Risk factors for cement leakage after percutaneous vertebral augmentation for osteoporotic vertebral compression fractures: a meta-analysis
Bibliographic record
Abstract
BACKGROUND: Osteoporotic vertebral compression fractures (OVCF) may necessitate percutaneous vertebral augmentation (PVA), a procedure not without its risks. One notable complication is cement leakage (CL), which can cause significant distress in patients. Despite its clinical importance, there remains a paucity of meta-analyses investigating these complications and their management in the existing literature. MATERIAL AND METHODS: The authors systematically reviewed PubMed, Cochrane Library, Embase, and Web of Science databases up to February 2024 to identify studies examining CL following PVA treatment in OVCF. The authors assessed the quality of eligible cohort studies using the Newcastle-Ottawa Scale (NOS), extracted data on incidence, identified risk factors for CL, and conducting meta-analysis with Revman 5.2 software. The authors calculated odd ratios (OR) and mean differences (MD) with 95% CI applying random-effects models. RESULTS: The authors identified twelve cohort studies that matched our strict inclusion criteria. These studies included a total of 2388 patients and 3392 vertebrae. CL was identified in 1132 vertebrae. Notable risk factors for CL included compromised cortical bone integrity (OR 5.00, 95% CI 3.01-8.29, P <0.00001), presence of intravertebral vacuum clefts (OR 1.68, 95% CI 1.07-2.65, P =0.03), basivertebral foramen sign (OR 1.77, 95% CI 1.09-2.89, P =0.02), and volume of cement used (MD 0.75, 95% CI 0.41-1.10, P <0.0001). CONCLUSION: The authors' findings underscore the significance of cortical bone integrity, intravertebral vacuum cleft, basivertebral foramen sign, and cement volume as principal determinants of CL risk in PVA for OVCF. These insights advocate for tailored surgical strategies to mitigate the risk of CL in this patient population.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".