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Record W4415570864 · doi:10.1302/1358-992x.2025.11.033

HOW DOES NUMBER OF CERCLAGE CABLES IMPACT TITANIUM TAPERED-STEM STABILITY IN PERIPROSTHETIC FEMORAL FRACTURE? A BIOMECHANICAL CADAVERIC STUDY

2025· article· en· W4415570864 on OpenAlexaff
Troy D. Bornes, H-Y Lee, Christopher G. Anderson, Timothy M. Wright, Mathias P. Bostrom, José A. Rodríguez, Friedrich Boettner, Peter K. Sculco

Bibliographic record

VenueOrthopaedic Proceedings · 2025
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCadaveric spasmPeriprostheticFemurFixation (population genetics)BiomechanicsCadaverReamerFluoroscopyInitial stability

Abstract

fetched live from OpenAlex

Periprosthetic femoral fractures around total hip arthroplasty stems are commonly treated with femoral component revision using a titanium tapered stem and cerclage fixation. Peri-isthmic periprosthetic fractures are particularly challenging to treat given that the fracture extends through the isthmus and compromises the zone of bone available for stem contact and stability. Limited biomechanical evidence exists to guide fixation strategies. We previously found that a 4-cm cortical contact length between intact bone and stem provided superior stability compared to shorter contact lengths. The objective of this study was to evaluate the difference in tapered stem stability when using 2 versus 3 cerclage cables in the treatment of simulated peri-isthmic fractures with a 4-cm contact length. Twenty-four fresh frozen cadaveric female femora (12 matched pairs) from donors with an age of 65.4±7.9 years were included. The femoral isthmus was identified using fluoroscopy and the bone proximal to the isthmus was resected. The femoral shaft was over-reamed in a retrograde fashion to create a consistent 4-cm contact length at the isthmus. A simulated oblique fracture was created using a 3D-printed cutting guide, reduced, and fixed using beaded 2.0-mm cerclage cables (2 cables on one femur and 3 on the contralateral femur of each matched pair; Fig.1A). The femur was prepared, and a 195-mm monobloc tapered stem was implanted. The proximal aspect of each stem was loaded axially in a stepwise fashion to up 10000 N using a servohydraulic testing system (Fig.1B). Stem subsidence and fracture displacement were determined at 2600 N (simulating load during gait). Load-to-failure was determined with failure defined as stem subsidence ≥10 mm, the initiations of a new fracture, and/or cable failure (Fig.1C). At a 2600 N load, stem subsidence was significantly lower in specimens treated with 3 cables (2.8±4.5 mm) than 2 cables (4.5±2.2 mm; p=0.04; Table 1). Fracture displacement was <2.5 mm in all specimens at a 2600 N load (0.4±0.3 mm for 3 cables; 0.8±0.6 mm for 2 cables; p=0.02). During load-to-failure testing, all constructs failed. The load-to-failure was superior in specimens treated with 3 cables (4223±1168 N) compared to those treated with 2 cables (3504±698 N; p=0.02). The initial failure mode was subsidence ≥10 mm in most specimens (3-cable specimens, 11/12; 2-cable specimens, 8/12). New fracture lines were noted in 11/12 3-cable specimens and 12/12 2-cable specimens. Force at which stems subsided ≥10 mm was higher in specimens treated with 3 cables (4323±1118 N) compared to those treated with 2 cables (3692±729 N; p=0.02). Force at which new fracture occurred was also higher in specimens treated with 3 cables (5479±1907 N) compared to those with 2 cables (4033±662 N; p=0.01). In a peri-isthmic periprosthetic fracture model with a 4-cm cortical contact length, titanium tapered stems had improved initial axial stability and reduced stem subsidence in fractures treated with 3 cerclage cables compared to 2 cables. In load-to-failure testing, femora fixed with 3 cables demonstrated superior biomechanical properties to femora with 2 cables as higher loads were required for failure to occur. For any figures or tables, please contact the authors directly.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.284
Teacher spread0.271 · 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 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

Citations0
Published2025
Admission routes1
Has abstractyes

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