Comparison of laboratory-based and non-laboratory-based WHO cardiovascular disease risk charts: a population-based study

Rezaei, Fatemeh; Seif, Mozhgan; Gandomkar, Abdullah; Fattahi, Mohammad Reza; Malekzadeh, Fatemeh; Sepanlou, Sadaf G; Hassanzadeh, Jafar

doi:10.1186/s12967-022-03336-4

Cited by 23 publications

(24 citation statements)

References 27 publications

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“…Additionally, for a threshold of 10-year CHD risk > 20%, the corresponding agreement ranged from 94.9 to 96.5% and 96.6–97.9% for men and women, respectively [ 27 ]. Rezaei and et al by using WHO risk model showed that the non-laboratory-based risk prediction model classifies individuals almost identically to the laboratory-based model [ 18 ]. The results of a study showed that BMI is a good proxy blood sugar, and serum cholesterol [ 9 , 10 ], which could replace these variables in settings where cost may be more prohibitive for using the laboratory-based model.…”

Section: Discussionmentioning

confidence: 99%

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Jahangiry

Dehghan

Farjam

et al. 2022

BMC Med Res Methodol

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Background Globorisk is a novel risk prediction model for predicting cardiovascular disease (CVD). Globorisk is a country-specific risk prediction model that determines CVD risk for all countries. This model has two versions; laboratory-based and office-based. This study aimed to determine the agreement between laboratory-based and office-based models in a large sample of the general population. Methods Baseline data from the Fasa cohort study was used for the current study. In total, 6810 participants ≥ 40 years without any history of cardiovascular disease or stroke were included in the study. To determine the laboratory-based risk model, factors include age, sex, current smoking status, history of diabetes, systolic blood pressure (SBP), and total cholesterol. To estimate the office-based risk model, factors were age, sex, current smoking status, SBP, and body mass index (BMI). Kappa statistics was used to distinguish the agreement between grouped scores in these two models. Additionally, correlation coefficients and scatter plots were used to determine the linear correlation between the two models. Results In this study 46.53% of the participants were men. The mean age (SD) of participants was 51.08 (7.88) years. Agreements between the two models were moderate and substantial in all women and all men, respectively. The agreement between the two CVD risk groups was 90.15% (kappa = 0.717) in all men, 92.94% (kappa = 0.571) among men aged < 60 years and 77.60% (kappa = 0.645) in men aged ≥ 60 years. The agreement between the two CVD risk groups was 86.68% (kappa = 0.572) among all women, 93.96% (kappa = 0.274) among women aged < 60 years and 62.46% (kappa = 0.422) among women aged ≥ 60 years. A very strong positive correlation (r = 0.94) was found between the two risk scores in all men, and it was similar among men aged < 60 years (r = 0.84) and men aged > 60 years (r = 0.94). Among all women, there was a very strong positive correlation (r = 0.87), and the strong positive correlation remained among < 60 years old (r = 0.76) and women > 60 years old (r = 0.76). Conclusion The Globorisk office-based model which is easier to use as it does not require blood testing can determine the risk groups in this population. The Globorisk office-based model may be used for CVD risk screening in low-middle income countries where resources are limited.

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Section: Discussionmentioning

confidence: 99%

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Jahangiry

Dehghan

Farjam

et al. 2022

BMC Med Res Methodol

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“…Routine CVD risk screening and education regarding modifiable risk factors supported occupational professional standards for EBP implementation during opportune encounters with this high-risk population. limited (Jones et al, 2015;Rezaei et al, 2021Rezaei et al, , 2022. Nonlaboratory risk models have been validated and provided reliable results with superior sensitivity and specificity when compared to other CVD risk algorithms (Gaziano et al, 2008;Kariuki et al, 2017;Rezaei et al, 2022).…”

Section: Applications To Professional Practicementioning

confidence: 97%

Cardiovascular Disease Risk Screening for Commercial Drivers Examined in Occupational Practice: Implementing Evidence-Based Practice to Champion the Health of Essential Workers

