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Objective Ischaemic heart disease (IHD) is a major source of disease burden worldwide. Recent trends show incidence is declining but it is unclear whether the trends are similar in urban and rural populations. This study examines the trends of IHD events (i.e. hospitalisations and deaths) in New South Wales, Australia by rurality. Methods This was a retrospective analysis of linked administrative data for hospitalisation and death records across NSW between 2001 and 2015. Participants were NSW residents aged 15–105 years who died or were hospitalised with a principal diagnosis of IHD. The main outcome measures were annual age-standardised mortality and hospitalisations for IHD by calendar year and rurality. Results Between 2001 and 2015, age-standardised annual IHD hospitalisations declined in urban areas from 587 to 260 and in rural areas from 766 to 395 per 100,000 people. The annual decline in hospitalisations was greater in urban than rural areas, with Annual Percentage Change (APC) of −5.6% (95% CI, −6.1%, −5.0%) and −4.5% (95% CI, −5.0%, −4.0%), respectively (p=0.012). Ischaemic heart disease mortality declined at a similar rate in urban and rural regions (APC −7.6% and −6.7% per annum, p=0.28). Absolute inequalities in IHD deaths persisted until 2015 when there were 49 (urban) and 70 (rural) IHD deaths per 100,000 people. Conclusions Ischaemic heart disease hospitalisations and mortality have declined considerably between 2001 and 2015 in both rural and urban areas, yet inequalities persist, suggesting more intensive preventive efforts are required to further reduce the burden of IHD in rural populations.

Background For researchers working in gerontology or the demography of ageing, knowledge of and access to population-based data, which includes mature age respondents, is critical. The collection of metadata (information describing data) supports researchers in their search for relevant data. Aims This proof-of-concept project seeks to develop a metadata database including metadata on Australian sample surveys relevant to ageing over the period 2010–2018. Data and methods We used a five-stage approach to create the Centre for Excellence in Population Ageing Research (CEPAR) metadata database on ageing: 1) identification of in-scope survey datasets; 2) indexing the in-scope surveys; 3) scraping metadata from publicly available sources; 4) appending metadata to a master database; and 5) creation of a webtool to enable users to search and export metadata and obtain contact details for the relevant data custodian. Results The CEPAR Metadata Database webtool is available from: https://mspgh.unimelb.edu.au/centres-institutes/centre-for-health-policy/research-group/metadata-database. Conclusions Metadata database collections can assist researchers to identify what data has been collected (for their specific research interest in ageing), how it was collected and how to gain access to the data.

OBJECTIVE To develop a patient-level simulation model for predicting lifetime health outcomes of patients with type 1 diabetes and as a tool for economic evaluation of type 1 diabetes treatment based on data from a large, longitudinal cohort. RESEARCH DESIGN AND METHODS Data for model development were obtained from the Swedish National Diabetes Register. We derived parametric proportional hazards models predicting absolute risk of diabetes complications and death based on a wide range of clinical variables and history of complications. We used linear regression models to predict risk factor progression. Internal validation was performed, estimates of life expectancies for different age-sex strata were computed, and the impact of key risk factors on life expectancy was assessed. RESULTS The study population consisted of 27,841 patients with type 1 diabetes with a mean duration of follow-up of 7 years. Internal validation showed good agreement between predicted and observed cumulative incidence of death and 10 complications. Simulated life expectancy was approximately 13 years lower than that of the sex- and age-matched general population, and patients with type 1 diabetes could expect to live with one or more complications for approximately 40% of their remaining life. Sensitivity analysis showed the importance of preventing renal dysfunction, hypoglycaemia and hyperglycaemia, and lowering HbA1c in reducing the risk of complications and death. CONCLUSIONS Our model was able to simulate risk factor progression and event histories that closely match the observed outcomes, and project events occurring over patients’ lifetimes. The model can serve as a tool to estimate the impact of changing clinical risk factors on health outcomes to inform economic evaluations of interventions in type 1 diabetes.

