intact, incompletely disrupted, or disrupted. During the surgical procedure, the surgeon identified each component of the PLC as intact, incompletely disrupted, or disrupted. The radiologist's interpretation and surgical findings were compared. RESULTS: Forty-two patients with 62 levels of injury were studied. There were 33 males (78.6%) and 9 females (21.4%), and the average age was 35.7 years. According to the kappa score, there was a moderate level of agreement between the radiologist's interpretation and the intraoperative findings for all PLC components except the thoracolumbar fascia, for which there was slight agreement. The sensitivity for the various PLC components ranged from 79% (left facet capsule) to 90% (interspinous ligament). The specificity ranged from 53% (thoracolumbar fascia) to 65% (ligamentum flavum). There was less agreement between the radiologist and surgeon for the patients with less severe neurologic compromise, i.e., those patients with an AIS grade of either D or E. CONCLUSION: The sensitivity and specificity of MRI for diagnosing injury of the PLC are lower than previously reported in the literature. The integrity of the PLC as determined by MRI should not be used in isolation to determine treatment.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".