Severity and Mortality in Maintenance Hemodialysis Patients Infected with COVID-19 Omicron Strain: a Single-Centered, Retrospective Study in China (preprint)

Purpose The aim of this study was to observe the characteristics of COVID-19 infected maintenance hemodialysis (MHD) patients, identify the risk factors for severe illness and mortality in this population, and establish a preliminary risk prediction model for severe COVID-19 infection of MHD patients.Methods We included patients who underwent long-term maintenance hemodialysis and were hospitalized for COVID-19 infection at our hospital from December 2022 to March 2023. We retrospectively analyzed their demographic characteristics, clinical manifestations, laboratory tests, hemodialysis-related information, treatment strategies and complications. The patients were divided into severe (heavy and critical) and non-severe (mild and moderate) groups. Logistic regression and Cox proportional hazards analysis were used to identify the risk factors for severe COVID-19 progression.Results The presence of cerebrovascular disease, elevated NLR, fibrinogen, and D-dimer are independent risk indicators for severe COVID-19 infection in MHD patients in early stage. The presence of diabetes, cerebrovascular disease, and elevated D-dimer and NLR were associated with mortality.Conclusion MHD patients have a high probability of developing into severe and critical COVID-19 infection, and NLR, fibrinogen, and D-dimer can serve as early warning indicators for severe and critical progression of COVID-19 infection. The presence of diabetes, cerebrovascular disease, elevated NLR and D-dimer levels attribute to worse clinical outcomes and increased mortality.

Clinical characteristics and analysis of risk factors for disease progression in patients on maintenance hemodialysis infected with SARS-CoV-2 omicron variant (preprint)

Objective:To summarize the clinical characteristics of patients on maintenance hemodialysis (MHD) with the novel coronavirus omicron variant and explore the risk factors for severe cases. Methods:We retrospectively analyzed the data of 158 patients on MHD from Zhongnan Hospital of Wuhan University between December 7, 2022 and January 31, 2023. We collected clinical data, described clinical characteristics, and analyzed the relationships between these factors and critical illness using univariate and multivariate logistic regression analyses. Results: The median age of the 158 patients was 63 (interquartile range: 52–71) years, and 128 (63.7%) were men. Fever (62.7%) and cough (60.1%) were the two most common symptoms. Hypertension (80.4%) was the most common comorbidity, followed by diabetes (31.0%), cardiovascular disease (22.8%), and cerebrovascular disease (15.2%). Unvaccinated patients constituted the majority of the enrolled patients (88.6%, 140/158), whereas only a small proportion (11.4%, 18/158) had been vaccinated (including fully vaccinated and partially vaccinated patients). Multivariate logistic regression analysis indicated that an elevated C-reactive protein (CRP) level (odds ratio [OR]: 1.03, 95% confidence interval [CI], 1.014–1.046], p<0.001) and a decreased platelet count (OR: 0.986, 95% CI, 0.986 (0.976–0.997), p=0.013) during hospitalization were risk factors for the severe group. Conclusions:This study demonstrated a high mortality rate among patients on MHD infected with omicron variant. Furthermore, advanced age, increased CRP levels, and decreased platelet count were predictors of critical illness.

Correlations between somatic symptoms and resilience among a group of Vietnamese : Lessons learned from Covid 19 (preprint)

This study aims to examine the relationships between somatic symptoms and resilience among a group of Vietnamese in the time of Covid 19. In earlier literature, no attention was paid to name what exactly somatic symptoms related to components of resilience among this group. In this research, 1252 willing participants were administered in August 2021, using an online survey on the demographic questionnaires, somatic symptoms (PHQ 15) and Resilience (RIS-CD, 2003).  Through descriptive statistics resulting from SPSS 26, self-efficacy was found significant in the expressions of resilience. In addition, the result from the correlation and  regression analysis also showed the significantly negative relationships between somatic symptoms(e.g., insomnia, fatigue) and resilience (e.g., self-efficacy). The discussions on the main findings will address cultural implications. Lessons learned from Covid 19 and recommendations for future research in the fields of Scientific Reports also suggested.

