Short, Medium and Long-Term Cause-Specific Mortality Following First-Ever Heart Failure Hospitalisation in New Zealand.

BACKGROUND: Heart failure (HF) is associated with high mortality, but there are limited reports on the underlying cause of death. This study reports short-, medium- and long-term cause-specific mortality following first-ever HF hospitalisation in New Zealand. METHOD: First-ever HF hospitalisations were identified from hospital discharge coding between 2010 and 2013. Mortality outcomes were obtained via anonymised linkage to national datasets. Short (0-30 days), medium (31-364 days), and long-term (1-5 years) mortality rates were identified. Cause of death was identified from death certification coding and classified as cardiovascular and non-cardiovascular. Cox regression analysis was performed to adjust for confounding variables. RESULTS: A cohort of 34,264 individuals with first-ever HF hospitalisation were identified. Mean age was 75.8±13 years and 50.5% were male. A total of 21,637 (63.1%) died within 5 years of hospitalisation; 4,122 (12.0%) within the first 30 days, 6,358 (18.6%) between 31-364 days, and 11,157 (32.6%) between 1 and 5 years. Older age, male gender, Maori ethnicity, higher socioeconomic deprivation and increased comorbidity were independent factors associated with higher all-cause mortality. Cardiovascular causes accounted for 51% of total deaths. Cardiovascular mortality was 6.0%, 9.5%, and 16.7% at 30 days, 31-364 days, and 1-5 years, respectively. The most common causes of non-cardiovascular mortality were neoplasms, chronic respiratory diseases and infections, accounting for 14.6%, 11.0%, and 5.5% of total deaths respectively. Comorbidity was associated with higher non-cardiovascular mortality (hazard ratio [HR] 3.35; 95% confidence interval [CI] 3.16-3.55) but not cardiovascular mortality (HR 0.79; 95% CI 0.72-0.86). CONCLUSIONS: In New Zealand, mortality following first-ever HF hospitalisation is high. Non-cardiovascular death is common and there are ethnic inequities.

Smoking data quality of primary care practices in comparison with smoking data from the New Zealand Maori and Pacific abdominal aortic aneurysm screening programme: an observational study.

BACKGROUND: Quality smoking data is crucial for assessing smoking-related health risk and eligibility for interventions related to that risk. Smoking information collected in primary care practices (PCPs) is a major data source; however, little is known about the PCP smoking data quality. This project compared PCP smoking data to that collected in the Maori and Pacific Abdominal Aortic Aneurysm (AAA) screening programme. METHODS: A two stage review was conducted. In Stage 1, data quality was assessed by comparing the PCP smoking data recorded close to AAA screening episodes with the data collected from participants at the AAA screening session. Inter-rater reliability was analysed using Cohen's kappa scores. In Stage 2, an audit of longitudinal smoking status was conducted, of a subset of participants potentially misclassified in Stage 1. Data were compared in three groups: current smoker (smoke at least monthly), ex-smoker (stopped > 1 month ago) and never smoker (smoked < 100 cigarettes in lifetime). RESULTS: Of the 1841 people who underwent AAA screening, 1716 (93%) had PCP smoking information. Stage 1 PCP smoking data showed 82% concordance with the AAA data (adjusted kappa 0.76). Fewer current or ex-smokers were recorded in PCP data. In the Stage 2 analysis of discordant and missing data (N = 313), 212 were enrolled in the 29 participating PCPs, and of these 13% were deceased and 41% had changed PCP. Of the 93 participants still enrolled in the participating PCPs, smoking status had been updated for 43%. Data on quantity, duration, or quit date of smoking were largely missing in PCP records. The AAA data of ex-smokers who were classified as never smokers in the Stage 2 PCP data (N = 27) showed a median smoking cessation duration of 32 years (range 0-50 years), with 85% (N = 23) having quit more than 15 years ago. CONCLUSIONS: PCP smoking data quality compared with the AAA data is consistent with international findings. PCP data captured fewer current and ex-smokers, suggesting ongoing improvement is important. Intervention programmes based on smoking status should consider complementary mechanisms to ensure eligible individuals are not missed from programme invitation.

