Improving Indirect Methods for Calculating Reference Limits for Nerve Conduction Studies From Historical Data

High quality reference limits for nerve conduction studies (NCS) are essential for diagnosis of neuromuscular disorders. Examining healthy controls to calculate reference limits directly is expensive and time consuming. Indirect methods, including extrapolated norms (E-norms), extrapolated reference values (E-Ref), and multivariate extrapolated reference values (MeRef), use historical hospital data instead. These methods sort the historical measurements in increasing order, creating so-called S-curves, and select normal measurements based on the shape of these S-curves. Current versions of these methods have several limitations, and we aimed to improve them by modifying how they select normal measurements.

E-norms, E-Ref, and MeRef were modified with new S-curve selection algorithms. The modified versions of the methods were used to calculate reference limits for common NCS measurements from a large historical database. The results were compared to reference limits calculated from 680 healthy subjects using Youden's J statistic and z-score deviation.

The modified methods provided reference limits with Youden's J > 0.8 and z-score deviation < 0.9 for most types of NCS measurements and similar or higher Youden's J than the unmodified methods. In most cases, the methods required at least 500 measurements and fewer than 20% abnormal measurements for good performance.

Changing the S-curve selection algorithms improves E-norms, E-Ref, and MeRef. The modifications require a sufficient number and proportion of normal measurements in the historical database. When these prerequisites are met, a combination of indirect methods can be used when developing reference limits from historical patient data.