Renfree Sean P, Zhang Nan, Renfree Kevin J
University of Arizona College of Medicine Tucson, USA.
Mayo Clinic Arizona, Phoenix, USA.
Hand (N Y). 2025 Mar;20(2):246-251. doi: 10.1177/15589447231213382. Epub 2023 Nov 28.
High-quality lateral radiographs with the wrist in neutral (0°) or near neutral (less than 15° flexion or extension) are felt to be important for diagnosing carpal instability using intracarpal angular measurements, but may be unavailable. In addition, radiolunate (RLA) and capitolunate (CLA) measurement angles for defining carpal instability have poor validation. We sought to establish 95% confidence intervals (CIs) for predicted RLA and CLA throughout the arc of wrist motion in normal cadaveric wrists.
Fresh frozen cadaveric upper extremities were secured in a limb positioner. Scaphopisocapitate lateral radiographs were obtained throughout the arc of motion and RLA and CLA, and wrist flexion or extension angles (WA) were measured by a board-certified hand surgeon. Scatter plots of variables were constructed, and correlation coefficients calculated for areas under the curves. Regression equations for predicted RLA and CLA based on WA were developed.
Both RLA and CLA correlated strongly with WA for each measurement in both flexion and extension ( = 0.7-0.8). Linear regression modeling demonstrated a good relationship between RLA ( = 84%) and CLA ( = 80%) with WA. Regression equations were constructed to give predicted values for RLA and CLA based on WA and 95% prediction CI.
If RLA and CLA exceed 20° with neutral (0°) wrist alignment, it likely represents pathologic carpal alignment. Presented tables demonstrate 95% CI of RLA and CLA throughout the arc of wrist flexion/extension. Values outside of the 95% CI are also likely to indicate pathologic carpal alignment.
高质量的腕关节中立位(0°)或接近中立位(屈曲或伸展小于15°)的侧位X线片对于使用腕骨间角度测量来诊断腕骨不稳很重要,但可能无法获得。此外,用于定义腕骨不稳的桡月角(RLA)和头月角(CLA)测量角度的验证性较差。我们试图在正常尸体腕关节的整个运动弧度中建立预测RLA和CLA的95%置信区间(CI)。
将新鲜冷冻的尸体上肢固定在肢体定位器中。在整个运动弧度中获取舟月头侧位X线片,并由一名获得委员会认证的手外科医生测量RLA、CLA以及腕关节屈曲或伸展角度(WA)。构建变量的散点图,并计算曲线下面积的相关系数。建立基于WA的预测RLA和CLA的回归方程。
在屈曲和伸展的每次测量中,RLA和CLA与WA均密切相关(=0.7 - 0.8)。线性回归模型显示RLA(=84%)和CLA(=80%)与WA之间具有良好的关系。构建回归方程以根据WA和95%预测CI给出RLA和CLA的预测值。
如果腕关节中立位(0°)时RLA和CLA超过20°,可能代表病理性腕骨排列。所呈现的表格展示了腕关节屈伸整个弧度中RLA和CLA的95% CI。超出95% CI的值也可能表明病理性腕骨排列。