TY - JOUR
T1 - The SIFK score
T2 - a validated predictive model for arthroplasty progression after subchondral insufficiency fractures of the knee
AU - Pareek, Ayoosh
AU - Parkes, Chad W
AU - Bernard, Christopher D
AU - Abdel, Matthew P
AU - Saris, Daniel B F
AU - Krych, Aaron J
N1 - Publisher Copyright:
© 2019, European Society of Sports Traumatology, Knee Surgery, Arthroscopy (ESSKA).
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - Purpose: The purpose of this study was to create a predictive model utilizing baseline demographic and radiographic characteristics for the likelihood that a patient with subchondral insufficiency fracture of the knee will progress to knee arthroplasty with emphasis on clinical interpretability and usability. Methods: A retrospective review of baseline and final radiographs in addition to MRIs were reviewed for evaluation of insufficiency fractures and associated injuries. Patient and radiographic factors were used in building predictive models for progression to arthroplasty with Train: Validation: Test subsets. Multiple models were compared with emphasis on clinical utility. Results: Total of 249 patients with a mean age of 64.6 (SD 10.5) years were included. Knee arthroplasty rate was 27% at mean of 4 years of follow-up. Lasso Regression was non-inferior to other models and was chosen for ease of interpretability. In order of importance, predictors for progression to arthroplasty included lateral meniscus extrusion, Kellgren–Lawrence Grade 4, SIFK on MFC, lateral meniscus root tear, and medial meniscus extrusion. The final SIFK Score stratified patients into low-, medium-, and high-risk categories with arthroplasty rates of 8.8%, 40.4%, and 78.9% (p ' 0.001) and an area under the curve of 82.5%. Conclusion: In this validated model, lateral meniscus extrusion, K-L Grade 4, SIFK on MFC, lateral meniscus root tear, and medial meniscus extrusion were the most important factors in predicting progression to arthroplasty (in that order). This model assists in patient treatment and counseling in providing prognostic information based on patient-specific risk factors by classifying them into a low-, medium-, and high-risk categories. This model can be used both by medical professionals treating musculoskeletal injuries in guiding patient decision making. Level of evidence: Level III.
AB - Purpose: The purpose of this study was to create a predictive model utilizing baseline demographic and radiographic characteristics for the likelihood that a patient with subchondral insufficiency fracture of the knee will progress to knee arthroplasty with emphasis on clinical interpretability and usability. Methods: A retrospective review of baseline and final radiographs in addition to MRIs were reviewed for evaluation of insufficiency fractures and associated injuries. Patient and radiographic factors were used in building predictive models for progression to arthroplasty with Train: Validation: Test subsets. Multiple models were compared with emphasis on clinical utility. Results: Total of 249 patients with a mean age of 64.6 (SD 10.5) years were included. Knee arthroplasty rate was 27% at mean of 4 years of follow-up. Lasso Regression was non-inferior to other models and was chosen for ease of interpretability. In order of importance, predictors for progression to arthroplasty included lateral meniscus extrusion, Kellgren–Lawrence Grade 4, SIFK on MFC, lateral meniscus root tear, and medial meniscus extrusion. The final SIFK Score stratified patients into low-, medium-, and high-risk categories with arthroplasty rates of 8.8%, 40.4%, and 78.9% (p ' 0.001) and an area under the curve of 82.5%. Conclusion: In this validated model, lateral meniscus extrusion, K-L Grade 4, SIFK on MFC, lateral meniscus root tear, and medial meniscus extrusion were the most important factors in predicting progression to arthroplasty (in that order). This model assists in patient treatment and counseling in providing prognostic information based on patient-specific risk factors by classifying them into a low-, medium-, and high-risk categories. This model can be used both by medical professionals treating musculoskeletal injuries in guiding patient decision making. Level of evidence: Level III.
KW - Machine learning
KW - Meniscus extrusion
KW - Meniscus tear
KW - Predictive model
KW - Root
KW - SONK
KW - SPONK
KW - Spontaneous osteonecrosis
KW - Subchondral insufficiency fracture
UR - http://www.scopus.com/inward/record.url?scp=85075283695&partnerID=8YFLogxK
U2 - 10.1007/s00167-019-05792-w
DO - 10.1007/s00167-019-05792-w
M3 - Article
C2 - 31748919
SN - 0942-2056
VL - 28
SP - 3149
EP - 3155
JO - Knee Surgery Sports Traumatology Arthroscopy
JF - Knee Surgery Sports Traumatology Arthroscopy
IS - 10
ER -