Effects of a online brief modified mindfulness-based stress reduction therapy for anxiety among Chinese adults: A randomized clinical trial

The COVID-19 pandemic has exacerbated anxiety and related symptoms among the general population. In order to cope with the mental health burden, we developed an online brief modified mindfulness-based stress reduction (mMBSR) therapy. We performed a parallel-group randomized controlled trial to evaluate the efficacy of the mMBSR for adult anxiety with cognitive-behavioral therapy (CBT) as an active control. Participants were randomized to mMBSR, CBT or waitlist group. Those in the intervention arms performed each therapy for 6 sections in 3 weeks. Measurements were conducted at baseline, post-treatment and 6 months post-treatment by Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Patient Health Questionnaire-15, reverse scored Cohen Perceived Stress scale, Insomnia Severity Index, and Snaith-Hamilton Pleasure Scale. 150 participants with anxiety symptoms were randomized to mMBSR, CBT or waitlist group. Post intervention assessments showed that mMBSR improved the scores of all the six mental problem dimensions (anxiety, depression, somatization, stress, insomnia, and the experience of pleasure) significantly compared to the waitlist group. During 6-month post treatment assessment, the scores of all six mental problem dimensions in the mMBSR group still showed improvement compared to baseline and showed no significant difference with the CBT group. Our results provide positive evidence for the efficacy and feasibility of an online brief modified MBSR program to alleviate anxiety and related symptoms of individuals from the general population, and the therapeutic benefits of mMBSR persisted for up to six months. This low resource-consuming intervention could facilitate the challenges of supplying psychological health therapy to large scale of population.

Effects of a online brief modified mindfulness-based stress reduction therapy for anxiety among Chinese adults: A randomized clinical trial.

The COVID-19 pandemic has exacerbated anxiety and related symptoms among the general population. In order to cope with the mental health burden, we developed an online brief modified mindfulness-based stress reduction (mMBSR) therapy. We performed a parallel-group randomized controlled trial to evaluate the efficacy of the mMBSR for adult anxiety with cognitive-behavioral therapy (CBT) as an active control. Participants were randomized to mMBSR, CBT or waitlist group. Those in the intervention arms performed each therapy for 6 sections in 3 weeks. Measurements were conducted at baseline, post-treatment and 6 months post-treatment by Generalized Anxiety Disorder-7, Patient Health Questionnaire-9, Patient Health Questionnaire-15, reverse scored Cohen Perceived Stress scale, Insomnia Severity Index, and Snaith-Hamilton Pleasure Scale. 150 participants with anxiety symptoms were randomized to mMBSR, CBT or waitlist group. Post intervention assessments showed that mMBSR improved the scores of all the six mental problem dimensions (anxiety, depression, somatization, stress, insomnia, and the experience of pleasure) significantly compared to the waitlist group. During 6-month post treatment assessment, the scores of all six mental problem dimensions in the mMBSR group still showed improvement compared to baseline and showed no significant difference with the CBT group. Our results provide positive evidence for the efficacy and feasibility of an online brief modified MBSR program to alleviate anxiety and related symptoms of individuals from the general population, and the therapeutic benefits of mMBSR persisted for up to six months. This low resource-consuming intervention could facilitate the challenges of supplying psychological health therapy to large scale of population.

Association Between Ischemic Stroke and COVID-19 in China: A Population-Based Retrospective Study.

