Baseline symptoms of depression and anxiety negatively impact the effectiveness of CBTi in treating acute insomnia among young adults.

Background: Cognitive-behavioural therapy for insomnia (CBTi) is the first-line treatment for those with this sleep disorder. However, depressive and anxiety symptoms often co-occur with acute insomnia, which may affect the effectiveness of CBTi treatment. Aims: This study aimed to determine the impact of depressive and anxiety symptoms on the efficacy of CBTi in treating acute insomnia. Methods: A single-arm clinical trial was conducted among individuals who have acute insomnia. Participants underwent self-guided CBTi for 1-week. Their insomnia, depressive symptoms and anxiety symptoms were evaluated using the Insomnia Severity Index and the Hospital Anxiety and Depression Scale at baseline, post-treatment and 3-month follow-up. Repeated measures analysis of variance was used to assess the effectiveness of CBTi in treating insomnia, depressive symptoms and anxiety symptoms. A multivariate Cox regression model was used to determine the impact of depressive and anxiety symptoms on insomnia. Results: The study found significant reductions in insomnia, depressive symptoms and anxiety symptoms at both post-treatment and 3-month follow-up (F=17.45, p<0.001; F=36.37, p=0.001; and F=81.51, p<0.001, respectively). The duration of CBTi treatment had a positive impact on insomnia recovery (hazard ratio (HR)=0.94, p=0.018). However, baseline depressive symptoms (HR=1.83, p=0.004) and baseline anxiety symptoms (HR=1.99, p=0.001) had significant negative effects on insomnia recovery. Conclusions: The study showed that a 1-week self-guided CBTi treatment is effective in treating acute insomnia and comorbid depressive and anxiety symptoms. However, baseline depressive and anxiety symptoms negatively impact treatment effectiveness. Therefore, clinicians should assess for depressive and anxiety symptoms before treating acute insomnia with monotherapy CBTi.

Ambient air pollutants concentration prediction during the COVID-19: A method based on transfer learning.

Research on the correlation analysis between COVID-19 and air pollution has attracted increasing attention since the COVID-19 pandemic. While many relevant issues have been widely studied, research into ambient air pollutant concentration prediction (APCP) during COVID-19 is still in its infancy. Most of the existing study on APCP is based on machine learning methods, which are not suitable for APCP during COVID-19 due to the different distribution of historical observations before and after the pandemic. Therefore, to fulfill the predictive task based on the historical observations with a different distribution, this paper proposes an improved transfer learning model combined with machine learning for APCP during COVID-19. Specifically, this paper employs the Gaussian mixture method and an optimization algorithm to obtain a new source domain similar to the target domain for further transfer learning. Then, several commonly used machine learning models are trained in the new source domain, and these well-trained models are transferred to the target domain to obtain APCP results. Based on the real-world dataset, the experimental results suggest that, by using the improved machine learning methods based on transfer learning, our method can achieve the prediction with significantly high accuracy. In terms of managerial insights, the effects of influential factors are analyzed according to the relationship between these influential factors and prediction results, while their importance is ranked through their average marginal contribution and partial dependence plots.

COVID-19 vaccines in patients with decompensated cirrhosis: a retrospective cohort on safety data and risk factors associated with unvaccinated status.

BACKGROUND: Safety data reported from the large-scale clinical trials of the coronavirus disease 2019 (COVID-19) vaccine are extremely limited in patients with decompensated cirrhosis. The vaccination campaign in this specific population could be difficult due to uncertainty about the adverse events following vaccination. We aimed to assessed the COVID-19 vaccination rate, factors associated with unvaccinated status, and the adverse events following vaccination in patients with decompensated cirrhosis. METHODS: This is a retrospective study from Ruijin Hospial (Shanghai, China) on an ongoing prospective cohort designed for long-term survival analysis of decompensated cirrhotic patients who recovered from decompensating events or acute-on-chronic liver failure (ACLF) between 2016 and 2018. We assessed the COVID-19 vaccination rate, the number of doses, type of vaccine, safety data, patient-reported reasons for remaining unvaccinated, factors associated with unvaccinated status, and the adverse events of COVID-19 vaccine. Binary logistic regression was used for identifying factors associated with unvaccinated status. RESULTS: A total of 229 patients with decompensated cirrhosis without previous SARS-CoV-2 infection participated (mean age, 56 ± 12.2 years, 75% male, 65% viral-related cirrhosis). Mode of decompensation were grade II‒III ascites (82.5%), gastroesophageal varices bleeding (7.9%), hepatic encephalopathy (7.9%). Eighty-five participants (37.1%) received at least one dose of vaccination (1 dose: n = 1, 2 doses: n = 65, 3 doses: n = 19) while 62.9% remained unvaccinated. Patient-reported reasons for remaining unvaccinated were mainly fear of adverse events (37.5%) and lack of positive advice from healthcare providers (52.1%). The experience of hepatic encephalopathy (OR = 5.61, 95% CI: 1.24-25.4) or ACLF (OR = 3.13, 95% CI: 1.12-8.69) and post-liver transplantation status (OR = 2.47, 95% CI: 1.06-5.76) were risk factors of remaining unvaccinated independent of residential areas. The safety analysis demonstrated that 75.3% had no adverse events, 23.6% had non-severe reactions (20% injection-site pain, 1.2% fatigue, 2.4% rash) and 1.2% had a severe event (development of acute decompensation requiring hospitalization). CONCLUSIONS: Patients with decompensated cirrhosis in eastern China are largely remained at unvaccinated status, particularly those with previous episodes of ACLF or hepatic encephalopathy and liver transplantation recipients. Vaccination against COVID-19 in this population is safe.

