scholarly journals CARDIOVASCULAR RISK PREDICTION AND ITS RELATIONSHIP WITH METABOLIC SYNDROME AND EMERGING SERUM MARKERS IN OCCUPATIONAL HEALTH SURVEILLANCE

2014 ◽  
Vol 17 (2) ◽  
pp. 91-96 ◽  
Author(s):  
Luis Reinoso-Barbero ◽  
Ana Capapé-Aguilar ◽  
Ramón Díaz-Garrido ◽  
Catalina Santiago Dorrego ◽  
Félix Gómez-Gallego ◽  
...  
2010 ◽  
Vol 20 (9) ◽  
pp. 676-682 ◽  
Author(s):  
G. Brevetti ◽  
E. Laurenzano ◽  
G. Giugliano ◽  
S. Lanero ◽  
L. Brevetti ◽  
...  

2013 ◽  
Vol 47 (4) ◽  
pp. 210-216 ◽  
Author(s):  
Marika Salminen ◽  
Marikka Kuoppamäki ◽  
Tero Vahlberg ◽  
Ismo Räihä ◽  
Kerttu Irjala ◽  
...  

2012 ◽  
Vol 21 (3) ◽  
pp. 384-390 ◽  
Author(s):  
Ella Zomer ◽  
Danny Liew ◽  
Alice Owen ◽  
Dianna J Magliano ◽  
Zanfina Ademi ◽  
...  

Author(s):  
Paulin Paul ◽  
Noel George ◽  
B. Priestly Shan

Background: The accuracy of Joint British Society calculator3 (JBS3) cardiovascular risk prediction may vary within Indian population, and is not yet studied using south Indian Kerala based population data. Objectives: To evaluate the cardiovascular disease (CV) risk estimation using the traditional CVD risk factors (TRF) in Kerala based population. Methods: This cross sectional study has 977 subjects aged between 30 and 80 years. The traditional CVD risk markers are recorded from the medical archives of clinical locations at Ernakulum district, in Kerala The 10 year risk categories used are low (<7.5%), intermediate (≥7.5% and <20%), and high (≥20%). The lifetime classifications low lifetime (≤39%) and high lifetime (≥40%) are used. The study was evaluated using statistical analysis. Chi-square test was done for dependent and categorical CVD risk variable comparison. Multivariate ordinal logistic regression for 10-year risk model and odds logistic regression analysis for lifetime model was used to identify significant risk variables. Results: The mean age of the study population is 52.56±11.43 years. The risk predictions has 39.1% in low, 25.0% in intermediate, and 35.9% had high 10-year risk. The low lifetime risk had 41.1% and 58.9% is high lifetime risk. Reclassifications to high lifetime are higher from intermediate 10-year risk category. The Hosmer-Lemeshow goodness-of-fit statistics indicates a good model fit. Conclusion: The risk prediction and timely intervention with appropriate therapeutic and lifestyle modification is useful in primary prevention. Avoiding short-term incidences and reclassifications to high lifetime can reduce the CVD mortality rates.


2021 ◽  
Vol 6 (4) ◽  
pp. S127
Author(s):  
S. Veillette ◽  
F. Lamarche ◽  
M. Agharazii ◽  
S. Wassertheurer ◽  
B. Hametner ◽  
...  

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