Value of History, Physical Examination, and Radiographic Findings in the Diagnosis of Symptomatic Meniscal Tear Among Middle‐Aged Subjects With Knee Pain
2016; Wiley; Volume: 69; Issue: 4 Linguagem: Inglês
10.1002/acr.22975
ISSN2151-4658
AutoresJeffrey N. Katz, Savannah R. Smith, Heidi Y. Yang, Scott D. Martin, John Wright, Laurel A. Donnell‐Fink, Elena Losina,
Tópico(s)Shoulder Injury and Treatment
ResumoObjective To evaluate the utility of clinical history, radiographic findings, and physical examination findings in the diagnosis of symptomatic meniscal tear (SMT) in patients over age 45 years, in whom concomitant osteoarthritis is prevalent. Methods In a cross‐sectional study of patients from 2 orthopedic surgeons' clinics, we assessed clinical history, physical examination findings, and radiographic findings in patients age >45 years with knee pain. The orthopedic surgeons rated their confidence that subjects' symptoms were due to meniscal tear; we defined the diagnosis of SMT as at least 70% confidence. We used logistic regression to identify factors independently associated with diagnosis of SMT, and we used the regression results to construct an index of the likelihood of SMT. Results In 174 participants, 6 findings were associated independently with the expert clinician having ≥70% confidence that symptoms were due to meniscal tear: localized pain, ability to fully bend the knee, pain duration <1 year, lack of varus alignment, lack of pes planus, and absence of joint space narrowing on radiographs. The index identified a low‐risk group with 3% likelihood of SMT. Conclusion While clinicians traditionally rely upon mechanical symptoms in this diagnostic setting, our findings did not support the conclusion that mechanical symptoms were associated with the expert's confidence that symptoms were due to meniscal tear. An index that includes history of localized pain, full flexion, duration <1 year, pes planus, varus alignment, and joint space narrowing can be used to stratify patients according to their risk of SMT, and it identifies a subgroup with very low risk.
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