scholarly journals Cardiovascular disease risk prediction in older people: a qualitative study

2021 ◽  
pp. BJGP.2020.1038
Author(s):  
Denise Ann Taylor ◽  
Katharine Wallis ◽  
Sione Feki ◽  
Sione Segili Moala ◽  
Manusiu He-Naua Esther Latu ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Qualitative Study ◽  
Older People ◽  
Focus Groups ◽  
Risk Prediction ◽  
Heart Attack ◽  
Clinical Decision Making ◽  
Community Dwelling ◽  
Cvd Risk

Background: Despite cardiovascular disease (CVD) risk prediction equations becoming more widely available for people aged 75 years and over, views of older people on CVD risk assessment are unknown. Aim: To explore older people’s views on CVD risk prediction and its assessment. Design and Setting: Qualitative study of community dwelling older New Zealanders. Methods: We purposively recruited a diverse group of older people. Semi-structured interviews and focus groups were conducted, transcribed verbatim and thematically analysed. Results: Thirty-nine participants (mean age 74 years) of Māori, Pacific, South Asian and European ethnicities participated in one of 26 interviews or three focus groups. Three key themes emerged, (1) Poor knowledge and understanding of cardiovascular disease and its risk assessment, (2) Acceptability and perceived benefit of knowing and receiving advice on managing personal cardiovascular risk; and (3) Distinguishing between CVD outcomes; stroke and heart attack are not the same. Most participants did not understand CVD terms but were familiar with ‘heart attack,’ ‘stroke’ and understood lifestyle risk factors for these events. Participants valued CVD outcomes differently, fearing stroke and disability which might adversely affect independence and quality of life, but being less concerned about a heart attack, perceived as causing less disability and swifter death. These findings and preferences were similar across ethnic groups. Conclusion: Older people want to know their CVD risk and how to manage it, but distinguish between CVD outcomes. To inform clinical decision making for older people, risk prediction tools should provide separate event types rather than just composite outcomes.

scholarly journals Application of Cardiovascular disease (CVD) risk assessment equations to the Thai population

2019 ◽  
Vol 2 (1) ◽  
pp. 4-11
Author(s):  
Rungkarn Inthawong ◽  
Khaled Khatab ◽  
Malcolm Whitfield ◽  
Karen Collins ◽  
Maruf A. Raheem ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Cvd Risk ◽  
Thai Population

Cardiovascular Risk Based on ASCVD and KDIGO Categories in Chinese Adults: A Nationwide, Population-Based, Prospective Cohort Study

2021 ◽  
pp. ASN.2020060856
Author(s):  
Yu Xu ◽  
Mian Li ◽  
Guijun Qin ◽  
Jieli Lu ◽  
Li Yan ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Cohort Study ◽  
Risk Prediction ◽  
Cox Regression ◽  
Rank Test ◽  
Atherosclerotic Cardiovascular Disease ◽  
Cvd Risk ◽  
Cox Regression Analysis ◽  
Ascvd Risk ◽  
Risk Categories

BackgroundThe Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guideline used eGFR and urinary albumin-creatinine ratio (ACR) to categorize risks for CKD prognosis. The utility of KDIGO’s stratification of major CVD risks and predictive ability beyond traditional CVD risk prediction scores are unknown.MethodsTo evaluate CVD risks on the basis of ACR and eGFR (individually, together, and in combination using the KDIGO risk categories) and with the atherosclerotic cardiovascular disease (ASCVD) score, we studied 115,366 participants in the China Cardiometabolic Disease and Cancer Cohort study. Participants (aged ≥40 years and without a history of cardiovascular disease) were examined prospectively for major CVD events, including nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death.ResultsDuring 415,111 person-years of follow-up, 2866 major CVD events occurred. Incidence rates and multivariable-adjusted hazard ratios of CVD events increased significantly across the KDIGO risk categories in ASCVD risk strata (all P values for log-rank test and most P values for trend in Cox regression analysis <0.01). Increases in c statistic for CVD risk prediction were 0.01 (0.01 to 0.02) in the overall study population and 0.03 (0.01 to 0.04) in participants with diabetes, after adding eGFR and log(ACR) to a model including the ASCVD risk score. In addition, adding eGFR and log(ACR) to a model with the ASCVD score resulted in significantly improved reclassification of CVD risks (net reclassification improvements, 4.78%; 95% confidence interval, 3.03% to 6.41%).ConclusionsUrinary ACR and eGFR (individually, together, and in combination using KDIGO risk categories) may be important nontraditional risk factors in stratifying and predicting major CVD events in the Chinese population.

