Risk factors for new vertebral compression fractures after vertebroplasty: a meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The risk factors for new vertebral compression fractures (VCFs) after vertebroplasty are unclear. The aim of this meta-analysis was to identify potential risk factors. METHODS: A systematic electronic literature search was performed using the following databases: PubMed, Embase and Cochrane Library; the databases were searched from the earliest available records in 1966 to May 2015. Pooled odds ratios (ORs) or standardized mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using random- or fixed-effects models. The Newcastle-Ottawa scale was used to evaluate the methodological quality of the studies, and Stata 11.0 was used to analyse the data. RESULTS: The primary factors that were associated with new fractures after vertebroplasty were low bone mineral density (SMD -0.375; 95% CI -0.579 to -0.171), steroid usage (OR 2.632; 95% CI 1.399 to 4.950) and the presence of multiple treated vertebrae (OR 2.027; 95% CI 1.442 to 2.851). The data did not support that age, sex, body mass index, non-steroidal anti-inflammatory drug usage, vacuum cleft, thoracolumbar junction, cement volume, kyphosis correction, or intradiscal cement leakage could lead to infection after vertebroplasty. CONCLUSIONS: The present analysis demonstrated that low bone mineral density, the presence of multiple treated vertebrae and a history of steroid usage were associated with the new VCFs after vertebroplasty. Patients with these factors should be informed of the potential increased risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.006 | 0.011 |
| Bibliometrics | 0.001 | 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 it