Robot-assisted percutaneous pedicle screw placement accuracy compared with alternative guidance in lateral single-position surgery: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: While single-position surgery (SPS) eliminates the need for patient repositioning, the placement of screws in the unconventional lateral position poses unique challenges related to asymmetry relative to the surgical table. Use of robotic guidance or intraoperative navigation can help to overcome this. The aim of this study was to compare the relative accuracies offered by these various navigation modalities for pedicle screws placed in lateral SPS. METHODS: According to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the PubMed/Medline, Embase, and Cochrane Library databases were queried for studies reporting pedicle screw placement accuracy using fluoroscopic, CT-navigated, O-arm, or robotic guidance in lateral SPS, and a systematic review and meta-analysis was performed. Included studies all compared evaluated screw placement accuracy in lateral SPS using a single navigation method. Quality assessment was performed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system; risk of bias was assessed using the Newcastle-Ottawa Scale and the Joanna Briggs Institute checklist. The primary outcome, rate of pedicle screw breach, was analyzed using random-effects meta-analysis. RESULTS: Eleven studies were included comprising 548 patients who underwent the placement of instrumentation with 2488 screws. For the fluoroscopic, CT-navigated, O-arm, and robotic guidance cohorts, there were 3, 2, 3, and 3 studies, respectively. Breach rates by modality were as follows: fluoroscopic guidance (6.6%), CT navigation (4.7%), O-arm (3.9%), and robotic guidance (3.9%). Random-effects meta-analysis showed a significant difference between studies, with an overall breach rate of 4.9% (95% CI 3.1%-7.5%; p < 0.001); however, testing for subgroup differences failed to show a significant difference between guidance modalities (QM = 0.69, df = 3; p = 0.88). Heterogeneity between studies was significant (I2 = 79.0%, τ2 = 0.41, χ2 = 47.65, df = 10; p < 0.001). CONCLUSIONS: Robotic guidance of screws is noninferior to alternative guidance modalities in lateral SPS; however, additional prospective studies directly comparing different guidance types are merited.
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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 | 0.047 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.038 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| 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".