Mental disorders during the pandemic of a new coronavirus infection: causes and predisposing factors.

Objective: to study the causes and predictors of mental disorders during the COVID-19 epidemic in those who turned to psychiatrist for the first time, as well as in patients with already diagnosed mental illness. Patients and methods. We examined 100 patients who turned to a psychiatrist due to a deterioration in their mental state during the pandemic, 50 patients were newly diagnosed (Group 1) and 50 with previously diagnosed mental disorders (Group 2). The study was carried out by a clinical method using a specially designed map, followed by statistical processing of the obtained data. Results and discussion. Mental disorders caused by the COVID-19 pandemic more often occurred at a young age, in patients with higher and secondary specialized education, and in single patients. In the 1st group, as a result of exposure to psychogenic factors (the influence of the media, quarantine, economic changes), anxiety (36.8%) and depressive (21.1%) disorders occurred more often, and after the coronavirus infection, depressive disorders were in the first place (54.2%). The 2nd group mostly included patients with endogenous disorders (bipolar affective disorder - 24%, recurrent depressive disorder - 20%, schizophrenia - 20%), which were exacerbated more often as a result of COVID-19, to a lesser extent - psychogenic (experiences associated with a change in material status and illness of relatives). Obsessive-compulsive disorder, generalized anxiety disorder, somatoform disorders have been associated with epidemic factors. Conclusion. The results obtained indicate that there are differences between the mental disorders that first appeared during the pandemic and the exacerbations of the condition in mentally ill patients, which relate to the predictors, causes and clinical manifestations of these disorders.Copyright © 2022 Ima-Press Publishing House. All rights reserved.

Clinical and laboratory indicators in predicting the risk of chronic heart failure in COVID-19 survivors.

Coronavirus disease has many systemic disease symptoms and has severe consequences for the cardiovascular system. Objective. To assess the role of clinical and laboratory indicators in determining the risk of chronic heart failure (CHF) in COV-ID-19 survivors. Material and methods. In total, 151 patients treated in a monoinfectious hospital from 03.11.20 to 10.02.21 with a confirmed diagnosis of COVID-19 were retrospectively selected. Medical history and laboratory data were collected by reviewing electronic medical records. The data included age, gender, body mass index, smoking status, and comorbidities. The laboratory data included the results of hematology and blood chemistry, coagulation, and the levels of acute-phase proteins. The CHF occurrence was used as the study endpoint. Results and discussion. The study patients were divided into two groups depending on the presence of CHF: group 1 included 46 patients with CHF, and group 2 included 105 patients without CHF. The median age was 66.2 (50-92) years;91 (60.3%) were females. Laboratory tests, such as levels of the hs-C-reactive protein, lactate dehydrogenase, procalcitonin, creatinine, and bilirubin, were statistically significantly different in patients of the study groups, and the median values were higher in patients with CHF. Neutrophil-lymphocyte ratio (NLR) showed statistically significant differences between groups: in patients with CHF, the median was 4.97% compared to 3.62% (p=0.011) in those without CHF. The most significant predictors of an increased risk of CHF were age >=66 years (OR=8.038, p<0.001), procalcitonin level >=0.09 ng/mL (increased the CHF risk by 3.8 times, p<0.001), thrombocy-topenia <=220x109/L (p=0.010), an NLR ratio >=4.11% (p=0.010), and a history of chronic kidney disease (p=0.018). Conclusion. A model has been developed to determine the factors closely associated with the risk of chronic heart failure in CO-VID-19 survivors.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.

GENETIC PATTERN OF THE COVID-19 COURSE AND REINFECTION

A new coronavirus infection (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) broke out at the end of 2019 in Wuhan (China). The disease has become a global pandemic and claimed more than 6 million lives after spreading rapidly around the world. Issues related to the complicated course of COVID-19 mechanisms continue to be the subject of active study. It is known that morbidity and mortality increase dramatically with increasing age and concomitant diseases, including obesity, diabetes, cancer, and cardiovascular diseases. Although most infected people recover, even young and otherwise healthy patients can get sick with this disease. In this regard, an urgent task is to search for specific genetic factors that can explain the predisposition of people to infection and the development of a severe COVID-19 form. Human genetic determinants can provide the scientific basis for disease prediction and the development of personalized therapies to counteract the epidemic. In addition, cases of repeated infection with SARS-CoV-2 are increasingly being registered, which occurs 1–6 months after initial infection on average and depends on the virus genome structure. Studies conducted on sequencing viral genomes have shown that some patients were re-infected with the same strain of coronavirus, while others were different. This, in turn, causes researchers concerns about the effectiveness of immunity after infection and vaccine reliability. The genetic characteristics of a person and a virus commonly determine the tendency for reinfection. It is difficult to determine the true COVID-19 reinfection prevalence, which is explained by the low detectability of asymptomatic reinfection and the fact that many patients with a mild course of the disease were not tested at an early stage of the pandemic. Therefore, the true prevalence of reinfection with COVID-19 does not reflect the current reality. There are many more cases of reinfection than are described in the literature. In this regard, the true contribution of a virus' genetic features to reinfection of COVID-19 can be determined only after population studies, and when developing immunization programs against a COVID-19, it is necessary to take into account the prevalence of reinfection in the population. The article can be used under the CC BY-NC-ND 4.0 license © Authors, 2022.