Pregnancy, mental well-being and lockdown: a nationwide online survey in France (preprint)

Objective: To compare the mental well-being of French women who were and were not pregnant during the first COVID-19 pandemic lockdown. Design: Survey. Setting: France. Population: Women between 18 and 45 years of age during the second and third weeks of global lockdown (March 25–April 07, 2020) during the COVID-19 pandemic. Methods: : Nationwide online quantitative survey. Main Outcome Measures: Mental well-being measured by the Warwick-Edinburgh Mental Well-Being Scale (WEMWBS). Results: : This study analysed 275 responses from pregnant women and compared them with those from a propensity score–matched sample of 825 non-pregnant women. The median WEMWBS score was 49.0 and did not differ by pregnancy status. Women living in urban areas reported better well-being, while those with sleep disorders or who spent more than an hour a day watching the news reported poorer well-being. Conclusion: During the first lockdown in France, women had relatively low mental well-being scores, with no significant difference between pregnant and non-pregnant women. More than ever, health-care workers need to find a way to maintain their support for women’s well-being. Minor daily annoyances of pregnancy, such as insomnia, should not be trivialised because they are a potential sign of poor well-being.

Development of a nomogram model for predicting the risk of insomnia in nurses who underwent the Long- COVID (preprint)

Purpose To investigate the prevalence of insomnia among nurses diagnosed with Long-COVID, analyze the potential risk factors, and establish a nomogram prediction model.Methods General demographic information was obtained, and assessments of sleep quality, burnout, and stress were performed in a single center in May 2023. Three hundred and ninety-eight nurses were recruited. The Lasso regression technique was employed to screen for potential factors contributing to insomnia. A prognostic nomogram was constructed and evaluated by receiver operating characteristic curves and calibration curves.Results Fifty-four percent of nurses complained of insomnia in this study. Eleven variables were independently associated with sleep patterns, including family, years of work, relaxion time, sequela of respiratory system, sequela of nervous system, others sequela, attitudes towards COVID-19, sleep duration, previous sleep problems, stress, and job burnout. The R-squared value was 0.4642 and the area under curve was 0.8661. The derived nomogram showed that neurological sequela, stress, job burnout, sleep time before infection, and previous sleep problems also made the most substantial contributions to predicting sleep patterns. The calibration curves for predicting insomnia showed significant agreement between the nomogram models and actual observations.Conclusion The present study established a nomogram prediction model of insomnia for nurses diagnosed with Long-COVID, which is helpful for the early clinical identification of high-risk individuals with insomnia.

Neural alterations of Omicron infection comorbid with insomnia in Chinese: Insight from surface-based morphometry and bibliometric analysis (preprint)

Growing evidence suggests that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can affect the central nervous system (CNS), and insomnia-related acute and long-term CNS sequelae may be suffered by infected patients. Nevertheless, as a common sub-typic strain of SARS-CoV-2, it is currently unknown the impacts of Omicron comorbid with insomnia on brain cortex. The purpose of this study was to mine the neural markers involving cortical grey matter volume (GMV), thickness, and surface area within Omicron individuals either with or without insomnia. Additionally, correlations between these morphological metrics and neuropsychiatric assessments were analyzed. 234 participants were recruited from a prospective cross-sectional study cohort during the Omicron pandemic (December 2022-May 2023) at the Second Xiangya Hospital (China). We further divided participants into healthy controls (HCs), Omicron infection with insomnia group (Omicron_insomnia group), and Omicron infection without insomnia group (Omicron_non_insomnia group). Based on T1-weighted MPRAGE image, cortical thickness, surface area, and GMV were compared via surface-based morphometry (SBM) analysis, and significant morphological metrics were then correlated with neuropsychiatric manifestations. Our findings revealed altered cortical morphology in Omicron individuals. Morphological changes in the temporal, frontal, cingulate, transverse collateral, and lingual gyrus were independent from insomnia comorbidity. The decreased cortical thickness in superior temporal gyrus (STG) was a specific feature for Omicron infection comorbid with insomnia. Then, we discovered greater morphological size indicating neuropsychiatric improvement. This study explores the neural mechanisms underlying Omicron infection comorbid with insomnia, which will help to promote improvement in post-Omicron neuropsychiatric prognosis and clinical management.

Causal Model Analysis of the Effect of Policy Formalism, Equipment Insufficiency, Covid-19 Fear and Job Insecurity on Construction Workers’ Insomnia during the Epidemic (preprint)

This study mainly explores the effect of policy formalism, equipment insufficiency, covid-19 fear and job insecurity on construction workers’ insomnia during the epidemic. The main contribution of this article is to introduce policy formalism into the exploration of the causes of insomnia among construction site workers during the epidemic. This study collected 733 valid samples of construction site workers. We tested the established hypotheses using confirmatory factor analysis and structural equation modeling. The research results found that equipment insufficiency positively affects Covid-19 fear. Policy formalism and Covid-19 fear positively affect job burnout. Social support negatively affects job burnout. Job burnout and job insecurity positively affect insomnia.

