BMC Med Inform Decis Mak - Combinational risk factors of metabolic syndrome identified by fuzzy neural network analysis of health-check data.

Tópicos

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Resumo

CKGROUND: Lifestyle-related diseases represented by metabolic syndrome develop as results of complex interaction. By using health check-up data from two large studies collected during a long-term follow-up, we searched for risk factors associated with the development of metabolic syndrome.METHODS: In our original study, we selected 77 case subjects who developed metabolic syndrome during the follow-up and 152 healthy control subjects who were free of lifestyle-related risk components from among 1803 Japanese male employees. In a replication study, we selected 2196 case subjects and 2196 healthy control subjects from among 31343 other Japanese male employees. By means of a bioinformatics approach using a fuzzy neural network (FNN), we searched any significant combinations that are associated with MetS. To ensure that the risk combination selected by FNN analysis was statistically reliable, we performed logistic regression analysis including adjustment.RESULTS: We selected a combination of an elevated level of -glutamyltranspeptidase (-GTP) and an elevated white blood cell (WBC) count as the most significant combination of risk factors for the development of metabolic syndrome. The FNN also identified the same tendency in a replication study. The clinical characteristics of -GTP level and WBC count were statistically significant even after adjustment, confirming that the results obtained from the fuzzy neural network are reasonable. Correlation ratio showed that an elevated level of -GTP is associated with habitual drinking of alcohol and a high WBC count is associated with habitual smoking.CONCLUSIONS: This result obtained by fuzzy neural network analysis of health check-up data from large long-term studies can be useful in providing a personalized novel diagnostic and therapeutic method involving the -GTP level and the WBC count.

Resumo Limpo

ckground lifestylerel diseas repres metabol syndrom develop result complex interact use health checkup data two larg studi collect longterm followup search risk factor associ develop metabol syndromemethod origin studi select case subject develop metabol syndrom followup healthi control subject free lifestylerel risk compon among japanes male employe replic studi select case subject healthi control subject among japanes male employe mean bioinformat approach use fuzzi neural network fnn search signific combin associ met ensur risk combin select fnn analysi statist reliabl perform logist regress analysi includ adjustmentresult select combin elev level glutamyltranspeptidas gtp elev white blood cell wbc count signific combin risk factor develop metabol syndrom fnn also identifi tendenc replic studi clinic characterist gtp level wbc count statist signific even adjust confirm result obtain fuzzi neural network reason correl ratio show elev level gtp associ habitu drink alcohol high wbc count associ habitu smokingconclus result obtain fuzzi neural network analysi health checkup data larg longterm studi can use provid person novel diagnost therapeut method involv gtp level wbc count

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