The Post-traumatic Stress Disorder in COVID-19 Recovered Patients: A Cross-sectional Study

Objective Post-traumatic stress disorder (PTSD) is one of the anxiety disorders caused by a specific event, which can be catastrophic events (natural disasters, war, imprisonment in a forced labor camp) or everyday adversities (death of relatives, divorce, carrying bags). Since patients who have recovered from COVID-19 are exposed to such events, this research was conducted to determine the prevalence of PTSD in this group.Materials & Methods This study was cross-sectional. The statistical population included all patients who recovered from COVID-19 between November 2021 and February 2022 in Hamedan City, Iran;based on Krejcie and Morgan's sample size table, 185 patients were selected by simple random sampling method. The research tool was the demographic questionnaire and the Mississippi post -traumatic stress disorder questionnaire (Mississippi PTSD);the data were analyzed using the Mann -Whitney and Kruskal-Wallis tests.Results The results showed that the Mean +/- SD score of PTSD was 80.37 +/- 17.37 in the subjects who recovered from COVID-19. The relationship between the demographic variables of gender (P=0.01), education (P=0.039), occupation (P=0.24), marriage (P=0.62), age (P=0.048), weight (P=0.047), height (P=0.023) with PTSD were reported.Conclusion The results showed that 76.2% of people who recovered from COVID-19 were exposed to PTSD with moderate and high severity;therefore, techniques to reduce anxiety from the corona -virus are recommended.

Clinical and laboratory predictors of disease severity and outcome in COVID 19 infected patients in Suez Canal University Hospital, single center study from Egypt

Background: The novel corona virus is a high contagious disease, declared by World Health Organization (WHO) as a global pandemic in 2020 with profound impact on morbidity and mortality, assessment of outcomes in infected patients and knowledge of prediction of mortality and morbidity are important. We aimed to assess the clinical and laboratory findings in predicting COVID-19 severity and outcome in patients admitted to Suez Canal University Teaching Hospital. Methodology: This cross-sectional prospective study included 500 confirmed PCR COVID-19 infected patients, selected through random sampling. A structured checklist was used to collect patient data. Results: Mean age was 61.8 years, 56.2% were males, 74.8% had comorbidities. Lung involvement was evident in more than 75% on CT, 17.2% had leukopenia, 42.2% had lymphocytopenia between 5 – 10% and 93% of the patients had elevated neutrophil-lymphocyte ratio. 65.8% had elevated D-dimer, and elevated liver and kidney functions were found in 40.6% and 25% respectively. The mortality rate in studied population was 30.2% and it was significantly associated with old age, hypoxemia, having high involvement of the lungs on CT. Decreased WBC count, high D-dimer level and high NLR associated with severity and increased death rate of the disease. Conclusion: The study revealed many findings with impact on the patient's severity and outcome old age, laboratory findings, CT imaging and need to antiviral therapy the most predicting factors of the severity and prognosis of the patient. © 2020 The author (s). Published by Zagazig University.

Asthma in the elderly and COVID-19: results of the 90-day post-hospital follow-up.

