Open AccessDiagnosis of Compressed Nerve Root in Lumbar Disc Herniation Patients by Surface Electromyography
Author(s) -
Li Wei,
Liu Yancheng,
Zheng Chenfan,
Miao Jun,
Chen Hui,
Quan Haiying,
Yan Songhua,
Zhang Kuan
Publication year - 2018
Publication title -
orthopaedic surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.666
H-Index - 23
eISSN - 1757-7861
pISSN - 1757-7853
DOI - 10.1111/os.12362
Subject(s) - receiver operating characteristic , nerve root , medicine , electromyography , logistic regression , area under the curve , kappa , root mean square , lumbar , compression (physics) , nuclear medicine , surgery , mathematics , materials science , physical medicine and rehabilitation , geometry , electrical engineering , composite material , engineering
Objective To establish a logistic regression model using surface electromyography (SEMG) parameters for diagnosing the compressed nerve root at L 5 or S 1 level in patients with lumbar disc herniation (LDH). Methods This study recruited 24 patients with L 5 nerve root compression and 23 patients with S 1 nerve root compression caused by LDH from May 2014 to May 2016. SEMG signals from the bilateral tibialis anterior and lateral gastrocnemius were measured. The root mean square (RMS), the RMS peak time, the mean power frequency (MPF), and the median frequency (MF) were analyzed. The accuracy, sensitivity, and specificity values were calculated separately. The areas under the curve (AUC) of the receiver‐operating characteristic (ROC) curve and the kappa value were used to evaluate the accuracy of the SEMG diagnostic model. Results The accuracy of the SEMG model ranged from 85.71% to 100%, with an average of 93.57%. The sensitivity, specificity, AUC, and kappa value of the logistic regression model were 0.98 ± 0.05, 0.92 ± 0.09, 0.95 ± 0.04 ( P = 0.006), and 0.87 ± 0.11, respectively ( P = 0.001). The final diagnostic model was: P = 1 − 1 1 + e y; y = 10.76 − (5.95 × TA_RMS Ratio) − (0.38 × TA_RMS Peak Time Ratio) – (5.44 × 44 × LG_RMS Peak Time Ratio). L 5 nerve root compression is diagnosed when P < 0.5 and S 1 nerve root compression when P ≥ 0.5. Conclusions The logistic regression model developed in this study showed high diagnostic accuracy in detecting the compressed nerve root (L 5 and S 1 ) in these patients with LDH.