Is Lever Test Superior to Lachman, Pivot Shift, Drawer Tests in Diagnosing Anterior Cruciate Ligament Injuries?
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info:eu-repo/semantics/openAccessAttribution 4.0 International (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/Tarih
2022Üst veri
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İpek, D., Zehir, S., & Dündar, A. (2022). Is Lever Test Superior to Lachman, Pivot Shift, Drawer Tests in Diagnosing Anterior Cruciate Ligament Injuries?. Cureus, 14(2).Özet
Abstract
Introduction: The physical examination in anterior cruciate ligament (ACL) injuries is extremely important, and the Lever test is commonly utilized on ACL evaluation. However, the number and scope of studies on the Lever test is limited. In this prospective cross-sectional study, we aimed to evaluate the effectiveness of the diagnostic values of Lachman, Pivot Shift, Lever, and Anterior Drawer tests in terms of quadriceps atrophy and case phase in ACL injuries.
Methods: In this prospective study, diagnostic values of Lachman, Pivot Shift, Lever, and Anterior Drawer tests were examined on 189 patients with positive MRI results as the gold standard.
Results: Lever test positivity was significantly more frequent in the group with quadriceps atrophy preoperative and after sedation (p<0.05). Anterior Drawer test positivity was significantly more frequent in the group with positive quadriceps atrophy preoperatively, after sedation and after spinal anesthesia (p<0.05). Lever and Anterior Drawer tests were positively correlated with quadriceps atrophy preop and after sedation (p<0.05). Lever test before surgery, after sedation and after spinal anesthesia in the chronic patient group was more positive than in the acute and subacute groups (p<0.05). Lever test was positively correlated with phase preoperatively, after sedation and after spinal anesthesia (p<0.01).
Conclusion: The presence or absence of quadriceps atrophy in patients with acute, sub-acute, or chronic ACL injury has a significant effect on the predictive value of the Lever test. We think that univariate analyzes may give incorrect results when demonstrating predictive value, and it would be more correct to perform multivariate analyzes.
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