Making predictions under interventions: a case study from the PREDICT-CVD cohort in New Zealand primary care.

Background: Most existing clinical prediction models do not allow predictions under interventions. Such predictions allow predicted risk under different proposed strategies to be compared and are therefore useful to support clinical decision making. We aimed to compare methodological approaches for predicting individual level cardiovascular risk under three interventions: smoking cessation, reducing blood pressure, and reducing cholesterol. Methods: We used data from the PREDICT prospective cohort study in New Zealand to calculate cardiovascular risk in a primary care setting. We compared three strategies to estimate absolute risk under intervention: (a) conditioning on hypothetical interventions in non-causal models; (b) combining existing prediction models with causal effects estimated using observational causal inference methods; and (c) combining existing prediction models with causal effects reported in published literature. Results: The median absolute cardiovascular risk among smokers was 3.9%; our approaches predicted that smoking cessation reduced this to a median between a non-causal estimate of 2.5% and a causal estimate of 2.8%, depending on estimation methods. For reducing blood pressure, the proposed approaches estimated a reduction of absolute risk from a median of 4.9% to a median between 3.2% and 4.5% (both derived from causal estimation). Reducing cholesterol was estimated to reduce median absolute risk from 3.1% to between 2.2% (non-causal estimate) and 2.8% (causal estimate). Conclusions: Estimated absolute risk reductions based on non-causal methods were different to those based on causal methods, and there was substantial variation in estimates within the causal methods. Researchers wishing to estimate risk under intervention should be explicit about their causal modelling assumptions and conduct sensitivity analysis by considering a range of possible approaches.

The Prevalence and Management of Atrial Fibrillation in New Zealand Maori Detected through an Abdominal Aortic Aneurysm Screening Program.

BACKGROUND: Atrial fibrillation (AF) screening was incorporated into an abdominal aortic aneurysm screening (AAA) program for New Zealand (NZ) Maori. METHODS: AF screening was performed as an adjunct to AAA screening of Maori men aged 60-74 years and women aged 65-74 years registered with primary health care practices in Auckland, NZ. Pre-existing AF was determined through coded diagnoses or medications in the participant's primary care record. Subsequent audit of the record assessed accuracy of pre-screening coding, medication use and clinical follow-up. RESULTS: Among 1,933 people successfully screened, the prevalence of AF was 144 (7.4%), of which 46 (2.4% of the cohort) were patients without AF coded in the medical record. More than half of these were revealed to be known AF but that was not coded. Thus, the true prevalence of newly detected AF was 1.1% (n=21). An additional 48 (2.5%) of the cohort had been coded as AF but were not in AF at the time of screening. Among the 19 at-risk screen-detected people with AF, 10 started appropriate anticoagulation therapy within 6 months. Of the nine patients who did not commence anticoagulation therapy, five had a subsequent adverse clinical outcome in the follow-up period, including one with ischaemic stroke; two had contraindications to anticoagulants. Among those with previously diagnosed AF, the proportion receiving anticoagulation therapy rose from 57% pre-screening to 83% at 6 months post-screening (p<0.0001); among newly diagnosed AF the proportion rose from 0% to 53% (p<0.01). CONCLUSIONS: AF screening is a feasible low-cost adjunct to AAA screening with potential to reduce ethnic inequities in stroke incidence. However, effective measures are needed to ensure that high-risk newly diagnosed AF is managed according to best practice guidelines.