A pragmatic randomized controlled trial of a telemedicine self-management intervention for adults with long COVID: The COPE study protocol (preprint)

Background: Long COVID is a serious public health concern due to its high prevalence and potentially debilitating symptoms. Symptoms may include fatigue, dyspnea, cognitive problems, insomnia, anxiety and depression. There is currently no cure for long COVID and the average length of recovery and proportion of patients who fully recover are still unknown. Subsequently, there is a critical need to improve function. Research in other chronic conditions suggests that psychosocial self-management interventions reduce symptom severity and interference with functioning. We describe the design of our study to examine the feasibility, acceptability, appropriateness and preliminary efficacy of an intervention designed to improve symptom management and coping in adults with long COVID. Methods: This pilot trial (N=50) uses a pragmatic, randomized 2-group parallel design set within the MASKED Post-COVID Rehabilitation and Recovery Clinic. The self-management intervention is a 6-week, group-based telemedicine intervention that teaches evidence-based strategies to manage common symptoms and improve stress management as well as communication and self-advocacy. The comparator is a wait-list control. Participants complete self-report measures of the primary and secondary outcomes at baseline and post-treatment/wait-list. Primary outcomes include intervention feasibility, acceptability, and appropriateness. Secondary outcomes include Patient-Reported Outcomes Measurement Information System measures of fatigue, sleep disturbance, cognitive difficulties, self-efficacy, pain interference, depression and anxiety symptoms as well as a measure of long COVID symptoms and impression of change. At post-intervention, intervention participants also complete a qualitative interview to inform intervention refinement. Quantitative data will be examined using descriptive and statistical analysis including ttests and chi-square tests to compare the intervention and wait-list groups on secondary outcomes. Qualitative data will be analyzed using the rigorous and accelerated data reduction technique. Discussion: Results of this pilot randomized controlled trial will characterize the feasibility, acceptability, and appropriateness of the self-management intervention and inform intervention refinement necessary prior to further testing. Long COVID is a public health concern and rehabilitation approaches that equip patients to manage symptoms may improve patient function and quality of life and reduce burden on the health system. Clinical Trial Registration No.: NCT05658536. Date of Trial Registration: December 16, 2022

Psychological impact of COVID-19 on frontline healthcare workers during the early months of the pandemic and responses to reduce the burden, helping to prepare for Disease X: A systematic Review (preprint)

ObjectiveThe COVID-19 pandemic placed enormous strain on healthcare workers (HCW) and systems. With currently over 766 million cases, a high risk of workplace-acquired infection and a constantly evolving disease trajectory, COVID-19 placed an incredible burden on frontline HCWs. Studies from previous pandemics highlight significant psychological distress in these workers, yet mental health remained a secondary consideration in many hospitals pandemic response. This review explores the psychological impact of COVID-19 on frontline HCWs during the early stages of the pandemic and describes responses implemented by health services to reduce this impact. Additionally, it aims to provide a framework for future evidence-based programs that support the wellbeing of frontline HCWs throughout the ongoing pandemic and into the future, helping to prepare for Disease X. MethodsA systematic review was completed using MEDLINE, CINHAL and Cochrane databases with bibliographic and grey literature searches. Results17 publications were included. Symptoms of psychological distress were reported in up to 70% of frontline HCWs, with as many as 50% suffering depression, 62% reporting anxiety and 45% of those requiring quarantine experiencing insomnia. Mindfulness training, safe rest areas, mental health practitioners and pandemic rostering are responses that have been implemented across health services during the pandemic, but their efficacy in reducing psychological burden has not been fully assessed. ConclusionsThe impact of COVID-19 has been enormous; however, its final toll remains unknown. High rates of psychological distress amongst frontline HCWs means the impact will extend far beyond the virus itself. Health services must implement evidence-based resilience strategies to ensure the safety of their frontline staff now and into the future.

[Sleep disorders in nurses working during the COVID-19 pandemic]. / Rasstroistva sna u meditsinskikh sester, rabotayushchikh v period pandemii COVID-19.