Abstract 36: The Role of Sleep as a Cardiovascular Health Metric: Does It Improve Cardiovascular Disease Risk Prediction? Results From The Multi-Ethnic Study of Atherosclerosis

Circulation ◽  
2020 ◽  
Vol 141 (Suppl_1) ◽  
Author(s):  
Nour Makarem ◽  
Cecilia Castro-Diehl ◽  
Marie-Pierre St-Onge ◽  
Susan Redline ◽  
Steven Shea ◽  
...  
Keyword(s):  
Cardiovascular Disease ◽  
Sleep Duration ◽  
Risk Prediction ◽  
Cardiovascular Health ◽  
Cvd Risk ◽  
Sleep Study ◽  
Lower Odds ◽  
Wrist Actigraphy ◽  
Incident Cases

Background: The AHA Life’s Simple 7 (LS7) is a measure of cardiovascular health (CVH). Sufficient and healthy sleep has been linked to higher LS7 scores and lower cardiovascular disease (CVD) risk, but sleep has not been included as a CVH metric. Hypothesis: A CVH score that includes the LS7 plus sleep metrics would be more strongly associated with CVD outcomes than the LS7 score. Methods: Participants were n=1920 diverse adults (mean age: 69.5 y) in the MESA Sleep Study who completed 7 days of wrist actigraphy, overnight in-home polysomnography, and sleep questionnaires. Logistic regression and Cox proportional hazards models were used to compare the LS7 score and 4 new CVH scores that incorporate aspects of sleep in relation to CVD prevalence and incidence (Table). There were 95 prevalent CVD events at the Sleep Exam and 93 incident cases during a mean follow up of 4.4y. Results: The mean LS7 score was 7.3, and the means of the alternate CVH scores ranged from 7.4 to 7.8. Overall, 63% of participants slept <7h, 10% had sleep efficiency <85%, 14% and 36% reported excess daytime sleepiness and insomnia, respectively, 47% had obstructive sleep apnea, and 39% and 25% had high night-to-night variability in sleep duration and sleep onset timing. The LS7 score was not significantly associated with CVD prevalence or incidence (Table). Those in the highest vs. lowest tertile of CVH score 1, that included sleep duration, and CVH score 2, that included sleep characteristics linked to CVD in the literature, had lower odds of prevalent CVD. Those in the highest vs. lowest tertile of CVH scores 3 and 4, which included sleep characteristics linked to cardiovascular risk in MESA, had lower odds of prevalent CVD and lower risk of developing CVD. Conclusions: CVH scores that include sleep were more strongly associated with CVD prevalence and incidence than the traditional LS7 score. The incorporation of sleep as a metric of CVH, akin to other health behaviors, may improve CVD risk prediction. Findings warrant confirmation in larger samples and over longer follow-up.

scholarly journals ‘I’ve never drunk very much water and I still don’t, and I see no reason to do so’: a qualitative study of the views of community-dwelling older people and carers on hydration in later life

