Minimally invasive sacroiliac joint fusion using triangular titanium implants versus nonsurgical management for sacroiliac joint dysfunction: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Minimally invasive sacroiliac joint (MISIJ) fusion is a surgical option to relieve SIJ pain. The aim of this systematic review and meta-analysis was to compare MISIJ fusion with triangular titanium implants (TTI) to nonoperative management of SIJ dysfunction. METHODS: We searched MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials. We included prospective clinical trials that compared MISIJ fusion to nonoperative management in individuals with chronic low back pain attributed to SIJ dysfunction. We evaluated pain on visual analogue scale, Oswestry Disability Index (ODI) score, health-related quality of life (HRQoL) using the 36-Item Short Form Health Survey (SF-36) physical component (PCS) and mental component summary (MCS) scores, patient satisfaction, and adverse events. RESULTS: A total of 8 articles representing 3 trials that enrolled 423 participants were deemed eligible. There was a significant reduction in pain score with MISIJ fusion compared with nonoperative management (standardized mean difference [SMD] -1.71, 95% confidence interval [CI] -2.03 to -1.39). Similarly, ODI scores (SMD -1.03, 95% CI -1.24 to -0.81), SF-36 PCS scores (SMD 1.01, 95% CI 0.83 to 1.19), SF-36 MCS scores (SMD 0.72, 95% CI 0.54 to 0.9), and patient satisfaction (odds ratio 6.87, 95% CI 3.73 to 12.64) were significantly improved with MISIJ fusion. No significant difference was found between the 2 groups with respect to adverse events (SMD -0.03, 95% CI -0.28 to 0.23). CONCLUSION: Our analysis showed that MISIJ fusion with TTI shows a clinically important and statistically significant improvement in pain, disability score, HRQoL, and patient satisfaction with a similar adverse event profile to nonoperative management in patients with chronic low back pain attributed to SIJ dysfunction.
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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 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.020 | 0.029 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".