A Pilot Study of a Family History Risk Assessment Tool for Cardiovascular Disease

2008 ◽  
Vol 17 (5) ◽  
pp. 499-507 ◽  
Author(s):  
Heather M. MacLeod ◽  
Elizabeth M. McNally
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Pilot Study ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool

scholarly journals External validation of the European risk assessment tool for cardio metabolic disease in a Middle Eastern population

2020 ◽  
Author(s):  
Samaneh Asgari ◽  
Fatemeh Moosaie ◽  
Davood Khalili ◽  
Fereidoun Azizi ◽  
Farzad Hadaegh
Keyword(s):  
Metabolic Disease ◽  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Goodness Of Fit ◽  
Assessment Tool ◽  
External Validation ◽  
Iranian Population ◽  
Risk Assessment Tool ◽  
Goodness Of Fit Test

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.

The genetic family history as a risk assessment tool in internal medicine

2003 ◽  
Vol 5 (2) ◽  
pp. 84-91 ◽  
Author(s):  
Theresa M. Frezzo ◽  
Wendy S. Rubinstein ◽  
Daniel Dunham ◽  
Kelly E. Ormond
Keyword(s):  
Internal Medicine ◽  
Risk Assessment ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool

Development of a risk assessment tool for women with a family history of breast cancer

2005 ◽  
Vol 29 (5) ◽  
pp. 433-439 ◽  
Author(s):  
Dejana Braithwaite ◽  
Stephen Sutton ◽  
James Mackay ◽  
Judith Stein ◽  
Jon Emery
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Family History ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
History Of

scholarly journals External validation of the European risk assessment tool for Chronic Cardio-metabolic disorders in a Middle Eastern population

2020 ◽  
Author(s):  
Samaneh Asgari ◽  
Fatemeh Moosaie ◽  
Davood Khalili ◽  
Fereidoun Azizi ◽  
Farzad Hadaegh
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Metabolic Disorders ◽  
Assessment Tool ◽  
External Validation ◽  
Multivariable Analysis ◽  
Iranian Population ◽  
Risk Assessment Tool ◽  
Goodness Of Fit Test

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.

scholarly journals Using Crowdsourcing to Develop a Peer-Led Intervention for Safer Dating App Use: Pilot Study

10.2196/12098 ◽  
2020 ◽  
Vol 4 (4) ◽  
pp. e12098 ◽  
Author(s):  
William Chi Wai Wong ◽  
Lin Song ◽  
Christopher See ◽  
Stephanie Tze Hei Lau ◽  
Wai Han Sun ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Pilot Study ◽  
Intervention Program ◽  
Development Process ◽  
Assessment Tool ◽  
Risk Assessment Tool ◽  
Simulation Game ◽  
First Person ◽  
Peer Mentors ◽  
Dating Apps

Background Smartphone-based dating apps are rapidly transforming how people seek potential sexual and romantic partners. However, they can also increase the risk of unsafe sexual behaviors, harassment, and infringement of personal privacy. Current research on interventions for safer dating app use remains insufficient. Objective The goal of this study was to describe the development of an intervention for safer dating app usage using crowdsourcing and peer-led approaches. Methods This paper describes the development of an intervention program designed to promote safer dating app use among college students. Crowdsourcing and peer-led approaches were adopted during key stages of the development process. Focus group discussions were held to assess the experience and needs of dating app users. A crowdsourcing contest then solicited ideas for performance objectives for the intervention. These objectives were grouped to further identify practical strategies. A one-day intensive workshop was subsequently held with peer mentors to brainstorm ideas for the production of creative interventional materials. The intervention programs were produced and tested in a pilot study. The app’s effectiveness will be evaluated in a cluster randomized controlled trial. Results The intervention program consists of a risk assessment tool, a first-person scenario game, and four short videos. The risk assessment tool, comprised of 14 questions, will give the participant a score to determine their level of risk of adverse events when using dating apps. The scenario game is a first-person simulation game where the players are presented with choices when faced with different scenarios. The short videos each last 2-4 minutes, with points of discussion aimed at addressing the risks of using dating apps. The programs were piloted and were found to be relatable and helpful when further modifications were made. Conclusions Potential challenges identified during the development process included data management and analysis, sustaining peer mentors’ interests and participation, and balancing between providing more information and perpetuating social stigma around dating app use. By integrating new approaches, such as crowdsourcing and the peer-led approach, in developing an intervention for safer dating app use, our development process provides a viable model for developing future interventions to address the risks associated with dating app use.

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