MétaCan
Menu
Back to cohort
Record W4415439007 · doi:10.1302/1358-992x.2025.10.138

COMPARISON OF MAJOR SPINE NAVIGATION PLATFORMS BASED ON KEY PERFORMANCE METRICS: A META-ANALYSIS OF 16,040 SCREWS

2025· article· en· W4415439007 on OpenAlexaff
J-P. Bonello, Robert Koucheki, Ali E. Abbas, Johnathan R. Lex, Nicholas Nucci, Albert Yee, Henry Ahn, Joe Finkelstein, Shirley Lewis

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldEngineering
TopicMedical Imaging and Analysis
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsBlood lossNavigation systemSpinal surgeryReduction (mathematics)MEDLINEMeta-analysis

Abstract

fetched live from OpenAlex

Navigation technologies continue to develop and aid the instrumentation of spinal hardware. This meta-analysis attempted to evaluate all available published literature on computer-assisted spine navigation to compare the placement accuracy and surgical outcomes of prominent platforms such as Medtronic, Brainlab, and Stryker, using conventional techniques (free-hand or fluoroscopy) as a common control. Literature searches were performed using OVID MEDLINE and EMBASE databases. Included studies must have performed postoperative computed tomography to evaluate screw placement. Screw placement accuracy, neurologic complications, operative time, and blood loss were then analysed directly via network meta-analysis. Among the 28 included studies, 2959 patients underwent spinal instrumentation surgery, of which 1471 patients were in the navigation group and 1488 patients in the conventional group. Average age of patients in the navigation and conventional groups were 59.1 and 57.8 years old, respectively. 16,040 screws were included of which 7957 screws were placed using navigation technologies and 8083 screws were placed using conventional methods. Navigation manufactures included in the pooled analysis were Medtronic (15 studies, screws=9421), BrainLab (8 studies, screws=4778), Stryker (4 studies, screws=1684), and SeaSpine (7D Surgical) (1 study, screws=157). At all spinal levels, there was a significantly lower risk of major breach and improved screw accuracy in the navigation group compared to the conventional group (OR 0.42, 95% CI 0.27 to 0.63, p<0.0001, I2 = 56%, random effect model). Across platforms, Stryker demonstrated the highest screw accuracy with an 84% reduction in risk of breach (OR 0.16 95% CI 0.06 to 0.41, P < 0.00001, I2 = 0%, REM), followed by Medtronic and then Brainlab. Additionally, there were no significant differences in secondary surgical outcomes including rates of neurologic complications and blood loss between navigation platforms. However, BrainLab demonstrated significantly faster operative time compared to Medtronic by approximately 30 minutes (95% CI −63.27 to −2.47, p=0.03, I2=74%). Our results indicate that use of computer-assisted navigation platforms in spine surgery leads to an approximately 60% reduction in risk of major breach compared to conventional methods, with Stryker demonstrating the highest accuracy among platforms. Furthermore, we demonstrated that this increased accuracy is without negative change to surgical outcomes such as neurologic complications and blood loss. Although the studies analysed are highly heterogeneous, this study is the first to directly and quantitatively compare available navigation platforms. As such, our findings provide a foundation for further investigations and offer insight in guiding the acquisition of navigation platforms by surgeons and institutions.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.820
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.296
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueOrthopaedic ProceedingsSame topicMedical Imaging and AnalysisFrench-language works237,207