Does Vertebral Cement Augmentation Reduce Postoperative Proximal Junction Complications in Spinal Deformity Corrective Surgery: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
OBJECTIVE: To assess the effectiveness of vertebral cement augmentation (VCA) at upper instrumented vertebra (UIV) and UIV+1 in preventing proximal junction complications in correction surgery for adult spinal deformity patients. METHODS: A literature search was conducted on Web of Science, PubMed, and Cochrane Library databases for comparative studies published before December 30th, 2024. Two reviewers independently screened eligible articles based on the inclusion and exclusion criteria, assessed study quality with Newcastle-Ottawa scale, and extracted data like study characteristics, surgical details, primary and secondary outcomes. Data analysis was performed using Review Manager 5.4 and Stata software. RESULTS: Of all 513 papers screened, a meta-analysis was conducted on 7 articles, which included 333 cases in the VCA group and 827 cases in the control group. Patients in the VCA group had significantly older age and lower T score than patients in the control group. Although there was no statistically significant difference in the incidence of proximal junctional failure between the 2 groups, the results of the meta-analysis showed that the incidence of proximal junctional failure and the need for revision surgery were reduced by 36% and 71%, respectively, in the VCA group. One study reported 2 clinically silent pulmonary cement embolism and 1 patient requiring surgical decompression for cement leak into the spinal canal. CONCLUSION: This meta-analysis supported the use of VCA in corrective surgery for spinal deformities patients, especially in patients with advanced age and osteoporosis.
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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 | 0.008 | 0.020 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.035 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".