Background Persistent opioid use following total joint replacement (TJR) surgery is common; however, the association between pre‐surgical opioid use and surgery type has not been established. The objective of this study was to determine the association between pre‐surgery opioid use and persistent post‐surgery opioid use in TJR patients compared to other elective surgical patients. Methods This is a retrospective cohort study, of univariate and multinomial logistic regression of linked, de‐identified Medicare Benefits Schedule and Pharmaceutical Benefits Schedule data, adjusted for perioperative opioid use, age and sex. Oral morphine equivalents daily doses (OMEDD) were calculated and opioid use was categorized into three mutually exclusive categories for each observation window: low (0–5 OMEDD), moderate (5–10 OMEDD), high (10+ OMEDD). Persistent opioid use was defined as opioid use between 180 and 270 days after the date of surgery. Results Persistent opioid use was associated with older age, female gender and pre‐surgery opioid use. There was no increased risk for persistent opioid use for TJR patients compared to other surgical patients. The intensity of pre‐surgery opioid usage is strongly associated with persistent opioid use in all observed surgical patients. Conclusions Our results suggest that many patients who use opioids prior to surgery will persist in their opioid use following surgery. No association was found between persistent opioid use and TJR surgery, but rather a risk reduction compared to other elective surgeries when associations with opioid use are controlled for. Primary care clinicians and surgeons should monitor the duration and dosage of perioperative opioid use., While pain relief is more commonly associated with total joint replacement patients than other surgical procedures it is not associated with an increased risk when pre‐surgical opioid use is taken into account. Primary care clinicians and surgeons should monitor the duration and dosage of pre‐surgery opioid use regardless of surgery procedure and conservative pre‐operative management of total joint replacement patients with opioids should be discouraged.

Purpose To assess the relative cost-effectiveness of cascade genetic testing in asymptomatic relatives of patients with dilated cardiomyopathy (DCM) compared with periodical clinical surveillance. Methods A decision-analytic model, combining a decision tree and a Markov model, was used to determine the lifetime costs and quality-adjusted life years (QALYs) for the two strategies. Deterministic and probabilistic sensitivity analyses were undertaken to assess the robustness of findings and to explore decision uncertainty. Results The incremental cost per additional QALY of cascade genetic testing prior to periodical clinical surveillance of first-degree relatives compared with periodical clinical surveillance alone was estimated at approximately AUD $6100. At established thresholds of cost-effectiveness, there is a 90% probability that cascade genetic testing is cost-effective. Extensive sensitivity analyses, including the addition of second-degree relatives, did not alter the conclusions drawn from the main analysis. Conclusion Using cascade genetic testing to guide clinical surveillance of asymptomatic relatives of patients with DCM is very likely to be cost-effective. As the DCM pathogenic variant detection rate rises and new evidence for personalized treatment of at-risk individuals becomes available, the cost-effectiveness of cascade testing will further increase.

IntroductionThere are conflicting perspectives as to whether antidepressant medication increases, decreases or has no effect on violence perpetration, impulsivity and aggressive behaviour. This is an important question given the widespread use of antidepressant medication and the significant medical, social, legal and health consequences of violence. We aim to: (1) systematically identify observational studies and randomised controlled trials that quantify the relationship between antidepressant use and interpersonal violence; (2) assess the quality of studies that quantify the relationship between antidepressant use and interpersonal violence and (3) estimate the pooled prevalence and measure of effect for the relationship between antidepressant use and interpersonal violence.Methods and analysisWe will search MEDLINE, EMBASE, CINAHL, PsycINFO, PubMed and the Cochrane Library for relevant peer-reviewed literature. Our primary outcome is the perpetration of violent acts directed at others. Our secondary outcome is physical, interpersonal aggression measured through validated surveys. We will include randomised controlled trials, cohort studies and case–control studies that examine the association between the use of antidepressants and violence perpetration and/or physical aggression. No restrictions will be placed on the population. We will use the Methodological Standard for Epidemiological Research scale to assess the quality of included studies. We will provide an overview of the included studies and assess heterogeneity and publication bias. If there are sufficient studies, we will conduct meta-analyses to examine the possible association between antidepressants and violence, and undertake meta-regression to examine the effect of antidepressant class, length of follow-up, age of participants and population subgroups on the association between antidepressants and violence.Ethics and disseminationNo ethics approval is required. Our findings will be disseminated through a peer-reviewed journal article and conference presentations.PROSPERO registration detailsCRD42020175474.

