Life changes and mental health among Chinese children and adolescents during the pandemic: a combination of cross-sectional, longitudinal and clustering studies (preprint)

The measures to prevent COVID-19 pandemic had caused significant life changes, which could be distressing for mental health among children and adolescents. We aimed to evaluate the short- and long-term effects of life changes on children’s mental health in a large Chinese cohort. Survey-based life changes during COVID-19 lockdown were measured among 7,829 Chinese students at Grade 1–9, including social contacts, lifestyles and family financial status. Clustering analysis was applied to identify potential patterns of these changes. Depressive and anxiety symptoms were measured using the Center for Epidemiologic Studies Depression Scale and Screen for Child Anxiety Related Emotional Disorders. Logistic regression models were used to investigate the associations between these changes, their patterns and the presence of depression/anxiety symptoms using both cross-sectional and longitudinal designs. We found that the prevalence of depression and anxiety symptoms decreased during pandemic (34.6–32.6%). However, during and shortly after lockdown, students who reported negative impacts on their study, social and outside activities and diet, and decreased electronic time and sugar-sweetened consumption, as well as family income decline and unemployment had increased risks of depressive/anxiety symptoms, and students with changed sleep time had increased depressive symptoms. These associations attenuated or disappeared one year later. Similar patterns were observed in clustering analysis, while only the group with severe impact on family financial status showed a sustained increase in depression symptoms. In summary, restrictive measures that changed children and adolescents’ daily life during COVID-19 lockdown showed negative effects on their mental health, with some commonalities and distinctions patterns in the manifestation of depression and anxiety symptoms.

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence (preprint)

Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection of large-scale representative medical data, posing a considerable challenge for training a well-generalised model in clinical practices. To address this, we launch the Unified CT-COVID AI Diagnostic Initiative (UCADI), where the AI model can be distributedly trained and independently executed at each host institution under a federated learning framework (FL) without data sharing. Here we show that our FL model outperformed all the local models by a large yield (test sensitivity /specificity in China: 0.973/0.951, in the UK: 0.730/0.942), achieving comparable performance with a panel of professional radiologists. We further evaluated the model on the hold-out (collected from another two hospitals leaving out the FL) and heterogeneous (acquired with contrast materials) data, provided visual explanations for decisions made by the model, and analysed the trade-offs between the model performance and the communication costs in the federated training process. Our study is based on 9,573 chest computed tomography scans (CTs) from 3,336 patients collected from 23 hospitals located in China and the UK. Collectively, our work advanced the prospects of utilising federated learning for privacy-preserving AI in digital health.

Influence of the First-wave COVID-19 Pandemic on Emergency Acute Coronary Syndrome: a Multicenter Retrospective Study From a Non-epicenter Region (preprint)

Background: The COVID-19 pandemic presented severe challenges to emergency practice of acute coronary syndrome (ACS). However, poor evidence was shown on ACS in a non-hot-spot region. We sought to clarify the influence of the first-wave COVID-19 pandemic on emergency ACS from a non-epicenter region. Methods: : This retrospective multicenter study was conducted in emergency ACS patients during the pandemic (from 2020-01-23 to 2020-03-29) and the ones during the same period in 2019. Clinical characteristics, timeline parameters and treatment strategies were compared between different groups. Association of the pandemic with non-invasive therapy was further assessed. Results: : Compared with 2019, ACS had a drop in admission (267 cases vs. 475 cases) and invasive therapy (140 cases vs. 318 cases). Also, process delays were detected including the period from symptom onset to first medical contact (S-to-FMC, 5h vs. 2.5h), the period from FMC to electrocardiogram (ECG) completed (8min vs. 4min) and the period from FMC to dual antiplatelet therapy (FMC-to-DAPT, 25min vs. 19min). Primary percutaneous coronary intervention (PPCI) decreased by 54.9% in STEMI and early invasive therapy decreased by 59.2% in NSTE-ACS. The proportion of invasive therapy in NSTE-ACS decreased more than in STEMI (16.9% vs. 10.1%) with longer process delay. The pandemic was associated with increased non-PPCI in STEMI (OR=1.707, 95%CI 1.082-2.692, P=0.021) and elevated medication in NSTE-ACS (OR=2.029, 95%CI 1.268-3.247, P=0.003), respectively. Conclusion: Even in a non-epicenter region, the first-wave COVID-19 pandemic caused a significant reduction of invasive therapy and evident process delays in emergency ACS.

