SINGLE POTENTIAL ANALYSIS OF CORPUS CAVERNOSUM ELECTROMYOGRAPHY FOR THE ASSESSMENT OF ERECTILE DYSFUNCTION - PROVOCATION, REPRODUCIBILITY AND AGE DEPENDENCE-FINDINGS IN 36 HEALTHY-VOLUNTEERS AND 324 PATIENTS

Purpose: Corpus cavernosum electromyography is a controversial method for assessing erectile failure. For its application as a diagnostic to ol with clinical relevance, intra-individual stability of the paramete rs in independent recordings as well as information about provocation and age dependence are required.Materials and Methods: We investigated reproducibility, provocation and age dependence of 11 parameters of s ingle potential analysis of corpus cavernosum electromyography for 36 healthy volunteers in 2 independent recordings with surface electrodes using a visual evaluation technique. Recording 1 results were compare d to findings for 324 men with erectile dysfunction. Results: Tn healt hy subjects all parameters varied extremely among individuals and they were poorly reproducible at repetition. The definition of a normal ra nge as mean plus or minus 2.5 standard deviations did not result in us eful diagnostic criteria for individual cases. Activity was not age de pendent. Significant differences between healthy and impotent men as d efined groups were found in provocation (overall maximum likelihood ch i-square 15.5, dF = 2, p < 0.0005). Conclusions: Single potential anal ysis of corpus cavernosum electromyography seems to be appropriate for distinguishing potent volunteers from patients with erectile dysfunct ion. Provocation of slow cavernous electric activity seems to be a pro mising parameter that should be considered for ongoing studies. Howeve r, a high range of variation of findings even intra-individually does not currently qualify the method for routine clinical use. Further res earch will show whether different means of documentation or evaluation , that is corpus cavernosum electromyography pattern analysis at rest after audiovisual sexual stimulation, drug application or digital conv ersion of data, will lead to better results.