PurposeThe St Vincent’s Melbourne Arthroplasty Outcomes (SMART) Registry is an institutional clinical registry housed at a tertiary referral hospital in Australia. The SMART Registry is a pragmatic prospective database, which was established to capture a broad range of longitudinal clinical and patient-reported outcome data to facilitate collaborative research that will improve policy and practice relevant to arthroplasty surgery for people with advanced arthritis of the hip or knee. The purpose of this cohort profile paper is to describe the rationale for the SMART Registry’s creation, its methods, baseline data and future plans for the Registry. A full compilation of the data is provided as a reference point for future collaborators.ParticipantsThe SMART Registry cohort comprises over 13 000 consecutive arthroplasty procedures in more than 10 000 patients who underwent their procedure at St Vincent’s Hospital Melbourne, since January 1998. Participant recruitment, data collection and follow-up is ongoing and currently includes up to 20 years follow-up data.Findings to dateSMART Registry data are used for clinical audit and feedback, as well as for a broad range of research including epidemiological studies, predictive statistical modelling and health economic evaluations. At the time of writing, there were 46 publications from SMART Registry data, with contributions from more than 67 coauthors.Future plansWith the recent linking of the SMART Registry with Medicare Benefits Schedule and Pharmaceutical Benefits Scheme data through the Australian Institute of Health and Welfare, research into prescribing patterns and health system utilisation is currently underway. The SMART Registry is also being updated with the Clavien-Dindo classification of surgical complications.

Aims/hypothesis Tables reporting life expectancies by common risk factors are available for individuals with type 2 diabetes; however, there is currently no published equivalent for individuals with type 1 diabetes. We aimed to develop a life expectancy table using a recently published simulation model for individuals with type 1 diabetes. Methods The simulation model was developed using data from a real-world population of patients with type 1 diabetes selected from the Swedish National Diabetes Register. The following six important risk factors were included in the life table: sex; age; current smoking status; BMI; eGFR; and HbA1c. For each of 1024 cells in the life expectancy table, a synthetic cohort containing 1000 individuals was created, with other risk factors assigned values representative of the real-world population. The simulations were executed for all synthetic cohorts and life expectancy for each cell was calculated as mean survival time of the individuals in the respective cohort. Results There was a substantial variation in life expectancy across patients with different risk factor levels. Life expectancy of 20-year-old men varied from 29.3 years to 50.6 years, constituting a gap of 21.3 years between those with worst and best risk factor levels. In 20-year-old women, this gap was 18.9 years (life expectancy range 35.0–53.9 years). The variation in life expectancy was a function of the combination of risk factor values, with HbA1c and eGFR consistently showing a negative and positive correlation, respectively, with life expectancy at any level combination of other risk factors. Individuals with the lowest level (20 kg/m2) and highest level of BMI (35 kg/m2) had a lower life expectancy compared with those with a BMI of 25 kg/m2. Non-smokers and women had a higher life expectancy than smokers and men, respectively, with the difference in life expectancy ranging from 0.4 years to 2.7 years between non-smokers and smokers, and from 1.9 years to 5.9 years between women and men, depending on levels of other risk factors. Conclusions/interpretation The life expectancy table generated in this study shows a substantial variation in life expectancy across individuals with different modifiable risk factors. The table allows for rapid communications of risk in an easily understood format between healthcare professionals, health economists, researchers, policy makers and patients. Particularly, it supports clinicians in their discussion with patients about the benefits of improving risk factors. Graphical abstract

Aims To demonstrate a novel method for presenting and exploring data in systematic reviews of the alcohol literature. Methods Harvest plots are a graphical method for displaying data on the overall pattern of evidence from a systematic review. They can display the direction of effects and risk of bias within studies for multiple outcomes in a single graphical chart. Using data from our previous meta-analysis on the association between personality disorder and alcohol treatment outcome, we extended the application of harvest plots by developing an interactive online harvest plot application. Results Studies included in the review were heterogeneous in design. There were many different primary outcomes, and similar outcomes were often defined differently across studies. The interactive harvest plot allows readers to explore trends in the data across multiple outcomes, including the impact of within-study bias and year of publication. In contrast, meta-analysis on the same data was hampered by a lack of consistency in the way outcomes were measured, and incomplete reporting of effect sizes and their variance. This meant many studies included in the systematic review could not be meta-analysed. Conclusions Interactive harvest plots are a novel graphical method to present data from systematic reviews. They can supplement or even replace meta-analysis when the studies included in a systematic review use heterogeneous designs and measures, as is often the case in the alcohol literature.