2019 ◽  
Vol 49 (1) ◽  
pp. 111-118 ◽  
Author(s):  
Cini Bhanu ◽  
Christina Avgerinou ◽  
Kalpa Kharicha ◽  
Yehudit Bauernfreund ◽  
Helen Croker ◽  
...  
Keyword(s):  
Qualitative Study ◽  
Older People ◽  
Later Life ◽  
Adverse Outcomes ◽  
Community Dwelling ◽  
Drinking Patterns ◽  
Adequate Hydration ◽  
Perceived Importance ◽  
Community Dwelling Older People ◽  
Informal Carers

Abstract Background dehydration is associated with significant adverse outcomes in older people despite being largely preventable and treatable. Little research has focused on the views of community-dwelling older people on hydration, healthy drinking and the perceived importance of drinking well in later life. Objectives to understand community-dwelling older people and informal carers’ views on hydration in later life and how older people can be supported to drink well. Methods qualitative study using interviews and a focus group exploring hydration and nutrition in later life (24 older people at risk of malnutrition and dehydration, 9 informal carers) and thematic analysis. Results this article presents the findings on hydration alone. Four themes are presented: perceptions of healthy drinking, barriers to and facilitators of drinking in later life and supporting older people to drink well. The perceived importance of adequate hydration in later life was polarised. Concerns about urinary incontinence and knowledge gaps were significant barriers. Consideration of individual taste preference and functional capacity acted as facilitators. Distinct habitual drinking patterns with medications and meals exist within individuals. Many relied on thirst at other times or when fluid demands are greater (such as hot weather), a known unreliable prompt in later life. Conclusions older people could be supported to drink well by building upon existing habitual drinking patterns. Primary care and public health should consider individual barriers, facilitators and tailored education. A multidisciplinary approach to promote hydration should be incorporated into care for older people with more complex needs.

Psychological Frailty and Quality of Life of Community Dwelling Older People: a Qualitative Study

2019 ◽  
Vol 15 (5) ◽  
pp. 1395-1412
Author(s):  
Lieve J. Hoeyberghs ◽  
◽  
Jos M. G. A. Schols ◽  
Dominique Verté ◽  
Nico De Witte
Keyword(s):  
Quality Of Life ◽  
Qualitative Study ◽  
Older People ◽  
Community Dwelling ◽  
Community Dwelling Older People

scholarly journals A Cox-Based Risk Prediction Model for Early Detection of Cardiovascular Disease: Identification of Key Risk Factors for the Development of a 10-Year CVD Risk Prediction

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Xiaona Jia ◽  
Mirza Mansoor Baig ◽  
Farhaan Mirza ◽  
Hamid GholamHosseini
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Heart Rate ◽  
Prediction Model ◽  
Risk Prediction ◽  
Risk Model ◽  
Clinical Laboratory ◽  
Risk Prediction Model ◽  
Validation Dataset ◽  
Cvd Risk

Background and Objective. Current cardiovascular disease (CVD) risk models are typically based on traditional laboratory-based predictors. The objective of this research was to identify key risk factors that affect the CVD risk prediction and to develop a 10-year CVD risk prediction model using the identified risk factors. Methods. A Cox proportional hazard regression method was applied to generate the proposed risk model. We used the dataset from Framingham Original Cohort of 5079 men and women aged 30-62 years, who had no overt symptoms of CVD at the baseline; among the selected cohort 3189 had a CVD event. Results. A 10-year CVD risk model based on multiple risk factors (such as age, sex, body mass index (BMI), hypertension, systolic blood pressure (SBP), cigarettes per day, pulse rate, and diabetes) was developed in which heart rate was identified as one of the novel risk factors. The proposed model achieved a good discrimination and calibration ability with C-index (receiver operating characteristic (ROC)) being 0.71 in the validation dataset. We validated the model via statistical and empirical validation. Conclusion. The proposed CVD risk prediction model is based on standard risk factors, which could help reduce the cost and time required for conducting the clinical/laboratory tests. Healthcare providers, clinicians, and patients can use this tool to see the 10-year risk of CVD for an individual. Heart rate was incorporated as a novel predictor, which extends the predictive ability of the past existing risk equations.