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. The cohort was followed until study outcome, death, or 5 years. The study outcome was death or hospitalization due to ischaemic heart disease, stroke, heart failure, or peripheral vascular disease. Sex-specific 5-year CVD risk prediction equations were developed using multivariable Fine and Gray models. A total of 43 862 men {median age: 67 years [interquartile range (IQR): 59-75]} and 32 724 women [median age: 70 years (IQR: 60-77)] had 14 252 and 9551 cardiovascular events, respectively. Equations were well calibrated with good discrimination. Increasing age and deprivation, recent cardiovascular hospitalization, Mori ethnicity, smoking history, heart failure, diabetes, chronic renal disease, atrial fibrillation, use of blood pressure lowering and anti-thrombotic drugs, haemoglobin A1c, total cholesterol/HDL cholesterol, and creatinine were statistically significant independent predictors of the study outcome. Fourteen per cent of men and 23% of women had predicted 5-year cardiovascular risk <15%, while 28 and 24% had ≥40% risk. CONCLUSION: Robust cardiovascular risk prediction equations were developed from linked routine health databases, a currently underutilized resource worldwide. The marked heterogeneity demonstrated in predicted risk suggests that preventive therapy in people with known CVD would be better informed by risk stratification beyond a one-size-fits-all high-risk categorization.

Using regionwide New Zealand health databases, methods of predicting hospitalization risk in patients with existing heart disease were developed. Using only data from health databases, it was possible to predict the risk accurately.Among patients with existing heart disease, the predicted risk varied markedly which could help improve preventive strategies.

Guideline-Directed Medical Therapy Before and After Primary Prevention Implantable Cardioverter Defibrillator Implantation in New Zealand (ANZACS-QI 66).

INTRODUCTION: Guidelines recommend angiotensin converting enzyme inhibitors (ACEi)/angiotensin receptor blockers (ARB)/angiotensin receptor neprilysin inhibitors (ARNI); beta blockers; and mineralocorticoid receptor antagonists (MRA) in patients with symptomatic heart failure and reduced left ventricular ejection fraction before consideration of primary prevention implantable cardioverter defibrillator (ICD). This study aims to investigate dispensing rates of guideline-directed medical therapy (GDMT) before and after primary prevention ICD implantation in New Zealand. METHODS: All patients receiving a primary prevention ICD between 2009 and 2018 were identified using nationally collected data on all public hospital admissions in New Zealand. This was anonymously linked to national pharmaceutical data to obtain medication dispensing. Medications were categorised as low dose (<50% of target dose), 50-99% of target dose or target dose based on international guidelines. RESULTS: Of the 1,698 patients identified, ACEi/ARB/ARNI, beta blockers and MRA were dispensed in 80.2%, 83.6% and 45.4%, respectively, prior to ICD implant. However, ≥50% target doses of each medication class were dispensed in only 51.8%, 51.8% and 34.5%, respectively. Only 15.8% of patients were receiving ≥50% target doses of all three classes of medications. In the 1,666 patients who survived 1 year after ICD implant, the proportions of patients dispensed each class of medications remained largely unchanged. CONCLUSION: Dispensing of GDMT was suboptimal in patients before and after primary prevention ICD implantation in New Zealand, and only a minority received ≥50% target doses of all classes of medication. Interventions are needed to optimise use of these standard evidence-based medications to improve clinical outcomes and avoid unnecessary device implantation.

Cardiovascular risk prediction in healthy older people.

Identification of individuals with increased risk of major adverse cardiovascular events (MACE) is important. However, algorithms specific to the elderly are lacking. Data were analysed from a randomised trial involving 18,548 participants ≥ 70 years old (mean age 75.4 years), without prior cardiovascular disease events, dementia or physical disability. MACE included coronary heart disease death, fatal or nonfatal ischaemic stroke or myocardial infarction. Potential predictors tested were based on prior evidence and using a machine-learning approach. Cox regression analyses were used to calculate 5-year predicted risk, and discrimination evaluated from receiver operating characteristic curves. Calibration was also assessed, and the findings internally validated using bootstrapping. External validation was performed in 25,138 healthy, elderly individuals in the primary care environment. During median follow-up of 4.7 years, 594 MACE occurred. Predictors in the final model included age, sex, smoking, systolic blood pressure, high-density lipoprotein cholesterol (HDL-c), non-HDL-c, serum creatinine, diabetes and intake of antihypertensive agents. With variable selection based on machine-learning, age, sex and creatinine were the most important predictors. The final model resulted in an area under the curve (AUC) of 68.1 (95% confidence intervals 65.9; 70.4). The model had an AUC of 67.5 in internal and 64.2 in external validation. The model rank-ordered risk well but underestimated absolute risk in the external validation cohort. A model predicting incident MACE in healthy, elderly individuals includes well-recognised, potentially reversible risk factors and notably, renal function. Calibration would be necessary when used in other populations.

