scholarly journals Reynolds Risk Score as a Risk Assessment Tool for Cardiovascular Disease After 10 Years: Its Strong Relationship With Blood Pressure

2012 ◽  
Vol 14 (8) ◽  
pp. 571-572 ◽  
Author(s):  
Tomoyuki Kawada
2020 ◽  
Author(s):  
Samaneh Asgari ◽  
Fatemeh Moosaie ◽  
Davood Khalili ◽  
Fereidoun Azizi ◽  
Farzad Hadaegh

Abstract Background: High burden of chronic cardio-metabolic disease (CCD) including type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD) have been reported in the Middle East and North Africa region. We aimed to externally validate a Europoid risk assessment tool designed by Alssema et al, including non-laboratory measures, for the prediction of the CCD in the Iranian population. Methods: The predictors included age, body mass index, waist circumference, use of antihypertensive, current smoking, and family history of cardiovascular disease and or diabetes. For external validation of the model in the Tehran lipids and glucose study (TLGS), the Area under the curve (AUC) and the Hosmer-Lemeshow (HL) goodness of fit test were performed for discrimination and calibration, respectively. Results: Among 1310 men and 1960 women aged 28-85 years, 29.5% and 47.4% experienced CCD during the 6 and 9-year follow-up, respectively. The model showed acceptable discrimination, with an AUC of 0.72(95% CI: 0.69-0.75) for men and 0.73(95% CI: 0.71-0.76) for women. The calibration of the model was good for both genders (min HL P=0.5). Considering separate outcomes, AUC was highest for CKD (0.76(95% CI: 0.72-0.79)) and lowest for T2DM (0.65(95% CI: 0.61-0.69)), in men. As for women, AUC was highest for CVD (0.82(95% CI: 0.78-0.86)) and lowest for T2DM (0.69(95% CI: 0.66-0.73)). The 9-year follow-up demonstrated almost similar performances compared to the 6-year follow-up. Conclusion: This model showed acceptable discrimination and good calibration for risk prediction of CCD in short and long-term follow-up in the Iranian population.


2020 ◽  
Author(s):  
Samaneh Asgari ◽  
Fatemeh Moosaie ◽  
Davood Khalili ◽  
Fereidoun Azizi ◽  
Farzad Hadaegh

Abstract Background: High burden of chronic cardio-metabolic disorders including type 2 diabetes mellitus (T2DM), chronic kidney disease (CKD), and cardiovascular disease (CVD) have been reported in the Middle East and North Africa region. We aimed to externally validate a non-laboratory risk assessment tool for the prediction of the chronic cardio-metabolic disorders in the Iranian population. Methods: The predictors included age, body mass index, waist circumference, use of antihypertensive, current smoking, and family history of cardiovascular disease and/or diabetes. For external validation of the model in the Tehran lipids and glucose study (TLGS), the Area under the curve (AUC) and the Hosmer-Lemeshow (HL) goodness of fit test were performed for discrimination and calibration, respectively. Results: Among 1310 men and 1960 women aged 28-85 years, 29.5% and 47.4% experienced chronic cardio-metabolic disorders during the 6 and 9-year follow-up, respectively. The model showed acceptable discrimination, with an AUC of 0.72(95% CI: 0.69-0.75) for men and 0.73(95% CI: 0.71-0.76) for women. The calibration of the model was good for both genders (min HL P=0.5). Considering separate outcomes, AUC was highest for CKD (0.76(95% CI: 0.72-0.79)) and lowest for T2DM (0.65(95% CI: 0.61-0.69)), in men. As for women, AUC was highest for CVD (0.82(95% CI: 0.78-0.86)) and lowest for T2DM (0.69(95% CI: 0.66-0.73)). The 9-year follow-up demonstrated almost similar performances compared to the 6-year follow-up. Using Cox regression in place of logistic multivariable analysis, model’s discrimination and calibration were reduced for prediction of chronic cardio-metabolic disorders; the issue which had more effect on the prediction of incident CKD among women. Moreover, adding data of educational levels and marital status did not improve, the discrimination and calibration in the enhanced model.Conclusion: This model showed acceptable discrimination and good calibration for risk prediction of chronic cardio-metabolic disorders in short and long-term follow-up in the Iranian population.


2015 ◽  
Vol 88 (5) ◽  
pp. 547
Author(s):  
In Hye Ku ◽  
Ji Hyun Lee ◽  
Seong Man Kim ◽  
Sung Min Kang ◽  
Hae Koo Kim ◽  
...  

Author(s):  
Fenghui Pan ◽  
Wenxia Cui ◽  
Lei Gao ◽  
Xiaoting Shi ◽  
Mingrui Zhang ◽  
...  

Abstract Purpose To develop a simple and clinically useful assessment tool for osteoporosis in older women with type 2 diabetes mellitus (T2DM). Methods A total of 601 women over 60 years of age with T2DM were enrolled in this study. The levels of serum sex hormones and bone metabolism markers were compared between the osteoporosis and non-osteoporosis groups. The least absolute shrinkage and selection operator regularization (LASSO) model was applied to generate a risk assessment tool. The risk score formula was evaluated using receiver operating characteristic analysis and the relationship between the risk score and the bone mineral density (BMD) and T-value were investigated. Results Serum sex hormone-binding globulin (SHBG), cross-linked C-telopeptide of type 1 collagen (CTX), and osteocalcin (OC) were significantly higher in the osteoporosis group. After adjustment for age and body mass index (BMI), SHBG was found to be correlated with the T-value or BMD. Then, a risk score was specifically generated with age, BMI, SHBG, and CTX using the LASSO model. The risk score was significantly negatively correlated with the T-value and BMD of the lumbar spine, femoral neck, and total hip (all P<0.05). Conclusion A risk score using age, BMI, SHBG, and CTX performs well for identifying osteoporosis in older women with T2DM.


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