Background. After the first wave of the new SARS-CoV-2 coronavirus infection, the researchers focused on identifying potential short-and long-term complications of COVID-19, especially in high-risk patients, after prolonged hospitalization and intensive care. Objective. To study the outcomes, adverse effects of severe COVID-19 and their predictors 90 days after hospital discharge in elderly patients with asthma. Material and methods. The study included elderly patients (101 subjects, 42 males and 59 females;median age 74 (67;79) years) with asthma, discharged from the hospital after treatment of severe COVID-19. They were followed up for 90 days after discharge. In the hospital, COVID-19 was confirmed by laboratory tests (polymerase chain reaction method) and/or clinically and radiologically. All patients had a documented history of asthma according to GINA 2020 criteria. Results and discussion. During the 90-day post-hospital follow-up, 86 (85%) patients survived, and 15 (15%) died after discharge. Deaths were reported within 1 to 4 weeks after discharge: 6 subjects died during re-hospitalization, 6 at home, and 3 in a rehabilitation center. The multivariate regression analysis model, adjusted for all statistically significant indicators, and the ROC analysis showed the most significant predictors of 90-day post-hospital mortality and their threshold values. They include the Charlson comorbidity index >=4 points, lung damage according to computed tomography >=30%, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The analysis showed that 90-day post-hospital mortality depends on combinations of identified risk factors;a combination of two, three, and especially four risk factors statistically significantly is associated with patients' lower average survival time. Conclusion. The key risk factors for 90-day post-hospital mortality in elderly patients with asthma after severe COVID-19 include the Charlson comorbidity index, lung damage >=30% according to computed tomography, the absolute number of eosinophils <=100 cells/muL, and concomitant diabetes mellitus. The 90-day post-hospital survival rate is correlated with the number of risk factors identified in patients. The effect of asthma severity on 90-day post-hospital mortality in elderly patients was not observed.Copyright © 2023, Media Sphera Publishing Group. All rights reserved.

Prevalence a prediktory sebevražednosti mezi studenty ošetřovatelství v Indonésii

Úvod: Studenti ošetřovatelství jsou během pandemie covidu-19 zranitelnou populací, protože zažívají vyšší úroveň stresu a problémů s duševním zdravím než studenti mimo zdravotní péči, což je vystavuje vyššímu riziku sebevražedného chování. Cíl: Prozkoumat sebevražednost mezi studenty ošetřovatelství a posoudit souvislost mezi nezávislými proměnnými a sebevražedností. Metody: Tato průřezová studie zahrnovala 670 studentů ošetřovatelství z 5 indonéských univerzit, kteří byli vybráni metodou postupného vzorkování. Vlastní validované nástroje se skládaly z 8 sekcí: sociodemografický dotazník, RSES k posouzení sebe- úcty, BHS k posouzení beznaděje, UCLA-3 k posouzení osamělosti, GSES k posouzení sebeúčinnosti, PHQ-9 k posouzení deprese, CD-RISC-10 k posouzení odolnosti a SBQ-R k posouzení sebevražednosti. K identifikaci významných prediktorů sebevražednosti byla použita binární logistická regrese. Výsledky: Prevalence sebevražednosti mezi studenty ošetřovatelství byla 22,8 %. Se sebevražedností byly významně spojeny následující faktory (p < 0,05): nízká odolnost (AOR = 2,044;95 %CI: 1,309-3,192), osamělost (AOR = 1,609;95 %CI: 1,040-2,492), beznaděj (AOR = 48,48 95 %CI: 2,356-8,398) a deprese (AOR = 9,413;95 %CI: 5,795-15,288). Závěr: Tato zjištění poskytují důkaz, že odolnost, osamělost, beznaděj a deprese jsou rizikovými faktory sebevražednosti mezi studenty ošetřovatelství. Tento výsledek lze použít jako základ pro rozvoj vhodných strategií prevence sebevražd.Alternate :Introduction: Nursing students are a vulnerable population during the COVID-19 pandemic because they experience a higher level of stress and mental health problems than the non-healthcare student population, putting them at a higher risk for suicidal behaviour. Aim: To explore suicidality among nursing students and assess the association between independent variables and suicidality. Methods: This cross-sectional study involved 670 nursing students from 5 Indonesian universities who were recruited using consecutive sampling. Self-administered validated instruments consisted of 8 sections: sociodemographic questionnaire, RSES to assess self-esteem, BHS to assess hopelessness, UCLA-3 to assess loneliness, GSES to assess self-efficacy, PHQ-9 to assess depression, CD-RISC-10 to assess resilience, and SBQ-R to assess suicidality. Binary logistic regression was employed to identify significant predictors of suicidality. Results: Suicidality prevalence among nursing students was 22.8%. The following factors were significantly associated with suicidality (p < 0.05): low resilience (AOR = 2.044;95%CI: 1.309-3.192), loneliness (AOR = 1.609;95%CI: 1.040-2.492), hopelessness (AOR = 4.448;95%CI: 2.356-8.398), and depression (AOR = 9.413;95%CI: 5.795-15.288). Conclusions: These findings provide evidence that resilience, loneliness, hopelessness, and depression are risk factors for suicidality among nursing students. This outcome can be used as a basis to develop appropriate suicide prevention strategies.