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. After excluding people with prior CVD, we developed sex-specific deep learning and Cox proportional hazards models to estimate the risk of CVD events within 5 years. Models were compared based on the proportion of explained variance, model calibration and discrimination, and hazard ratios for predictor variables. RESULTS: First CVD events occurred in 61 927 of 2 164 872 people. Within the reference group, the largest hazard ratios estimated by the deep learning models were for tobacco use in women (2.04, 95% CI: 1.99, 2.10) and chronic obstructive pulmonary disease with acute lower respiratory infection in men (1.56, 95% CI: 1.50, 1.62). Other identified predictors (e.g. hypertension, chest pain, diabetes) aligned with current knowledge about CVD risk factors. Deep learning outperformed Cox proportional hazards models on the basis of proportion of explained variance (R2: 0.468 vs 0.425 in women and 0.383 vs 0.348 in men), calibration and discrimination (all P <0.0001). CONCLUSIONS: Deep learning extensions of survival analysis models can be applied to large health administrative datasets to derive interpretable CVD risk prediction equations that are more accurate than traditional Cox proportional hazards models.

Impact of change in iron status over time on clinical outcomes in heart failure according to ejection fraction phenotype.

AIMS: The importance of iron deficiency (ID) in heart failure with preserved ejection fraction (HFpEF) is unknown. In HF with reduced ejection fraction (HFrEF), ID is reported as an independent predictor of mortality in HF although not all published studies agree. Different definitions of ID have been assessed, and the natural history of untreated ID not established, which may explain the conflicting results. This study aimed to assess the relationship between ID and mortality in HFpEF, clarify which definition of ID correlates best with outcomes in HFrEF, and determine the prognostic importance of change in ID status over time. METHODS AND RESULTS: Analyses were conducted on data from 1563 patients participating in a prospective international cohort study comparing HFpEF with HFrEF. Plasma samples from baseline and 6 month visits were analysed for the presence of ID. Two ID definitions were evaluated: IDFerritin  = 'ferritin < 100 mcg/L or ferritin 100-300 mcg/L + transferrin saturation < 20%' and IDTsat  = 'transferrin saturation < 20%'. The risk of all-cause mortality and death/HF hospitalization associated with baseline ID (IDFerritin or IDTsat ) and change in ID status at 6 months (persistent, resolving, developing, or never present) was estimated in multivariable Cox proportional hazards models. Of 1563 patients, 1115 (71%) had HFrEF and 448 (29%) HFpEF. Prevalence of ID was similar in HFpEF and HFrEF (58%). Patients with ID were more likely to be female, diabetic, and have a higher co-morbid burden than patients without ID. ID by either definition did not confer independent risk for either all-cause mortality or death/HF hospitalization for patients with HFpEF [IDFerritin hazard ratio (HR) 0.65 (95% confidence interval 0.40-1.05), P = 0.08; IDTsat HR 1.16 (0.72-1.87), P = 0.55]. In the overall study cohort (HFrEF + HFpEF) and HFrEF subgroup, IDFerritin was inferior to IDTsat in prediction of all-cause mortality [overall cohort: HR 1.21 (0.95-1.53), P = 0.12 vs. HR 1.95 (1.52-2.51), P < 0.01; HFrEF: HR 1.12 (0.85-1.48), P = 0.43 vs. HR 1.57 (1.15-2.14), P < 0.01]. Persistence of IDTsat at 6 months was strongly associated with poor outcomes compared with never having IDTsat [HR 2.22 (1.42-3.46), P < 0.01] or having IDTsat at baseline self-resolve by 6 months [HR 1.40 (1.06-1.86), P = 0.02]. CONCLUSIONS: Iron deficiency is equally prevalent in HFpEF and HFrEF but is negatively prognostic only in HFrEF. The natural history of ID is important; persistent ID is strongly associated with mortality whereas resolution is not. IDTsat is the superior definition of ID and should inform future trials investigating the efficacy of intravenous iron replacement in patients with HFrEF.

