Agreement between laboratory-based and non-laboratory-based Framingham risk score in Southern Iran

Rezaei, Fatemeh; Seif, Mozhgan; Gandomkar, Abdullah; Fattahi, Mohammad Reza; Hasanzadeh, Jafar

doi:10.1038/s41598-021-90188-5

Cited by 18 publications

(42 citation statements)

References 26 publications

(14 reference statements)

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“…In some studies, the agreement between different CVDs risk prediction models has been investigated [ 17 , 18 ]. Moreover, some other studies have evaluated the agreement or correlation between laboratory-based and non-laboratory-based Framingham risk scores [ 12 , 19 , 20 ].…”

Section: Discussionmentioning

confidence: 99%

“…In Iran, the American College of Cardiology/American Heart Association (ACC/AHA) and World Health Organization/International Society of Hypertension (WHO/ISH) risk models have been used for risk prediction [ 10 , 11 ]. In another study, the agreement between laboratory-based and non-laboratory-based models was calculated using the Framingham risk score for the pars cohort population [ 12 ]. However, no study has compered the laboratory-based and non-laboratory-based WHO CVD risk prediction charts.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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Background Determining the risk of Cardiovascular Disease (CVD) is a necessity for timely preventive interventions in high-risk groups. However, laboratory testing may be impractical in countries with limited resources. This study aimed at comparison and assessment of the agreement between laboratory-based and non-laboratory-based WHO risk charts models. Methods This study was performed using the baseline data of 8138 participants in the pars cohort study who had no history of CVD and stroke. The updated 2019 WHO model was used to determine the 10-year fatal and non-fatal CVD risks. In general, there are two types of new WHO risk prediction models for CVD. The scores were determined based on age, sex, smoking status, diabetes, Systolic Blood Pressure (SBP), and total cholesterol for the laboratory-based model and age, sex, smoking status, SBP, and Body Mass Index (BMI) for the non-laboratory-based model. The agreement of these two models was determined via kappa statistics for the classified risk (low: < 10%, moderate: 10–< 20%, high: ≥ 20%). Correlation coefficients (r) and scatter plots was used for correlation between scores. Results The results revealed very strong correlation coefficients for all sex and age groups (r = 0.84 for males < 60 years old, 0.93 for males ≥ 60 years old, 0.85 for females < 60 years old, and 0.88 for females ≥ 60 years old). In the laboratory-based model, low, moderate, and high risks were 76.10%, 18.17%, and 5.73%, respectively. These measures were respectively obtained as 77.00%, 18.08%, and 4.92% in the non-laboratory-based model. Based on risk classification, the agreement was substantial for males < 60 years old and for both males and females aged ≥ 60 years (kappa values: 0.79 for males < 60 years old, 0.65 for males ≥ 60 years old, and 0.66 for females ≥ 60 years old) and moderate for females < 60 years old (kappa = 0.46). Conclusions The non-laboratory-based risk prediction model, which is simple, inexpensive, and non-invasive, classifies individuals almost identically to the laboratory-based model. Therefore, in countries with limited resources, these two models can be used interchangeably.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

et al. 2022

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“…In the WHO risk models, the individuals were classified into very low (<5%), low (5 to <10%), moderate (10% to <20%), high (20% to <30%), and very high risk (≥30%) groups (9). It is worth mentioning that the authors have already estimated the FRS for this population (13).…”

Section: Who Risk Prediction Chartsmentioning

confidence: 99%

“…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%

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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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Temporal trends of thyroid cancer between 2010 and 2019 in Asian countries by geographical region and SDI, comparison with global data

Rezaei,

Mazidimoradi,

Pasokh

et al. 2023

Aging Medicine

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ObjectiveThis study aims to describe temporal trends of thyroid cancer (ThC) from 2010 to 2019, in Asian countries by geographical region and sociodemographic index, compared with global data.MethodAnnual case data and age‐standardized rates (ASRs) of epidemiological indicators of ThC cancer data were collected from the 2019 Global Burden of Disease (GBD) study from 2010 to 2019 in 49 countries and territories in Asia. The relative difference (%) between years was used to show comparative variations of ASRs for the indicators studied. The female/male ratio was calculated by dividing female ASRs by male ASRs. Also, these rates were compared between the age group ≥70 years old and younger age groups.ResultsIn 2019, more than 50% of ThC cases and deaths occurred in Asian countries. A total of 53% of ThC patients lived in Asia and more than 60% of the global burden of ThC was imposed on Asian countries. From 2010 to 2019, incidences, deaths, prevalence cases, and DALYs number of ThC cancer increased over 1.28‐, 1.26‐, 1.3‐, and 1.2‐fold, in Asia, respectively. During this period, the age‐standardized incidence rate (ASIR) and the age‐standardized prevalence rate (ASPR) of ThC cancer increased by 5% and 8%, respectively, while the age‐standardized death rate (ASDR) and the age‐standardized DALYs rate (DALYs ASR) of ThC cancer decreased by 6% and 4%, respectively. These trends are different from what happens in other continents. In 2019, age‐specific incidence, death, prevalence, and DALY cases of ThC cancer were peaking at 50–54, 75–79, 50–54, and 55–59 years, respectively. In 2019, the highest ASIR and ASPR of ThC cancer was observed in high‐income Asia Pacific countries and the highest ASDR and DALYs ASR in Southeast Asia countries. Only high‐income Asia Pacific countries experienced a decreasing trend in ASIR and ASPR from 2010 to 2019. ASDR and DALYs ASR have the highest decreasing trend in high‐income Asia Pacific. In 2019, among high SDI Asian countries, the Republic of Korea had the highest ASIR and ASPR, and Brunei Darussalam had the highest ASDR and DALYs ASR. The highest ASIR, ASDR, ASPR, and DALY ASR of ThC cancer was found in Lebanon and Malaysia (high‐middle SDIs), Vietnam (middle SDIs), and Cambodia and Palestine (low‐middle SDIs). Among low SDI Asian countries, Pakistan had the highest ASIR, ASDR, ASPR, and DALY ASR of ThC cancer. All indicators for most countries were higher in women than men.ConclusionMore than half of the burden of thyroid cancer is imposed on the residents of the Asian continent. Although the incidence and prevalence of this cancer in Asian countries is lower than that of the world, America, and Europe, the highest rate of death from thyroid cancer occurs in Asia and they witness the highest burden of the disease. Therefore, it seems that implementing early detection strategies and increasing access to treatment facilities in Asia is one of the necessities of thyroid cancer control in its residents.

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Agreement between laboratory-based and non-laboratory-based Framingham risk score in Southern Iran

Cited by 18 publications

References 26 publications

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

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

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

Temporal trends of thyroid cancer between 2010 and 2019 in Asian countries by geographical region and SDI, comparison with global data

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