Hematological and coagulation parameters as predictors of death by Coronavirus disease in hospitalized patients: a Brazilian follow-up study

Abstract This study aimed to evaluate the hematological and coagulation parameters according to the clinical outcomes of coronavirus disease (COVID-19). We analyzed the hematological and coagulation parameters of hospitalized patients with COVID-19 at admission, and two and three weeks during hospitalization. To assess the performance of these parameters in predicting poor outcomes, receiver operating characteristic (ROC) curves were created. We studied 128 patients with COVID-19 (59.2±17.7 years, 56% male). Non-survivors (n=54, 42%) presented significant alterations in hematological and coagulation parameters at admission, such as increased in white blood cells (WBC), neutrophil, and band cell counts, as well as elevated prothrombin time (PT), activated partial thromboplastin time, and D-dimer levels. During follow-up, the same group presented a gradual increase in D-dimer and PT levels, accompanied by a reduction in PT activity, hemoglobin, and red blood cell count (RBC). ROC curves showed that WBC, neutrophil, and band cell counts presented the best area under the curve (AUC) values with sensitivity and specificity of >70%; however, a logistic regression model combining all the parameters, except for RBC, presented an AUC of 0.89, sensitivity of 84.84%, and specificity of 77.41%. Our study shows that significant alterations in hematological and coagulation tests at admission could be useful predictors of disease severity and mortality in COVID-19.

Retrospective Analysis of the Psychological Predictors of Public Health Support in Bulgarians at the Beginning of the Coronavirus Pandemic.

The earliest critical context of the pandemic, preceding the first real epidemiological wave of contagion in Bulgaria, was examined using a socio-affective perspective. A retrospective and agnostic analytical approach was adopted. Our goal was to identify traits and trends that explain public health support (PHS) of Bulgarians during the first two months of the declared state of emergency. We investigated a set of variables with a unified method within an international scientific network named the International Collaboration on Social & Moral Psychology of COVID-19 (ICSMP) in April and May 2020. A total of 733 Bulgarians participated in the study (67.3% females), with an average age of 31.8 years (SD = 11.66). Conspiracy Theories Beliefs were a significant predictor of lower PHS. Psychological Well-Being was significantly associated with Physical Contact and Anti-Corona Policy Support. Physical Contact was significantly predicted by fewer Conspiracy Theories Beliefs, higher Collective Narcissism, Open-mindedness, higher Trait Self-Control, Moral Identity, Risk Perception and Psychological Well-Being. Physical Hygiene compliance was predicted by fewer Conspiracy Theories Beliefs, Collective Narcissism, Morality-as-Cooperation, Moral Identity and Psychological Well-Being. The results revealed two polar trends of support and non-support of public health policies. The contribution of this study is in providing evidence for the affective polarization and phenomenology of (non)precarity during the outbreak of the pandemic.

Serum IL-23, IL-10, and TNF-α predict in-hospital mortality in COVID-19 patients.

Objective: The hyperinflammatory response, caused by severe acute respiratory syndrome-2 (SARS-CoV-2), is the most common cause of death in patients with coronavirus disease 2019 (COVID-19). The etiopathogenesis of this illness is not fully understood. Macrophages appear to play a key part in COVID-19's pathogenic effects. Therefore, this study aims to examine serum inflammatory cytokines associated with the activation state of macrophages in COVID-19 patients and attempt to find accurate predictive markers for disease severity and mortality risk in hospital. Methods: 180 patients with COVID-19 and 90 healthy controls (HCs) participated in this study. Patients were divided into three different subgroups, mild (n=81), severe (n=60), and critical groups (n=39). Serum samples were collected and IL (Interleukin)-10, IL-23, tumor necrosis factor-alpha (TNF-α), interferon-gamma (IFN-γ), IL-17, monocyte chemoattractant protein-1 (MCP-1) and chemokine ligand 3 (CCL3) were determined by ELISA. In parallel, myeloperoxidase (MPO) and C-reactive protein (CRP) were measured using colorimetric and electrochemiluminescence methods, respectively. Data were collected, and their associations with disease progression and mortality were assessed using regression models and receiver operating characteristic (ROC) curves. Results: Compared to HCs, a significant increase in IL-23, IL-10, TNF-α, IFN-γ and MCP-1, were observed in COVID-19 patients. Serum levels of IL-23, IL-10, and TNF-α were significantly higher in COVID-19 patients with critical cases compared to mild and severe cases, and correlated positively with CRP level. However, non-significant changes were found in serum MPO and CCL3 among the studied groups. Moreover, significant positive association has been observed among increased IL-10, IL-23 and TNF-α in serum of COVID-19 patients. Furthermore, a binary logistic regression model was applied to predict death's independent factors. Results showed that IL-10 alone or in combination with IL23 and TNF-α are strongly linked with non-survivors in COVID-19 patients. Finally, ROC curve results uncovered that IL-10, IL-23 and TNF-α were excellent predictors for prognosing COVID-19. Conclusion: The elevations of IL-10, IL-23, and TNF-α levels were seen in severe and critical cases of COVID-19 patients and their elevations were linked to the in-hospital mortality of the disease. A prediction model shows that the determination of these cytokines upon admission is important and should be done on COVID-19 patients as a way of evaluating the prognosis of the disease. COVID-19 Patients with high IL-10, IL-23, and TNF-α on admission are more likely to experience a severe form of the disease; therefore, those patients should be cautionary monitored and treated.

