Nussbaum ED, Gatt CJ, Epstein R, Bechler JR, Swan KG, Tyler D, Bjornaraa J. Validation of the Shin Pain Scoring System: A Novel Approach for Determining Tibial Bone Stress Injuries.
Orthop J Sports Med 2019;
7:2325967119877803. [PMID:
31696132 PMCID:
PMC6822191 DOI:
10.1177/2325967119877803]
[Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
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.
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