The reorganization of treatment facilities during the COVID-19 pandemic has altered the working conditions of large numbers of the health workers (HW) worldwide. The implementation of professional activities in such realities has led to an increased risk of developing a number of psychological disorders, including insomnia. The percentage of insomnia in HW has increased significantly. The nurses were the most vulnerable, because they are women and they work in an understaffed environment. The influence of shift work and stress conditions on the risk of insomnia, methods of prevention and treatment of this disorder are thoroughly examined in the article.

Association between Love Breakup and Suicidal Ideation in Peruvian Medical Students: A Cross-Sectional Study during the COVID-19 Pandemic (preprint)

Objective: We aimed to determine the association between a major romantic breakup and suicidal ideation in medical students from three universities in Peru.  Methods: A cross-sectional study was conducted during the first pandemic wave in 2021 on medical students from three universities in northern Peru. The outcome was suicidal ideation, measured with question nine of the PHQ-9. The exposure was the experience of a major love breakup during the pandemic. In addition, its association with other covariates (age, sex, family members infected with COVID-19, deceased family members with COVID-19, insomnia, and anxiety, among others) was examined.  Results and discussions: Out of 370 students, 19.5% reported a major love breakup during the pandemic (95%CI: 15.5–23.8), and 34.3% had suicidal ideation (95%CI: 29.4–39.4). Having a major love breakup was associated with a higher prevalence of suicidal ideation (PR: 1.49, 95%CI: 1.32–1.67). Moderate insomnia (PR: 2.56, 95%CI: 1.70–3.87) and anxiety symptoms (PR: 1.94, 1.10–3.44) were also associated with suicidal ideation.  Conclusion: Our study provides evidence of a significant association between a major love breakup and suicidal ideation. This finding emphasizes the need for further research to better understand this association and inform the development of effective suicide prevention policies in medical education.

Insomnia and job stressors among healthcare workers who served COVID-19 patients in Bangladesh.

BACKGROUND: The global outbreak of COVID-19 has created unprecedented havoc among health care workers, resulting in significant psychological strains like insomnia. This study aimed to analyze insomnia prevalence and job stressors among Bangladeshi health care workers in COVID-19 units. METHODOLOGY: We conducted this cross-sectional study to assess insomnia severity from January to March 2021 among 454 health care workers working in multiple hospitals in Dhaka city with active COVID-dedicated units. We selected 25 hospitals conveniently. We used a structured questionnaire for face-to-face interviews containing sociodemographic variables and job stressors. The severity of insomnia was measured by the Insomnia Severity Scale (ISS). The scale has seven items to evaluate the rate of insomnia, which was categorized as the absence of Insomnia (0-7); sub-threshold Insomnia (8-14); moderate clinical Insomnia (15-21); and severe clinical Insomnia (22-28). To identify clinical insomnia, a cut-off value of 15 was decided primarily. A cut-off score of 15 was initially proposed for identifying clinical insomnia. We performed a chi-square test and adjusted logistic regression to explore the association of different independent variables with clinically significant insomnia using the software SPSS version 25.0. RESULTS: 61.5% of our study participants were females. 44.9% were doctors, 33.9% were nurses, and 21.1% were other health care workers. Insomnia was more dominant among doctors and nurses (16.2% and 13.6%, respectively) than others (4.2%). We found clinically significant insomnia was associated with several job stressors (p < 0.05). In binary logistic regression, having sick leave (OR = 0.248, 95% CI = 0.116, 0.532) and being entitled to risk allowance (OR = 0.367, 95% CI = 0.124.1.081) showed lower odds of developing Insomnia. Previously diagnosed with COVID-19-positive health care workers had an OR of 2.596 (95% CI = 1.248, 5.399), pointing at negative experiences influencing insomnia. In addition, we observed that any training on risk and hazard increased the chances of suffering from Insomnia (OR = 1.923, 95% CI = 0.934, 3.958). CONCLUSION: It is evident from the findings that the volatile existence and ambiguity of COVID-19 have induced significant adverse psychological effects and subsequently directed our HCWs toward disturbed sleep and insomnia. The study recommends the imperativeness to formulate and implement collaborative interventions to help HCWs cope with this crisis and mitigate the mental stresses they experience during the pandemic.

Internet addiction and mental health disorders in high school students in a Peruvian region: a cross-sectional study.