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. METHODS: New Zealanders aged 30-74 years with type 2 diabetes and without known cardiovascular disease, heart failure, or substantial renal impairment were identified from the 400 000-person PREDICT primary care cohort study between Oct 27, 2004, and Dec 30, 2016, covering the period before and after widespread screening. Sex-specific equations estimating 5-year risk of cardiovascular disease were developed using Cox regression models, with 18 prespecified predictors, including diabetes-related and renal function measures. Equation performance was compared with an equivalent equation derived in the New Zealand Diabetes Cohort Study (NZDCS), which recruited between 2000 and 2006, before widespread screening. FINDINGS: 46 652 participants were included in the PREDICT-1° Diabetes subcohort, of whom 4114 experienced first cardiovascular events during follow-up (median 5·2 years, IQR 3·3-7·4). 14 829 (31·8%) were not taking oral hypoglycaemic medications or insulin at baseline. Median 5-year cardiovascular risk estimated by the new equations was 4·0% (IQR 2·3-6·8) in women and 7·1% (4·5-11·2) in men. The older NZDCS equation overestimated median cardiovascular risk by three times in women (median 14·2% [9·7-20·0]) and two times in men (17·1% [4·5-20·0]). Model and discrimination performance measures for PREDICT-1° Diabetse equations were also significantly better than for the NZDCS equation (eg, for women: R2=32% [95% CI 29-34], Harrell's C=0·73 [0·72-0·74], Royston's D=1·410 [1·330-1·490] vs R2=24% [21-26], C=0·69 [0·67-0·70], and D=1·147 [1·107-1·187]). INTERPRETATION: International treatment guidelines still consider most people with diabetes to be at high cardiovascular risk; however, we show that recent widespread diabetes screening has radically changed the cardiovascular risk profile of people with diabetes in New Zealand. Many of these patients have normal renal function, are not dispensed glucose-lowering medications, and have low cardiovascular risk. These findings have clear international implications as increased diabetes screening is inevitable due to increasing obesity, simpler screening tests, and the introduction of new-generation glucose-lowering medications that prevent cardiovascular events. Cardiovascular risk prediction equations derived from contemporary diabetes populations, with multiple diabetes-related and renal function predictors, will be required to better differentiate between low-risk and high-risk patients in this increasingly heterogeneous population and to inform appropriate non-pharmacological management and cost-effective targeting of expensive new medications. FUNDING: Health Research Council of New Zealand, Heart Foundation of New Zealand, and Healthier Lives National Science Challenge.

Variation in publicly funded bariatric surgery in New Zealand by ethnicity: cohort study of 328,739 patients.

