Design of Improved Intertrochanteric Fracture Treatment (DRIFT) Study: Protocol for Biomechanical Testing and Finite Element Analysis of Stable and Unstable Intertrochanteric Fractures Treated With Intramedullary Nailing or Dynamic Compression Screw
Bibliographic record
Abstract
BACKGROUND: Intertrochanteric hip fractures rank in the top 10 of all impairments worldwide in terms of loss in disability-adjusted years for people aged older than 60 years. The type of surgery is usually carried out with dynamic hip screw (DHS) devices or cephalomedullary nails (CMN). Cut-out of the hip screw is considered the most frequent mechanical failure for all implants with an estimated incidence ranging from 2% to 16.5%; this entails both enhancing our understanding of the prognostic factors of cut-out and improving all aspects of intertrochanteric fracture treatment. OBJECTIVE: The Design of Improved Intertrochanteric Fracture Treatment (DRIFT) study's main objective is to provide intertrochanteric fracture treatment expertise, requirements and specifications, clinical relevance, and validation to improve treatment outcomes by developing a universal algorithm for designing patient- and fracture-oriented treatment. The hypothesis to be tested is that a more valgus reduction angle and implants of higher angles will lead to a more favorable biomechanical environment for fracture healing-that is, higher compressive loads at the fracture site with lower shear loads at the hip screw femoral head interface. A new implant with enhanced biomechanical and technical characteristics will be designed and fabricated; in addition, an integrated design and optimization platform based on computer-aided design tools and topology optimization modules will be developed. METHODS: To test this hypothesis, a biomechanical study comprising experimental loading of synthetic femora (Sawbones Inc) and finite element analysis (FEA) will be conducted. Detailed FEA of existing implants (DHS and CMN) implemented in different clinical cases under walking conditions will be performed to derive the stress and strain fields developed at the implant-bone system and identify critical scenarios that could lead to failure of therapy. These models would be validated against instrumented mechanical tests using strain gages and a digital image correlation process. RESULTS: After testing, geometric drawbacks of existing implants will be fully recognized, and geometric characteristics will be correlated with critical failure scenarios. The last step would be the numeric design, computer-aided design (using FEA codes and design packages), and optimization of the new proposed implant with regard to improved biomechanical surgical technique and enhanced mechanical performance that will reduce the possibility for critical failure scenarios. CONCLUSIONS: The optimization of the biomechanical behavior of the fracture-osteosynthesis model by the application of the ideal reduction angle and implant is expected to have a positive effect to the rate of mechanical failure and, subsequently, the healing rates, morbidity, and mortality in this fragile patient group. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/12845.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".