Predictors of second COVID-19 booster dose or new COVID-19 vaccine hesitancy among nurses: A cross-sectional study.

AIMS AND OBJECTIVES: To assess the levels of second COVID-19 booster dose/new COVID-19 vaccine hesitancy among nurses and explore the potential predictors of vaccine hesitancy. BACKGROUND: COVID-19 full vaccination seems to be highly effective against highly contagious variants of SARS-CoV-2. Healthcare workers are at high-risk group since they have experienced high levels of COVID-19-associated morbidity and mortality. DESIGN: An on-line cross-sectional study was carried out in Greece in May 2022, using a self-administered questionnaire. METHODS: The study population included nurses in healthcare services who were fully vaccinated against COVID-19 at the time of study. We considered socio-demographic characteristics, COVID-19-related variables, and attitudes toward COVID-19 vaccination and pandemic as potential predictors of vaccine hesitancy. We applied the STROBE checklist in our study. RESULTS: Among 795 nurses, 30.9% were hesitant toward a second booster dose or a new COVID-19 vaccine. Independent predictors of hesitancy included lower educational level, absence of a chronic condition, good/very good self-perceived physical health, lack of flu vaccination during 2021, front-line nurses that provided healthcare to COVID-19 patients, nurses that had not been diagnosed with COVID-19 and nurses that had at least one relative/friend that has died from COVID-19. Moreover, increased compliance with hygiene measures, increased fear of a second booster dose/new COVID-19 vaccine and decreased trust in COVID-19 vaccination were associated with increased hesitancy. CONCLUSIONS: Our study shows that a significant percentage of nurses are hesitant toward a second booster dose/new COVID-19 vaccine. This initial hesitancy could be a barrier to efforts to control the COVID-19 pandemic. RELEVANCE TO CLINICAL PRACTICE: Nurses' role during the COVID-19 pandemic is essential since they are the front-line healthcare workers empowering the public with their passion and empathy. There is a need to communicate COVID-19 vaccine science in a way that is accessible to nurses in order to decrease COVID-19 vaccine hesitancy. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

Predictors of a weak antibody response to COVID-19 mRNA vaccine in systemic lupus erythematosus.

OBJECTIVES: To characterize the antibody response to COVID-19 mRNA vaccination in patients with Systemic Lupus Erythematosus (SLE) and identify predictors of poor response. METHODS: SLE patients who are followed at the Beth Israel Deaconess Medical Center Lupus Cohort (BID-LC) were enrolled. SARS-CoV-2 IgG Spike antibody was measured in patients who received two doses of either the BNT162b2 (Pfizer-BioNTech) or the mRNA-1273 (Moderna) COVID-19 vaccine (n = 62). We defined non-responders as patients with an IgG Spike antibody titer less than two-fold (< 2) the index value of the test and responders as patients with antibody levels greater or equal to two-fold (≥ 2). A web-based survey was used to collect information regarding immunosuppressive medication use and SLE flares after vaccination. RESULTS: In our cohort of lupus patients, 76% were vaccine responders. The use of two or more immunosuppressive drugs was associated with being a non-responder (Odds Ratio 5.26; 95% CI 1.23-22.34, p = 0.02). Both Belimumab use and higher Prednisone dose were associated with vaccine non-response (p = 0.04 and p = 0.04). The non-responder group had higher mean levels of serum IL-18 than the responder group (p = 0.04) as well as lower C3 levels (p = 0.01). Lupus flares and breakthrough infections were uncommon post-vaccination. CONCLUSIONS: Immunosuppressive medications have a negative impact on vaccine humoral response in SLE individuals. We observed a trend towards vaccine no-response in BNT162b2 recipients and a relationship between IL-18 and impaired antibody response that merits further investigation.

[Predictors of severe course of new coronavirus infection (COVID-19): study design].

