METHODOLOGY: The Asia Pacific Evaluation of Cardiovascular Therapies (ASPECT) collaboration consists of data from various PCI registries across Australia, Hong Kong, Singapore, Malaysia, Indonesia and Vietnam. Clinical characteristics, lesion characteristics, and outcomes were provided for STEMI patients. Key outcomes included 30-day overall mortality and major adverse cardiovascular events (MACE).
RESULTS: A total of 12,144 STEMI patients (mean(SD) age 59.3(12.3)) were included, of which 3912 (32.2%) had diabetes. Patients with diabetes were likely to have a higher baseline risk profile, poorer clinical presentation, and more complex lesion patterns (all p
METHODS: Seven (7) ASPECT members were approached to provide a harmonised anonymised dataset from their local registry. Patient characteristics were summarised and associations between the characteristics and in-hospital outcomes for STEMI patients were analysed.
RESULTS: Six (6) participating sites (86%) provided governance approvals for the collation of individual anonymised patient data from 2015 to 2017. Five (5) sites (83%) provided >90% of agreed data elements and 68% of the collated elements had <10% missingness. From the registry (n=12,620), 84% were male. The mean age was 59.2±12.3 years. The Malaysian cohort had a high prevalence of previous myocardial infarction (34%), almost twice that of any other sites (p<0.001). Adverse in-hospital outcomes were the lowest in Hong Kong whilst in-hospital mortality varied from 2.7% in Vietnam to 7.9% in Singapore.
CONCLUSIONS: Governance approvals for the collation of individual patient anonymised data was achieved with a high level of data alignment. Secure data transfer process and repository were established. Patient characteristics and presentation varied significantly across the Asia-Pacific region with this likely to be a major predictor of variations in the clinical outcomes observed across the region.
METHODS: We recruited adults in 30 countries covering all World Health Organization (WHO) regions from July 2020 to August 2021. 5 Likert-point scales were used to measure their perceived change in 32 aspects due to COVID-19 (-2 = substantially reduced to 2 = substantially increased) and perceived importance of 13 preparations (1 = not important to 5 = extremely important). Samples were stratified by age and gender in the corresponding countries. Multidimensional preference analysis displays disparities between 30 countries, WHO regions, economic development levels, and COVID-19 severity levels.
RESULTS: 16 512 adults participated, with 10 351 females. Among 32 aspects of impact, the most affected were having a meal at home (mean (m) = 0.84, standard error (SE) = 0.01), cooking at home (m = 0.78, SE = 0.01), social activities (m = -0.68, SE = 0.01), duration of screen time (m = 0.67, SE = 0.01), and duration of sitting (m = 0.59, SE = 0.01). Alcohol (m = -0.36, SE = 0.01) and tobacco (m = -0.38, SE = 0.01) consumption declined moderately. Among 13 preparations, respondents rated medicine delivery (m = 3.50, SE = 0.01), getting prescribed medicine in a hospital visit / follow-up in a community pharmacy (m = 3.37, SE = 0.01), and online shopping (m = 3.33, SE = 0.02) as the most important. The multidimensional preference analysis showed the European Region, Region of the Americas, Western Pacific Region and countries with a high-income level or medium to high COVID-19 severity were more adversely impacted on sitting and screen time duration and social activities, whereas other regions and countries experienced more cooking and eating at home. Countries with a high-income level or medium to high COVID-19 severity reported higher perceived mental burden and emotional distress. Except for low- and lower-middle-income countries, medicine delivery was always prioritised.
CONCLUSIONS: Global increasing sitting and screen time and limiting social activities deserve as much attention as mental health. Besides, the pandemic has ushered in a notable enhancement in lifestyle of home cooking and eating, while simultaneously reducing the consumption of tobacco and alcohol. A health care system and technological infrastructure that facilitate medicine delivery, medicine prescription, and online shopping are priorities for coping with future pandemics.
METHODS: An international cross-sectional study was conducted in 30 countries across six World Health Organization regions from July 2020 to August 2021, with 16 512 adults self-reporting changes in 18 lifestyle factors and 13 interim health outcomes since the pandemic.
RESULTS: Three networks were computed and tested. The central variables decided by the expected influence centrality were consumption of fruits and vegetables (centrality = 0.98) jointly with less sugary drinks (centrality = 0.93) in the lifestyles network; and quality of life (centrality = 1.00) co-dominant (centrality = 1.00) with less emotional distress in the interim health outcomes network. The overall amount of exercise had the highest bridge expected influence centrality in the bridge network (centrality = 0.51). No significant differences were found in the network global strength or the centrality of the aforementioned key variables within each network between males and females or health workers and non-health workers (all P-values >0.05 after Holm-Bonferroni correction).
CONCLUSIONS: Consumption of fruits and vegetables, sugary drinks, quality of life, emotional distress, and the overall amount of exercise are key intervention components for improving overall lifestyle, overall health and overall health via lifestyle in the general population, respectively. Although modifications are needed for all aspects of lifestyle and interim health outcomes, a larger allocation of resources and more intensive interventions were recommended for these key variables to produce the most cost-effective improvements in lifestyles and health, regardless of gender or occupation.
METHODS: We surveyed 16 512 adults from July 2020 to August 2021 in 30 territories. Participants self-reported their medical histories and the perceived impact of COVID-19 on 18 lifestyle factors and 13 health outcomes. For each disease subgroup, we generated lifestyle, health outcome, and bridge networks. Variables with the highest centrality indices in each were identified central or bridge. We validated these networks using nonparametric and case-dropping subset bootstrapping and confirmed central and bridge variables' significantly higher indices through a centrality difference test.
FINDINGS: Among the 48 networks, 44 were validated (all correlation-stability coefficients >0.25). Six central lifestyle factors were identified: less consumption of snacks (for the chronic disease: anxiety), less sugary drinks (cancer, gastric ulcer, hypertension, insomnia, and pre-diabetes), less smoking tobacco (chronic obstructive pulmonary disease), frequency of exercise (depression and fatty liver disease), duration of exercise (irritable bowel syndrome), and overall amount of exercise (autoimmune disease, diabetes, eczema, heart attack, and high cholesterol). Two central health outcomes emerged: less emotional distress (chronic obstructive pulmonary disease, eczema, fatty liver disease, gastric ulcer, heart attack, high cholesterol, hypertension, insomnia, and pre-diabetes) and quality of life (anxiety, autoimmune disease, cancer, depression, diabetes, and irritable bowel syndrome). Four bridge lifestyles were identified: consumption of fruits and vegetables (diabetes, high cholesterol, hypertension, and insomnia), less duration of sitting (eczema, fatty liver disease, and heart attack), frequency of exercise (autoimmune disease, depression, and heart attack), and overall amount of exercise (anxiety, gastric ulcer, and insomnia). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P