Determining the Optimal Methodology for Identifying Incident Stroke Deaths Using Administrative Datasets Within Australia.

BACKGROUND AND AIM: Quantifying stroke incidence and mortality is crucial for disease surveillance and health system planning. Administrative data offer a cost-effective alternative to "gold standard" population-based studies. However, the optimal methodology for establishing stroke deaths from administrative data remains unclear. We aimed to determine the optimal method for identifying stroke-related deaths in administrative datasets as the fatal component of stroke incidence, comparing counts derived using underlying and all causes of death (CoD). METHOD: Using whole-population multijurisdictional person-level linked data from hospital and death datasets from South Australia, the Northern Territory, and Western Australia, we identified first-ever stroke events between 2012 and 2015, using underlying CoD and all CoD to identify fatal stroke counts. We determined the 28-day case fatality for both counts and compared results with gold standard Australian population-based stroke incidence studies. RESULTS: The total number of incident stroke events was 16,150 using underlying CoD and 18,074 using all CoD. Case fatality was 24.7% and 32.7% using underlying and all CoD, respectively. Case fatality using underlying CoD was similar to that observed in four Australian "gold standard" population-based studies (20%-24%). CONCLUSIONS: Underlying CoD generates fatal incident stroke estimates more consistent with population-based studies than estimates based on stroke deaths identified from all-cause fields in death registers.

Sex- and Age-Specific Differences in Risk Profiles and Early Outcomes in Adults With Acute Coronary Syndromes.

BACKGROUND: Adults <55 years of age comprise a quarter of all acute coronary syndromes (ACS) hospitalisations. There is a paucity of data characterising this group, particularly sex differences. This study aimed to compare the clinical and risk profile of patients with ACS aged <55 years with older counterparts, and measure short-term outcomes by age and sex. METHOD: The study population comprised patients with ACS enrolled in the AUS-Global Registry of Acute Coronary Events (GRACE), Cooperative National Registry of Acute Coronary Syndrome Care (CONCORDANCE) and SNAPSHOT ACS registries. We compared clinical features and combinations of major modifiable risk factors (hypertension, smoking, dyslipidaemia, and diabetes) by sex and age group (20-54, 55-74, 75-94 years). All-cause mortality and major adverse events were identified in-hospital and at 6-months. RESULTS: There were 16,658 patients included (22.3% aged 20-54 years). Among them, 20-54 year olds had the highest proportion of ST-elevation myocardial infarction compared with sex-matched older age groups. Half of 20-54 year olds were current smokers, compared with a quarter of 55-74 year olds, and had the highest prevalence of no major modifiable risk factors (14.2% women, 12.7% men) and of single risk factors (27.6% women, 29.0% men), driven by smoking. Conversely, this age group had the highest proportion of all four modifiable risk factors (6.6% women, 4.7% men). Mortality at 6 months in 20-54 year olds was similar between men (2.3%) and women (1.7%), although lower than in older age groups. CONCLUSIONS: Younger adults with ACS are more likely to have either no risk factor, a single risk factor, or all four modifiable risk factors, than older patients. Targeted risk factor prevention and management is warranted in this age group.

Risk Factors Associated with Major Adverse Cardiovascular Events after Ischemic Stroke: A Linked Registry Study.

