Department of Rheumatology, Norfolk and Norwich Hospital, Brunswick Road, Norwich NR1 3SR, UK
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Abstract |
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Method. A cohort of patients being referred with possible carpal tunnel syndrome had clinical and electrophysiological testing, from which the simple calculations for sensitivity, specificity and prevalence were made and subsequently used in the formula of Bayes's theorem. The algorithm was then tested prospectively in a further cohort of similarly referred patients.
Results. The algorithm proved to be reliable when tested prospectively, and was similar to nerve conduction studies in diagnostic accuracy.
Conclusion. A simple algorithm of clinical tests can identify patients without resort to nerve conduction studies, facilitating early treatment.
When reaching a diagnosis, most doctors are blissfully unaware of the underlying logical process, preferring to imagine...some mystical process...making of them an elite priesthood [1]. Nonetheless, we owe much to Thomas Bayes, whose theorem underpins the sequential application of observations, historical findings and clinical examination that leads to the (most probable) diagnosis. The probability of a particular diagnosis can be calculated from the prior probability of having that condition (before a test) and the likelihoods of positive tests in those with or without that diagnosis. The result is called the posterior probability. This value may then be used as the prior probability for a further diagnostic test, allowing one to combine mathematically a sequence of tests. In particular, the posterior probability calculated in this way takes account of all sensitivities and specificities in a single value, and is therefore superior to a single test with high sensitivity but usually poor specificity, or vice versa. This process is explained in detail elsewhere [1].
The role of nerve conduction studies (NCS) in carpal tunnel syndrome (CTS) continues to stimulate debate [2, 3] and waiting lists of patients with the condition are long. Clinicians need a sufficiently powerful clinical test that obviates the need for NCS before steroid injection except in the most atypical situations or preoperatively. The commonly used clinical tests do not allow such accuracy [4]. We set out to examine their predictive power when used in series, as supported by Bayes's theorem.
Inclusion of patients required a suspicion of CTS by the referring clinician on any grounds. Patients previously treated for CTS or with recognized associated conditions were excluded. Patients (n = 105) first completed a hand diagram (HD), on which they outlined the symptomatic area [4]. Katz et al. [4] included those with classical, probable or possible distributions on the diagram as positive when determining sensitivity. Only those with classical or probable distributions were considered positive in this study, in order to optimize the likelihood ratio. One examiner carried out Phalen's test (PT) and Tinel's test (TT) in the standard way. NCS were then carried out on all patients. Sensitivity and specificity for each test were calculated using NCS as the definitive test (sensory amplitude <10 µV or motor latency >3.7 ms).
The prevalence of CTS (by NCS) was 0.71 (75/105). Sensitivities (and number of true positives) for HD, TT and PT were 0.92 (69), 0.55 (41) and 0.72 (54), respectively, and specificities were 0.4, 0.72 and 0.53, similar to values reported previously [4]. Bayes's theorem was then applied to calculate the probability of having CTS with each combination of results (Table 1).
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