The platform development, adherence and efficacy to a digital Brief therapy for insomnia (dBTI) during the COVID-19 pandemic.

Brief therapy for insomnia (BTI) is a short-term cognitive behavioral therapy for insomnia. At present, there is no study combining BTI with digital technology. However, in the context of the outbreak of coronavirus disease 2019 (COVID-19), patients with acute insomnia may need an online treatment which can quickly improve insomnia symptoms. Our team built a digital BTI (dBTI) platform based on the WeChat mini program. This research provides a framework design and a course design of dBTI, and evaluates the system via recruiting participants suffering from acute insomnia in pandemic. What's more, it explores patients' adherence, the efficiency of the system and their relationship. As the result demonstrates, 68% of participants have completed more than half of the course with medium to high adherence. Gender, pre-sleep arousal scale (PSAS) somatic score and insomnia severity index (ISI) score have affected participants' adherence, and higher adherence has led to better improvement in the severity of insomnia and somatic pre-sleep arousal. It is proved that the platform we built is effective, which not only offers an entry point for the study of how to set up a dBTI platform, but also provides theoretical basis for its clinical application.

Peramivir, an Anti-Influenza Virus Drug, Exhibits Potential Anti-Cytokine Storm Effects.

Coronavirus Disease 2019 (COVID-19) infected by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has been declared a public health emergency of international concerns. Cytokine storm syndrome (CSS) is a critical clinical symptom of severe COVID-19 patients, and the macrophage is recognized as the direct host cell of SARS-CoV-2 and potential drivers of CSS. In the present study, peramivir was identified to reduce TNF-α by partly intervention of NF-κB activity in LPS-induced macrophage model. In vivo, peramivir reduced the multi-cytokines in serum and bronchoalveolar lavage fluid (BALF), alleviated the acute lung injury and prolonged the survival time in mice. In human peripheral blood mononuclear cells (hPBMCs), peramivir could also inhibit the release of TNF-α. Collectively, we proposed that peramivir might be a candidate for the treatment of COVID-19 and other infections related CSS.

Decreased Transition Rate From Situational Insomnia to Chronic Insomnia by One-Week Internet Cognitive Behavioral Treatments for Insomnia During the COVID-19 Pandemic.

Purpose: The purpose of the study was to determine the long-term effects of one-week self-guided internet cognitive behavioral treatments for insomnia (CBTI) on situational insomnia during the COVID-19 pandemic. Patients and Methods: The participants with situational insomnia (n = 194) were recruited from March 2020 to April 2020 in Guangzhou, China. The insomnia severity index (ISI), pre-sleep arousal scale (PSAS), and hospital anxiety and depression scale (HADS) were evaluated at baseline and a one-week internet CBTI program was delivered to all individuals. The participants were divided into the complete treatment group (the participants completed all seven modules of the CBTI course, n = 75), and the incomplete treatment group (the participants completed 0-6 modules of the CBTI course, n = 119). A total of 135 participants completed the post-intervention assessments. At 3 months follow-up, a total of 117 participants (complete treatment group: n = 51; incomplete treatment group: n = 66) completed the assessments of the ISI, PSAS and HADS. The transition rate from situational insomnia to chronic insomnia (duration of insomnia ≥ 3 months and ISI ≥ 8) was calculated in the two groups. Linear mixed effect model was used to investigate the effect of group (between the two groups), time (baseline vs. follow-up), and interaction (group x time) on various questionnaire score. Results: The transition rate from situational insomnia to chronic insomnia was significantly lower in the complete treatment group compared to the incomplete treatment group (27.5%, 14/51 vs. 48.5%, 32/66, p = 0.023). There were significant differences in group effect (p = 0.032), time effect (p = 0.000) and group × time effect (p = 0.048) between the two groups in the ISI total score. The ISI total scores decreased in both groups during follow-up compared to their baseline values, with a greater magnitude of decrease in the complete treatment group. There were no significant group x time effects between the two groups in the PSAS-total score, PSAS-somatic, PSAS-cognitive score, HADS total score, HADS anxiety score or HADS depression score. Conclusion: Our results suggested that one-week self-guided internet CBTI prevented the development of chronic insomnia from situational insomnia during the COVID-19 pandemic.

