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High reliability of an algorithm for choice of implants in hip fracture patients
Henrik Palm1, Eva Posner, Hans-Ulrik Ahler-Toftehøj
1Department of Orthopaedic Surgery, Hvidovre Hospital, Copenhagen, Denmark. hpalm@dadlnet.dk
Insights
This study found that while hip fracture classification can be unreliable, an algorithm reliably measures posterior tilt and selects implant types for hip fracture surgery. This improves standardized treatment for patients.
Area of Science:
- Orthopaedic surgery
- Surgical outcomes
- Medical device technology
Background:
- Hip fracture treatment presents challenges due to high complication rates.
- Existing fracture classifications are often unreliable, impacting surgical decisions.
- A novel algorithm aims to standardize hip fracture surgery and reduce reoperations.
Purpose of the Study:
- To investigate the reliability of a hip fracture surgery algorithm.
- To assess the algorithm's accuracy in classifying fractures and selecting implants.
- To determine if the algorithm improves treatment standardization.
Main Methods:
- Four observers classified 100 hip fractures using an algorithm, assessing 15 fracture types and choosing from five surgical procedures.
- Classifications and implant choices were reassessed ten weeks later.
- Consensus decisions were made within and between two hospitals.
Main Results:
- Fracture classification showed moderate intra- and interobserver reliability (kappa 0.60-0.65).
- Posterior tilt measurement demonstrated high reliability (ICC 0.87-0.91).
- Implant type selection by the algorithm was highly reliable (kappa 0.86-0.88), with 91% agreement between hospitals.
Conclusions:
- The algorithm reliably measures posterior tilt and selects appropriate implant types for hip fractures.
- Despite limitations in fracture classification, the algorithm offers a path to standardized hip fracture treatment.
- This standardization has the potential to improve patient outcomes and reduce complications.
Purpose:
Hip fracture treatment is controversial, with high complication rates. An algorithm for hip fracture surgery has shown reduced reoperation rates, but choice of implant is based on the commonly used fracture classifications, which were previously evaluated to be unreliable. The purpose of this study was to investigate the reliability of the algorithm.
Methods:
From two hospitals, four observers (orthopaedic consultant, fellow, resident and intern) used the algorithm to classify into 15 hip fracture types [Garden type I-IV femoral neck including posterior tilt, vertical femoral neck, basocervical and Arbeitsgemeinschaft für Osteosynthesefragen (AO)-31 A1.1 to A3.3 trochanteric fractures] and to choose between five surgical procedures [parallel implants, prosthesis, two-or four-hole sliding hip screw (SHS) and intermedullary (IM) nail]. After individual assessment, each hospital made a consensus decision. Observations were performed twice, ten weeks apart, on pelvic, anteroposterior (AP) and axial X-rays from 100 consecutive patients.
Results:
For fracture classification, mean kappa values were 0.60 for intra and 0.62 for interobserver variation, with interobserver variation between hospitals at 0.65. For posterior tilt, mean intraclass correlation coefficient was 0.91 for intra and 0.87 for interobserver variation. For choice of implant type, mean kappa values were 0.86 for both intra and interobserver variation. The two hospital consensus decisions chose same implant in 91 of 100 patients, giving a kappa value at 0.88.
Conclusion:
Although hip fracture classification confirmed to be somewhat unreliable in this study, posterior tilt measurement and subsequent choice of implant type by the algorithm was found to be reliable, which opens up the possibility for a more standardized treatment of hip fracture patients between hospitals.
