Age-stratified comparison of heart age and predicted cardiovascular risk in 370 000 primary care patients.

Background: Cardiovascular disease (CVD) preventive medications are recommended for patients at high short-term CVD risk. As most younger people with multiple raised CVD risk factors levels have low short-term risk, they could be falsely reassured to take no action. Heart age-the chronological age of a hypothetical person with the same short-term absolute CVD risk as the patient being assessed, but with an 'ideal' risk profile-is a complementary relative CVD risk metric developed to encourage these younger patients to make long-term lifestyle changes.

Comparing five-year and ten-year predicted cardiovascular disease risk in Aotearoa New Zealand: national data linkage study of 1.7 million adults.

Aim: There is no consensus on the optimal time horizon for predicting cardiovascular disease (CVD) risk to inform treatment decisions. New Zealand and Australia recommend 5 years, whereas most countries recommend 10 years. We compared predicted risk and treatment-eligible groups using 5-year and 10-year equations.

Treatment drop-in in a contemporary cohort used to derive cardiovascular risk prediction equations.

Background: No routinely recommended cardiovascular disease (CVD) risk prediction equations have adjusted for CVD preventive medications initiated during follow-up (treatment drop-in) in their derivation cohorts. This will lead to underestimation of risk when equations are applied in clinical practice if treatment drop-in is common. We aimed to quantify the treatment drop-in in a large contemporary national cohort to determine whether equations are likely to require adjustment.

Development and validation of cardiovascular risk prediction equations in 76 000 people with known cardiovascular disease.

Aims: Multiple health administrative databases can be individually linked in Aotearoa New Zealand, using encrypted identifiers. These databases were used to develop cardiovascular risk prediction equations for patients with known cardiovascular disease (CVD).

Methods And Results: Administrative health databases were linked to identify all people aged 18-84 years with known CVD, living in Auckland and Northland, Aotearoa New Zealand, on 1 January 2014.

Association between gout and cardiovascular outcomes in adults with no history of cardiovascular disease: large data linkage study in New Zealand.

Objective: To examine the association of gout with cardiovascular outcomes using linked administrative health data in Aotearoa New Zealand.

Design: Data linkage study.

Setting: National registries of pharmaceutical dispensing, hospital admission, and deaths linked to the Auckland/Northland regional repository of laboratory results to create a regional health contact population as of 31 December 2011.

Prediction of first cardiovascular disease event in 2.9 million individuals using Danish administrative healthcare data: a nationwide, registry-based derivation and validation study.

Aims: The aim of this study was to derive and validate a risk prediction model with nationwide coverage to predict the individual and population-level risk of cardiovascular disease (CVD).

Methods And Results: All 2.98 million Danish residents aged 30-85 years free of CVD were included on 1 January 2014 and followed through 31 December 2018 using nationwide administrative healthcare registries.

Cardiovascular disease preventive medication dispensing for almost every New Zealander 65 years and over: a preventive treatment paradox?

Objective: To describe the dispensing of cardiovascular disease (CVD) preventive medications among older New Zealanders with and without prior CVD or diabetes.

Methods: New Zealanders aged ≥65 years in 2013 were identified using anonymised linkage of national administrative health databases. Dispensing of blood pressure lowering (BPL), lipid lowering (LL) or antithrombotic (AT) medications, was documented, stratified by age and by history of CVD, diabetes, or neither.

Predicting cardiovascular risk from national administrative databases using a combined survival analysis and deep learning approach.

Background: Machine learning-based risk prediction models may outperform traditional statistical models in large datasets with many variables, by identifying both novel predictors and the complex interactions between them. This study compared deep learning extensions of survival analysis models with Cox proportional hazards models for predicting cardiovascular disease (CVD) risk in national health administrative datasets.

Methods: Using individual person linkage of administrative datasets, we constructed a cohort of all New Zealanders aged 30-74 who interacted with public health services during 2012.

Are competing-risk models superior to standard Cox models for predicting cardiovascular risk in older adults? Analysis of a whole-of-country primary prevention cohort aged ≥65 years.

Background: Both cardiovascular disease (CVD) risk and deaths from non-CVD causes, which may preclude a CVD event, increase with age. We evaluated whether accounting for the competing risk of non-CVD death improves the performance of CVD risk-prediction equations in older adults.

Methods: All New Zealanders aged ≥65 years in 2012 without a prior CVD hospitalization were identified by anonymized linkage of eight routinely collected national health data sets.