Barnes

2023

Workplace Health Saf

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Background: Cardiovascular disease (CVD) remains the leading cause of morbidity and mortality in the United States, with 20% of deaths in adults under age 65. Commercial drivers have an increased CVD incidence rate of 50% compared to 30% for the general population, yet one third of drivers will not be screened for risk factors due to a lack of insurance or primary care. With approximately 3.5 million commercial drivers nationally and correlation of CVD to increased motor vehicle accidents, fatalities, and excessive healthcare costs, addressing the care gap for this high-risk population is imperative. Methods: An evidence-based practice (EBP) project synthesized the literature and implemented CVD risk screening for commercial drivers examined in an occupational practice setting. Using the non-laboratory Framingham CVD risk score calculator, over 90% of drivers were screened during mandated medical examinations and provided education regarding modifiable risk factors during a 2-month period. Findings: Over 40% of commercial drivers were at high risk for CVD with 25% uninsured and 32% without primary care. The average CVD risk score was twice the general population’s risk score, with obesity, hypertension, and smoking being the most common risk factors discussed. Conclusions/Application to Practice: Incorporating CVD risk screening and education during opportune encounters is logical, efficient, and financially prudent. The EBP change supports occupational professionals’ standards, and ongoing review of CVD screening guidelines with integration into practice provides health promotion and promotes public safety for these essential workers.

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“…BP was measured in the sitting position using a mercury sphygmomanometer after five minutes of rest. For each person, BP was measured twice on each arm and the average value was recorded (13,14). According to the JNC8 criteria, hypertension was defined as SBP ≥ 140 mmHg, or diastolic blood pressure (DBP) ≥ 90 mmHg (19), or taking medications.…”

Section: Definition Of Variablesmentioning

confidence: 99%

“…International clinical guidelines for accurate identification and subsequent evidence-based treatment of people at high risk for CVD have recommended the application of CVD risk assessment tools in routine clinical practice (11). In Iran, some studies have used different CVD risk prediction models such as FRS and WHO charts (12)(13)(14). In 2017, a risk chart for CVD in Eastern Mediterranean Region was presented by Sarrafzadegan et al (15).…”

Section: Introductionmentioning

confidence: 99%

Estimation of 10-Year Risk of Cardiovascular Diseases Using WHO Risk Prediction Charts: A Population-Based Study in Southern Iran

Rezaei¹,

Seif²,

Fattahi³

et al. 2022

ijph

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Background: An effective strategy for primary prevention of Cardiovascular Disease (CVD) is accurate diagnosis and the subsequent evidence-based treatment for high-risk people. This study aimed to estimate the 10-year risk of CVD and its related factors. Methods: The baseline data of 8138 participants of the Pars cohort study (PCS) in southern Iran were used. Risk scores were calculated using the updated 2019 WHO CVD risk prediction charts. The scores were determined based on age, gender, current smoking status, systolic blood pressure (SBP), diabetes status, and total serum cholesterol. Demographic and socioeconomic variables, physical activity, and anthropometric indices were measured and analyzed. Multivariable logistic regression was applied to estimate the adjusted odds ratio (aOR) and 95% confidence intervals (CI). Results: The mean (SD) age of the participants was 51.65 (9.06) years, and 53.44% were female. The 10-year CVD risk for 23.89% of participants was ≥10%. The prevalence of hypertension, diabetes, hypercholesterolemia, and smoking was 12.79%, 8.38%, 12.80%, and 14.41%, respectively. Having abdominal obesity, having low or moderate physical activity, being illiterate or having diplomas or lower degrees, and being in the third quartile of the wealth score group were associated with a higher 10-year risk of CVD. Conclusion: About one-fourth of the participants had moderate risk and higher. Due to the relatively high prevalence of CVD risk factors in the middle-aged population, the modifiable risk factors are recommended to be adjusted. Additionally, individual- and community-based educational policies are essential to create a healthy lifestyle.

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Comparison of laboratory-based and non-laboratory-based WHO cardiovascular disease risk charts: a population-based study

Cited by 23 publications

References 27 publications

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Laboratory-based and office-based Globorisk scores to predict 10-year risk of cardiovascular diseases among Iranians: results from the Fasa PERSIAN cohort

Cardiovascular Disease Risk Screening for Commercial Drivers Examined in Occupational Practice: Implementing Evidence-Based Practice to Champion the Health of Essential Workers

Estimation of 10-Year Risk of Cardiovascular Diseases Using WHO Risk Prediction Charts: A Population-Based Study in Southern Iran

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