OBJECTIVES: To determine the association between internet addiction disorder (IAD) and anxiety and depressive symptomatology in high school students in two private schools in Chiclayo, Peru, during the COVID-19 pandemic. MATERIALS AND METHODS: Analytical cross-sectional investigation of 505 adolescents from two private schools. The dependent variables were anxiety and depressive symptomatology, measured with the Beck Adapted Depression Questionnaire (BDI-IIA) and the Beck Anxiety Inventory (BAI), respectively. The main independent variable was IAD, measured with the Internet Addiction Test instrument(IATI). Prevalence ratios (PR) and 95% confidence intervals (95%CI) were estimated. RESULTS: The average age was 14.16 years and 54.9% were women. 22.2% and 3.2% presented mild and moderate IAD; respectively. 9.3% presented severe anxiety and 34.3% severe depressive symptomatology. In the simple regression, adolescents with mild, moderate and severe IAD presented 19% (PR = 1.19; 95%CI: 1.05-1.35), 25% (PR = 1.25; 95%CI: 1.02-1.53) and 53% (PR = 1.47; 95% CI: 1.47-1.60) higher prevalence of depressive symptomatology; however, this association was not maintained in the multiple model. Anxiety increased 196% in adolescents with severe IAD (PR = 2.96; 95%CI: 1.86-4.71). CONCLUSION: We found that 2, 1, and 3 out of 10 students presented IAD, depressive symptomatology, and anxiety, respectively. We did not find an association between IAD and depressive symptomatology, but we did find an association with anxiety. Among the factors associated with the development of depressive symptomatology were the male sex, the presence of eating disorders, subclinical insomnia, using devices for more than 2 h, and using the Internet for academic activities. About anxiety, the associated factors are the female sex, the presence of eating disorders, subclinical insomnia, and the use of the Internet as social interaction. We recommend implementing counseling programs in view of the imminent introduction of the Internet as a pillar in education.

Behavioral and psychosocial factors and their effects on insomnia among people undergoing entry quarantine in hotels during COVID-19 pandemic: a cross-sectional study in Guangzhou, China.

BACKGROUND: The COVID-19 pandemic continues to impact global health and China requires a 14-day quarantine for individuals on flights with positive COVID-19 cases. This quarantine can impact mental well-being, including sleep. This study aims to examine the impact of psychosocial and behavioral factors on insomnia among individuals undergoing quarantine in hotels. METHODS: This study was a cross-sectional survey carried out in Guangzhou, China. The data was gathered through online questionnaires distributed to international passengers who arrived in Guangzhou on flights and were required to undergo a 14-day quarantine in hotels arranged by the local government. The questionnaires were sent to the participants through the government health hotline "12,320." RESULTS: Of the 1003 passengers who were quarantined, 6.7% reported significant anxiety and 25.0% had varying degrees of insomnia. Anxiety was positively associated with insomnia (ß = 0.92, P < 0.001), while collectivism (ß = -0.07, P = 0.036), indoor exercise (ß = -0.50, P < 0.001), and the perceived people orientation of the public health service (ß = -0.20, P = 0.001) were negatively associated with insomnia. The study also identified moderating effects, such that a higher sense of collectivism, a greater frequency of indoor exercise, and a higher perception of the people-oriented of the public health service were associated with a lower impact of anxiety on insomnia. These moderating effects were also observed in participants with varying degrees of insomnia. CONCLUSIONS: This study reveals that a proportion of people undergoing entry quarantine experience insomnia and confirms how psychosocial and behavioral factors can alleviate insomnia in this population.

The public health impact of poor sleep on severe COVID-19, influenza and upper respiratory infections.