INTRODUCTION: Survivors of stroke are at risk of experiencing subsequent major adverse cardiovascular events (MACE). We aimed to determine the incidence of, and risk factors for, MACE after first-ever ischemic stroke, by age group (18-64 years vs. ≥65 years). METHODS: Observational cohort study using patient-level data from the Australian Stroke Clinical Registry (2009-2013), linked with hospital administrative data. We included adults with first-ever ischemic stroke who had no previous acute cardiovascular admissions and followed these patients for 2 years post-discharge, or until the first post-stroke MACE event. A Fine-Gray sub-distribution hazard model, accounting for the competing risk of non-cardiovascular death, was used to determine factors for incident post-stroke MACE. RESULTS: Among 5,994 patients with a first-ever ischemic stroke (median age 73 years, 45% female), 17% were admitted for MACE within 2 years (129 events per 1,000 person-years). The median time to first post-stroke MACE was 117 days (89 days if aged <65 years vs. 126 days if aged ≥65 years; p = 0.025). Among patients aged 18-64 years, receiving intravenous thrombolysis (sub-distribution hazard ratio [SHR] 0.51 [95% CI, 0.28-0.92]) or being discharged to inpatient rehabilitation (SHR 0.65 [95% CI, 0.46-0.92]) were associated with a reduced incidence of post-stroke MACE. In those aged ≥65 years, being unable to walk on admission (SHR 1.33 [95% CI 1.15-1.54]), and history of smoking (SHR 1.40 [95% CI 1.14-1.71]) or atrial fibrillation (SHR 1.31 [95% CI 1.14-1.51]) were associated with an increased incidence of post-stroke MACE. Acute management in a large hospital (>300 beds) for the initial stroke event was associated with reduced incidence of post-stroke MACE, irrespective of age group. CONCLUSIONS: MACE is common within 2 years of stroke, with most events occurring within the first year. We have identified important factors to consider when designing interventions to prevent MACE after stroke, particularly among those aged <65 years.

Excess Deaths Associated with Rheumatic Heart Disease, Australia, 2013-2017.

During 2013-2017, the mortality rate ratio for rheumatic heart disease among Indigenous versus non-Indigenous persons in Australia was 15.9, reflecting health inequity. Using excess mortality methods, we found that deaths associated with rheumatic heart disease among Indigenous Australians were probably substantially undercounted, affecting accuracy of calculations based solely on Australian Bureau of Statistics data.

Global Trends in Atherosclerotic Cardiovascular Disease.

PURPOSE: Cardiovascular disease (CVD) is the leading cause of morbidity and mortality, affecting over 523 million people globally. Atherosclerotic diseases, particularly ischemic heart disease (IHD) and stroke, are the primary mediators of CVD burden and trends, with half of CVD deaths attributed to IHD, and another quarter to ischemic stroke. The aim of this review was to provide an overview of world-wide trends in the burden of atherosclerotic CVD. METHODS: A literature review of published studies reporting regional or global trends or burden of CVD was undertaken, with a specific focus on atherosclerotic-mediated CVDs. FINDINGS: While long-term trends in age-standardized rates of CVD mortality and incidence indicate substantial declines in disease burden, the impact of population growth and ageing has contributed to a continued increase in the absolute number of people living with CVD. Additionally, when data are restricted to the most recent decade, there are indications that even declines in age-standardized CVD rates may have attenuated. Trends are also heterogeneous across countries and regions, with a relative increase in CVD burden in developing countries and differing trends within countries. The impact of the COVID-19 pandemic resulted in substantial short-term reductions in hospitalization rates for major atherosclerotic CVDs including acute coronary syndromes and heart failure in some countries. IMPLICATIONS: Recent attenuation of declines in atherosclerotic CVDs with increasing absolute burden has significant implications for health systems and resource availability, with the impact of the COVID-19 pandemic on longer-term trends in CVD yet to be clearly established.

The Australian Genetic Heart Disease Registry: Protocol for a Data Linkage Study.

BACKGROUND: Genetic heart diseases such as hypertrophic cardiomyopathy can cause significant morbidity and mortality, ranging from syncope, chest pain, and palpitations to heart failure and sudden cardiac death. These diseases are inherited in an autosomal dominant fashion, meaning family members of affected individuals have a 1 in 2 chance of also inheriting the disease ("at-risk relatives"). The health care use patterns of individuals with a genetic heart disease, including emergency department presentations and hospital admissions, are poorly understood. By linking genetic heart disease registry data to routinely collected health data, we aim to provide a more comprehensive clinical data set to examine the burden of disease on individuals, families, and health care systems. OBJECTIVE: The objective of this study is to link the Australian Genetic Heart Disease (AGHD) Registry with routinely collected whole-population health data sets to investigate the health care use of individuals with a genetic heart disease and their at-risk relatives. This linked data set will allow for the investigation of differences in outcomes and health care use due to disease, sex, socioeconomic status, and other factors. METHODS: The AGHD Registry is a nationwide data set that began in 2007 and aims to recruit individuals with a genetic heart disease and their family members. In this study, demographic, clinical, and genetic data (available from 2007 to 2019) for AGHD Registry participants and at-risk relatives residing in New South Wales (NSW), Australia, were linked to routinely collected health data. These data included NSW-based data sets covering hospitalizations (2001-2019), emergency department presentations (2005-2019), and both state-wide and national mortality registries (2007-2019). The linkage was performed by the Centre for Health Record Linkage. Investigations stratifying by diagnosis, age, sex, socioeconomic status, and gene status will be undertaken and reported using descriptive statistics. RESULTS: NSW AGHD Registry participants were linked to routinely collected health data sets using probabilistic matching (November 2019). Of 1720 AGHD Registry participants, 1384 had linkages with 11,610 hospital records, 7032 emergency department records, and 60 death records. Data assessment and harmonization were performed, and descriptive data analysis is underway. CONCLUSIONS: We intend to provide insights into the health care use patterns of individuals with a genetic heart disease and their at-risk relatives, including frequency of hospital admissions and differences due to factors such as disease, sex, and socioeconomic status. Identifying disparities and potential barriers to care may highlight specific health care needs (eg, between sexes) and factors impacting health care access and use. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48636.