AIM: To identify predictors of the severe course of a new coronavirus infection. MATERIALS AND METHODS: A retrospective analysis of 120 clinical case histories of patients hospitalized in hospitals in Tyumen with a confirmed diagnosis of COVID-19 within one year (01.08.2020-01.08.2021) was carried out. The patients were divided into two groups: 1st - with a favorable outcome (n=96), 2nd - with an unfavorable (fatal) outcome (n=24). For a more complete analysis, scales for assessing the clinical condition of patients (SHOCK-COVID), severity assessment (NEWS2) were used. Information processing was carried out in the IBM.SPSS.Statistics-19 program (USA). RESULTS: As a result of the study, the median age for the 1st group was significantly lower (58 years) than for patients of the 2nd group (69 years; p=0.029). A certain set of laboratory parameters for group 2 patients deviate significantly from the reference values (C-reactive protein - CRP - 7.6 [4.7; 15.2] mg/dl, D-dimer - 1.89 [1.36; 5.3] mcg/ml, ferritin - 605 [446.7; 792] ng/ml). When analyzed in groups, taking into account the main markers of the severity of the disease, using the V.Yu. Mareev CCAS-COVID (Clinical Condition Assessment Scale) scale, for the 1st group, the sum of the set of parameters was 6 [2; 7] points, which corresponds to the average severity of coronavirus infection, for the 2nd group 13 [9; 16] points - severe course. For patients of the 2nd group, a significant increase in the indicators of an unfavorable prognosis was revealed in comparison with the 1st group. CONCLUSION: Thus, in this study, the level of CRP, ferritin, D-dimer, the percentage of lung tissue damage according to computed tomography results, SaO2 were significantly associated with an unfavorable prognosis.

The Psychosocial Impact of COVID-19 on an Adult Indian Population.

BACKGROUND: Coronavirus disease (COVID-19) was a pandemic with many physical, psychological, and socioeconomic effects. COVID-19 caused a global increase in anxiety and depression because of its novelty, high infectivity, varied presentation, and unpredictable mortality. In the face of collapsing healthcare facilities, monetary setbacks, and loneliness because of lockdowns, people were anxious, and this was compounded by media sensationalism. We aimed to study the psychosocial impact of COVID-19 on the adult Indian population. METHODS: An online survey using SurveyMonkey was floated through WhatsApp messages in April 2020, using the 'chain-referral sampling' method. Responses from individuals >18 years were included, and questions included age, sex, occupation, demographics, and socioeconomic conditions. The prevalence of anxiety and depression was assessed using the Generalized Anxiety Disorder (GAD-7) and the Patient Health Questionnaire (PHQ-9) scales. Data was analyzed using IBM SPSS software, and predictors of anxiety and depression were assessed. RESULTS: A total of 2640 responses from individuals between 18 years and 81 years were analyzed, of which 39% were from females and 85% from those <50 years of age. There were students (15.6%), teachers (10.7%), healthcare workers (16.8%), homemakers (9%), and daily wage laborers (4.1%), among others. Nearly 80% lived in cities, 55% had salaried jobs, 37% were working from home, 22% were temporarily unemployed, 10% were feeling work stress, 11% had increased alcohol intake, and 7.5% saw an increase in domestic violence. The income of 50% was adversely affected. Nearly 50% of our respondents had some symptoms of anxiety, and 23% had significant anxiety (GAD ≥5). The presence of anxiety was significantly higher in females, younger adults, city dwellers, healthcare workers, unemployed people, individuals living away from home, those without fixed salaries, those with work stress, and in people whose incomes had been adversely affected by the pandemic. On logistic regression analysis, female sex, younger age, unemployment, lack of salaried jobs, work stress, being a healthcare worker, and media reports were independent predictors of anxiety. About 60% of our respondents had some symptoms of depression, with 26% having significant depression (PHQ-9 ≥5). The presence of depression was significantly higher in females, younger adults, city dwellers, unemployed people, individuals living away from home without fixed salaries, and people with work stress. On logistic regression analysis, younger age, female sex, unemployment, lack of salaried jobs, work stress, and media reports were independent predictors of depression. Among our respondents, 70% used the time during the lockdown to study, 77% caught up with their families, and 56% reconnected with hobbies. Nearly 88% of our respondents had adjusted to their changing circumstances, helped by their religious beliefs and faith, the support of family and friends, good government measures, and the assurance of healthcare. CONCLUSIONS:  Significant anxiety and depression were seen in 23% and 26% of respondents, respectively. Being a healthcare worker was an independent predictor of anxiety. Female sex, younger age, unemployment, work stress, and sensational media reports were independent predictors of both anxiety and depression.

