METHODS: OPTIMISTmain is an international, multicenter, prospective, stepped wedge, cluster randomized, blinded outcome assessed trial aims to determine whether a less-intensity monitoring protocol is at least as effective, safe, and efficient as standard post-IVT monitoring in patients with mild deficits post-AIS. Clinically stable adult patients with mild AIS (defined by a NIHSS <10) who do not require intensive care within 2 h post-IVT are recruited at hospitals in Australia, Chile, China, Malaysia, Mexico, UK, USA, and Vietnam. An average of 15 patients recruited per period (overall 60 patient participants) at 120 sites for a total of 7,200 IVT-treated AIS patients will provide 90% power (one-sided α 0.025). The initiation of eligible hospitals is based on a rolling process whenever ready, stratified by country. Hospitals are randomly allocated using permuted blocks into 3 sequences of implementation, stratified by country and the projected number of patients to be recruited over 12 months. These sequences have four periods that dictate the order in which they are to switch from control (usual care) to intervention (implementation of low intensity monitoring protocol) to different clusters of patients in a stepped manner. Compared to standard monitoring, the low-intensity monitoring protocol includes assessments of neurological and vital signs every 15 min for 2 h, 2 hourly (vs. every 30 min) for 8 h, and 4 hourly (vs. every 1 h) until 24 h, post-IVT. The primary outcome measure is functional recovery, defined by the modified Rankin scale (mRS) at 90 days, a seven-point ordinal scale (0 [no residual symptom] to 6 [death]). Secondary outcomes include death or dependency, length of hospital stay, and health-related quality of life, sICH, and serious adverse events.
CONCLUSION: OPTIMISTmain will provide level I evidence for the safety and effectiveness of a low-intensity post-IVT monitoring protocol in patients with mild severity of AIS.
METHODS: A mixed-methods approach with quantitative and qualitative data was collected between September 2021 and November 2022. Implementer surveys were undertaken at pre- and post-intervention phases to understand the perceptions of low-intensity monitoring strategy. A sample of stroke care nurses were invited to participate in semi-structured interviews at an early stage of post-intervention. Qualitative data were analyzed deductively using the normalization process theory; quantitative data were tabulated.
RESULTS: Interviews with 21 nurses at 8 hospitals have shown low-intensity monitoring was well accepted as there were less time constraints and reduced workload for each patient. There were initial safety concerns over missing deteriorating patients and difficulties in changing established routines. Proper training, education, and communication, and changing the habits and culture of care, were key elements to successfully adopting the new monitoring care into routine practice. Similar results were found in the post-intervention survey (42 nurses from 13 hospitals). Nurses reported time being freed up to provide patient education (56%), daily living care (50%), early mobilization (26%), mood/cognition assessment (44%), and other aspects (i.e., communication, family support).
CONCLUSIONS: Low-intensity monitoring for patients with mild-to-moderate AIS, facilitated by appropriate education and organizational support, appears feasible and acceptable at US hospitals.
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
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: From July 2020 to August 2021, we surveyed 16 461 adults across 29 countries who self-reported changes in 18 lifestyle factors and 13 health outcomes due to the pandemic. Three networks were generated by network analysis for each country: lifestyle, health outcome, and bridge networks. We identified the variables with the highest bridge expected influence as central or bridge variables. Network validation included nonparametric and case-dropping subset bootstrapping, and centrality difference tests confirmed that the central or bridge variables had significantly higher expected influence than other variables within the same network.
RESULTS: Among 87 networks, 75 were validated with correlation-stability coefficients above 0.25. Nine central lifestyle types were identified in 28 countries: cooking at home (in 11 countries), food types in daily meals (in one country), less smoking tobacco (in two countries), less alcohol consumption (in two countries), less duration of sitting (in three countries), less consumption of snacks (in five countries), less sugary drinks (in five countries), having a meal at home (in two countries), taking alternative medicine or natural health products (in one country). Six central health outcomes were noted among 28 countries: social support received (in three countries), physical health (in one country), sleep quality (in four countries), quality of life (in seven countries), less mental burden (in three countries), less emotional distress (in 13 countries). Three bridge lifestyles were identified in 19 countries: food types in daily meals (in one country), cooking at home (in one country), overall amount of exercise (in 17 countries). The centrality difference test showed the central and bridge variables had significantly higher centrality indices than others in their networks (P