Differing Definitions of First-Ever Stroke Influence Incidence Estimates More than Trends: A Study Using Linked Administrative Data.

INTRODUCTION: Researchers apply varying definitions when measuring stroke incidence using administrative data. We aimed to investigate the sensitivity of incidence estimates to varying definitions of stroke and lookback periods and to provide updated incidence rates and trends for Western Australia (WA). METHODS: We used linked state-wide hospital and death data from 1985 to 2017 to identify incident strokes from 2005 to 2017. A standard definition was applied which included strokes coded as the principal hospital diagnosis or the underlying cause of death, with a 10-year lookback used to clear prevalent cases. Alternative definitions were compared against the standard definition by percentage difference in case numbers. Age-standardised incidence rates were calculated, and age- and sex-adjusted Poisson regression models were used to estimate incidence trends. RESULTS: The standard definition with a 10-year lookback period captured 31,274 incident strokes. Capture increased by 19.3% when including secondary diagnoses, 4.1% when including nontraumatic subdural and extradural haemorrhage, and 8.1% when including associated causes of death. Excluding death records reduced capture by 11.1%. A 20-year lookback reduced over-ascertainment by 2.0%, and a 1-year lookback increased capture by 13.3%. Incidence declined 0.6% annually (95% confidence interval -0.9, -0.3). Annual reductions were similar for most definitions except when death records were excluded (-0.1%, CI: -0.4, 0.2) and with the shortest lookback periods (greatest annual reduction). CONCLUSION: Stroke incidence has declined in WA. Differing methods of identifying stroke influence estimates of incidence to a greater extent than estimates of trends. Reductions in stroke incidence over time are primarily driven by declines in fatal strokes.

Long-term exposure to low-concentration PM2.5 and heart disease in older men in Perth, Australia: The Health in Men Study.

Exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 µm (PM2.5) is associated with increased risk of heart disease, but less is known about the relationship at low concentrations. This study aimed to determine the dose-response relationship between long-term PM2.5 exposure and risk of incident ischemic heart disease (IHD), incident heart failure (HF), and incident atrial fibrillation (AF) in older men living in a region with relatively low ambient air pollution. Methods: PM2.5 exposure was estimated for 11,249 older adult males who resided in Perth, Western Australia and were recruited from 1996 to 1999. Participants were followed until 2018 for the HF and AF outcomes, and until 2017 for IHD. Cox-proportional hazards models, using age as the analysis time, and adjusting for demographic and lifestyle factors were used. PM2.5 was entered as a restricted cubic spline to model nonlinearity. Results: We observed a mean PM2.5 concentration of 4.95 µg/m3 (SD 1.68 µg/m3) in the first year of recruitment. After excluding participants with preexisting disease and adjusting for demographic and lifestyle factors, PM2.5 exposure was associated with a trend toward increased incidence of IHD, HF, and AF, but none were statistically significant. At a PM2.5 concentration of 7 µg/m3 the hazard ratio for incident IHD was 1.04 (95% confidence interval [CI] = 0.86, 1.25) compared with the reference category of 1 µg/m3. Conclusions: We did not observe a significant association between long-term exposure to low-concentration PM2.5 air pollution and IHD, HF, or AF.

