The Frequency and Treatment of Dural Tears and Cerebrospinal Fluid Leakage in 266 Patients With Thoracic Myelopathy Caused by Ossification of the Ligamentum Flavum
Bibliographic record
Abstract
STUDY DESIGN: Retrospective review. OBJECTIVE: To perform a single-institution analysis of incidence, treatment, and clinical outcome in patients with thoracic ossification of the ligamentum flavum (OLF) who experienced dural tears and cerebrospinal fluid (CSF) leakage. SUMMARY OF BACKGROUND DATA: There is a paucity of clinical reports focusing on dural tears and CSF leakage after thoracic OLF surgery. Because dural adhesion and dural ossification are common features of thoracic OLF, the incidence of CSF leakage in OLF patients is high and represents a significant clinical challenge. METHODS: A total of 266 patients with thoracic OLF were admitted to our hospital from 1995 to 2011. Each patient's medical records were reviewed to identify cases of dural tears and CSF leakage. Information on therapeutic strategy used to repair the dural tears and complications related to CSF leakage was extracted. RESULTS: The incidence of dural tears and CSF leakage in OLF patients was 32% (85/266). The incidence of dural ossification was 25.2%. The dural tears were repaired with a range of materials, including gelatin sponge, muscle/fascia, artificial dura, silk suture, and fibrin glue. The intraoperative repair procedure did not resolve CSF leakage in 65 cases, and 16 of those cases experienced complications related to the continued CSF leakage, including CSF pseudocyst, wound dehiscence, and meningitis. Fifty-eight patients with CSF leakage were eventually cured by a series of comprehensive treatments, which included prone position, continuous pressure by sandbag, ultrasound-guided puncture, and aspiration. Only 7 patients required reoperation. CONCLUSION: Dural ossification was the main reason for dural tears. In all, 78 of the 85 patients with CSF leakage or dural tear were successfully cured. The success rate was 91.8%, which indicated that a series of comprehensive treatments was an effective strategy to treat these patients.
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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) | 0.000 | 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".