Objective This study determined the economic impact of 16 ‘high-priority’ hospital-acquired complications (HACs), as defined by the Australian Commission on Safety and Quality in Health Care, from the perspective of an individual Australian health service. Methods A retrospective cohort study was performed using a deidentified patient dataset containing 93 056 in-patient separations in Northern Health (Victoria, Australia) from 1 July 2016 to 30 June 2017. Two log-linked generalised linear regression models were used to obtain additional costs and additional length of stay (LOS) for 16 different HACs, with the main outcome measures being the additional cost and LOS for all 16 HACs. Results In all, 1700 separations involving HACs (1.83%) were identified. The most common HAC was health care-associated infections. Most HACs were associated with a statistically significant risk of increased cost (15/16 HACs) and LOS (11/16 HACs). HACs involving falls resulting in fracture or other intracranial injury were associated with the highest additional cost (A$17 173). The biggest increase in additional LOS was unplanned admissions to the intensive care unit (5.42 days). Conclusions This study shows the economic impact of HACs from the perspective of an individual health service. The methodology used demonstrates how other health services could determine safety priorities corresponding to their own casemix. What is known about the topic? HACs are a major issue in Australian health care; however, their effect on cost and LOS at the individual health service level is not well quantified. What does this paper add? Additional cost and LOS implications for 16 high-priority HACs have been quantified within an Australian health service. There is substantial variation in terms of the number of HACs and the economic impact of each HAC. What are the implications for practitioners? This study provides a template for other health services to assess the economic impact of HACs corresponding to their own casemix and to inform targeted patient safety programs.

IntroductionMounting evidence now indicates that preoperative opioid use is associated with an array of complications following total joint replacement (TJR). However, evidence of these risks remains fragmented. A comprehensive and well-integrated understanding of this body of evidence is necessary to appropriately inform treatment decisions, the allocation of limited healthcare resources, and the direction of future clinical research. The proposed systematic review and meta-analysis aims to identify and synthesise the available evidence of an association between opioid use prior to TJR and postoperative complications, categorised by complication type.Methods and analysisWe will search MEDLINE, EMBASE, CINAHL, PsycINFO, and Web of Science from inception to April 2020. Observational and experimental studies that compare preoperative opioid users who have undergone elective TJR to opioid naïve TJR patients will be included. The primary outcomes will be postoperative complications, which will be categorised as either mortality, morbidity, or joint-related complications. The secondary outcomes will be persistent postoperative opioid use, readmission, and length of stay. Individual study quality will be assessed using the relevant NIH–NHLBI study quality assessment tools. Findings will be reported in narrative and tabular form, and, where possible, odds ratios (dichotomous outcomes) or standardised mean differences (continuous outcomes) will be reported with 95% confidence intervals. Where appropriate, random effect meta-analyses will be conducted for each outcome, and heterogeneity will be quantified using the I2 statistic and Cochran’s Q test. This study will be reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) and Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guidelines.Ethics and disseminationEthics approval will not be required as no primary or private data are being collected. Findings will be disseminated through peer-reviewed publication and presentation at academic conferences.PROSPERO registration numberCRD42020153047.

Cardiovascular disease (CVD) is the leading cause of death internationally. We aimed to model the impact of CVD preventive double therapy (a statin and anti-hypertensive) by clinician-assessed absolute risk level. An established and validated multi-state life-table model for the national New Zealand (NZ) population was adapted. The new version of the model specifically considered the 60–64-year-old male population which was stratified by risk using a published NZ-specific CVD risk equation. The intervention period of treatment was for five years, but a lifetime horizon was used for measuring benefits and costs (a five-year horizon was also implemented). We found that for this group offering double therapy was highly cost-effective in all absolute risk categories (eg, NZ$1580 per QALY gained in the >20% in 5 years risk stratum; 95%UI: Dominant to NZ$3990). Even in the lowest risk stratum (≤5% risk in 5 years), the cost per QALY was only NZ$25,500 (NZ$28,200 and US$19,100 in 2018). At an individual level, the gain for those who responded to the screening offer and commenced preventive treatment ranged from 0.6 to 4.9 months of quality-adjusted life gained (or less than a month gain with a five-year horizon). Nevertheless, at the individual level, patient considerations are critical as some people may decide that this amount of average health gain does not justify taking daily medication.