The New South Wales Sudden Cardiac Arrest Registry: A Data Linkage Cohort Study.

BACKGROUND: Sudden cardiac arrest (SCA) in young people aged 1 to 50 years often occurs with no presenting symptoms or risk factors prompting screening for cardiovascular disease prior to their cardiac arrest. Approximately 3,000 young Australians suffer from sudden cardiac death (SCD) each year, making this a major public health issue. However, there is significant variation in the way incidence is estimated resulting in discrepancy across reporting which impacts our ability to understand and prevent these devastating events. We describe the New South Wales (NSW) Sudden Cardiac Arrest Registry: a retrospective, data linkage study which will identify all SCAs in the young in NSW from 2009 through to June 2022. OBJECTIVE: To determine the incidence, demographic characteristics and causes of SCA in young people. We will develop an NSW-based registry that will contribute to a greater understanding of SCA including risk factors and outcomes. METHODS: The cohort will include all people who experience a SCA in the NSW community aged between 1 to 50 years. Cases will be identified using the following three datasets: the Out of Hospital Cardiac Arrest Register housed at NSW Ambulance, the NSW Emergency Department Data Collection, and the National Coronial Information System. Data from eight datasets will be collected, anonymised and linked for the entire cohort. Analysis will be undertaken and reported using descriptive statistics. CONCLUSIONS: The NSW SCA registry will be an important resource for the improved understanding of SCA and inform the widespread impacts it has on individuals, their families and society.

Stroke clinical coding education program in Australia and New Zealand.

BACKGROUND: Accurate coded diagnostic data are important for epidemiological research of stroke. OBJECTIVE: To develop, implement and evaluate an online education program for improving clinical coding of stroke. METHOD: The Australia and New Zealand Stroke Coding Working Group co-developed an education program comprising eight modules: rationale for coding of stroke; understanding stroke; management of stroke; national coding standards; coding trees; good clinical documentation; coding practices; and scenarios. Clinical coders and health information managers participated in the 90-minute education program. Pre- and post-education surveys were administered to assess knowledge of stroke and coding, and to obtain feedback. Descriptive analyses were used for quantitative data, inductive thematic analysis for open-text responses, with all results triangulated. RESULTS: Of 615 participants, 404 (66%) completed both pre- and post-education assessments. Respondents had improved knowledge for 9/12 questions (p < 0.05), including knowledge of applicable coding standards, coding of intracerebral haemorrhage and the actions to take when coding stroke (all p < 0.001). Majority of respondents agreed that information was pitched at an appropriate level; education materials were well organised; presenters had adequate knowledge; and that they would recommend the session to colleagues. In qualitative evaluations, the education program was beneficial for newly trained clinical coders, or as a knowledge refresher, and respondents valued clinical information from a stroke neurologist. CONCLUSION: Our education program was associated with increased knowledge for clinical coding of stroke. To continue to address the quality of coded stroke data through improved stroke documentation, the next stage will be to adapt the educational program for clinicians.

Incidence of Stroke in the Aboriginal and Non-Aboriginal Populations of Australia: A Data Linkage Study.