Background and Purpose: To investigate the effect of prior ischemic stroke on the outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19), and to describe the incidence, clinical features, and risk factors of acute ischemic stroke (AIS) following COVID-19. Methods: In this population-based retrospective study, we included all the hospitalized positive patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020. Clinical data were extracted from administrative datasets coordinated by the Wuhan Health Commission. The propensity score matching and multivariate logistic regression analyses were used to adjust the confounding factors. Results: There are 36,358 patients in the final cohort, in which 1,160 (3.2%) had a prior stroke. After adjusting for available baseline characteristics, patients with prior stroke had a higher proportion of severe and critical illness and mortality. We found for the first time that the premorbid modified Rankin Scale (MRS) grouping (odds ratio [OR] = 1.796 [95% CI 1.334-2.435], p < 0.001) and older age (OR = 1.905 [95% CI 1.211-3.046], p = 0.006) imparted increased risk of death. AIS following COVID-19 occurred in 124 (0.34%) cases, and patients with prior stroke had a much higher incidence of AIS (3.4%). Logistic regression analyses confirmed an association between the severity of COVID-19 with the incidence of AIS. COVID-19 patients with AIS had a significantly higher mortality compared with COVID-19 patients without stroke and AIS patients without COVID-19. Conclusions: Coronavirus disease 2019 patients with prior stroke, especially those with the higher premorbid MRS or aged, have worse clinical outcomes. Furthermore, COVID-19 increases the incidence of AIS, and the incidence is positively associated with the severity of COVID-19.

Association Between Ischemic Stroke and COVID-19 in China: A Population-Based Retrospective Study

Background and Purpose To investigate the effect of prior ischemic stroke on the outcomes of patients hospitalized with coronavirus disease 2019 (COVID-19), and to describe the incidence, clinical features, and risk factors of acute ischemic stroke (AIS) following COVID-19. Methods In this population-based retrospective study, we included all the hospitalized positive patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020. Clinical data were extracted from administrative datasets coordinated by the Wuhan Health Commission. The propensity score matching and multivariate logistic regression analyses were used to adjust the confounding factors. Results There are 36,358 patients in the final cohort, in which 1,160 (3.2%) had a prior stroke. After adjusting for available baseline characteristics, patients with prior stroke had a higher proportion of severe and critical illness and mortality. We found for the first time that the premorbid modified Rankin Scale (MRS) grouping (odds ratio [OR] = 1.796 [95% CI 1.334–2.435], p < 0.001) and older age (OR = 1.905 [95% CI 1.211–3.046], p = 0.006) imparted increased risk of death. AIS following COVID-19 occurred in 124 (0.34%) cases, and patients with prior stroke had a much higher incidence of AIS (3.4%). Logistic regression analyses confirmed an association between the severity of COVID-19 with the incidence of AIS. COVID-19 patients with AIS had a significantly higher mortality compared with COVID-19 patients without stroke and AIS patients without COVID-19. Conclusions Coronavirus disease 2019 patients with prior stroke, especially those with the higher premorbid MRS or aged, have worse clinical outcomes. Furthermore, COVID-19 increases the incidence of AIS, and the incidence is positively associated with the severity of COVID-19.

Age-Related Risk Factors and Complications of Patients With COVID-19: A Population-Based Retrospective Study

Objective: To study the differences in clinical characteristics, risk factors, and complications across age-groups among the inpatients with the coronavirus disease 2019 (COVID-19). Methods: In this population-based retrospective study, we included all the positive hospitalized patients with COVID-19 at Wuhan City from December 29, 2019 to April 15, 2020, during the first pandemic wave. Multivariate logistic regression analyses were used to explore the risk factors for death from COVID-19. Canonical correlation analysis (CCA) was performed to study the associations between comorbidities and complications. Results: There are 36,358 patients in the final cohort, of whom 2,492 (6.85%) died. Greater age (odds ration [OR] = 1.061 [95% CI 1.057–1.065], p < 0.001), male gender (OR = 1.726 [95% CI 1.582–1.885], p < 0.001), alcohol consumption (OR = 1.558 [95% CI 1.355–1.786], p < 0.001), smoking (OR = 1.326 [95% CI 1.055–1.652], p = 0.014), hypertension (OR = 1.175 [95% CI 1.067–1.293], p = 0.001), diabetes (OR = 1.258 [95% CI 1.118–1.413], p < 0.001), cancer (OR = 1.86 [95% CI 1.507–2.279], p < 0.001), chronic kidney disease (CKD) (OR = 1.745 [95% CI 1.427–2.12], p < 0.001), and intracerebral hemorrhage (ICH) (OR = 1.96 [95% CI 1.323–2.846], p = 0.001) were independent risk factors for death from COVID-19. Patients aged 40–80 years make up the majority of the whole patients, and them had similar risk factors with the whole patients. For patients aged <40 years, only cancer (OR = 17.112 [95% CI 6.264–39.73], p < 0.001) and ICH (OR = 31.538 [95% CI 5.213–158.787], p < 0.001) were significantly associated with higher odds of death. For patients aged >80 years, only age (OR = 1.033 [95% CI 1.008–1.059], p = 0.01) and male gender (OR = 1.585 [95% CI 1.301–1.933], p < 0.001) were associated with higher odds of death. The incidence of most complications increases with age, but arrhythmias, gastrointestinal bleeding, and sepsis were more common in younger deceased patients with COVID-19, with only arrhythmia reaching statistical difference (p = 0.039). We found a relatively poor correlation between preexisting risk factors and complications. Conclusions: Coronavirus disease 2019 are disproportionally affected by age for its clinical manifestations, risk factors, complications, and outcomes. Prior complications have little effect on the incidence of extrapulmonary complications.