BACKGROUND:Cardiovascular disease (CVD) is the leading cause of death for Indigenous Australians. There is widespread belief that current tools have deficiencies for assessing CVD risk in this high-risk population. We sought to develop a 5-year CVD risk score using a wide range of known risk factors to further improve CVD risk prediction in this population. METHODS:We used clinical and demographic information on Indigenous people aged between 30 and 74 years without a history of CVD events who participated in the Well Person's Health Check (WPHC), a community-based survey. Baseline assessments were conducted between 1998 and 2000, and data were linked to administrative hospitalisation and death records for identification of CVD events. We used Cox proportional hazard models to estimate the 5-year CVD risk, and the Harrell's c-statistic and the modified Hosmer-Lemeshow (mH-L) χ2 statistic to assess the model discrimination and calibration, respectively. RESULTS:The study sample consisted of 1,583 individuals (48.1% male; mean age 45.0 year). The risk score consisted of sex, age, systolic blood pressure, diabetes mellitus, waist circumference, triglycerides, and albumin creatinine ratio. The bias-corrected c-statistic was 0.72 and the bias-corrected mH-L χ2 statistic was 12.01 (p-value, 0.212), indicating good discrimination and calibration, respectively. Using our risk score, the CVD risk of the Indigenous Australians could be stratified to a greater degree compared to a recalibrated Framingham risk score. CONCLUSIONS:A seven-factor risk score could satisfactorily stratify 5-year risk of CVD in an Indigenous Australian cohort. These findings inform future research targeting CVD risk in Indigenous Australians.

A recent article in The Lancet establishing the principles of inclusion health, highlighted substantial gaps in our understanding of the drivers of health inequalities in socially excluded groups such as people with a history of incarceration, people who experience homelessness, sex workers, people with mental illness, and people who inject drugs1. Cross-sectoral data linkage of electronic health records with services working with socially excluded groups was one of the key recommendations of this article. The magnitude of health disparities observed in people that experience social exclusion necessitates an international public health response and addressing the determinants of social exclusion has been identified as a key component of closing the gap of Indigenous disadvantage2. This symposium will establish data linkage as a key component of the inclusion health and will complement the efforts of the Pan American Health Oranization's (PAHO) Commission on Equity and Health Inequalities in the Americas. Traditional survey methodology is costly and often results in studies that are highly parochial in nature. Due to difficulties recruiting and retaining marginalized groups, these studies are commonly forced to adopt methodological concessions, often selecting the most convenient participants (i.e., selection bias) or incurring increased rates of loss-to-follow-up (i.e., attrition bias). Conversely, global studies aimed at modelling the burden of disease are often not sufficiently nuanced to answer specific inferential research questions. Data-linkage has the potential to overcome these common biases and limitations. Thus, harmonised international data-linkage studies are an important component of the inclusion health response to identify the determinants of health inequalities in socially excluded groups and inform the global inclusion health agenda. This symposium will bring together facilitators from three countries with extensive experience conducting data linkage studies that generate evidence on health and social inequality in socially excluded groups. Using a current multinational study as an example, barriers to international data-linkage studies, methodological solutions, and distributed approaches to generating international comparative evidence will be presented. Innovative examples of cross-sectoral approaches to linkage with social service, correctional and national survey data will be discussed. The development of a novel framework for identifying social exclusion exposures and determinants of health inequalities typically not captured in administrative health data will also be discussed. The session will conclude with a discussion aimed at forming the foundation of an international data linkage project to address these current gaps identified in the inclusion health series and best practice for translation to policy and practice to address health disparities in socially excluded groups. References Aldridge et al. Morbidity and mortality in homeless individuals, prisoners, sex workers, and individuals with substance use disorders in high-income countries: a systematic review and meta-analysis. The Lancet. 2017;391(10117):241-250. https://doi.org/10.1016/S0140-6736(17)31869-X Greenwood M et al. Challenges in health equity for Indigenous peoples in Canada. The Lancet. 2018;Epub ahead of print. https://doi.org/10.1016/S0140-6736(18)30177-6