BACKGROUND: New Zealand health services are responsible for equitable health service delivery, particularly for Maori, the Indigenous peoples of New Zealand. Recent research has indicated the presence of inequities in publicly funded bariatric surgery in New Zealand by ethnicity, but it is unclear whether these inequities persist after adjustment for co-morbidities. OBJECTIVES: To determine whether receipt of publicly funded bariatric surgery varies by ethnicity, after adjustment for co-morbidities. SETTING: New Zealand primary care. METHODS: A cohort study of New Zealanders aged 30-79 years who had cardiovascular risk assessment in primary care between January 1, 2010 and June 30, 2018. Data were collated and analyzed using an encrypted unique identifier with regional and national datasets. Cox proportional hazard modeling was performed to determine the likelihood of receipt of a primary publicly funded bariatric procedure up to December 31, 2018, after adjustment for sex, age, ethnicity, locality, socioeconomic deprivation, body mass index, diabetes status, smoking status, and co-morbidities. RESULTS: A total of 328,739 participants (44% female, median age 54 yr [interquartile range, IQR, 46-62], 54% European, 13% Maori, 13% Pacific, 20% Asian) were included in the study and followed up for a median of 5.6 years (IQR 4.1-6.9). The likelihood of receipt of bariatric surgery was lower for Maori and Pacific compared with Europeans (adjusted hazard ratio .82 [95% CI .69-.96] and .24 [.20-.29], respectively). The likelihood of receiving bariatric surgery was also inversely related with increasing socioeconomic deprivation and rurality. CONCLUSIONS: Consistent with data worldwide, there is evidence of unequal access to publicly funded bariatric surgery by ethnicity, locality as well as socioeconomic deprivation among New Zealanders who were cardiovascular risk assessed in primary care.

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 Maori, 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. Primary care data were supplemented with linked data from regional/national databases. Comparisons between ethnic groups were made using age-adjusted summaries of continuous or categorical data. RESULTS: 475,241 people (43% women) were included. Fourteen percent were Maori, 13% Pacific, 8% Indian, 10% Other Asian and 55% European. Maori and Pacific people had a much higher prevalence of smoking, obesity, heart failure, atrial fibrillation and prior CVD compared with other ethnic groups. Pacific and Indian peoples, and to a lesser extent Maori and Other Asian people, had markedly elevated diabetes prevalence compared with Europeans. Indian men had the highest prevalence of prior coronary heart disease. CONCLUSIONS: Maori and Pacific people experience the most significant inequities in exposure to CVD risk factors compared with other ethnic groups. Indians have a high prevalence of diabetes and coronary heart disease. Strong political commitment and cross-sectoral action to implement effective interventions are urgently needed.

Private and Public Bariatric Surgery Trends in New Zealand 2004-2017: Demographics, Cardiovascular Comorbidity and Procedure Selection.

BACKGROUND: For bariatric surgery, patient selection, procedural choice and availability has changed over time internationally. We analysed the annual volume and location of bariatric surgery in New Zealand by demographic characteristics, clinical history and procedure. METHODS: Patients who underwent bariatric procedures between 1 January 2004 and 31 December 2017 were identified through New Zealand hospitalisation records. Hospitalisation and medication data were used to indicate a clinical history of cardiovascular disease (CVD) and/or diabetes. Publicly funded intervention rate by ethnicity was calculated using year- and sex-specific ethnic population estimates and obesity prevalence statistics. RESULTS: This study included 9109 patients, undergoing gastric bypass (GB, n = 3323) and sleeve gastrectomy (SG, n = 5452) as the most common procedures. Nationally, annual bariatric surgery volume increased in the public sector, from 34 to 516 between 2004 and 2017, with a similar increase in available private sector figures. Public recipients were significantly more likely to have a history of diabetes (33.8% vs 14.4%) and/or CVD (9.0% vs 4.7%) than private recipients. Male recipients had higher prevalence of diabetes (29.9% vs 17.6%) and CVD (12.9% vs 4.1%) than female recipients. After adjustment for the adult population prevalence of morbid obesity, Pacific people had half the intervention rate of European and Maori. CONCLUSION: Bariatric surgery is increasing in frequency in New Zealand, with SG and GB being the most common procedures. Significant differences in patient characteristics exist between the public and private sectors. Ensuring equitable selection of publicly funded bariatric surgery candidates remains a challenge.