Cardiovascular risk prediction in type 2 diabetes before and after widespread screening: a derivation and validation study.

Background: Until recently, most patients with diabetes worldwide have been diagnosed when symptomatic and have high cardiovascular risk, meaning most should be prescribed cardiovascular preventive medications. However, in New Zealand, a world-first national programme led to approximately 90% of eligible adults being screened for diabetes by 2016, up from 50% in 2012, identifying many asymptomatic patients with recent-onset diabetes. We hypothesised that cardiovascular risk prediction equations derived before widespread screening would now significantly overestimate risk in screen-detected patients.

Risk of major bleeding by ethnicity and socioeconomic deprivation among 488,107 people in primary care: a cohort study.

Background: Antithrombotic medications (antiplatelets and anticoagulants) reduce the risk of cardiovascular disease (CVD), but with the disadvantage of increasing bleeding risk. Ethnicity and socioeconomic deprivation are independent predictors of major bleeds among patients without CVD, but it is unclear whether they are also predictors of major bleeds among patients with CVD or atrial fibrillation (AF) after adjustment for clinical variables.

Methods: Prospective cohort study of 488,107 people in New Zealand Primary Care (including 64,420 Māori, the indigenous people of New Zealand) aged 30-79 years who had their CVD risk assessed between 2007 and 2016.

Cardiovascular preventive pharmacotherapy stratified by predicted cardiovascular risk: a national data linkage study.

Aims: Cardiovascular disease (CVD) risk management guided by predicted CVD risk is widely recommended internationally. This is the first study to examine CVD preventive pharmacotherapy in a whole-of-country primary prevention population, stratified by CVD risk.

Methods And Results: Anonymized individual-level linkage of New Zealand administrative health and non-health data identified 2 250 201 individuals without atherosclerotic CVD, alive, and aged 30-74 years on 31 March 2013.

Inequity in one-year mortality after first myocardial infarction in Māori and Pacific patients: how much is associated with differences in modifiable clinical risk factors? (ANZACS-QI 49).

Aims: Ischaemic heart disease (IHD) mortality rates after myocardial infarction (MI) are higher in Māori and Pacific compared to European people. The reasons for these differences are complex and incompletely understood. Our aim was to use a contemporary real-world national cohort of patients presenting with their first MI to better understand the extent to which differences in the clinical presentation, cardiovascular (CVD) risk factors, comorbidity and in-hospital treatment explain the mortality outcomes for Māori and Pacific peoples.

Ethnic differences in cardiovascular risk profiles among 475,241 adults in primary care in Aotearoa, New Zealand.

Aim: In Aotearoa, New Zealand, cardiovascular disease (CVD) burden is greatest among Indigenous Māori, Pacific and Indian people. The aim of this study was to describe CVD risk profiles by ethnicity.

Methods: We conducted a cross-sectional analysis of a cohort of people aged 35-74 years who had a CVD risk assessment in primary care between 2004 and 2016.

Performance of CVD risk equations for older patients assessed in general practice: a cohort study.

Aims: To investigate how well the New Zealand PREDICT-CVD risk equations, derived in people aged 30-74 years and US Pooled Cohort Equations (PCEs) derived in people aged 40-79 years, perform for older people.

Methods: The PREDICT cohort study automatically recruits participants when clinicians use PREDICT software to conduct a CVD risk assessment. We identified patients aged 70 years and over, without prior CVD, renal disease or heart failure who had been risk assessed between 2004 and 2016.

How do cardiovascular risk prediction equations developed among 30-74 year olds perform in older age groups? A validation study in 125 000 people aged 75-89 years.

Background: Cardiovascular disease (CVD) risk prediction equations are being used to guide risk management among increasingly older individuals. We examined the performance of recent equations, derived from a 2006 cohort including almost all New Zealanders aged 30-74 years, among older people.

Methods: All New Zealanders aged 75-89 years in contact with state-funded health services in 2006 without prior CVD or heart failure and with complete predictor data were identified by anonymised individual-level linkage of eight national administrative health datasets.

Personalized Prediction of Cardiovascular Benefits and Bleeding Harms From Aspirin for Primary Prevention: A Benefit-Harm Analysis.

Background: Whether the benefits of aspirin for the primary prevention of cardiovascular disease (CVD) outweigh its bleeding harms in some patients is unclear.

Objective: To identify persons without CVD for whom aspirin would probably result in a net benefit.

