Screw-Related Complications After Instrumentation of the Osteoporotic Spine: A Systematic Literature Review With Meta-Analysis
Bibliographic record
Abstract
STUDY DESIGN: Systematic literature review with meta-analysis. OBJECTIVE: Osteoporosis is common in elderly patients, who frequently suffer from spinal fractures or degenerative diseases and often require surgical treatment with spinal instrumentation. Diminished bone quality impairs primary screw purchase, which may lead to loosening and its sequelae, in the worst case, revision surgery. Information about the incidence of spinal instrumentation-related complications in osteoporotic patients is currently limited to individual reports. We conducted a systematic literature review with the aim of quantifying the incidence of screw loosening in osteoporotic spines. METHODS: Publications on spinal instrumentation of osteoporotic patients reporting screw-related complications were identified in 3 databases. Data on screw loosening and other local complications was collected. Pooled risks of experiencing such complications were estimated with random effects models. Risk of bias in the individual studies was assessed with an adapted McHarm Scale. RESULTS: From 1831 initial matches, 32 were eligible and 19 reported screw loosening rates. Studies were heterogeneous concerning procedures performed and risk of bias. Screw loosening incidences were variable with a pooled risk of 22.5% (95% CI 10.8%-36.6%, 95% prediction interval [PI] 0%-81.2%) in reports on nonaugmented screws and 2.2% (95% CI 0.0%-7.2%, 95% PI 0%-25.1%) in reports on augmented screws. CONCLUSIONS: The findings of this meta-analysis suggest that screw loosening incidences may be considerably higher in osteoporotic spines than with normal bone mineral density. Screw augmentation may reduce loosening rates; however, this requires confirmation through clinical studies. Standardized reporting of prespecified complications should be enforced by publishers.
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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 | 0.017 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.048 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 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".