Prevalence and Risk Factors Associated with Insomnia Symptoms Among the Chinese General Public After the Coronavirus Disease 2019 Epidemic Was Initially Controlled.

INTRODUCTION: The prevalence rate and related factors of insomnia remained unknown after the COVID-19 epidemic had been under control. Therefore, we conducted this survey to investigate the prevalence rate and related factors of insomnia symptoms in the Chinese general public after the COVID-19 had been initially control. METHODS: An online survey was conducted among Chinese citizens through the JD Health APP. The questionnaire was used for collecting demographic data and self-designed questions related to the COVID-19 outbreak. Insomnia Severity Index, Patient Health Questionnaire-9, Somatic Symptom Scale-8 and Impact of Events Scale-Revised were used for measuring psychological symptoms. To examine the associations of sociodemographic and psychological factors with insomnia symptoms, a binary logistic regression was used. RESULTS: In total, there were 14,894 eligible participants, and 4601 (30.9%) participants were found to have insomnia symptoms. The regression model revealed that a higher risk of insomnia symptoms was associated with being over the age of 40 years, having history of psychiatric disorders, smoking, having infected friends or colleagues, having depressive or somatic symptoms, experiencing psychological distress and feeling estranged from family members. Meanwhile a lower risk of insomnia symptoms was associated with being female, having closer family relationships, not feeling alienated from others and being satisfied with the available information. CONCLUSION: In our study, 30.9% of the participants in the general public reported insomnia symptoms after the COVID-19 epidemic had been initially controlled. When providing precise interventions for insomnia, extra attention should be paid to the individuals who are male, elderly and smokers, and those with psychiatric disorder history, with infected friends or colleagues, with psychological symptoms and with poor social support.

Gender differences in mental health problems of healthcare workers during the coronavirus disease 2019 outbreak.

The coronavirus disease 2019 (COVID-19) pandemic has imposed both physical and psychological burdens on healthcare workers (HCWs). What is more, few studies have focused on the gender differences in mental health problems (MHPs) among HCWs during such an outbreak. Thus, the current study investigated the prevalence and gender differences of various MHPs among HCWs in China during the COVID-19 outbreak. This nationwide survey was conducted online from January 29 to February 3, 2020. General information was collected by questions about socio-demographics, work-related factors, and living situations. Depressive, anxiety, stress, and insomnia symptoms were assessed by the Patient Health Questionnaire-9, the Generalized Anxiety Disorder-7, the Impact of Event Scale-Revised, and the Insomnia Severity Index, respectively. Among the 2198 contacted HCWs, 1563 (71.1%) responded with valid data, of whom 1293 (82.7%) were females. The prevalences of depressive, anxiety, stress, and insomnia symptoms in participants were 50.7%, 44.7%, 52.5%, and 36.1%, respectively. Female HCWs had significantly higher scores in all four scales (p < 0.001) and higher prevalences in all MHPs involved (range, odds ratio [OR] 1.55-1.97). After adjusting for potential confounders, female HCWs still had higher risks for all MHPs involved than males (range, adjusted OR 1.36-1.96). HCWs present high prevalences of depressive, anxiety, stress, and insomnia symptoms during the COVID-19 outbreak. Furthermore, female HCWs are more vulnerable to all MHPs involved. These findings highlight the need for timely, special care and support for HCWs during the outbreak, especially for females.

One-Week Self-Guided Internet Cognitive Behavioral Treatments for Insomnia in Adults With Situational Insomnia During the COVID-19 Outbreak.