BACKGROUND: Most estimates of stroke incidence among Aboriginal and Torres Strait Islander (hereinafter Aboriginal) Australians are confined to single regions and include small sample sizes. We aimed to measure and compare stroke incidence in Aboriginal and non-Aboriginal residents across central and western Australia. METHODS: Whole-population multijurisdictional person-linked data from hospital and death datasets were used to identify stroke admissions and stroke-related deaths (2001-2015) in Western Australia, South Australia, and the Northern Territory. Fatal (including out-of-hospital deaths) and nonfatal incident (first-ever) strokes in patients aged 20-84 years were identified during the 4-year study period (2012-2015), using a 10-year lookback period to exclude people with prior stroke. Incidence rates per 100 000 population/year were estimated for Aboriginal and non-Aboriginal populations, age-standardized to the World Health Organization World Standard population. RESULTS: In a population of 3 223 711 people (3.7% Aboriginal), 11 740 incident (first-ever) strokes (20.6% regional/remote location of residence; 15.6% fatal) were identified from 2012 to 2015, 675 (5.7%) in Aboriginal people (73.6% regional/remote; 17.0% fatal). Median age of Aboriginal cases (54.5 years; 50.1% female) was 16 years younger than non-Aboriginal cases (70.3 years; 44.1% female; P<0.001), with significantly greater prevalence of comorbidities. Age-standardized stroke incidence in Aboriginal people (192/100 000 [95% CI, 177-208]) was 2.9-fold greater than in non-Aboriginal people (66/100 000 [95% CI, 65-68]) aged 20-84 years; fatal incidence was 4.2-fold greater (38/100 000 [95% CI, 31-46] versus 9/100 000 [95% CI, 9-10]). Disparities were particularly apparent at younger ages (20-54 years), where age-standardized stroke incidence was 4.3-fold greater in Aboriginal people (90/100 000 [95% CI, 81-100]) than non-Aboriginal people (21/100 000 [95% CI, 20-22]). CONCLUSIONS: Stroke occurred more commonly, and at younger ages, in Aboriginal than non-Aboriginal populations. Greater prevalence of baseline comorbidities was present in the younger Aboriginal population. Improved primary prevention is required. To optimize stroke prevention, interventions should include culturally appropriate community-based health promotion and integrated support for nonmetropolitan health services.

The evidence that rheumatic heart disease control programs in Australia are making an impact.

OBJECTIVE: Rheumatic heart disease (RHD) comprises heart-valve damage caused by acute rheumatic fever (ARF). The Australian Government Rheumatic Fever Strategy funds RHD Control Programs to support detection and management of ARF and RHD. We assessed epidemiological changes during the years of RHD Control Program operation. METHODS: Linked RHD register, hospital and death data from four Australian jurisdictions were used to measure ARF/RHD outcomes between 2010 and 2017, including: 2-year progression to severe RHD/death; ARF recurrence; secondary prophylaxis delivery and earlier disease detection. RESULTS: Delivery of secondary prophylaxis improved from 53% median proportion of days covered (95%CI: 46-61%, 2010) to 70% (95%CI: 71-68%, 2017). Secondary prophylaxis adherence protected against progression to severe RHD/death (hazard ratio 0.2, 95% CI 0.1-0.8). Other measures of program effectiveness (ARF recurrences, progression to severe RHD/death) remained stable. ARF case numbers and concurrent ARF/RHD diagnoses increased. CONCLUSIONS: RHD Control Programs have contributed to major success in the management of ARF/RHD through increased delivery of secondary prevention yet ARF case numbers, not impacted by secondary prophylaxis and sensitive to increased awareness/surveillance, increased. IMPLICATIONS FOR PUBLIC HEALTH: RHD Control Programs have a major role in delivering cost-effective RHD prevention. Sustained investment is needed but with greatly strengthened primordial and primary prevention.

Risk of early recurrence and mortality in high-risk myocardial infarction patients: A population-based linked data study.

Background: Survival during the early period following myocardial infarction (MI) has significantly improved although there are limited data on cardiovascular recurrence during this period. Methods: We identified all emergency hospitalisations for MI from November 1, 2011 to October 31, 2016 in Western Australia from a linked hospitalisation/mortality dataset. Patients were included if they survived >3 days, had no acute kidney injury, and had ≥1 of: ≥65 years, prior MI, diabetes or peripheral arterial disease. Outcomes were major adverse cardiovascular events (MACE, a composite of CVD death, recurrent MI or stroke), cardiovascular disease (CVD) death, all-cause mortality, recurrent MI and stroke. Cumulative risks at 90-days and 1-year were estimated from Kaplan-Meier analyses and predictors of each outcome from multivariable Cox regression models. Results: There were 8024 high-risk MI patients identified (males 61.8%). Median age was 73.7 years (IQR 66.3-82.2). Half of the risk of MACE occurred in the first 90-days post-MI (6.6% vs 12.6% at 1-year) and was underpinned by risk of recurrent MI. Risk was generally higher in women than men (MACE: 6.0% males, 7.7% females, p = 0.0025; CVD mortality: 1.7% males, 3.7% females; all-cause mortality: 2.8% males, 5.6% females, p < 0.0001). Independent predictors of 90-day MACE were increasing age, heart failure history, hypertension and prior stroke. Female sex was not associated with a higher rate of any of the outcomes after multivariable adjustment. Conclusion: Half of cardiovascular events in the year following an MI occur within 90-days, demonstrating that reductions in MI burden could be achieved by further targeted intervention in the early period following an MI.