Acute psychological impact on COVID-19 patients in Hubei: a multicenter observational study.

We conducted a multicentre cross-sectional survey of COVID-19 patients to evaluate the acute psychological impact on the patients with coronavirus disease 2019 (COVID-19) during isolation treatment based on online questionnaires from 2 February to 5 March 2020. A total of 460 COVID-19 patients from 13 medical centers in Hubei province were investigated for their mental health status using online questionnaires (including Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, Patient Health Questionnaire-15, and Insomnia Severity Index scales). Among all 460 COVID-19 patients, 187 (40.65%) of them were healthcare workers (HCWs). 297 (64.57%) of them were females. The most common psychological problems were somatization symptoms (66.09%, n = 304), followed by depression (53.48%, n = 246), anxiety (46.30%, n = 213), problems of insomnia (42.01%, n = 171), and then self-mutilating or suicidal thoughts (23.26%, n = 107). Of all the patients, 15.65% (n = 72) had severe somatization symptoms, and 2.83% (n = 13) had severe (almost every day) self-mutilating or suicidal thoughts. The most common psychological problems for HCWs were somatization symptoms (67.84%, n = 125), followed by depression (51.87%, n = 97), anxiety (44.92%, n = 84), problems of insomnia (36.18%, n = 55), and then self-mutilating or suicidal thoughts (20.86%, n = 39). Patients with lower education levels were found to be associated with higher incidence of self-mutilating or suicidal thoughts (odds ratio [OR], 2.68, 95% confidence interval [95% CI], 1.66-4.33 [P < 0.001]). Patients with abnormal body temperature were found to be associated with higher incidence of self-mutilating or suicidal thoughts (OR, 3.97, 95% CI, 2.07-7.63 [P < 0.001]), somatic symptoms (OR, 2.06, 95% CI, 1.20-3.55 [P = 0.009]) and insomnia (OR, 1.66, 95% CI, 1.04-2.65 [P = 0.033]). Those with suspected infected family members displayed a higher prevalence of anxiety than those without infected family members (OR, 1.61, 95% CI, 1.1-2.37 [P = 0.015]). Patients at the age of 18-44 years old had fewer somatic symptoms than those aged over 45 years old (OR, 1.91, 95% CI, 1.3-2.81 [P = 0.001]). In conclusion, COVID-19 patients tended to have a high prevalence of adverse psychological events. Early identification and intervention should be conducted to avoid extreme events such as self-mutilating or suicidal impulsivity for COVID-19 patients, especially for those with low education levels and females who have undergone divorce or bereavement.

Prevalence of psychological disorders in the COVID-19 epidemic in China: A real world cross-sectional study.