Objective: In the current global home confinement due to COVID-19, most individuals are facing unprecedented stress which can induce situational insomnia. We explored the efficacy of self-guided online cognitive behavioral treatment for insomnia (CBTI) on situational insomnia during the COVID-19 outbreak. Methods: Participants were recruited from March to April in 2020 in Guangzhou, China. A 1-week Internet CBTI intervention was performed for all individuals with situational insomnia. The Pre-sleep Arousal Scale (PSAS), Insomnia Severity Index (ISI), and Hospital Anxiety and Depression Scale (HADS) were measured before and after the intervention and compared between individuals who completed the intervention and those who did not. Results: One hundred and ninety-four individuals with situational insomnia were included. For PSAS score, significant group effects were found on total score (p = 0.003), somatic score (p = 0.014), and cognitive score (p = 0.009). Time effect was significant on total score (p = 0.004) and cognitive score (p < 0.001). There was a significant group × time effect of the somatic score (p = 0.025). For ISI total score, there were significant time effect (p < 0.001) and group × time effect (p = 0.024). For the HADS score, a significant group effect was found on the anxiety score (p = 0.045). The HADS had significant time effects for anxiety and depressive symptoms (all p < 0.001). Conclusion: Our study suggests good efficacy of CBTI on situational insomnia during COVID-19 for adults in the community, as well as on pre-sleep somatic hyperarousal symptom. The CBTI intervention is not applied to improve pre-sleep cognitive hyperarousal, depression, and anxiety symptoms.

Drug repurposing of anti-infective clinical drugs: Discovery of two potential anti-cytokine storm agents.

Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus -2 (SARS-CoV-2) has been widely spread in the world with a high mortality. Cytokine storm syndrome (CSS) and acute lung injury caused by SARS-CoV-2 infection severely threaten the patients. With the purpose to find effective and low-toxic drugs to mitigate CSS, entecavir and imipenem were identified to reduce TNF-α using a LPS-induced macrophage model from the anti-infective drug library. Entecavir and imipenem efficiently suppressed the release of inflammatory cytokines by partly intervention of NF-κB activity. The acute lung injury was also alleviated and the survival time was prolonged in mice. In addition, entecavir and imipenem inhibited the release of TNF-α and IL-10 in human peripheral blood mononuclear cells (hPBMCs). Collectively, we proposed that entecavir and imipenem might be candidates for the treatment of CSS.

Survey of Insomnia and Related Social Psychological Factors Among Medical Staff Involved in the 2019 Novel Coronavirus Disease Outbreak.

OBJECTIVE: The outbreak of the 2019 novel coronavirus disease (COVID-19) not only caused particularly large public health problems, but also caused great psychological distress, especially for medical staff. We aimed to investigate the prevalence rate of insomnia and to confirm the related social psychological factors among medical staff in hospitals during the COVID-19 outbreak. METHOD: Medical staff members in China were recruited, including frontline medical workers. The questionnaire, administered through the WeChat program, obtained demographic data and asked self-design questions related to the COVID-19 outbreak, insomnia/depressive/anxiety symptoms, and stress-related symptoms. We used a logistic regression analysis to examine the associations between sociodemographic factors and insomnia symptoms. RESULT: There were a total of 1,563 participants in our study. Five-hundred-and-sixty-four (36.1%) participants had insomnia symptoms according to the Insomnia Severity Index (ISI) (total score ≥ 8). A multiple binary logistic regression model revealed that insomnia symptoms were associated with an education level of high school or below (OR = 2.69, p = 0.042, 95% CI = 1.0-7.0), being a doctor (OR = 0.44, p = 0.007, 95% CI = 0.2-0.8), currently working in an isolation unit (OR = 1.71, p = 0.038, 95% CI = 1.0-2.8), is worried about being infected (OR = 2.30, p < 0.001, 95% CI = 1.6-3.4), perceived lack of helpfulness in terms of psychological support from news or social media with regard to COVID-19 (OR = 2.10, p = 0.001, 95% CI = 1.3-3.3), and having very strong uncertainty regarding effective disease control (OR = 3.30, p = 0.013, 95% CI = 1.3-8.5). CONCLUSION: Our study found that more than one-third of the medical staff suffered insomnia symptoms during the COVID-19 outbreak. The related factors included education level, an isolation environment, psychological worries about the COVID-19 outbreak, and being a doctor. Interventions for insomnia among medical staff are needed considering the various sociopsychological factors at play in this situation.