Rheumatic heart disease mortality in Indigenous and non-Indigenous Australians between 2010 and 2017.

OBJECTIVES: To generate contemporary age-specific mortality rates for Indigenous and non-Indigenous Australians aged <65 years who died from rheumatic heart disease (RHD) between 2013 and 2017, and to ascertain the underlying causes of death (COD) of a prevalent RHD cohort aged <65 years who died during the same period. METHODS: For this retrospective, cross-sectional epidemiological study, Australian RHD deaths for 2013-2017 were investigated by first, mortality rates generated using Australian Bureau of Statistics death registrations where RHD was a coded COD, and second COD analyses of death records for a prevalent RHD cohort identified from RHD register and hospitalisations. All analyses were undertaken by Indigenous status and age group (0-24, 25-44, 45-64 years). RESULTS: Age-specific RHD mortality rates per 100 000 were 0.32, 2.63 and 7.41 among Indigenous 0-24, 25-44 and 45-64 year olds, respectively, and the age-standardised mortality ratio (Indigenous vs non-Indigenous 0-64 year olds) was 14.0. Within the prevalent cohort who died (n=726), RHD was the underlying COD in 15.0% of all deaths, increasing to 24.6% when RHD was included as associated COD. However, other cardiovascular and non-cardiovascular conditions were the underlying COD in 34% and 43% respectively. CONCLUSION: Premature mortality in people with RHD aged <65 years has approximately halved in Australia since 1997-2005, most notably among younger Indigenous people. Mortality rates based solely on underlying COD potentially underestimates true RHD mortality burden. Further strategies are required to reduce the high Indigenous to non-Indigenous mortality rate disparity, in addition to optimising major comorbidities that contribute to non-RHD mortality.

Large Burden of Stroke Incidence in People with Cardiac Disease: A Linked Data Cohort Study.

Purpose: People with cardiac disease have 2-4 times greater risk of stroke than the general population. We measured stroke incidence in people with coronary heart disease (CHD), atrial fibrillation (AF) or valvular heart disease (VHD). Methods: We used a person-linked hospitalization/mortality dataset to identify all people hospitalized with CHD, AF or VHD (1985-2017), and stratified them as pre-existing (hospitalized 1985-2012 and alive at October 31, 2012) or new (first-ever cardiac hospitalization in the five-year study period, 2012-2017). We identified first-ever strokes occurring from 2012 to 2017 in patients aged 20-94 years and calculated age-specific and age-standardized rates (ASR) for each cardiac cohort. Results: Of the 175,560 people in the cohort, most had CHD (69.9%); 16.3% had multiple cardiac conditions. From 2012-17, 5871 first-ever strokes occurred. ASRs were greater in females than males in single and multiple condition cardiac groups, largely driven by rates in females aged ≥75 years, with stroke incidence in this age group being at least 20% greater in females than males in each cardiac subgroup. In females aged 20-54 years, stroke incidence was 4.9-fold greater in those with multiple versus single cardiac conditions. This differential declined with increasing age. Non-fatal stroke incidence was greater than fatal stroke in all age groups except in the 85-94 age group. Incidence rate ratios were up to 2-fold larger in new versus pre-existing cardiac disease. Conclusion: Stroke incidence in people with cardiac disease is substantial, with older females, and younger patients with multiple cardiac conditions, at elevated risk. These patients should be specifically targeted for evidence-based management to minimize the burden of stroke.

Corrigendum to: Evolution of non-fatal burden estimates for cardiovascular disease in Australia: a comparison of national and state-wide methodology of burden of disease.

