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Background Arrhythmia has a high incidence, and is a serious threat to human health. However, due to concealed symptoms and unpredictability of onset, it is difficult for traditional ECG equipment to capture the ECG data at the onset of the arrhythmic events, so it could be misdiagnosed and under-treated. Fortunately, the diagnosis rate of arrhythmia could be greatly enhanced by analyzing the uploaded real-time ECG data of individuals measured at home using the wearable single-lead ECG monitoring system under the guidance of community doctors, but there is a lack of relevant evidence from real-world studies. Objective To assess the diagnostic accuracies of three schemes for screening arrhythmia in the community using a wearable single-lead ECG monitoring system. Methods A real-world, community-based study design was used for comparing three schemes for screening arrhythmia using a wearable single-lead ECG monitoring system: scheme 1 was used for collecting 24-hour ECG data on any three nonconsecutive days in two weeks, scheme 2 was used for collecting 24-hour ECG data on any day and at least three 1-hour ECG data in two weeks, and scheme 3 was adopted for collecting 72-hour ECG data on any three consecutive days and at least one 1-hour ECG data on any one day in two weeks. Subjects were 435 community-living residents, who were recruited from Yinchuan from September 2020 to September 2021. They were divided into male group (177 cases) , female group (258 cases) ; young group (135 cases) , middle-aged group (200 cases) and elderly group (100 cases) by age; primary school group (77 cases) , middle school group (165 cases) and university group (193 cases) by educational level; arrhythmia group (233 cases) and non-arrhythmia group (202 cases) by the history of arrhythmia. Subjects measured the ECG either at the onset time of perceived arrhythmia or not using any one of the three screening schemes chosen voluntarily with the wearable single-lead ECG monitoring system, then uploaded the measurement results to the cloud platform. The number of participants using each of the three screening schemes was counted. The correlation of age, education level or history of arrhythmia with scheme selection was analyzed. And detection rates of the three screening schemes were compared. Results The number of subjects who selected the three screening schemes was 321, 40 and 74, respectively. The average age of the subjects was significantly different (P=0.047) . There was no correlation between gender, education level, medical history and protocol selection (χ2=0.670, P=0.715; χ2=2.994, P=0.559; χ2=2.225, P=0.893) . There was a significant correlation between different age groups and protocol selection (χ2=9.939, P=0.041) . The arrhythmia detection rates of the three screening protocols were 85.67%, 82.50% and 85.14%, respectively, and the difference was not statistically significant (χ2=0.286, P=0.867) . There was no significant difference in the arrhythmia detection rate between the male group and the female group (χ2=0.966, P=0.707; χ2=0.917, P=0.678) . There was no significant difference in the detection rate of arrhythmia among young group, middle-aged group and elderly group (χ2=2.102, P=0.350; χ2=0.871, P=0.706; χ2=1.063, P=0.622) . There was no significant difference in the detection rate of arrhythmia among the three screening schemes in primary school group, middle school group and university group (χ2=2.421, P=0.271; χ2=1.115, P=0.633; χ2=2.181, P=0.353) . There was no significant difference in the arrhythmia detection rate between the three screening protocols in the history group and the no history group (χ2=1.442, P=0.507; χ2=0.548, P=0.818) . The frequency of 1-hour ECG data collection in protocol 2 was positively correlated with arrhythmia detection rate (rs=0.912, P=0.011) . The frequency of 1-hour ECG data collection in protocol 3 was positively correlated with arrhythmia detection rate (rs=0.852, P=0.026) . In protocol 2, the detection rate of arrhythmia in 24-hour ECG data was 72.5%, and that in 1-hour ECG data was 77.5%. There was a strong consistency between the two kinds of long-term ECG data (Kappa=0.601, P=0.001) . In protocol 3, the arrhythmia detection rate of 72-hour ECG data was 82.4%, and the arrhythmia detection rate of 1-hour ECG data was 63.5%. There was a medium consistency between the two kinds of long-term ECG data (Kappa=0.410, P

Individuals with autism spectrum disorder (ASD) show an enhanced response to stressors, and gender plays an important role in stress response. Thus, autistic traits (ATs) in the general population and gender may regulate the emotion changes before and during the COVID-19 pandemic. In the present study, participants were divided into higher and lower ATs groups. The generalized linear models were used to estimate the effects of the independent variables (e.g. the COVID-19 pandemic status (before, during), gender (male, female), and AT groups (higher ATs, lower ATs) and their interactions on emotions measured by the Positive and Negative Affect scales. The results showed that the COVID-19 pandemic reduced positive emotions and increased fear and anger. Furthermore, compared with the status before the COVID-19 pandemic, individuals with higher ATs and females experienced stronger anger and fear than individuals with lower ATs and males during the pandemic. The present study revealed the emotional impacts of the COVID-19 pandemic and greater emotional susceptibility to the pandemic among individuals with higher ATs and females. Our findings provide prospective evidence for understanding the ASD/ATs-related enhanced response to pathogen threat-related stressors and have implications for COVID-19 crisis interventions., Author(s): Xudong Zhao [sup.1] [sup.2] , Binglei Zhao [sup.3] , Wenrui Li [sup.1] , Yang Cai [sup.1] , Wendian Shi [sup.1] , Chunbo Li [sup.2] [sup.3] Author Affiliations: (1) grid.412531.0, [...]