Validation of the Shin Pain Scoring System: A Novel Approach for Determining Tibial Bone Stress Injuries

Author:

Nussbaum Eric D.12,Gatt Charles J.1,Epstein Robert34,Bechler Jeffrey R.12,Swan Kenneth G.12,Tyler David5,Bjornaraa Jaynie6

Affiliation:

1. Department of Orthopaedic Surgery, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA.

2. University Orthopaedic Associates, Somerset, New Jersey, USA.

3. Department of Radiology, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA.

4. University Radiology, New Brunswick, New Jersey, USA.

5. Department of Statistics and Biostatistics, Rutgers University, New Brunswick, New Jersey, USA.

6. St Catherine University, Minneapolis, Minnesota, USA.

Abstract

Background: The incidence of adolescent overuse injuries, including bone stress injuries (BSIs), is on the rise. The identification of a BSI in the early stages is key to successful treatment. The Shin Pain Scoring System (SPSS) was developed to aid clinicians in identifying patients with a BSI. Hypothesis: The SPSS will correlate with magnetic resonance imaging (MRI) grading of a BSI in an adolescent population. Study Design: Cohort study (diagnosis); Level of evidence, 2. Methods: Enrolled in this study were 80 adolescent high school athletes between the ages of 13 and 18 years participating in a variety of sports with more than 1 week of atraumatic shin pain. The SPSS questionnaire was completed for each participant, and physical examination findings were recorded. Each question and physical examination item was allotted a point value, which totaled 29 points. Radiographs and MRI scans of both lower legs were obtained for each participant. The SPSS score was statistically analyzed using logistic regression, a classification matrix, and a 2 × 2 contingency table to evaluate validity and predictability. Results: Logistic regression analysis of our data determined that 3 categories of SPSS scores provided the highest diagnostic value when compared with MRI grading based on the Fredericson classification (0-4). The SPSS correctly identified 43.5% of injuries for category 1 (MRI grades 0-1), 62.5% for category 2 (MRI grade 2), and 50.0% for category 3 (MRI grades 3-4). Overall, the SPSS correctly identified the degree of BSI in 54.4% of all tibias studied. Binary analysis for validity demonstrated a sensitivity of 96%, specificity of 26%, positive predictive value of 76%, and negative predictive value of 71% for the SPSS relative to the “gold standard” MRI results. Conclusion: The SPSS is a potentially valid method to identify tibial BSIs, given the sensitivity and negative and positive predictive values. It also provides helpful categorization to alert clinicians to the presence of a BSI and direct further diagnostics and/or interventions. The SPSS should be considered as an additional tool to use when evaluating adolescents with atraumatic tibial BSIs.

Publisher

SAGE Publications

Subject

Orthopedics and Sports Medicine

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