Objective Burden of disease studies measure the impact of disease at the population level;however, methods and data sources for estimates of prevalence vary. Using a selection of cardiovascular diseases, we aimed to describe the implications of using different disease models and linked administrative data on prevalence estimation within three Australian burden of disease studies. Methods Three different methods (A = 2011 Australian Burden of Disease Study; B = 2015 Australian Burden of Disease Study; C = 2015 Western Australian Burden of Disease Study), which used linked data, were used to compare prevalence estimates of stroke, aortic aneurysm, rheumatic valvular heart disease (VHD) and non-rheumatic VHD. We applied these methods to 2015 Western Australian data, and calculated crude overall and age-specific prevalence for each condition. Results Overall, Method C produced estimates of cardiovascular prevalence that were lower than the other methods, excluding non-rheumatic VHD. Prevalence of acute and chronic stroke was up to one-third higher in Method A and B compared to Method C. Aortic aneurysms had the largest change in prevalence, with Method A producing an eight-fold higher estimate compared to Method C, but Method B was 10-20% lower. Estimates of VHD varied dramatically, with an up to six-fold change in prevalence in Method C due to substantial changes to disease models and the use of linked data. Conclusions Prevalence estimates require the best available data sources, updated disease models and constant review to inform government policy and health reform. Availability of nation-wide linked data will markedly improve future burden estimates.

Evolution of non-fatal burden estimates for cardiovascular disease in Australia: a comparison of national and state-wide methodology of burden of disease.

Objective Burden of disease studies measure the impact of disease at the population level;however, methods and data sources for estimates of prevalence vary. Using a selection of cardiovascular diseases, we aimed to describe the implications of using different disease models and linked administrative data on prevalence estimation within three Australian burden of disease studies. Methods Three different methods (A = 2011 Australian Burden of Disease Study; B = 2015 Australian Burden of Disease Study; C = 2015 Western Australian Burden of Disease Study), which used linked data, were used to compare prevalence estimates of stroke, aortic aneurysm, rheumatic valvular heart disease (VHD) and non-rheumatic VHD. We applied these methods to 2015 Western Australian data, and calculated crude overall and age-specific prevalence for each condition. Results Overall, Method C produced estimates of cardiovascular prevalence that were lower than the other methods, excluding non-rheumatic VHD. Prevalence of acute and chronic stroke was up to one-third higher in Method A and B compared to Method C. Aortic aneurysms had the largest change in prevalence, with Method A producing an eight-fold higher estimate compared to Method C, but Method B was 10-20% lower. Estimates of VHD varied dramatically, with an up to six-fold change in prevalence in Method C due to substantial changes to disease models and the use of linked data. Conclusions Prevalence estimates require the best available data sources, updated disease models and constant review to inform government policy and health reform. Availability of nation-wide linked data will markedly improve future burden estimates.

The Allure of Big Data to Improve Stroke Outcomes: Review of Current Literature.

PURPOSE OF REVIEW: To critically appraise literature on recent advances and methods using "big data" to evaluate stroke outcomes and associated factors. RECENT FINDINGS: Recent big data studies provided new evidence on the incidence of stroke outcomes, and important emerging predictors of these outcomes. Main highlights included the identification of COVID-19 infection and exposure to a low-dose particulate matter as emerging predictors of mortality post-stroke. Demographic (age, sex) and geographical (rural vs. urban) disparities in outcomes were also identified. There was a surge in methodological (e.g., machine learning and validation) studies aimed at maximizing the efficiency of big data for improving the prediction of stroke outcomes. However, considerable delays remain between data generation and publication. Big data are driving rapid innovations in research of stroke outcomes, generating novel evidence for bridging practice gaps. Opportunity exists to harness big data to drive real-time improvements in stroke outcomes.

Relative contribution of trends in myocardial infarction event rates and case fatality to declines in mortality: an international comparative study of 1·95 million events in 80·4 million people in four countries.