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. Setting: New Zealand primary care. Participants: 245 028 persons (43.6% women) aged 30 to 79 years without established CVD who had their CVD risk assessed between 2012 and 2016. Measurements: The net effect of aspirin was calculated for each participant by subtracting the number of CVD events likely to be prevented (CVD risk score × proportional effect of aspirin on CVD risk) from the number of major bleeds likely to be caused (major bleed risk score × proportional effect of aspirin on major bleeding risk) over 5 years. Results: 2.5% of women and 12.1% of men were likely to have a net benefit from aspirin treatment for 5 years if 1 CVD event was assumed to be equivalent in severity to 1 major bleed, increasing to 21.4% of women and 40.7% of men if 1 CVD event was assumed to be equivalent to 2 major bleeds. Net benefit subgroups had higher baseline CVD risk, higher levels of most established CVD risk factors, and lower levels of bleeding-specific risk factors than net harm subgroups. Limitations: Risk scores and effect estimates were uncertain. Effects of aspirin on cancer outcomes were not considered. Applicability to non-New Zealand populations was not assessed. Conclusion: For some persons without CVD, aspirin is likely to result in net benefit. Primary Funding Source: Health Research Council of New Zealand.

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. Setting: New Zealand primary care. Participants: The study cohort comprised 385 191 persons aged 30 to 79 years whose CVD risk was assessed between 2007 and 2016. Those with indications for or contraindications to aspirin and those who were already receiving antiplatelet or anticoagulant therapy were excluded. Measurements: For each sex, Cox proportional hazards models were developed to predict major bleeding risk; participants were censored at the earliest of the date on which they first met an exclusion criterion, date of death, or study end date (30 June 2017). The main models included the following predictors: demographic characteristics (age, ethnicity, and socioeconomic deprivation), clinical measurements (systolic blood pressure and ratio of total-high-density lipoprotein cholesterol), family history of premature CVD, medical history (smoking, diabetes, bleeding, peptic ulcer disease, cancer, chronic liver disease, chronic pancreatitis, or alcohol-related conditions), and medication use (nonsteroidal anti-inflammatory agents, corticosteroids, and selective serotonin reuptake inhibitors). Results: During 1 619 846 person-years of follow-up, 4442 persons had major bleeding events (of which 313 [7%] were fatal). The main models predicted a median 5-year bleeding risk of 1.0% (interquartile range, 0.8% to 1.5%) in women and 1.1% (interquartile range, 0.7% to 1.6%) in men. Plots of predicted-against-observed event rates showed good calibration throughout the risk range. Limitation: Hemoglobin level, platelet count, and body mass index were excluded from the main models because of high numbers of missing values, and the models were not externally validated in non-New Zealand populations. Conclusion: Prognostic bleeding risk models were developed that can be used to estimate the absolute bleeding harms of aspirin among persons in whom aspirin is being considered for the primary prevention of CVD. Primary Funding Source: The Health Research Council of New Zealand.

Are the benefits of aspirin likely to exceed the risk of major bleeds among people in whom aspirin is recommended for the primary prevention of cardiovascular disease?