Design: Individualized benefit-harm analysis based on sex-specific risk scores and estimates of the proportional effect of aspirin on CVD and major bleeding from a 2019 meta-analysis.

Relationship between estimated glomerular filtration rate and incident cardiovascular disease in an ethnically diverse primary care cohort.

Aim: To investigate eGFR as an independent risk factor for CVD in a New Zealand primary care cohort, stratified by disease status (prior CVD, diabetes or no CVD or diabetes).

Method: The PREDICT-CVD open cohort study is a large, ethnically diverse, New Zealand primary care cohort, generated by using a web-based CVD risk assessment tool. Using encrypted identifiers, participant profiles were linked anonymously to a regional laboratory database (to determine renal function) and to national hospitalisation and mortality datasets.

Predicting Bleeding Risk to Guide Aspirin Use for the Primary Prevention of Cardiovascular Disease: A Cohort Study.

Background: Many prognostic models for cardiovascular risk can be used to estimate aspirin's absolute benefits, but few bleeding risk models are available to estimate its likely harms.

Objective: To develop prognostic bleeding risk models among persons in whom aspirin might be considered for the primary prevention of cardiovascular disease (CVD).

Design: Prospective cohort study.

Performance of a Framingham cardiovascular risk model among Indians and Europeans in New Zealand and the role of body mass index and social deprivation.

Objectives: To evaluate a Framingham 5-year cardiovascular disease (CVD) risk score in Indians and Europeans in New Zealand, and determine whether body mass index (BMI) and socioeconomic deprivation were independent predictors of CVD risk.

Methods: We included Indians and Europeans, aged 30-74 years without prior CVD undergoing risk assessment in New Zealand primary care during 2002-2015 (n=256 446). Risk profiles included standard Framingham predictors (age, sex, systolic blood pressure, total cholesterol/high-density lipoprotein ratio, smoking and diabetes) and were linked with national CVD hospitalisations and mortality datasets.

Development and validation of alternative cardiovascular risk prediction equations for population health planning: a routine health data linkage study of 1.7 million New Zealanders.

Background: Cardiovascular disease (CVD) risk prediction equations are primarily used in clinical settings to inform individual risk management decisions. We sought to develop and validate alternative equations derived solely from linked routinely collected national health data that could be applied countrywide to inform population health planning.

Methods: Individual-level linkage of eight administrative health datasets identified all New Zealand residents aged 30-74 years in contact with publicly funded health services during 2006 with no previous hospitalizations for CVD or heart failure, and with complete data on eight pre-specified predictors.

Is general practice identification of prior cardiovascular disease at the time of CVD risk assessment accurate and does it matter?

Aims: To determine the accuracy of general practice recording of prior cardiovascular disease (CVD) at the time of CVD risk assessment and whether recording impacts on CVD management.

Methods: Prior CVD status entered at the time of a first CVD risk assessment from 2002-2015 was compared to prior ischaemic CVD hospitalisations from national datasets using anonymous linkage with an encrypted National Health Index identifier. Clinical factors associated with inaccurate recording of prior events were identified using multivariable logistic regression.

Cardiovascular disease risk prediction equations in 400 000 primary care patients in New Zealand: a derivation and validation study.

Background: Most cardiovascular disease risk prediction equations in use today were derived from cohorts established last century and with participants at higher risk but less socioeconomically and ethnically diverse than patients they are now applied to. We recruited a nationally representative cohort in New Zealand to develop equations relevant to patients in contemporary primary care and compared the performance of these new equations to equations that are recommended in the USA.

Methods: The PREDICT study automatically recruits participants in routine primary care when general practitioners in New Zealand use PREDICT software to assess their patients' risk profiles for cardiovascular disease, which are prospectively linked to national ICD-coded hospitalisation and mortality databases.

Constructing whole of population cohorts for health and social research using the New Zealand Integrated Data Infrastructure.

Objectives: To construct and compare a 2013 New Zealand population derived from Statistics New Zealand's Integrated Data Infrastructure (IDI) with the 2013 census population and a 2013 Health Service Utilisation population, and to ascertain the differences in cardiovascular disease prevalence estimates derived from the three cohorts.

Methods: We constructed three national populations through multiple linked administrative data sources in the IDI and compared the three cohorts by age, gender, ethnicity, area-level deprivation and District Health Board. We also estimated cardiovascular disease prevalence based on hospitalisations using each of the populations as denominators.