Search

Chest pain is a common cause of presentation to the emergency department (ED), and its outcomes are affected by various diagnostic tests and timely management. Our aim was to identify determinants of invasive coronary angiography (ICA) in a chest pain cohort following ED presentation, and to compare outcomes by time to ICA. We identified all adults aged ≥20 years presenting with chest pain to public teaching hospital EDs in Perth, Western Australia, from 1 January 2016 to 31 March 2017. Data were obtained from linked administrative ED, hospitalisation, pathology, and death records. Multivariable logistic regression was used to identify determinants of ICA within 90 days of ED presentation. Restricted cubic splines fitted in multivariable Cox regression models showed the relationship between time to ICA and outcomes of death and major cardiovascular events. The cohort comprised 16,974 people, with 8,609 (51%) male patients and a mean age of 56 years; 986 (5.8%) patients had ICA within 1 day of presentation, 394 (2.3%) within 2–3 days, 543 (3.2%) within 4–90 days, and 15,051 (88.7%) had no ICA or had ICA after 90 days. Age, sex, residential area, triage code, troponin classification, ED diagnosis, and medical history were all significantly associated with 90-day ICA. The adjusted odds ratio of women receiving ICA was 0.53 (95% confidence interval 0.47–0.61) in comparison with men. Restricted cubic splines showed a biphasic relationship between time to ICA and death. The determinants of ICA reflect clinical practice guidelines, although ICA remains less likely in women than in men. Early ICA is associated with lower risk of death but may not affect myocardial infarction or composite outcomes after adjusting for cofactors. [ABSTRACT FROM AUTHOR]

While there is clear evidence that high levels of pollution are associated with increased all-cause mortality and cardiovascular mortality and morbidity, the biological mechanisms that would explain this association are less understood. We examined the association between long-term exposure to air pollutants and risk factors associated with cardiovascular disease. Air pollutant concentrations were estimated at place of residence for cohort members in the Western Australian Centre for Health and Ageing Health in Men Study. Blood samples and blood pressure measures were taken for a cohort of 4249 men aged 70 years and above between 2001 and 2004. We examined the association between 1-year average pollutant concentrations with blood pressure, cholesterol, triglycerides, C-reactive protein, and total homocysteine. Linear regression analyses were carried out, with adjustment for confounding, as well as an assessment of potential effect modification. The four pollutants examined were fine particulate matter, black carbon (BC), nitrogen dioxide, and nitrogen oxides. We found that a 2.25 μg/m3 higher exposure to fine particulate matter was associated with a 1.1 percent lower high-density cholesterol (95% confidence interval: -2.4 to 0.1) and 4.0 percent higher serum triglycerides (95% confidence interval: 1.5 to 6.6). Effect modification of these associations by diabetes history was apparent. We found no evidence of an association between any of the remaining risk factors or biomarkers with measures of outdoor air pollution. These findings indicate that long-term PM2.5 exposure is associated with elevated serum triglycerides and decreased HDL cholesterol. This requires further investigation to determine the reasons for this association. [ABSTRACT FROM AUTHOR]

Background: In disease mapping, fine-resolution spatial health data are routinely aggregated for various reasons, for example to protect privacy. Usually, such aggregation occurs only once, resulting in 'single-aggregation disease maps' whose representation of the underlying data depends on the chosen set of aggregation units. This dependence is described by the modifiable areal unit problem (MAUP). Despite an extensive literature, in practice, the MAUP is rarely acknowledged, including in disease mapping. Further, despite single-aggregation disease maps being widely relied upon to guide distribution of healthcare resources, potential inefficiencies arising due to the impact of the MAUP on such maps have not previously been investigated. Results: We introduce the overlay aggregation method (OAM) for disease mapping. This method avoids dependence on any single set of aggregate-level mapping units through incorporating information from many different sets. We characterise OAM as a novel smoothing technique and show how its use results in potentially dramatic improvements in resource allocation efficiency over single-aggregation maps. We demonstrate these findings in a simulation context and through applying OAM to a real-world dataset: ischaemic stroke hospital admissions in Perth, Western Australia, in 2016. Conclusions: The ongoing, widespread lack of acknowledgement of the MAUP in disease mapping suggests that unawareness of its impact is extensive or that impact is underestimated. Routine implementation of OAM can help avoid resource allocation inefficiencies associated with this phenomenon. Our findings have immediate worldwide implications wherever single-aggregation disease maps are used to guide health policy planning and service delivery. [ABSTRACT FROM AUTHOR]