AIM: The 2018 New Zealand Consensus Statement on cardiovascular disease (CVD) risk assessment and management recommends the use of aspirin in people aged less than 70 years with a five-year CVD risk >15% but without prior CVD. We determined whether the estimated number of CVD events avoided by taking aspirin is likely to exceed the number of additional major bleeds caused by aspirin in this patient population. METHOD: Major bleeding rates were obtained from the PREDICT primary care study, a large New Zealand cohort of people eligible for CVD risk assessment, after excluding those with no other indications for (eg, established CVD) or contraindications/cautions (eg, prior major bleed) to aspirin use. We modelled the benefits (CVD events avoided) and harms (additional major bleeds) of aspirin for primary prevention of CVD over five years using hypothetical populations aged 40 to 79 years, stratified by sex, age-group and estimated five-year CVD risk. Two clinical scenarios were modelled, according to whether or not optimisation of lipid- and blood pressure-lowering therapy was required prior to aspirin initiation. RESULTS: In both clinical scenarios the number of CVD events prevented by aspirin over five years was estimated to be, on average, more than the number of bleeds caused by aspirin among people aged less than 70 years with estimated five-year CVD risk of >15%. However, the magnitude of the net benefit of aspirin was modest among people aged 60-69 years, particularly if lipid- and blood pressure-lowering therapy had not already been optimised. CONCLUSION: The benefits of aspirin are likely to exceed the risk of major bleeds among people in whom aspirin is recommended for the primary prevention of CVD. A more cautious approach to the use of aspirin is appropriate for people aged 60-69 years who are likely to have a smaller net benefit from aspirin, particularly those in whom lipid- and blood pressure-lowering therapy has not already been optimised or who have other bleeding risk factors, such as diabetes or smoking. More specific recommendations will be possible when bleeding risk equations are developed to complement the recently developed New Zealand CVD risk equations.

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. The impact of recording accuracy was assessed by the dispensing of CVD preventive medications in the six months after first CVD risk assessment. RESULTS: Among 454,369 people aged 35-74 years who had CVD risk assessments, 30,924 (6.8%) had previously been admitted with ischaemic CVD. Of these people, only 61% were recorded as having prior CVD during risk assessment, with better recording for coronary and stroke events than for peripheral vascular procedures. Inaccurate primary care recording was more likely for younger people (<55 years), women, Maori, Pacific, Indian and Asian ethnic groups whereas smokers and people with diabetes were more likely to have prior CVD correctly identified. Over more than a decade, the odds of inaccurate recording during risk assessment increased [OR 1.09 (95% CIs 1.08-1.10)]. If prior CVD was entered at the time of risk assessment then dispensing of blood pressure-lowering, lipid-lowering, antiplatelet/anticoagulant medications, separately or together, was higher (86%, 85%, 83% and 69%, respectively) than if not recorded (70%, 60%, 60% and 43%). CONCLUSIONS: Overall, 39% of people with prior CVD hospitalisations were not recorded as having prior CVD when their CVD risk was first assessed in general practice. This was associated with inequities in evidence-based risk management. System-based measures are required for robust data sharing at the time of clinical decision making.

Screening for Atrial Fibrillation: A Report of the AF-SCREEN International Collaboration.

Approximately 10% of ischemic strokes are associated with atrial fibrillation (AF) first diagnosed at the time of stroke. Detecting asymptomatic AF would provide an opportunity to prevent these strokes by instituting appropriate anticoagulation. The AF-SCREEN international collaboration was formed in September 2015 to promote discussion and research about AF screening as a strategy to reduce stroke and death and to provide advocacy for implementation of country-specific AF screening programs. During 2016, 60 expert members of AF-SCREEN, including physicians, nurses, allied health professionals, health economists, and patient advocates, were invited to prepare sections of a draft document. In August 2016, 51 members met in Rome to discuss the draft document and consider the key points arising from it using a Delphi process. These key points emphasize that screen-detected AF found at a single timepoint or by intermittent ECG recordings over 2 weeks is not a benign condition and, with additional stroke factors, carries sufficient risk of stroke to justify consideration of anticoagulation. With regard to the methods of mass screening, handheld ECG devices have the advantage of providing a verifiable ECG trace that guidelines require for AF diagnosis and would therefore be preferred as screening tools. Certain patient groups, such as those with recent embolic stroke of uncertain source (ESUS), require more intensive monitoring for AF. Settings for screening include various venues in both the community and the clinic, but they must be linked to a pathway for appropriate diagnosis and management for screening to be effective. It is recognized that health resources vary widely between countries and health systems, so the setting for AF screening should be both country- and health system-specific. Based on current knowledge, this white paper provides a strong case for AF screening now while recognizing that large randomized outcomes studies would be helpful to strengthen the evidence base.