OBJECTIVE: This study aimed to explore the prevalence of psychological disorders and associated factors at different stages of the COVID-19 epidemic in China. METHODS: The mental health status of respondents was assessed via the Patient Health Questionnaire-9 (PHQ-9), Insomnia Severity Index (ISI) and the Generalized Anxiety Disorder 7 (GAD-7) scale. RESULTS: 5657 individuals participated in this study. History of chronic disease was a common risk factor for severe present depression (OR 2.2, 95% confidence interval [CI], 1.82-2.66, p < 0.001), anxiety (OR 2.41, 95% CI, 1.97-2.95, p < 0.001), and insomnia (OR 2.33, 95% CI, 1.83-2.95, p < 0.001) in the survey population. Female respondents had a higher risk of depression (OR 1.61, 95% CI, 1.39-1.87, p < 0.001) and anxiety (OR 1.35, 95% CI, 1.15-1.57, p < 0.001) than males. Among the medical workers, confirmed or suspected positive COVID-19 infection as associated with higher scores for depression (confirmed, OR 1.87; suspected, OR 4.13), anxiety (confirmed, OR 3.05; suspected, OR 3.07), and insomnia (confirmed, OR 3.46; suspected, OR 4.71). LIMITATION: The cross-sectional design of present study presents inference about causality. The present psychological assessment was based on an online survey and on self-report tools, albeit using established instruments. We cannot estimate the participation rate, since we cannot know how many potential subjects received and opened the link for the survey. CONCLUSIONS: Females, non-medical workers and those with a history of chronic diseases have had higher risks for depression, insomnia, and anxiety. Positive COVID-19 infection status was associated with higher risk of depression, insomnia, and anxiety in medical workers.

Deep learning-based triage and analysis of lesion burden for COVID-19: a retrospective study with external validation.

Background: Prompt identification of patients suspected to have COVID-19 is crucial for disease control. We aimed to develop a deep learning algorithm on the basis of chest CT for rapid triaging in fever clinics. Methods: We trained a U-Net-based model on unenhanced chest CT scans obtained from 2447 patients admitted to Tongji Hospital (Wuhan, China) between Feb 1, 2020, and March 3, 2020 (1647 patients with RT-PCR-confirmed COVID-19 and 800 patients without COVID-19) to segment lung opacities and alert cases with COVID-19 imaging manifestations. The ability of artificial intelligence (AI) to triage patients suspected to have COVID-19 was assessed in a large external validation set, which included 2120 retrospectively collected consecutive cases from three fever clinics inside and outside the epidemic centre of Wuhan (Tianyou Hospital [Wuhan, China; area of high COVID-19 prevalence], Xianning Central Hospital [Xianning, China; area of medium COVID-19 prevalence], and The Second Xiangya Hospital [Changsha, China; area of low COVID-19 prevalence]) between Jan 22, 2020, and Feb 14, 2020. To validate the sensitivity of the algorithm in a larger sample of patients with COVID-19, we also included 761 chest CT scans from 722 patients with RT-PCR-confirmed COVID-19 treated in a makeshift hospital (Guanggu Fangcang Hospital, Wuhan, China) between Feb 21, 2020, and March 6, 2020. Additionally, the accuracy of AI was compared with a radiologist panel for the identification of lesion burden increase on pairs of CT scans obtained from 100 patients with COVID-19. Findings: In the external validation set, using radiological reports as the reference standard, AI-aided triage achieved an area under the curve of 0·953 (95% CI 0·949-0·959), with a sensitivity of 0·923 (95% CI 0·914-0·932), specificity of 0·851 (0·842-0·860), a positive predictive value of 0·790 (0·777-0·803), and a negative predictive value of 0·948 (0·941-0·954). AI took a median of 0·55 min (IQR: 0·43-0·63) to flag a positive case, whereas radiologists took a median of 16·21 min (11·67-25·71) to draft a report and 23·06 min (15·67-39·20) to release a report. With regard to the identification of increases in lesion burden, AI achieved a sensitivity of 0·962 (95% CI 0·947-1·000) and a specificity of 0·875 (95 %CI 0·833-0·923). The agreement between AI and the radiologist panel was high (Cohen's kappa coefficient 0·839, 95% CI 0·718-0·940). Interpretation: A deep learning algorithm for triaging patients with suspected COVID-19 at fever clinics was developed and externally validated. Given its high accuracy across populations with varied COVID-19 prevalence, integration of this system into the standard clinical workflow could expedite identification of chest CT scans with imaging indications of COVID-19. Funding: Special Project for Emergency of the Science and Technology Department of Hubei Province, China.