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Record W3000305954 · doi:10.3340/jkns.2019.0090

Accuracy Analysis of Iliac Screw Using Freehand Technique in Spinal Surgery : Relation between Screw Breach and Revision Surgery

2020· article· en· W3000305954 on OpenAlexaff
Subum Lee, Sang Ku Jung, Sam Keshen, Stephen J. Lewis, Jin Hoon Park

Bibliographic record

VenueJournal of Korean Neurosurgical Society · 2020
Typearticle
Languageen
FieldMedicine
TopicScoliosis diagnosis and treatment
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineSurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To analyze the accuracy of iliac screws using freehand technique performed by the same surgeon. We also analyzed how the breach of iliac screws was related to the clinical symptoms resulting in revision surgery. METHODS: From January 2009 to November 2015, 100 patients (193 iliac screws) were analyzed using postoperative computed tomography scans. The breaches were classified based on the superior, inferior, lateral, and medial iliac wall violation by the screw. According to the length of screw extrusion, the classification grades were as follows : grade 1, screw extrusion <1 cm; grade II, 1 cm ≤ screw extrusion <2 cm; grade III, 2 cm ≤ screw extrusion <3 cm; and grade IV, 3 cm ≤ screw extrusion. We also reviewed the revision surgery associated with iliac screw misplacement. RESULTS: Of the 193 inserted screws, 169 were correctly located and 24 were misplaced screws. There were eight grade I, six grade II, six grade III, and four grade IV screw breaches, and 11, 8, 2, and 3 screws violated the medial, lateral, superior, and inferior walls, respectively. Four revision surgeries were performed for the grade III or IV iliac screw breaches in the lateral or inferior direction with respect to its related symptoms. CONCLUSION: In iliac screw placement, 12.4% breaches developed. Although most breaches were not problematic, symptomatic violations (2.1%) could result in revision surgery. Notably, the surgeon should keep in mind that lateral or inferior wall breaches longer than 2 cm can be risky and should be avoided.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
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 head0.095
GPT teacher head0.340
Teacher spread0.245 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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