Objectives To compare the determinants of initial statin prescribing between New Zealand and Australia. New Zealand has a system-wide absolute risk-based approach to primary care cardiovascular disease (CVD) management, while Australia has multiple guidelines. Method Classification and Regression Tree (CART) analysis of two observational studies of primary care CVD management from New Zealand (PREDICT-CVD) and Australia (AusHeart). Over 80% of eligible New Zealanders have been screened for CVD risk. PREDICT-CVD is used by approximately one-third of New Zealand GPs to perform web-based CVD risk assessment in routine practice, with the sample consisting of 126,519 individuals risk assessed between 1 January 2007 and 30 June 2014. AusHeart is a cluster-stratified survey of primary care CVD management that enrolled 534 GPs from across Australia, who in turn recruited 1381 patients between 1 April and 30 June 2008. Eligibility was restricted to 55–74 year old patients without prior CVD. Results The CART analyses demonstrated that New Zealand GPs prescribe statins primarily on the basis of absolute risk, while their Australian counterparts are influenced by a variety of individual risk factors, including total cholesterol, LDL cholesterol and diabetes. Conclusions Countries seeking to improve their management of CVD should consider adopting a ‘whole of system’ absolute risk-based approach with clear guidelines that are consistent with drug reimbursement rules; and include computerized decision-support tools that aid decision-making and allow monitoring of outcomes and continual improvement of practice.

Background A “Christmas holiday effect” showing elevated cardiovascular mortality over the Christmas holidays (December 25 to January 7) was demonstrated previously in study from the United States. To separate the effect of seasonality from any holiday effect, a matching analysis was conducted for New Zealand, where the Christmas holiday period falls within the summer season. Methods and Results New Zealand mortality data for a 25‐year period (1988–2013) was analyzed based on the same methodology used in the previous study. Locally weighted smoothing was used to calculate an “expected” number of deaths for each day of the year. The expected value was compared with the actual number of deaths. In addition, mean age at death was estimated and used to assess the life‐years lost due to excess mortality. There were 738 409 deaths (197 109 coded as cardiac deaths) during the period. We found evidence of a Christmas holiday effect in our of medical facility's cardiac deaths, with an excess event rate of 4.2% (95% CI 0.7–7.7%) leading to ≈4 additional deaths per annum. The average age of those with fatal cardiac deaths was 76.8 years ( SD 13.5) during the Christmas holiday period, resulting in 148 to 222 years of life lost per annum. Conclusions Cardiac mortality is elevated during the Christmas holiday period relative to surrounding time periods. Our findings are consistent with a previously reported study conducted in the United States , suggesting that cardiac mortality does not take a “summer break.”

Background Vitamin D has immune-modulating effects. We determined whether vitamin D supplementation during pregnancy and infancy prevents aeroallergen sensitization and primary care respiratory illness presentations. Methods A randomized, double-blind, placebo-controlled parallel-group trial. We assigned pregnant women, from 27-week gestation to birth, and then their infants, from birth to 6 months, to placebo or one of two dosages of daily oral vitamin D. Woman/infant pairs were randomized to: placebo/placebo, 1000 IU/400 IU or 2000 IU/800 IU. When the children were 18 months old, we measured serum-specific IgE antibodies and identified acute primary care visits described by the doctor to be due to a cold, otitis media, an upper respiratory infection, croup, asthma, bronchitis, bronchiolitis, a wheezy lower respiratory infection or fever and cough. Results Specific IgE was measured on 185 of 260 (71%) enrolled children. The proportion of children sensitized differed by study group for four mite antigens: Dermatophagoides farinae (Der-f1, Der-f2) and Dermatophagoides pteronyssinus (Der-p1, Der-p2). With results presented for placebo, lower dose, and higher dose vitamin D, respectively (all P < 0.05): Der-f1 (18%, 10%, 2%), Der-f2 (14%, 3%, 2%), Der-p1 (19%, 14%, 3%) and Der-p2 (12%, 2%, 3%). There were study group differences in the proportion of children with primary care visits described by the doctor as being for asthma (11%, 0%, 4%, P = 0.002), but not for the other respiratory diagnoses. Conclusions Vitamin D supplementation during pregnancy and infancy reduces the proportion of children sensitized to mites at age 18 months. Preliminary data indicate a possible effect on primary care visits where asthma is diagnosed.