BACKGROUND: Poor sleep is associated with an increased risk of infections and all-cause mortality but the causal direction between poor sleep and respiratory infections has remained unclear. We examined if poor sleep contributes as a causal risk factor to respiratory infections. METHODS: We used data on insomnia, influenza and upper respiratory infections (URIs) from primary care and hospital records in the UK Biobank (N ≈ 231,000) and FinnGen (N ≈ 392,000). We computed logistic regression to assess association between poor sleep and infections, disease free survival hazard ratios, and performed Mendelian randomization analyses to assess causality. FINDINGS: Utilizing 23 years of registry data and follow-up, we discovered that insomnia diagnosis associated with increased risk for infections (FinnGen influenza Cox's proportional hazard (CPH) HR = 4.34 [3.90, 4.83], P = 4.16 × 10-159, UK Biobank influenza CPH HR = 1.54 [1.37, 1.73], P = 2.49 × 10-13). Mendelian randomization indicated that insomnia causally predisposed to influenza (inverse-variance weighted (IVW) OR = 1.65, P = 5.86 × 10-7), URI (IVW OR = 1.94, P = 8.14 × 10-31), COVID-19 infection (IVW OR = 1.08, P = 0.037) and risk of hospitalization from COVID-19 (IVW OR = 1.47, P = 4.96 × 10-5). INTERPRETATION: Our findings indicate that chronic poor sleep is a causal risk factor for contracting respiratory infections, and in addition contributes to the severity of respiratory infections. These findings highlight the role of sleep in maintaining sufficient immune response against pathogens. FUNDING: Instrumentarium Science Foundation, Academy of Finland, Signe and Ane Gyllenberg Foundation, National Institutes of Health.

6-month consequences of COVID-19 in patients discharged from hospital: a cohort study.

BACKGROUND: The long-term health consequences of COVID-19 remain largely unclear. The aim of this study was to describe the long-term health consequences of patients with COVID-19 who have been discharged from hospital and investigate the associated risk factors, in particular disease severity. METHODS: We did an ambidirectional cohort study of patients with confirmed COVID-19 who had been discharged from Jin Yin-tan Hospital (Wuhan, China) between Jan 7 and May 29, 2020. Patients who died before follow-up; patients for whom follow-up would be difficult because of psychotic disorders, dementia, or readmission to hospital; those who were unable to move freely due to concomitant osteoarthropathy or immobile before or after discharge due to diseases such as stroke or pulmonary embolism; those who declined to participate; those who could not be contacted; and those living outside of Wuhan or in nursing or welfare homes were all excluded. All patients were interviewed with a series of questionnaires for evaluation of symptoms and health-related quality of life, underwent physical examinations and a 6-min walking test, and received blood tests. A stratified sampling procedure was used to sample patients according to their highest seven-category scale during their hospital stay as 3, 4, and 5-6, to receive pulmonary function test, high resolution CT of the chest, and ultrasonography. Enrolled patients who had participated in the Lopinavir Trial for Suppression of SARS-CoV-2 in China received SARS-CoV-2 antibody tests. Multivariable adjusted linear or logistic regression models were used to evaluate the association between disease severity and long-term health consequences. FINDINGS: In total, 1733 of 2469 discharged patients with COVID-19 were enrolled after 736 were excluded. Patients had a median age of 57·0 years (IQR 47·0-65·0) and 897 (52%) were male and 836 (48%) were female. The follow-up study was done from June 16 to Sept 3, 2020, and the median follow-up time after symptom onset was 186·0 days (175·0-199·0). Fatigue or muscle weakness (52%, 855 of 1654) and sleep difficulties (26%, 437 of 1655) were the most common symptoms. Anxiety or depression was reported among 23% (367 of 1616) of patients. The proportions of 6-min walking distance less than the lower limit of the normal range were 17% for those at severity scale 3, 13% for severity scale 4, and 28% for severity scale 5-6. The corresponding proportions of patients with diffusion impairment were 22% for severity scale 3, 29% for scale 4, and 56% for scale 5-6, and median CT scores were 3·0 (IQR 2·0-5·0) for severity scale 3, 4·0 (3·0-5·0) for scale 4, and 5·0 (4·0-6·0) for scale 5-6. After multivariable adjustment, patients showed an odds ratio (OR) of 1·61 (95% CI 0·80-3·25) for scale 4 versus scale 3 and 4·60 (1·85-11·48) for scale 5-6 versus scale 3 for diffusion impairment; OR 0·88 (0·66-1·17) for scale 4 versus scale 3 and OR 1·76 (1·05-2·96) for scale 5-6 versus scale 3 for anxiety or depression, and OR 0·87 (0·68-1·11) for scale 4 versus scale 3 and 2·75 (1·61-4·69) for scale 5-6 versus scale 3 for fatigue or muscle weakness. Of 94 patients with blood antibodies tested at follow-up, the seropositivity (96·2% vs 58·5%) and median titres (19·0 vs 10·0) of the neutralising antibodies were significantly lower compared with at the acute phase. 107 of 822 participants without acute kidney injury and with an estimated glomerular filtration rate (eGFR) of 90 mL/min per 1·73 m2 or more at acute phase had eGFR less than 90 mL/min per 1·73 m2 at follow-up. INTERPRETATION: At 6 months after acute infection, COVID-19 survivors were mainly troubled with fatigue or muscle weakness, sleep difficulties, and anxiety or depression. Patients who were more severely ill during their hospital stay had more severe impaired pulmonary diffusion capacities and abnormal chest imaging manifestations, and are the main target population for intervention of long-term recovery. FUNDING: National Natural Science Foundation of China, Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, National Key Research and Development Program of China, Major Projects of National Science and Technology on New Drug Creation and Development of Pulmonary Tuberculosis, and Peking Union Medical College Foundation.

