Effect of Wrist Deviation on Median Nerve Cross-Sectional Area Essays

Effect of Wrist Deviation on Median Nerve Cross-Sectional Area Essays

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Computer is widely used in daily work and become important and essential tools in the workplace. Repetitive and awkward positions are associated with musculoskeletal disorder of the upper extremities among computer users (1). The long hours of computer use in daily life have increased the discomfort level of neck, shoulder, elbow, and wrist and hand region. Studies has shown that approximately 20% of computer user experienced musculoskeletal disorder of the upper extremities (2, 3). Intensive use of computer keyboard and mouse may increase the risk of carpal tunnel syndrome (CTS,) and it is one of the commonly reported musculoskeletal disorder of the upper extremities when the median nerve is affected at carpal tunnel as a result from nerve compression (1). The etiology of CTS is multifactorial and mechanical compression stress on the median nerve is one of them.

The carpal tunnel located at volar wrist and formed by carpal bones as floor, flexor retinaculum as roof and proximal carpal tunnel is defined by the edge of retinaculum at pisiform level (4). There are total nine tendons and a median nerve enter through carpal tunnel which are flexor pollicis longus (FPL), four flexor digitorum superficialis (FDS), four flexor digitorum profundus (FDP) and a median nerve. Median nerve located beneath near to flexor retinaculum and vulnerable to compression stress. Wrist movements comprising flexion, extension, radial deviation and ulnar deviation (Figure 1). Finger dynamic movements imposed a compression stress on median nerve from FDS, FDP and FPL gliding motion (5). Dynamic kinematic movements of carpal bones may influence the carpal tunnel volume during wrist flexion-extension motion (6). Thus, the median nerve experience higher c...

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...tient-reported outcome measures in carpal tunnel syndrome. Ortopedia, Traumatologia, Rehabilitacja, 14(4), 335-340.
9. LaJoie, A. S., McCabe, S. J., Thomas, B., & Edgell, S. E. (2005). Determining the sensitivity and specificity of common diagnostic tests for carpal tunnel syndrome using latent class analysis. Plastic and Reconstructive Surgery, 116(2), 502-507.
10. Sambandam, S. N., Priyanka, P., Gul, A., & Ilango, B. (2008). Critical analysis of outcome measures used in the assessment of carpal tunnel syndrome. International Orthopaedics, 32(4), 497-504.
11. Schneider, C. A., Rasband, W. S., & Eliceiri, K. W. (2012). NIH image to ImageJ: 25 years of image analysis. Nature Methods, 9(7), 671-675.
12. Duncan, I., Sullivan, P., & Lomas, F. (1999). Sonography in the diagnosis of carpal tunnel syndrome. AJR.American Journal of Roentgenology, 173(3), 681-684.

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