Savage Nathan J, McKell John S
Department of Physical Therapy, Winston-Salem State University, Winston-Salem, North Carolina, USA.
Department of Physical Therapy, McKell Therapy Group, LLC, Orem, Utah, USA.
J Ultrasound Med. 2024 Sep;43(9):1645-1659. doi: 10.1002/jum.16486. Epub 2024 May 23.
Evaluate the diagnostic accuracy of median nerve cross-sectional area (CSA) to determine the severity of carpal tunnel syndrome (CTS) vs the presence of CTS across existing electrodiagnostic-based (EDX) classification systems.
Retrospective analysis of cross-sectional patient data. Receiver operating characteristic (ROC) analysis was used to determine CSA cutoff values and associated diagnostic likelihood ratios for all consolidated and binary EDX-based classifications of CTS severity. Identification of CSA cutoff values associated with likelihood ratios capable of achieving conclusive (but at least moderate) shifts in diagnostic probability.
Binary categorizations of CTS (ie, "Normal" vs "Absent") were statistically superior to consolidated categorizations of CTS severity (ie, "Normal," "Mild," "Moderate," or "Severe"). Binary categorizations established consistent CSA cutoff values across all EDX-based classifications examined and achieved conclusive shifts in diagnostic probability based on the following values of distal CSA or delta CSA: <7 or <1 mm to rule out and >13 or >7 mm to rule in CTS, respectively. Additionally, the following values of distal CSA and delta CSA may be used in certain circumstances because they produce only small shifts in diagnostic probability: ≤10 or ≤3 mm to rule out and ≥11 or ≥4 mm to rule in CTS, respectively.
Using median nerve CSA to categorize the severity of CTS is not recommended based on lack of consistent and meaningful shifts in diagnostic probability. Rather, binary categorizations to rule out or rule in CTS based on the proposed CSA cutoff values consistently provided conclusive shifts in diagnostic probability across all EDX-based classifications examined.
评估正中神经横截面积（CSA）在确定腕管综合征（CTS）严重程度方面的诊断准确性，以及与现有基于电诊断（EDX）的分类系统相比，其在诊断CTS存在与否方面的准确性。
对横断面患者数据进行回顾性分析。采用受试者操作特征（ROC）分析来确定所有基于EDX的CTS严重程度综合分类和二元分类的CSA临界值及相关诊断似然比。确定与能够实现诊断概率决定性（但至少为中度）变化的似然比相关的CSA临界值。
CTS的二元分类（即“正常”与“不存在”）在统计学上优于CTS严重程度的综合分类（即“正常”“轻度”“中度”或“重度”）。二元分类在所有检查的基于EDX的分类中建立了一致的CSA临界值，并根据以下远端CSA或增量CSA值实现了诊断概率的决定性变化：分别为<7或<1mm排除CTS，>13或>7mm纳入CTS。此外，在某些情况下可使用以下远端CSA和增量CSA值，因为它们仅产生较小的诊断概率变化：分别为≤10或≤3mm排除CTS，≥11或≥4mm纳入CTS。
基于诊断概率缺乏一致且有意义的变化，不建议使用正中神经CSA对CTS严重程度进行分类。相反，基于建议的CSA临界值对CTS进行排除或纳入的二元分类，在所有检查的基于EDX的分类中始终能提供诊断概率的决定性变化。