Use of machine learning to identify risk factors for insomnia.

IMPORTANCE: Sleep is critical to a person's physical and mental health, but there are few studies systematically assessing risk factors for sleep disorders. OBJECTIVE: The objective of this study was to identify risk factors for a sleep disorder through machine-learning and assess this methodology. DESIGN, SETTING, AND PARTICIPANTS: A retrospective, cross-sectional cohort study using the publicly available National Health and Nutrition Examination Survey (NHANES) was conducted in patients who completed the demographic, dietary, exercise, and mental health questionnaire and had laboratory and physical exam data. METHODS: A physician diagnosis of insomnia was the outcome of this study. Univariate logistic models, with insomnia as the outcome, were used to identify covariates that were associated with insomnia. Covariates that had a p<0.0001 on univariate analysis were included within the final machine-learning model. The machine learning model XGBoost was used due to its prevalence within the literature as well as its increased predictive accuracy in healthcare prediction. Model covariates were ranked according to the cover statistic to identify risk factors for insomnia. Shapely Additive Explanations (SHAP) were utilized to visualize the relationship between these potential risk factors and insomnia. RESULTS: Of the 7,929 patients that met the inclusion criteria in this study, 4,055 (51% were female, 3,874 (49%) were male. The mean age was 49.2 (SD = 18.4), with 2,885 (36%) White patients, 2,144 (27%) Black patients, 1,639 (21%) Hispanic patients, and 1,261 (16%) patients of another race. The machine learning model had 64 out of a total of 684 features that were found to be significant on univariate analysis (P<0.0001 used). These were fitted into the XGBoost model and an AUROC = 0.87, Sensitivity = 0.77, Specificity = 0.77 were observed. The top four highest ranked features by cover, a measure of the percentage contribution of the covariate to the overall model prediction, were the Patient Health Questionnaire depression survey (PHQ-9) (Cover = 31.1%), age (Cover = 7.54%), physician recommendation of exercise (Cover = 3.86%), weight (Cover = 2.99%), and waist circumference (Cover = 2.70%). CONCLUSION: Machine learning models can effectively predict risk for a sleep disorder using demographic, laboratory, physical exam, and lifestyle covariates and identify key risk factors.

Physical and stressful psychological impacts of prolonged personal protective equipment use during the COVID-19 pandemic: A cross-sectional survey study.

BACKGROUND: Healthcare workers (HCWs) caring for COVID-19 infected patients are exposed to stressful and traumatic events with potential for severe and sustained adverse mental and physical health consequences. Our aim was to assess the magnitude of physical and mental health outcomes of HCWs due to the prolonged use of personal protective equipment (PPE) treating COVID-19 patients. METHODS: This cross-sectional study assessed the symptoms of stress, anxiety, insomnia, and psychological resilience using the Stress and Anxiety to Viral Epidemics (SAVE) scale, Insomnia Severity Index (ISI), and Resilience Scale (RS), respectively, in Italy between 1st February and 31st March 2022. The physical outcomes reported included vertigo, dyspnea, nausea, micturition desire, retroauricular pain, thirst, discomfort at work, physical fatigue, and thermal stress. The relationships between prolonged PPE use and psychological outcomes and physical discomforts were analyzed using Generalized Linear Models (GLMs). We calculated the factor mean scores and a binary outcome to measure study outcomes. FINDINGS: We found that 23% of the respondents reported stress related symptoms, 33% anxiety, 43% moderate to severe insomnia, and 67% reported moderate to very low resilience. The GLMs suggested that older people (>55 years old) are less likely to suffer from stress compared to younger people (<35 y.o); conversely, HCW aged more than 35 years are more inclined to suffer from insomnia than younger people (<35 y.o). Female HCW reported a lower probability of resilience than males. University employed HCWs were less likely to report anxiety than those who worked in a community hospital. The odds of suffering from insomnia for social workers was significantly higher than for other HCWs. Female HCW>3 years old, enrolled in training programs for nursing, social work, technical training and other healthcare professionals increased the probability of reported physical discomforts. HCW that worked on non COVID-19 wards and used PPE for low-medium exposure level, were at lower risks for lasting physical side effects as compared to the HCW who worked in high-risk PPE intense, COVID-19 environments. INTERPRETATION: The study suggests that frontline HCWs who had extensive PPE exposure while directly engaged in the diagnosis, treatment, and care for patients with COVID-19 are at significant risks for lasting physical and psychological harm and distress.