Based on new systematic reviews of the evidence, the US Preventive Services Task Force has drafted updated guidelines on the use of low-dose aspirin for the primary prevention of both cardiovascular disease (CVD) and cancer. The Task Force generally recommends consideration of aspirin in adults aged 50-69 years with 10-year CVD risk of at least 10%, in who absolute health gain (reduction of CVD and cancer) is estimated to exceed absolute health loss (increase in bleeds). With the ongoing decline in CVD, current risk calculators for New Zealand are probably outdated, so it is difficult to be precise about what proportion of the population is in this risk category (roughly equivalent to 5-year CVD risk ≥5%). Nevertheless, we suspect that most smokers aged 50-69 years, and some non-smokers, would probably meet the new threshold for taking low-dose aspirin. The country therefore needs updated guidelines and risk calculators that are ideally informed by estimates of absolute net health gain (in quality-adjusted life-years (QALYs) per person) and cost-effectiveness. Other improvements to risk calculators include: epidemiological rigour (eg, by addressing competing mortality); providing enhanced graphical display of risk to enhance risk communication; and possibly capturing the issues of medication disutility and comparison with lifestyle changes.

To elucidate specific cytokine and chemokine markers in patients diagnosed with pediatric autoimmune neuropsychiatric disorder associated with streptococcus (PANDAS).Prospective cohort study.Academic university hospital.Tonsil tissue was collected from 24 patients and organized into 3 groups: experimental PANDAS cohort (12 patients), group A beta hemolytic streptococcus control cohort (6 patients), and obstructive sleep apnea control cohort (6 patients). Each tissue sample was extracted with MSD Tris lysis buffer, and protein lysates were analyzed for human chemokines and cytokines by the Human Cytokine 30-Plex Assay on the Mesoscale System.We identified a significant difference in expression regarding the 8 following cytokines when comparing the experimental PANDAS, group A beta hemolytic streptococcus, and obstructive sleep apnea control cohorts: tumor necrosis factor-α and eotaxin-3. In addition, our group also identified a significant reduction in the expression of interleukin (IL)-8, interferon inducible protein-10, IL-17a, interferon-γ, IL-10, and IL-12 across the aforementioned groups.Patients diagnosed with PANDAS appear to maintain significantly different concentrations of cytokines when compared with patients afflicted by chronic group A beta hemolytic streptococcus infections and obstructive sleep apnea. As a result, one could potentially use the described characterization of immunologic markers as a basis for future mechanistic and epidemiological studies.

BACKGROUND:Many national cardiovascular disease (CVD) risk factor management guidelines now recommend that drug treatment decisions should be informed primarily by patients' multi-variable predicted risk of CVD, rather than on the basis of single risk factor thresholds. To investigate the potential impact of treatment guidelines based on CVD risk thresholds at a national level requires individual level data representing the multi-variable CVD risk factor profiles for a country's total adult population. As these data are seldom, if ever, available, we aimed to create a synthetic population, representing the joint CVD risk factor distributions of the adult New Zealand population. METHODS AND RESULTS:A synthetic population of 2,451,278 individuals, representing the actual age, gender, ethnicity and social deprivation composition of people aged 30-84 years who completed the 2013 New Zealand census was generated using Monte Carlo sampling. Each 'synthetic' person was then probabilistically assigned values of the remaining cardiovascular disease (CVD) risk factors required for predicting their CVD risk, based on data from the national census national hospitalisation and drug dispensing databases and a large regional cohort study, using Monte Carlo sampling and multiple imputation. Where possible, the synthetic population CVD risk distributions for each non-demographic risk factor were validated against independent New Zealand data sources. CONCLUSIONS:We were able to develop a synthetic national population with realistic multi-variable CVD risk characteristics. The construction of this population is the first step in the development of a micro-simulation model intended to investigate the likely impact of a range of national CVD risk management strategies that will inform CVD risk management guideline updates in New Zealand and elsewhere.