Predictors of job satisfaction among teachers in Germany during the SARS-CoV-2 pandemic: cross-sectional results of a nationwide online questionnaire.

Introduction: During the SARS-CoV-2 pandemic teaching was changed several times to distance learning. To consider the associated stresses and challenges for teachers a nationwide cross-sectional study was performed in March 2021 in which N = 31,089 teachers from Germany participated. Methods: A multiple linear regression model with stepwise inclusion of thematically sorted variables (sociodemographic, SARS-CoV-2- and work-related variables) was used to identify relevant predictors of job satisfaction. Results: The analysis revealed that work-related variables were significant predictors of job satisfaction. In the third regression model, when all variables are included the adjusted R2 was 0.364. Overall, the results showed that, e.g., work predictability (b = 0.097), influence at work (b = 0.118), and meaning of work (b = 0.212) increased job satisfaction. In contrast, increased emotional exhaustion (b = -0.016), feelings of unfair treatment (b = -0.048), and work family conflicts (b = -0.154) deteriorated job satisfaction. Discussion: The results indicate that future research should focus especially the work-related topics in more detail and that job satisfaction is a useful concept for analyzing working conditions from a public health point of view.

Recurrent/Subsequent Stroke and Associated Outcomes in Geriatric Patients with OSA and Prior Stroke Events: A Retrospective Study Using the 2019 National Inpatient Sample.

Background: Obstructive sleep apnea (OSA) increases the risk of stroke and cardiovascular diseases. However, its impact on geriatric patients with a prior history of stroke/transient ischemic attack (TIA) has not been adequately studied. Methods: We utilized the 2019 National Inpatient Sample in the US to identify geriatric patients with OSA (G-OSA) who had a prior history of stroke/TIA. We then compared subsequent stroke (SS) rates among sex and race subgroups. We also compared the demographics and comorbidities of SS+ and SS- groups and utilized logistic regression models to assess outcomes. Results: Out of 133,545 G-OSA patients admitted with a prior history of stroke/TIA, 4.9% (6520) had SS. Males had a higher prevalence of SS, while Asian-Pacific Islanders and Native Americans had the highest prevalence of SS, followed by Whites, Blacks, and Hispanics. The SS+ group had higher all-cause in-hospital mortality rates, with Hispanics showing the highest rate compared to Whites and Blacks (10.6% vs. 4.9% vs. 4.4%, p < 0.001), respectively. Adjusted analysis for covariates showed that complicated and uncomplicated hypertension (aOR 2.17 [95% CI 1.78-2.64]; 3.18 [95% CI 2.58-3.92]), diabetes with chronic complications (aOR 1.28 [95% CI 1.08-1.51]), hyperlipidemia (aOR 1.24 [95% CI 1.08-1.43]), and thyroid disorders (aOR 1.69 [95% CI 1.14-2.49]) were independent predictors of SS. The SS+ group had fewer routine discharges and higher healthcare costs. Conclusions: Our study shows that about 5% of G-OSA patients with a prior history of stroke/TIA are at risk of hospitalization due to SS, which is associated with higher mortality and healthcare utilization. Complicated and uncomplicated hypertension, diabetes with chronic complications, hyperlipidemia, thyroid disorders, and admission to rural hospitals predict subsequent stroke.

Predictors of Pneumothorax in People With COVID-19 Pneumonia: A Multicenter Retrospective Investigation.

This multicenter retrospective investigation aimed to identify predictors of pneumothorax (PTX), pneumomediastinum (PM), and subcutaneous emphysema (SE) in patients with COVID-19 pneumonia admitted to the ICU. A total of 256 patients were included, with 128 in the case group and 128 in the control group. The study sample consisted of predominantly male patients with a mean age of around 53 years and a high prevalence of comorbidities. Significant predictors of PTX, PM, and SE included the presence of coronary artery disease, non-rebreather mask usage, high-flow oxygen therapy, mechanical ventilation, pressor usage, inpatient dialysis, steroid usage, sedative usage, narcotic usage, paralytic usage, elevated C-reactive protein levels, increased lung infiltration, the presence of PM and SE, mode of ventilation, duration of various respiratory support interventions, and severity of illness as indicated by APACHE and SOFA scores. These findings have important implications for the clinical management of patients with COVID-19 pneumonia, as they may help identify and closely monitor at-risk individuals, allowing for timely intervention and potentially improving clinical outcomes. Future research should focus on validating these predictors in larger cohorts and investigating the underlying mechanisms to develop targeted preventive and therapeutic strategies.

[Risk factors for adverse outcomes in elderly patients with asthma and severe COVID-19 at the hospital and early post-hospital stages].

