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Record W4362475850 · doi:10.14245/ns.2244952.476

Robotics in Cervical Spine Surgery: Feasibility and Safety of Posterior Screw Placement

2023· article· en· W4362475850 on OpenAlexaboutno aff
Lu-Ping Zhou, Zhigang Zhang, Dui Li, Shu Fang, Rui Sheng, Renjie Zhang, Cailiang Shen

Bibliographic record

VenueNeurospine · 2023
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineRandomized controlled trialConfidence intervalCochrane LibraryMeta-analysisCervical spineCervical vertebraeSurgeryMEDLINERelative riskSubgroup analysisCohort studyInternal medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: Robot-assisted (RA) techniques have been widely investigated in thoracolumbar spine surgery. However, the application of RA methods on cervical spine surgery is rare due to the complex morphology of cervical vertebrae and catastrophic complications. Thus, the feasibility and safety of RA cervical screw placement remain controversial. This study aims to evaluate the feasibility and safety of RA screw placement on cervical spine surgery. METHODS: A comprehensive search on PubMed, Cochrane Library, Embase Database, Web of Science, Chinese National Knowledge Databases, and Wanfang Database was performed to select potential eligible studies. Randomized controlled trials (RCTs), comparative cohort studies, and case series reporting the accuracy of cervical screw placement were included. The Cochrane risk of bias criteria and Newcastle-Ottawa Scale criteria were utilized to rate the risk of bias of the included literatures. The primary outcome was the rate of cervical screw placement accuracy with robotic guidance; subgroup analyses based on the screw type and insertion segments were also performed. RESULTS: One RCT, 3 comparative cohort studies, and 3 case series consisting of 160 patients and 719 cervical screws were included in this meta-analysis. The combined outcomes indicated that the rates of optimal and clinically acceptable cervical screw placement accuracy under robotic guidance were 88.0% (95% confidence interval [CI], 84.1%-91.4%; p = 0.073; I2 = 47.941%) and 98.4% (95% CI, 96.8%-99.5%; p = 0.167; I2 = 35.954%). The subgroup analyses showed that the rate of optimal pedicle screw placement accuracy was 88.2% (95% CI, 83.1%-92.6%; p = 0.057; I2 = 53.305%); the rates of optimal screw placement accuracy on C1, C2, and subaxial segments were 96.2% (95% CI, 80.5%-100.0%; p = 0.167; I2 = 44.134X%), 89.7% (95% CI, 80.6%-96.6%; p = 0.370; I2 = 0.000X%), and 82.6% (95% CI, 70.9%-91.9%; p = 0.057; I2 = 65.127X%;), respectively. CONCLUSION: RA techniques were associated with high rates of optimal and clinically acceptable screw positions. RA cervical screw placement is accurate, safe, and feasible in cervical spine surgery with promising clinical potential.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.348

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.043
GPT teacher head0.322
Teacher spread0.279 · 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 designObservational
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

Citations31
Published2023
Admission routes1
Has abstractyes

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