Health Risks

Cardiovascular Health Risks

RE.DOCTOR provides functionalities able to compute the following metrics related to cardiovascular system dysfunctions:

• Risks of cardiovascular events (CV events)
• Risks of cardiovascular diseases (CV diseases)
• Vascular age
• Risk factors scores

Risks of cardiovascular events

The estimated risk of a first hard atherosclerotic cardiovascular event in the next 10 years (coronary death, myocardial infarction, or stroke) for someone without CVD. The estimation is based on the race- and sex-specific Pooled Cohort Equations developed in 2013 by the Risk Assessment Work Group of the American College of Cardiology/American HeartAssociation using a combination of risk factors (age, high systolic blood pressure (treated or non-treated), dyslipedemia (total and high-density lipoprotein cholesterol), smoking, and diabetes) examined in several cohorts of patients in USA (Goff Jr et al. Circulation, 2014;129(25 Suppl 2):S49-73). For races other than caucasian white or African-American, the risk estimation is based on the model validated on caucasian white populations, and hence the actual risk may be different. In particular, compared to caucasian white population, the cardiovascular risk is generally higher for American-Indian populations, and lower for Hispanic/Latin and Asian populations.

The following risks are computed:

• Hard CV events (coronary death, myocardial infarction, or stroke) – based on Pooled Cohort Equations (USA)
• Fatal CV events (European SCORE):
  • Coronary death
  • Fatal stroke
  • Total cardiovascular mortality (coronary + stroke)

Note: Hard CV events risks model is based on studies with subjects between 40 and 79 years old, and fatal CV events risks model with subjects between 40 and 65 years old. Therefore, for input with lower or higher age, the result might be respectively higher or lower than true risk.

Data needed to compute CV events risks:

• age
• gender
• being currently a smoker
• fasting glucose > 125 mg/dL or use of insulin or hypoglycemic medications – diabetes (only for hard CV events)
• treated hypertension (only for hard CV events)
• systolic blood pressure
• total cholesterol level
• HDL level (only for hard CV events)
• race (only for hard CV events)
• country (only for fatal CV events)
• Risks of cardiovascular diseases

The estimated risk of atherosclerotic cardiovascular disease in the next 10 years is based on multivariable sex-specific risk prediction algorithms derived from the famous Framingham Heart Study (Framingham risk functions), with the following risk factors included: age, high systolic blood pressure (treated or non-treated), dyslipedemia (total and high-density lipoprotein cholesterol) or high body mass index (BMI), smoking, and diabetes (D’Agostino et al., Circulation, 2008;117:743-753). The Framingham risk functions are based on data mainly from caucasian white population, and hence for different races the actual risk may be different. In particular, compared to caucasian white population, the cardiovascular risk is generally higher for African-American and American-Indian populations, and lower for Hispanic/Latin and Asian populations.

Note: CVD risks model is based on studies with subjects between 30 and 74 years old. Therefore, for input with lower or higher age, the result might be respectively higher or lower than true risk.

The following risks are computed:

• Atherosclerotic cardiovascular disease (CVD) – overall risk
• Specific CVD risks:
• • Coronary heart disease risk (myocardial infarction, coronary death, coronary insuffciency, angina)
  • Stroke risk (ischemic stroke, hemorrhagic stroke, transient ischemic attack)
  • Heart failure risk
  • Peripheral vascular disease risk (intermittent claudication)

Data needed to compute CVD risks:

• age
• gender
• being currently a smoker
• fasting glucose > 125 mg/dL or use of insulin or hypoglycemic medications – diabetes
• treated hypertension
• systolic blood pressure
• total cholesterol level and HDL level or body height and weight

Depending on which data from the last point is provided, risks are computed based on cholesterol level (more accurate) or body mass index (less accurate).

Vascular age

Vascular age is calculated as the age of a person with the same predicted overall risk for developing atherosclerotic cardiovascular disease (CVD) but with all risk factors at a normal level (total cholesterol 180 mg/dL, HDL 45 mg/dL, non-treated systolic blood pressure 125 mm Hg, no diabetes, no smoking).

Note: Vascular age model is based on studies with subjects between 30 and 74 years old. Therefore, for input with lower or higher age, the result might be respectively higher or lower than true vascular age.

Data needed to compute vascular age:

• age
• gender
• being currently a smoker
• fasting glucose > 125 mg/dL or use of insulin or hypoglycemic medications – diabetes
• treated hypertension
• systolic blood pressure
• total cholesterol level and HDL level or body height and weight

Depending on which data from the last point is provided, risks are computed based on cholesterol level (more accurate) or body mass index (less accurate).

Risks factors scores

In addition to risks RE.DOCTOR can provide information how much each factor contributes to the overall risk of developing CVD in a scoring manner.

Scores computed for factors:

• age
• being currently a smoker
• diabetes
• systolic blood pressure
• total cholesterol level and HDL level or BMI
• total risk score

Integrating risks functionality

To provide RE.DOCTOR information about user’s risks factors, you should use the following structure:

interface RisksFactors {  age?: number;  cholesterol?: number;  cholesterolHdl?: number;  sbp?: number;  isSmoker?: boolean;  hypertensionTreatment?: boolean;  hasDiabetes?: boolean;  bodyHeight?: number; // in centimeters  bodyWeight?: number; // in kilograms  gender?: Gender;  country?: string; // country name ISO code: https://en.wikipedia.org/wiki/ISO_3166-1_alpha-2  race?: Race;} const enum Gender {  MALE = 0,  FEMALE,  OTHER,} const enum Race {  WHITE = 0,  AFRICAN_AMERICAN,  OTHER,}

If some data is not provided, then risks which requires this data also won’t be computed.

To compute the risks, you should use computeHealthRisks() function. It returns the following structure, with filled only these fields, that could be computed with provided data:

computeHealthRisks: (factors: RisksFactors) => HealthRisks; interface HealthRisks {  hardAndFatalEvents: HardAndFatalEventsRisks;  cvDiseases: CVDiseasesRisks;  vascularAge: number | null;  scores: RisksFactorsScores;}

The substructures are defined as follows:

interface HardAndFatalEventsRisks {  coronaryDeathEventRisk: number | null;  fatalStrokeEventRisk: number | null;  totalCVMortalityRisk: number | null;  hardCVEventRisk: number | null;} interface CVDiseasesRisks {  overallRisk: number | null;  coronaryHeartDiseaseRisk: number | null;  strokeRisk: number | null;  heartFailureRisk: number | null;  peripheralVascularDiseaseRisk: number | null;} interface RisksFactorsScores {  ageScore: number | null;  sbpScore: number | null;  smokingScore: number | null;  diabetesScore: number | null;  bmiScore: number | null;  cholesterolScore: number | null;  cholesterolHdlScore: number | null;  totalScore: number | null;}

Because different metrics have different value ranges, dependent also on the risks factors, RE.DOCTOR provides methods to get minimal and maximal values for each risk.

getMinimalRisks: (factors: RisksFactors) => HealthRisks;getMaximalRisks: (factors: RisksFactors) => HealthRisks;