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Record W4224284410 · doi:10.7759/cureus.24258

Robot-Assisted Versus Conventional Freehand Fluoroscopy-Guided Percutaneous Screw Fixation in Femoral Neck Fractures: A Systematic Review and Meta-analysis

2022· review· en· W4224284410 on OpenAlexaff
Abdulrahman Al-Naseem, Ahmed R Gonnah, Hussain Al-Ali, Abdulaziz Al-Naseem, Irfan Siddique

Bibliographic record

VenueCureus · 2022
Typereview
Languageen
FieldMedicine
TopicHip and Femur Fractures
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsMedicineFluoroscopyPercutaneousFixation (population genetics)RadiologyFemoral neckSurgeryOsteoporosis

Abstract

fetched live from OpenAlex

Robotic-assisted navigation for percutaneous femoral neck fracture fixation is a new technology that has shown enhanced intraoperative and postoperative outcomes compared to the conventional freehand fluoroscopy-guided technique. The authors aim to compare robot-assisted femoral neck fracture fixation to conventional freehand fluoroscopy-guided repair. Electronic databases were searched, identifying all observational studies comparing outcomes of both groups. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic review and meta-analysis were conducted. The primary outcomes included operative duration (minutes), intraoperative bleeding (mL), fluoroscopy exposure, and frequency of intraoperative drilling. The secondary outcomes included Harris scores, healing rate and time, screw accuracy, and postoperative complications. Seven observational studies were identified, enrolling 506 patients. There was a significant difference between the robot-assisted and conventional groups in terms of intraoperative blood loss (mean difference (MD) = -18.83, p ≤ 0.05), fluoroscopy exposure (MD = -1.81, p ≤ 0.05), and intraoperative drilling frequency (MD = -7.35, p < 0.05). There was no significant difference in operative duration between the groups (MD = -0.21, p = 0.66). Most secondary outcomes were improved in the robot-assisted group. Overall, robot-assisted fixation was superior in terms of safety and efficacy.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.837
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0100.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0120.000

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 head0.176
GPT teacher head0.418
Teacher spread0.242 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations13
Published2022
Admission routes1
Has abstractyes

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