BACKGROUND: Mortality and COVID-19 related factors are thoroughly analyzed. Given the large number of hospitalized patients, the potential short- and long-term COVID-19 related complications, further research is needed on the possible consequences of hospitalization, especially in higher-risk patients, after prolonged hospitalization and intensive care admission. AIM: To study the clinical course and outcomes of severe COVID-19 in elderly patients with asthma at the hospital and early post-hospital stages. MATERIALS AND METHODS: The study included 131 elderly patients (WHO, 2020) >60 years old, n=131 with asthma, hospitalized for severe COVID-19. Of these, 86 (65.6%) patients survived, 30 (22.9%) died in the hospital, and 15 (14.9%) patients died after discharge from the hospital (in the 90-day post-hospital period). COVID-19 was confirmed by laboratory tests (SARS-CoV-2 PCR RNA test) and/or clinically and radiologically. All patients had a documented history of asthma. Patients were followed up during the hospital stay and for 90 days after discharge. RESULTS: Comparison of outcomes showed that in the groups of patients with a fatal outcome (regardless of the stage), the Charlson comorbidity index, respiratory rate, extent of lung damage assessed by computed tomography, the absolute leukocyte and neutrophil number and the ratio of neutrophils to lymphocytes were statistically significantly higher. The absolute number of eosinophils was lower in these groups. In the group of patients who died during hospitalization, severe (IV-V) asthma (p=0.03), steroid use during the previous year (p=0.02), chronic heart failure with a reduced ejection fraction (p=0.009) were more common, and atopic asthma phenotype was less common (p=0.02). In those who died after discharge, more common were non-invasive ventilation and diabetes mellitus (p<0.001). The multivariate regression analysis model revealed the most significant predictors of mortality at the hospital and early post-hospital stages. CONCLUSION: Adverse outcomes of severe COVID-19 in elderly patients with asthma include hospital and post-hospital mortality. The most significant predictors of mortality are the comorbidity index and low eosinophil count. Hospital mortality is associated with a higher ratio of neutrophils to lymphocytes and lower total protein levels; early (90-day) post-hospital mortality is associated with extensive lung damage shown by computed tomography and diabetes mellitus.

The role of blood groups, vaccine type and gender in predicting the severity of side effects among university students receiving COVID-19 vaccines.

On March 11th, 2020, the World Health Organization (WHO) declared the coronavirus disease 2019 (COVID-19) a pandemic. To control the pandemic, billions of vaccine doses have been administered worldwide. Predictors of COVID-19 vaccine-related side effects are inconsistently described in the literature. This study aimed to identify the predictors of side effects' severity after COVID-19 vaccination among young adult students at Taif University (TU) in Saudi Arabia. An online, anonymous questionnaire was used. Descriptive statistics were calculated for numerical and categorical variables. Possible correlations with other characteristics were identified using the chi-square test. The study included 760 young adult participants from TU. Pain at the injection site (54.7%), headache (45.0%), lethargy and fatigue (43.3%), and fever (37.5%) were the most frequently reported COVID-19 vaccine-related side effects after the first dose. The most frequent side effects were reported among the 20-25-year-old age group for all doses of all vaccines. Females experienced remarkably more side effects after the second (p < 0.001) and third doses (p = 0.002). Moreover, ABO blood groups significantly correlated with vaccine-related side effects after the second dose (p = 0.020). The participants' general health status correlated with the side effects after the first and second doses (p < 0.001 and 0.022, respectively). The predictors of COVID-19 vaccine-related side effects in young, vaccinated people were blood group B, female gender, vaccine type, and poor health status.

On modelling student's resilience in learning statistics at a distance

Learning statistics online during the COVID-19 pandemic became a challenging experience for most students in higher institutions. This study aimed to measure the students' level of resilience and determine its influencing factors in distance learning during the pandemic. Data from an availability sampling of 129 engineering students were gathered with the aid of a Google form survey. The study used some descriptive measures and employed a regression modeling approach to extract detailed information from the survey data. Results showed that, on average, students were considered "resilient" in learning statistics during the pandemic. Statistical models revealed that sex, number of family members, household assets, and level of how conducive learning at home are significant predictors of students' resilience. Additionally, the model showed that male students are more resilient compared to female students. Lastly, more family members and household assets can increase students' resilience level as well as a comfortable place (at home) for learning. Hence, the study suggests that teachers must strengthen the interest of students especially female students by showing them a good attitude that promotes well-being. Furthermore, teachers must regularly monitor their learning progress, and provide comfortable and reasonable learning activities suitable for distance learning.