BACKGROUND: Myocardial infarction mortality has declined since the 1970s, but contemporary drivers of this trend remain unexplained. The aim of this study was to compare the contribution of trends in event rates and case fatality to declines in myocardial infarction mortality in four high-income jurisdictions from 2002-15. METHODS: Linked hospitalisation and mortality data were obtained from New South Wales (NSW), Australia; Ontario, Canada; New Zealand; and England, UK. People aged between 30 years and 105 years were included in the study. Age-adjusted trends in myocardial infarction event rates and case fatality were estimated from Poisson and binomial regression models, and their relative contribution to trends in myocardial infarction mortality calculated. FINDINGS: 1 947 895 myocardial infarction events from a population of 80·4 million people were identified in people aged 30 years or older. There were significant declines in myocardial infarction mortality, event rates, and case fatality in all jurisdictions. Age-standardised myocardial infarction event rates were highest in New Zealand (men 893/100 000 person-years in 2002, 536/100 000 person-years in 2015; women 482/100 000 person-years in 2002, 271/100 000 person-years in 2015) and lowest in England (men 513/100 000 person-years in 2002, 382/100 000 person-years in 2015; women 238/100 000 person-years in 2002, 173/100 000 person-years in 2015). Annual age-adjusted reductions in event rates ranged from -2·6% (95% CI -3·0 to -2·3) in men in England to -4·3% (-4·4 to -4·1) in women in Ontario. Age-standardised case fatality was highest in England in 2002 (48%), but declined at a greater rate than in the other jurisdictions (men -4·1%/year, 95% CI -4·2 to -4·0%; women -4·4%/year, -4·5 to -4·3%). Declines in myocardial infarction mortality rates ranged from -6·1%/year to -7·6%/year. Event rate declines were the greater contributor to myocardial infarction mortality reductions in Ontario (69·4% for men and women), New Zealand (men 68·4%; women 67·5%), and NSW women (60·1%), whereas reductions in case fatality were the greater contributor in England (60% in men and women) and for NSW men (54%). There were greater contributions from case fatality than event rate reductions in people younger than 55 years in all jurisdictions, with contributions to mortality declines varying by country in those aged 55-74 years. Event rate declines had a greater impact than changes in case fatality in those aged 75 years and older. INTERPRETATION: While the mortality burden of myocardial infarction has continued to fall across these four populations, the relative contribution of trends in myocardial infarction event rates and case fatality to declining mortality varied between jurisdictions, including by age and sex. Understanding the causes of this variation will enable optimisation of prevention and treatment efforts. FUNDING: National Health and Medical Research Council, Australia; Australian Research Council; Health Research Council of New Zealand; Canadian Institutes of Health Research, Canada; National Institute for Health Research, UK.

Validation of ICD-10-AM Coding for Myocardial Infarction Subtype in Hospitalisation Data.

BACKGROUND: International Classification of Disease (ICD) codes are central for identifying myocardial infarction (MI) in administrative hospitalisation data, however validation of MI subtype codes is limited. We measured the sensitivity and specificity of ICD-10-AM (Australian Modification) codes for ST-elevation MI (STEMI) and non-STEMI (NSTEMI). METHODS: A sample of MI admissions was obtained from a dataset containing all MI hospitalisations in Western Australia (WA) for 2003, 2008 and 2013. Clinical data were collected from hospital medical records (n=799 patients). Cases were classified by ICD-10-AM codes for STEMI, NSTEMI and unspecified MI, and compared to clinical classification from review of available electrocardiographs (ECGs) and cardiac biomarkers (n=660). Sensitivity and specificity for ICD-10-AM coding versus clinical classification was measured, stratified by calendar year of discharge. RESULTS: The majority of classifiable cases had MI recorded in the principal diagnosis field (STEMI n=293, 84.2%; NSTEMI n=202, 74.3%; unspecified MI n=20, 50.0%). Overall sensitivity of the ICD-10-AM STEMI code was 86.3% (95% CI 81.7-90.0%) and was higher when restricted to MI as a principal versus secondary diagnosis (88.8% vs 66.7%). Comparable values for NSTEMI were 66.7% (95% CI 61.5-71.6%), and 68.8% vs 61.4% respectively. Between 2003 and 2013, sensitivity for both MI subtypes increased: 80.2-89.5% for STEMI, and 51.2-73.8% for NSTEMI. Specificity was high for NSTEMI throughout (88.2% 95% CI 84.1-91.6%), although improving over time for STEMI (68.1-76.4%). CONCLUSIONS: The sensitivity and specificity of ICD-10-AM codes for MI subtypes in hospitalisation data are generally high, particularly for principal diagnosis cases. However, the temporal improvement in sensitivity in coding of MI subtypes, particularly NSTEMI, may necessitate modification to trend studies using administrative hospitalisation data.