Craniocervical Instability in Ehlers-Danlos Syndrome—A Systematic Review of Diagnostic and Surgical Treatment Criteria
Bibliographic record
Abstract
STUDY DESIGN: Systematic review. OBJECTIVE: Ehlers-Danlos Syndrome (EDS) comprises a spectrum of connective tissue disorders, which may be associated with cranio-cervical instability (CCI). There is a lack of consensus on diagnostic imaging parameters, indications, and outcomes of surgical treatment. METHODS: This systematic review analyses the literature on diagnostic methods and/or criteria for CCI, screening the databases Ovid Medline, Embase, Cochrane Library, and PubMed. Articles were included based on the PRISMA guidelines and assessed using the Newcastle-Ottawa Quality Assessment Scale (NOS) and according to their evidence level. RESULTS: Sixteen articles, including 78 surgical patients, met the inclusion criteria. The main diagnostic measures for CCI were dynamic x-rays and CT imaging. Ten different radiographic parameters were reported, of which 4 were the most frequently applied for surgical decision-making: the clivo-axial angle (CXA), the Harris measurement, the Grabb-Mapstone-Oakes measurement, and the angular displacement of C1 to C2. The evidence level ranged between III and V and the article quality between 4 and 8 out of 9 stars on the NOS Scale. CONCLUSIONS: There is a lack of high quality, prospective evidence regarding the evaluation of suspected CCI in patients with EDS. Based on our systematic review, we recommend that the CXA, Harris measurement, Grabb-Mapstone-Oakes measurement, and the angular displacement of C1 to C2 be used to evaluate suspected CCI in EDS patients. Surgical fixation of suspected CCI should only be performed in cases with clear radiographic presence of instability and concordant symptoms/signs. Consensus-based guidelines and care pathways are required.
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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 | 0.014 | 0.064 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.010 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".