Summary
Address to age feature modeling CVD risk predictor. Age 45 gender male body mass index 32 kg/m2 systolic blood pressure 145 mmHg diastolic blood pressure 85 mmHg smoking status former smoker diabetes mellitus type 2 diagnosed 6 years ago low density lipoprotein cholesterol 3.6 mmol/L family history of ischaemic heart disease in a first degree relative aged 65 years total cholesterol 5.5 mmol/L high density lipoprotein cholesterol 1.2 mmol/L cardiovascular event in 5 years,risk factor characteristic point cardiovascular age year 10% risk in 10 year 13%risk in 15 year smoker 16 diabetes 12 age 65-74 years 6 systolic blood pressure 140-159 mmHg 3 total cholesterol 5.2-6.2 mmol/L 3 high density lipoprotein cholesterol <1.0 mmol/L 2 male gender 2 family history of coronary heart disease 2 BMI 30-34.9 kg/m2 2 Ethnicity South Asian, Caribbean or Black 2 deprivation score 2 cardiovascular disease risk score may underestimate risk 10-15 year risk of fatal cardiovascular disease estimated using QRISK2 algorithm is 24% over 15 years family history cardiovascular age 58 years so exceeded chronological age by 13 years due to accumulation of cardiovascular risk factors especially obesity,hypertension,diabetes mellitus and smoking suggested need for pharmacological interventions and lifestyle modifications such as weight reduction diet cessation of smoking and increased exercise to reduce significantly the future cardiovascular events risk. review in 12 months to monitor cardiovascular disease risk factor control and adjust treatment as required.
Participants with stable chest pain, who were referred for diagnostic procedures of coronary angiography, were found to have a low diagnosis rate of obstructive coronary artery disease.
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TSS Genders, EW Steyerberg, MGM Hunink, K Nieman… - Bmj, 2012 - bmj.com
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In very old people, homocysteine levels accurately identify cardiovascular risk, while classic risk factors do not. Predicting risk of cardiovascular disease becomes less effective with age.
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W De Ruijter, RGJ Westendorp, WJJ Assendelft… - Bmj, 2009 - bmj.com
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X Rossello, JAN Dorresteijn… - European journal of …, 2019 - journals.sagepub.com
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JAAG Damen, L Hooft, E Schuit, TPA Debray… - bmj, 2016 - bmj.com
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Risk scores were used to categorize patients into different risk categories for incident hypertension, with the highest risk category having the highest number of patients diagnosed with hypertension in the following year. Efficient management of blood pressure is important for reducing morbidity and mortality from chronic diseases.
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C Ye, T Fu, S Hao, Y Zhang, O Wang, B Jin… - Journal of medical …, 2018 - jmir.org
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NP Paynter, DI Chasman, JE Buring… - Annals of internal …, 2009 - acpjournals.org
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The effectiveness of statins in reducing cardiovascular risk is supported by evidence from trials. The threshold for intervention for primary prevention with statins has been lowered from 40% to 20%.
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J Hippisley-Cox, C Coupland, Y Vinogradova… - Bmj, 2008 - bmj.com
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The study found that including hsCRP in cardiovascular risk prediction models improves accuracy. They developed a scoring system for risk classification based on this data.
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NR Cook, JE Buring, PM Ridker - Annals of internal medicine, 2006 - acpjournals.org
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Low fractal dimension analysis (DFA1) abnormal heart rate turbulence (HRT) is a significant risk factor for cardiovascular death (CVdth) in older adults, even after considering conventional cardiovascular disease (CVD) risk factors.
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PK Stein, JI Barzilay, PHM Chaves… - Journal of …, 2008 - Wiley Online Library
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Traditional regression models have been commonly used for developing prediction tools in healthcare, but more flexible models that allow for a versatile relationship between predictor variables and outcomes are now being favored. These models can better predict the occurrence of an outcome without relying on specific risk factors.
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BA Goldstein, AM Navar, RE Carter - European heart journal, 2017 - academic.oup.com
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