Predictive risk factors for recollapse of cemented vertebrae after percutaneous vertebroplasty: A meta-analysis
Bibliographic record
Abstract
BACKGROUND: As one of the most common complications of osteoporosis, osteoporotic vertebral compression fracture (OVCF) increases the risk of disability and mortality in elderly patients. Percutaneous vertebroplasty (PVP) is considered to be an effective, safe, and minimally invasive treatment for OVCFs. The recollapse of cemented vertebrae is one of the serious complications of PVP. However, the risk factors associated with recollapse after PVP remain controversial. AIM: To identify risk factors for the recollapse of cemented vertebrae after PVP in patients with OVCFs. METHODS: -squared test. The methodological quality of the included studies was assessed according to the Newcastle-Ottawa Scale. RESULTS: < 0.00001). The analysis did not support that age, gender, lumbar bone mineral density, preoperative visual analogue scale score, injected cement volume, intradiscal cement leakage, or vertebral height restoration could increase the risk for cemented vertebra recollapse after PVP in OVCFs. CONCLUSION: This meta-analysis suggests that thoracolumbar junction fractures, preoperative intravertebral cleft, and solid lump cement distribution pattern are associated with the recollapse of cemented vertebrae after PVP in OVCF patients.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.035 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".