What Risk Factors Are Associated With Recurrent Osteoporotic Vertebral Compression Fractures After Percutaneous Vertebral Augmentation? A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Osteoporotic vertebral compression fracture (OVCF) has been extensively treated clinically using percutaneous vertebral augmentation (PVA), which includes percutaneous kyphoplasty and percutaneous vertebroplasty. Postoperative refracture is a common complication after PVA, but the associated factors and specific mechanisms behind these fractures are not entirely clear. QUESTIONS/PURPOSES: In a systematic review and meta-analysis, we asked: What factors were associated with increased or decreased odds of refracture after PVA for OVCF? METHODS: Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines, we conducted a comprehensive search of the Cochrane Library, PubMed, Web of Science, and Embase for the time period from database inception to August 31, 2024 (which also was when we last searched). We included case-control studies in which participants were patients with OVCF and were treated with PVA, grouped into refracture versus non-refracture groups based on the presence or absence of refracture. We excluded studies published on preprint servers, conference reports, case reports, and systematic reviews or meta-analyses. We collected 2398 records in the database. After excluding studies that were duplicates and did not meet the inclusion criteria, we included 22 studies involving 7132 participants, 75% (5368) of whom were women, with a mean age of 76 years for patients in the refracture group and 74 years for patients in the non-refracture group. Quality assessment was performed using the Newcastle-Ottawa Scale, with which we assessed three aspects of the study; the mean ± SD score for the included studies was 7.3 ± 0.7 of 9 total (on this scale, higher scores are better), representing generally high study quality. The determination of heterogeneity relied on I 2 and chi-square test, and we used a random-effects model when the I 2 was > 50% and p ≤ 0.05; otherwise, a fixed-effects model was chosen. According to the Egger test and trim and fill method, publication bias did not significantly affect most of our results. RESULTS: The combined results showed that older age (mean difference 2.24 [95% confidence interval (CI) 1.25 to 3.23]; p < 0.001), lower bone mineral density (BMD) (standardized mean difference [SMD] -0.72 [95% CI -0.99 to -0.45]; p < 0.001), greater preoperative AP vertebral height ratio (SMD 0.26 [95% CI 0.07 to 0.45]; p = 0.01), greater preoperative kyphotic angle (KA) (SMD 0.47 [95% CI 0.10 to 0.83]; p = 0.01), bone cement leakage (OR 1.39 [95% CI 1.05 to 1.84]; p = 0.02), multivertebral fractures (OR 3.58 [95% CI 2.53 to 5.07]; p < 0.001), smoking (OR 1.53 [95% CI 1.16 to 2.02]; p = 0.003), use of glucocorticoids (OR 3.18 [95% CI 2.09 to 4.84]; p < 0.001), and previous osteoporotic vertebral fracture (OR 2.55 [95% CI 1.58 to 4.13]; p < 0.001) were associated with increased odds of refractures after surgery. Use of antiosteoporosis therapy was associated with a decreased odds of postoperative refracture (OR 0.39 [95% CI 0.24 to 0.64]; p < 0.001). CONCLUSION: Based on the results of our meta-analysis, surgeons can identify those who are more likely to have refracture by knowing basic information about their patients preoperatively, such as advanced age, lower BMD, greater preoperative AP ratio, greater preoperative KA, and the presence of multivertebral fractures or previous osteoporotic vertebral fracture. Also, intraoperative reduction of bone cement leakage and postoperative counseling of patients to quit smoking, reduce glucocorticoid use, and administration of antiosteoporosis therapy were used to reduce the probability of refracture. The association between some factors and refracture is uncertain, such as BMI and thoracolumbar fracture, and further studies are needed. LEVEL OF EVIDENCE: Level III, therapeutic study.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.063 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".