Anxiety, depression, insomnia, and PTSD among college students after optimizing the COVID-19 response in China.

BACKGROUND: The number of COVID-19 infections has increased sharply and quickly after optimizing the COVID-19 response in China. In the context of this population-size infection, college students' psychological response is yet to be understood. METHODS: A cross-sectional study was designed to investigate anxiety, depression, insomnia, and post-traumatic stress disorder (PTSD) symptoms among college students from December 31, 2022, to January 7, 2023. The questionnaire included the Generalized Anxiety Disorder 7 (GAD-7), Patient Health Questionnaire 9 (PHQ-9), Insomnia Severity Index (ISI), Impact of Event Scale (IES-R), and self-designed questionnaire. RESULTS: Of the 22,624 respondents, the self-reported prevalence of anxiety, depression, insomnia, PTSD, and any of the four psychological symptoms appeared as 12.7 %, 25.8 %, 11.6 %, 7.9 %, and 29.7 %, respectively. The self-reported COVID-19 infection rate was 80.2 %. Changes in the place for learning, longer time online, not recovering after infection, a higher proportion of family member infection, insufficient drug reserve, worry about sequela after infection, future studies, or employment contributed to a higher risk of anxiety/depression/insomnia symptoms or PTSD symptoms. Multinomial logistic regression showed that those who spent more extended time on the Internet, recovered after infection, and had insufficient drug reserves were less likely to have PTSD than anxiety/depression/insomnia symptoms. LIMITATIONS: The study was a non-probability sampling survey. CONCLUSIONS: Anxiety, depression, insomnia, and PTSD were common psychological symptoms among college students when infection went through a large-scale population. This study highlights the importance of continuing to care for the psychological symptoms of college students, especially timely responses to their concerns related to the epidemic situation and COVID-19 infection.

Brain Performance Capacity among a Sample of Aviation Crews: A Cross-sectional Survey and Pilot Study (preprint)

Background: To assess brain performance capacity (BPC) in relation to sleep quality, fatigue, and mental workload as evaluation indicators with explore the possible correlation with COVID-19. Methods: A cluster sampling method was adopted to randomly select 259 civil air crew members. The measurement of sleep quality, fatigue and mental workload (MWL) were assessed using Pittsburgh Sleep Quality Index (PSQI), Multidimensional Fatigue Inventory (MFI-20) and NASA Task Load Index. The impact of COVID-19 included 7 dimensions scored on a Likert scale. Canonical correlation analysis (CCA) was conducted to examine the relationship between BPC and COVID-19. Results: A total of 259 air crew members participated in the survey. Participants’ average PSQI score was 7.8 (SD = 3.8), with 49.8% reporting prevalence of insomnia, mostly of a minor degree. Participants’ MFI was an average was 56.1 (SD =10.0), with 100% reporting some incidence of fatigue, mainly severe. The weighted mental workload (MWL) score was an average of 43.1 (SD = 17.5), with reports of mostly a mid-level degree. There was a significant relationship between BPC and COVID-19, with a canonical correlation coefficient of 0.507 (P<0.001), an eigenvalue of 0.4 and a contribution rate of 69.1%. All components of BPC variable set: PSQI, MFI and MWL contributed greatly to BPC, with an absolute canonical loading of 0.8, 0.6 and 0.7, respectively; the same was true for the COVID-19 variable set, with absolute canonical loadings ranging from 0.6 to 0.95. Conclusion: CCA demonstrated that sleep, fatigue and mental workload could well evaluated BPC, and there was a medium correlation between BPC and the impact of COVID-19 in civil air crews. Trial registration: This study is registered in the Chinese Clinical Trial Registry, number ChiCTR2100053133.