| アブストラクト | AIMS: To determine incidence and predictors of starting dialysis in patients with diabetes emphasizing blood pressure variables. METHODS: A nationwide database with claim data on 18 935 people (15 789 men and 3146 women) with diabetes mellitus aged 19 to 72 years in Japan was used to elucidate predictors for starting dialysis. Initiation of dialysis was determined from claims using ICD-10 codes and medical procedures. Using multivariate Cox modelling, interactions between glycaemic and blood pressure values were determined. RESULTS: During a median follow-up of 5.3 years, incidence of dialysis was 0.81 per 1000 person-years. Multivariate analysis of a model involving systolic and diastolic blood pressure (SBP and DBP) simultaneously as covariates showed that hazard ratios (HRs) for starting dialysis for each 1-SD elevation in SBP and DBP were 2.05 (95% confidence interval 1.58-2.64) and 0.66 (0.50-0.88), respectively, implying that pulse pressure (PP) was a promising predictor. For confirmation, a model involving SBP and PP simultaneously as covariates demonstrated that HRs for each 1-SD elevation in SBP and PP were 1.09 (0.81-1.48) and 1.54 (1.14-2.08), respectively, with PP the more potent predictor. Compared with HbA1c <8% and PP <60 mmHg, the HR for those with HbA1c >/=8% and PP >/=60 mmHg was 6.32 (3.42-11.7). CONCLUSIONS: In our historical cohort analysis, SBP and PP were independent predictors for starting dialysis. PP was the more potent, suggesting the contribution of increased arterial stiffness to the incidence of dialysis. Future studies are needed to conclude the independent influence of PP and HbA1c on dialysis considering other risk factors. |
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| ジャーナル名 | Diabetes/metabolism research and reviews |
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| Pubmed追加日 | 2018/12/24 |
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| 投稿者 | Osawa, Taeko; Fujihara, Kazuya; Harada, Mayuko; Yamamoto, Masahiko; Ishizawa, Masahiro; Suzuki, Hiroshi; Ishiguro, Hajime; Matsubayashi, Yasuhiro; Seida, Hiroyasu; Yamanaka, Nauta; Tanaka, Shiro; Shimano, Hitoshi; Kodama, Satoru; Sone, Hirohito |
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| 組織名 | Department of Internal Medicine, Niigata University Faculty of Medicine, Niigata,;Japan.;Japan Medical Data Center Co., Ltd., Tokyo, Japan.;Department of Clinical Biostatistics, Graduate School of Medicine, Kyoto;University, Kyoto, Japan.;Department of Internal Medicine, University of Tsukuba School of Medicine,;Tsukuba, Japan. |
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| Pubmed リンク | https://www.ncbi.nlm.nih.gov/pubmed/30578707/ |
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