Ulnar variance according to gender and side during aging: An analysis of 600 wrists

Sayıt, Emrah; Sayit, Aslı Tanrıvermiş; Bağır, Melih; Terzi, Yüksel

doi:10.1016/j.otsr.2018.01.011

Cited by 10 publications

(4 citation statements)

References 20 publications

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“…Our study demonstrated that negative ulnar variance is lower in men than in women. This is consistent with the results by Nakamura et al (26), Jung et al (24), Elsaftawy (27), and Sayit et al (28). However, some other studies did not show any association between ulnar variance and sex (2,29,30).…”

Section: Discussionsupporting

confidence: 93%

“…Recently, excellent reliability (ICC value 0.94) was documented for computer-aided analysis using the CRP as a reference point for the measurement of ulnar variance (8) Our study demonstrated that negative ulnar variance is lower in men than in women. This is consistent with the results by Nakamura et al (26), Jung et al (24), Elsaftawy (27), and Sayit et al (28). However, some other studies did not show any association between ulnar variance and sex (2,29,30).…”

Section: Discussionsupporting

confidence: 92%

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Association of ulnar variance with three-dimensional carpal alignment and demographics in asymptomatic volunteers

Waris,

Höglund,

Sippo

et al. 2023

Acta Radiol

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Background Several carpal pathologies are considered to be related to ulnar variance. Recently, computer-aided computed tomography (CT) analysis software was introduced to quantify three-dimensional (3D) carpal alignment with high accuracy and reliability. Purpose To determine the association of ulnar variance with 3D carpal alignment and demographics. Material and Methods A wrist of 121 asymptomatic volunteers (69 men, 52 women; mean age = 38 ± 10.4 years) was imaged in the neutral wrist position with cone-beam CT. Computer-aided CT analysis software (Bonelogic), based on segmentation and numerical modelling, was used to define ulnar variance and standardized 3D axes for all carpal bones. The association of ulnar variance with 3D carpal alignment, age of the volunteer, and side and dominance of the imaged wrist was assessed. Results The mean ulnar variance was −1.6 ± 1.5 mm (range = −5.3 to 2.4 mm). The mean ulnar variance was −1.9 mm and −1.1 mm in men and women ( P = 0.007), respectively. Of the imaged 121 wrists, 18 (15%) had positive and 103 (85%) negative ulnar variance. There was no association between ulnar variance and any of the radio- or intercarpal angle values in either the sagittal or coronal plane (ρ = −0.16…0.17, r = −0.13….0.12). The ulnar variance showed no association with side ( P = 0.51) or dominance ( P = 0.27) of the imaged wrist. Conclusion 3D carpal alignment is not affected by ulnar variance. The association of ulnar variance with sex may in part explain the difference in reported prevalence of some carpal pathologies, such as ulnar impaction syndrome and Kienböck’s disease.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 92%

Association of ulnar variance with three-dimensional carpal alignment and demographics in asymptomatic volunteers

Waris,

Höglund,

Sippo

et al. 2023

Acta Radiol

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“…Nakamura et al stated that negative UV is higher in men (11). However, in some studies, no relationship was found between UV, age, and sex (2,8,35,36). In our study, we found that men were more common in the neutral variance group and women in the positive variance group ( P < 0.05).…”

Section: Discussionmentioning

confidence: 95%

The effect of ulnar variance on the pisotriquetral joint

et al. 2022

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Background Pisotriquetral joint (PTJ) disorders are an important cause of ulnar-sided wrist pain but are often underrecognized. Ulnar variance (UV) has been associated with several wrist pathologies. Purpose To determine the effect of UV on PTJ in patients with trauma. Material and Methods A total of 143 patients (77 men, 66 women; mean age=41.64 ± 18.07 years) were included. Patients with fractures, severe and high-energy trauma, arthritic conditions, avascular necrosis, congenital deformity, bone and soft-tissue tumors, suboptimal image quality, and incorrect joint position were excluded. UV and the amount of PTJ subluxation were evaluated using coronal and sagittal computed tomography images. Results PTJ subluxation was divided into five grades. A statistically significant difference was found between the presence of PTJ subluxation and sex ( P = 0.045). PTJ subluxation was more common in men (46.8%) than in women (30.3%). There was no significant difference between the presence of PTJ subluxation and age ( P = 0.758). The patients were also divided into three groups as positive, neutral, and negative UV. A statistically significant relationship was found between the UV and presence of PTJ subluxation ( P = 0.01). PTJ subluxation was significantly less in the neutral (none=51.1%, present=48.9%; P < 0.05) and negative (none=77.8%, present=22.2%; P < 0.05) groups. Conclusion PTJ subluxation was found to be less among the groups with neutral and negative UV in our study population. PTJ subluxation is more common in men while there is no relationship with age. UV and gender may be risk factors for PTJ subluxation by affecting force dynamics at the wrist joint.

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“…There have been many studies on ulnar variance that describes the relative length of the radius with respect to the ulna (Fu et al., 2009; Jung et al., 2001; Sayit et al., 2018; Yeh et al., 2001; Yoshioka et al., 2007). It has been shown that ulnar variance changes in different forearm positions, elbow positions and with hand grip (Fu et al., 2009; Jung et al., 2001; Yeh et al., 2001).…”

Section: Methodsmentioning

confidence: 99%

Kinematic analysis of forearm rotation using four-dimensional computed tomography

Oonk

Dobbe

Strijkers

et al. 2022

J Hand Surg Eur Vol

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This study aimed to quantify forearm kinematics with a focus on the forearm rotation axis. Ten healthy volunteers were included in the study. One three-dimensional computed tomographic scan and two four-dimensional computed tomographic scans were done in all the arms to capture forearm joint motion. After image processing, the rotation axis and the movement of the radius with respect to various axes were quantified. The rotation axis was calculated using finite helical axis analysis and a circle fitting approach. The mean error of the rotation axis found through circle fitting was 0.2 mm (SD 0.1) distally and 0.1 mm (SD 0.1) proximally, indicating an improvement in precision over the finite helical axis approach. The translations of the radius along the ulnar axis and the forearm rotation axis were 2.6 (SD 0.8) and 0.6 mm (SD 0.9), respectively. The rotation of the radius around the radial axis was 7.2°. The techniques presented provide a detailed description of forearm kinematics.

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Ulnar variance according to gender and side during aging: An analysis of 600 wrists

Abstract: Level III.

Cited by 10 publications

References 20 publications

Association of ulnar variance with three-dimensional carpal alignment and demographics in asymptomatic volunteers

Association of ulnar variance with three-dimensional carpal alignment and demographics in asymptomatic volunteers

The effect of ulnar variance on the pisotriquetral joint

Kinematic analysis of forearm rotation using four-dimensional computed tomography

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