Stratification of patients with type 2 diabetes mellitus for painless ischemic heart disease

被引:0
|
作者
Volkova, N. I. [1 ]
Harahashyan, A. V. [1 ]
Sorokina, Yu. A. [1 ]
Davidenko, I. Yu. [1 ]
机构
[1] Rostov State Med Univ, Rostov Na Donu, Russia
来源
DIABETES MELLITUS | 2012年 / 15卷 / 01期
关键词
diabetes mellitus type 2; silent myocardial ischemia; risk factors; cardiovascular diseases; screening method;
D O I
暂无
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Aims. Development of assessment model for type 2 diabetes mellitus (DM) patient stratification for painless ischemic heart disease (IHD). Materials and methods. 258 patients with DM type 2 participated in this study (109 male and 149 female) of mean age 58.4 +/- 8.5 with DM experience of 7.9 +/- 6.1 years. All participants were subdivided into three groups: first - DM type 2 without history of painless IHD (138 individuals); second - DM type 2 with diagnosed painless IHD (50 individuals); third - DM type 2 with painful myocardial ischemia. We assessed "classic" risk factors for IHD, immediately connected with DM comorbidity, as well as "additional" risk factors, potentially capable of provoking both painless and painful IHD. In addition, we screened our patients for structural abnormalities of heart by means of echocardiography. Painless IHD was diagnosed by treadmill-tests or Holter monitoring with submaximal exercise. Accumulated data was statistically processed with the use of Spearman's rank correlation, as well as binary logistic regression method. Results were deemed statistically significant at P< 0,05. Results. At the first stage all risk factors were analyzed according to Spearman's rank correlation coefficient. We identified 21 parameter with average (r= 0,5-0,7) and high (r> 0,7) correlation strength. Next we isolated 11 independent variables with highest predictive validity for painless IHD. Based on binary logistic regression method we calculated prediction coefficients and developed a special model, valid for prediction of painless IHD. After adjustment with account of type I and type II errors (with 50/50 ration), predictive validity of our model reached 76% with confidence limit of 95%. Conclusion. Only 11 of all assessed risk factors ("classic", "specific" and "additional") showed to have high predictive validity for development of IHD. Based upon our data, we offer an assessment model suitable for identification of patients at high risk of IHD development in everyday clinical practice.
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页码:19 / 24
页数:6
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