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Record W4205932205 · doi:10.3171/2021.10.focus21509

Evaluating robotic pedicle screw placement against conventional modalities: a systematic review and network meta-analysis

2022· article· en· W4205932205 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueNeurosurgical FOCUS · 2022
Typearticle
Languageen
FieldMedicine
TopicSpinal Fractures and Fixation Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsSurgical proceduresBlood lossMEDLINERobotic surgery

Abstract

fetched live from OpenAlex

OBJECTIVE: Several approaches have been studied for internal fixation of the spine using pedicle screws (PSs), including CT navigation, 2D and 3D fluoroscopy, freehand, and robotic assistance. Robot-assisted PS placement has been controversial because training requirements, cost, and previously unclear benefits. This meta-analysis compares screw placement accuracy, operative time, intraoperative blood loss, and overall complications of PS insertion using traditional freehand, navigated, and robot-assisted methods. METHODS: A systematic review was performed of peer-reviewed articles indexed in several databases between January 2000 and August 2021 comparing ≥ 2 PS insertion methods with ≥ 10 screws per treatment arm. Data were extracted for patient outcomes, including PS placement, misplacement, and accuracy; operative time, overall complications, intraoperative blood loss, postoperative hospital length of stay, postoperative Oswestry Disability Index (ODI) score, and postoperative visual analog scale (VAS) score for back pain. Risk of bias was assessed using the Newcastle-Ottawa score and Cochrane tool. A network meta-analysis (NMA) was performed to estimate PS placement accuracy as the primary outcome. RESULTS: Overall, 78 studies consisting of 6262 patients and > 31,909 PSs were included. NMA results showed that robot-assisted and 3D-fluoroscopy PS insertion had the greatest accuracy compared with freehand (p < 0.01 and p < 0.001, respectively), CT navigation (p = 0.02 and p = 0.04, respectively), and 2D fluoroscopy (p < 0.01 and p < 0.01, respectively). The surface under the cumulative ranking (SUCRA) curve method further demonstrated that robot-assisted PS insertion accuracy was superior (S = 0.937). Optimal screw placement was greatest in robot-assisted (S = 0.995) placement, and misplacement was greatest with freehand (S = 0.069) approaches. Robot-assisted placement was favorable for minimizing complications (S = 0.876), while freehand placement had greater odds of complication than robot-assisted (OR 2.49, p < 0.01) and CT-navigation (OR 2.15, p = 0.03) placement. CONCLUSIONS: The results of this NMA suggest that robot-assisted PS insertion has advantages, including improved accuracy, optimal placement, and minimized surgical complications, compared with other PS insertion methods. Limitations included overgeneralization of categories and time-dependent effects.

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.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.944
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.118
GPT teacher head0.380
Teacher spread0.262 · 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