Distribution patterns of demyelination correlate with clinical profiles in chronic inflammatory demyelinating polyneuropathy.

BACKGROUND Chronic inflammatory demyelinating polyneuropathy (CIDP) is a heterogeneous disorder having a wide clinical range, and is characterised by multifocal demyelination that can involve the distal nerve terminals, intermediate nerve segments, and nerve roots. OBJECTIVE To investigate whether the distribution patterns of demyelination along the course of the nerve correlate with clinical profiles in patients with CIDP. METHODS Motor nerve conduction studies were carried out on 42 consecutive patients. According to the physiological criteria for demyelination, the presence of a demyelinative lesion was determined in the distal nerve segments (distal pattern) or intermediate nerve segments (intermediate pattern), or in both (diffuse pattern). The serum concentration of tumour necrosis factor (TNF)-alpha was measured by immunoassay. RESULTS Patients were classified as having a distal (n=10), intermediate (n=13), or diffuse (n=15) pattern, or were unclassified (n=4). Patients with the distal or diffuse pattern had common clinical features such as subacute onset, symmetric symptoms, and weakness involving proximal as well as distal muscles. Patients with the distal pattern had a good response to treatment and a monophasic remitting course, but the diffuse pattern was associated with a treatment dependent relapsing course, reflecting longer disease activity. The serum TNF-alpha concentrations increased only in the "diffuse" subgroup of patients, and this might be associated with breakdown of the blood-nerve barrier and therefore, involvement of the intermediate segments. The intermediate pattern was characterised by a chronic course, asymmetric symptoms, less severe disability, and refractoriness to treatments. CONCLUSIONS CIDP consists of subtypes with varying predilections for lesions along the course of the nerve. The distribution patterns of conduction abnormalities may be useful in the prediction of outcome of patients with CIDP.