Copyright
©The Author(s) 2018.
World J Anesthesiol. Oct 27, 2018; 7(3): 20-23
Published online Oct 27, 2018. doi: 10.5313/wja.v7.i3.20
Published online Oct 27, 2018. doi: 10.5313/wja.v7.i3.20
Table 1 Agreement and prediction accuracy between diagnosis tools for detecting the involvement of the nerve root
| Agreement | Prediction | |||||
| Clinical findings | MRI | MRI and clinical findings | Pain relief after surgical decompression | MRI | Clinical findings | |
| Sen: 68.90% | ||||||
| Electrophysiology | 52.0%[2] | 59.6%[2] | 25.0%[9] | Sen: 86.3%[26] | ||
| 89.5%[6] | 54.0%[6] | |||||
| 60.0%[8] | ||||||
| MRI | 58.6%[6] | N/A | N/A | N/A | N/A | Spe: 16.0%-37.0% |
| 30.0%[7] | Spe: 61.0%-77.0%[27] | |||||
| 16.3%-64.9%[4] | ||||||
| 3.0%-22.0%[5] | ||||||
| SNB | N/A | N/A | N/A | Sen: 85.40% | ||
| Spe: 16.7%[10] | ||||||
| Sen: 93.00% | ||||||
| Spe: 26.0%[11] | ||||||
| Sen: 96.00% | ||||||
| Spe: 56.0%[12] | ||||||
- Citation: Lin JH, Chen CC. Current challenges in diagnosis of lumbar radiculopathy. World J Anesthesiol 2018; 7(3): 20-23
- URL: https://www.wjgnet.com/2218-6182/full/v7/i3/20.htm
- DOI: https://dx.doi.org/10.5313/wja.v7.i3.20