scholarly journals New Zealand Diabetes Cohort Study cardiovascular risk score for people with Type 2 diabetes: validation in the PREDICT cohort

2012 ◽  
Vol 4 (3) ◽  
pp. 181 ◽  
Author(s):  
Tom Robinson ◽  
C Raina Elley ◽  
Sue Wells ◽  
Elizabeth Robinson ◽  
Tim Kenealy ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Risk Assessment ◽  
Cohort Study ◽  
New Zealand ◽  
Cardiovascular Event ◽  
Cvd Risk ◽  
Risk Equation ◽  
Framingham Risk

INTRODUCTION: New Zealand (NZ) guidelines recommend treating people for cardiovascular disease (CVD) risk on the basis of five-year absolute risk using a NZ adaptation of the Framingham risk equation. A diabetes-specific Diabetes Cohort Study (DCS) CVD predictive risk model has been developed and validated using NZ Get Checked data. AIM: To revalidate the DCS model with an independent cohort of people routinely assessed using PREDICT, a web-based CVD risk assessment and management programme. METHODS: People with Type 2 diabetes without pre-existing CVD were identified amongst people who had a PREDICT risk assessment between 2002 and 2005. From this group we identified those with sufficient data to allow estimation of CVD risk with the DCS models. We compared the DCS models with the NZ Framingham risk equation in terms of discrimination, calibration, and reclassification implications. RESULTS: Of 3044 people in our study cohort, 1829 people had complete data and therefore had CVD risks calculated. Of this group, 12.8% (235) had a cardiovascular event during the five-year follow-up. The DCS models had better discrimination than the currently used equation, with C-statistics being 0.68 for the two DCS models and 0.65 for the NZ Framingham model. DISCUSSION: The DCS models were superior to the NZ Framingham equation at discriminating people with diabetes who will have a cardiovascular event. The adoption of a DCS model would lead to a small increase in the number of people with diabetes who are treated with medication, but potentially more CVD events would be avoided. KEYWORDS: Cardiovascular disease; diabetes; prevention; risk assessment; reliability and validity

scholarly journals Cardiovascular Disease Risk Prediction in Women: Is There a Role for Novel Biomarkers?

2014 ◽  
Vol 60 (1) ◽  
pp. 88-97 ◽  
Author(s):  
Nina P Paynter ◽  
Brendan M Everett ◽  
Nancy R Cook
Keyword(s):  
Cardiovascular Disease ◽  
Risk Prediction ◽  
Predictive Accuracy ◽  
Disease Risk ◽  
Troponin T ◽  
Cardiovascular Disease Risk ◽  
High Sensitivity ◽  
Preventive Therapy ◽  
Cvd Risk ◽  
Novel Biomarkers

Abstract BACKGROUND Risk prediction is an integral part of the current US guidelines for cardiovascular disease in women. Although current risk prediction algorithms exist to identify women at increased 10-year risk of cardiovascular disease (CVD), clinicians and researchers have been interested in developing novel biomarkers that might improve predictive accuracy further. These biomarkers have led to important insights into the pathophysiology of CVD, but results for their ability to improve prediction or guide preventive therapy have been mixed. The incidence of CVD is lower in women than men, and the effects of a number of traditional biomarkers on CVD risk differ in women compared to men. Both of these factors influence the ability to accurately predict CVD risk. CONTENT We review the distinctive aspects of CVD risk prediction in women, discuss the statistical challenges to improved risk prediction, and discuss a number of biomarkers in varying stages of development with a range of performance in prediction. SUMMARY A variety of biomarkers from different pathophysiologic pathways have been evaluated for improving CVD risk. While many have been incompletely studied or have not been shown to improve risk prediction in women, others, such as high-sensitivity troponin T, have shown promise in improving risk prediction. Increasing inclusion of women in CVD studies will be crucial to providing opportunities to evaluate future biomarkers.

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