Genetic predisposition to psychiatric disorders and risk of COVID-19 (preprint)

Background Pre-pandemic psychiatric disorders have been associated with an increased risk of COVID-19. However, the underlying mechanisms remain unknown, e.g. to what extent genetic predisposition to psychiatric disorders contributes to the observed association. Methods The analytic sample consisted of white British participants of UK Biobank registered in England, with available genetic data, and alive on Jan 31, 2020 (i.e., the start of the COVID-19 outbreak in the UK) (n=346,554). We assessed individuals' genetic predisposition to different psychiatric disorders, including substance misuse, depression, anxiety, and psychotic disorder, using polygenic risk score (PRS). Diagnoses of psychiatric disorders were identified through the UK Biobank hospital inpatient data. We performed a GWAS analysis for each psychiatric disorder in a randomly selected half of the study population who were free of COVID-19 (i.e., the base dataset). For the other half (i.e., the target dataset), PRS was calculated for each psychiatric disorder using the discovered genetic variants from the base dataset. We then examined the association between PRS of each psychiatric disorder and risk of COVID-19, or severe COVID-19 (i.e., hospitalization and death), using logistic regression models. The ascertainment of COVID-19 was through the Public Health England dataset, the UK Biobank hospital inpatient data and death registers, updated until July 26, 2020. For validation, we repeated the PRS analyses based on publicly available GWAS summary statistics. Results 155,988 participants (including 1,451 COVID-19 cases), with a mean age of 68.50 years at COVID-19 outbreak, were included for PRS analysis. Higher genetic liability forwards psychiatric disorders was associated with increased risk of both any COVID-19 and severe COVID-19, especially genetic risk for substance misuse and depression. The adjusted odds ratios (ORs) for any COVID-19 were 1.15 (95% confidence interval [CI] 1.02-1.31) and 1.26 (1.11-1.42) among individuals with a high genetic risk (above the upper tertile of PRS) for substance misuse and depression, respectively, compared with individuals with a low genetic risk (below the lower tertile). Largely similar ORs were noted for severe COVID-19 and similar albeit slightly lower estimates using PRSs generated from GWAS summary statistics from independent samples. Conclusion In the UK Biobank, genetic predisposition to psychiatric disorders was associated with an increased risk of COVID-19, including severe course of the disease. These findings suggest the potential role of genetic factors in the observed phenotypic association between psychiatric disorders and COVID-19, underscoring the need of increased medical surveillance of for this vulnerable population during the pandemic.

Pre-pandemic psychiatric disorders and risk of COVID-19: a cohort analysis in the UK Biobank (preprint)

ObjectiveTo determine the association between pre-pandemic psychiatric disorders and the risk of COVID-19. DesignCommunity-based prospective cohort study. SettingUK Biobank population. Participants421,048 participants who were recruited in England and alive by January 31st 2020, i.e., the start of COVID-19 outbreak in the UK. 50,815 individuals with psychiatric disorders recorded in the UK Biobank inpatient hospital data before the outbreak were included in the exposed group, while 370,233 participants without such conditions were in the unexposed group. MeasurementsWe obtained information on positive results of COVID-19 test as registered in the Public Health England, COVID-19 related hospitalizations in the UK Biobank inpatient hospital data, and COIVD-19 related deaths from the death registers. We also identified individuals who was hospitalized for infections other than COVID-19 during the follow-up. Logistic regression models were used to estimate odds ratios (ORs) with 95% confidence intervals (CIs), controlling for multiple confounders. ResultsThe mean age at outbreak was 67.8 years and around 43% of the study participants were male. We observed an elevated risk of COVID-19 among individuals with pre-pandemic psychiatric disorder, compared with those without such diagnoses. The fully adjusted ORs were 1.44 (95%CI 1.27 to 1.64), 1.67 (1.42 to 1.98), and 2.03 (1.56 to 2.63) for any COVID-19, inpatient COVID-19, COVID-19 related death, respectively. The excess risk was observed across all levels of somatic comorbidities and subtypes of pre-pandemic psychiatric disorders, while further increased with greater number of pre-pandemic psychiatric disorders. We also observed an association between pre-pandemic psychiatric disorders and increased risk of hospitalization for other infections (1.85 [1.65 to 2.07]). ConclusionsPre-pandemic psychiatric disorders are associated with increased risk of COVID-19, especially severe and fatal COVID-19. The similar association observed for hospitalization for other infections suggests a shared pathway between psychiatric disorders and different infections, including altered immune responses. Summary boxO_ST_ABSWhat is already known on this topic?C_ST_ABSPsychiatric morbidities have been associated with risks of severe infections through compromised immunity and/or health-behaviors. While recent studies showed that unhealthy lifestyle and psychosocial factors (including self-reported psychological distress) increased the risk of COVID-19 hospitalization, data on the role of clinically confirmed psychiatric disorders in COVID-19 susceptibility are to date absent. What this study adds?Using the large community-based data in UK Biobank, our analysis is the first to demonstrate an increase in the risk of COVID-19, especially severe and fatal COVID-19, among individuals with pre-pandemic psychiatric disorders, independently of many important confounders. A similar association was also observed between pre-pandemic psychiatric disorder and hospitalization due to other infections during the COVID-19 outbreak, suggesting a shared pathway between psychiatric disorders and different infections, including altered immune responses. This finding underscores the need of surveillance and care in vulnerable populations with history of psychiatric disorders during the COVID-19 outbreak.