Association of mental health with clinical outcomes in hospitalized patients with moderate COVID-19

Differential Anxiety Responses in Acute Myocardial Infarction vs. COVID-19 Pneumonia Patients

Background and Objectives: Amidst the COVID-19 pandemic, concerns about the psychological impact of disease-related anxiety on public health have risen. This study aims to compare general and death anxiety levels between acute coronary artery syndrome and COVID-19 pneumonia patients. Materials and Methods: A cross-sectional study of 132 individuals, including acute myocardial infarction (MI), COVID-19 pneumonia patients, and healthy volunteers from Trakya University Hospital (Turkey), was analyzed. Validated scales like the Beck Anxiety Inventory (BAI), Coronavirus Anxiety Scale Short Form, and Thorson-Powell Death Anxiety Scale (TPDAS) were employed. Demographic data such as age, gender, income levels, employment status, presence of a close relative with COVID-19, and whether participants followed COVID-19-related news were collected and compared across groups with significance level of 0.05 set for all analyses. Results: Among 41 COVID-19, 41 MI, and 50 healthy subjects, the pneumonia group showed highest COVID-19 anxiety (p = 0.01) and BAI scores (p = 0.008). Both COVID-19 and MI patients had significantly higher BAI and TPDAS scores compared to healthy controls (p < 0.001). Factors like female gender (p = 0.004), low education (p = 0.003), current employment (p = 0.008), and low income (p = 0.002) correlated with higher BAI scores. Low income (p = 0.001) and COVID-19 news exposure (p = 0.002) correlated with higher TPDAS scores. Males and married patients had lower anxiety scores (p = 0.008). High income, education, and employment reduced anxiety levels (p = 0.008). TPDAS scores decreased with higher income (p = 0.001), but increased in the MI group (p = 0.002) with COVID-19 news exposure. The multivariate linear regression analysis found that MI and COVID-19 pneumonia were associated with TPDAS; female gender, university education, and COVID-19 pneumonia with the Beck scale; and COVID-19 pneumonia with anxiety scores on the COVID-19 Anxiety scale. Conclusions: This research showcases differing anxiety patterns between illnesses such as MI and COVID-19 pneumonia amidst the pandemic, emphasizing the amplifying influence of media coverage on death-related anxieties. It underscores the imperative of targeted interventions and socioeconomic considerations in managing psychological consequences and formulating responsive public health strategies.

Assessing the risk of COVID-19 reinfection and severe outcomes among individuals with substance use disorders: a retrospective study using real-world electronic health records

OBJECTIVE

Despite advancement in vaccines and treatments for COVID-19 over the past 2 years, many concerns remain about reinfection and waning immunity against COVID-19 and its variants, especially among people with substance use disorder (SUD). The study assessed the risk of COVID-19 reinfection and severe illness among adults with SUD and their vaccination status to inform management in this vulnerable population as the pandemic continues.

DESIGN

Retrospective cohort study.

SETTING

Nationwide electronic health records (TriNetX database) in the USA among adults with COVID-19 infection from January 2020 to June 2022.

PARTICIPANTS

Adults (age ≥18 years) who were infected by COVID-19, excluding those who had cancer or lived in nursing homes or palliative care facilities.

OUTCOME MEASURES

COVID-19 reinfection was defined as a new diagnosis after 45 days of the initial infection. Logistic regression was applied to assess the OR of COVID-19 reinfection and severe outcomes within 30 day of reinfection for adults with alcohol (AUD), opioid (OUD), cocaine (CUD), stimulant (STUD), cannabis (CAUD) and other use disorders, controlled for demographic and comorbid conditions.

RESULTS

The SUD cohort was 13%-29% more likely to be reinfected by COVID-19 and had significantly higher 30-day mortality. Adults with AUD, STUD and OUD were at greater risks (adjusted ORs, AORs=1.69-1.86) of emergency department, hospital and intensive care admissions after 30 days of reinfection. Individuals with SUD and multiple vaccines doses were associated with decreased risks of worse COVID-19 outcomes. Lower COVID-19 reinfection rates (AORs=0.67-0.84) were only found among individuals with AUD, CUD or CAUD who had COVID-19 vaccination.

CONCLUSIONS

Individuals with SUD had greater risks of COVID-19 reinfection and poor outcomes, especially those with OUD, STUD and AUD. Multiple vaccinations are recommended to reduce severe illness after COVID-19 reinfection in the SUD population.

COVID-19 risk, course and outcome in people with mental disorders: a systematic review and meta-analyses

AIMS

It has been suggested that people with mental disorders have an elevated risk to acquire severe acute respiratory syndrome coronavirus 2 and to be disproportionally affected by coronavirus disease 19 (COVID-19) once infected. We aimed to analyse the COVID-19 infection rate, course and outcome, including mortality and long COVID, in people with anxiety, depressive, neurodevelopmental, schizophrenia spectrum and substance use disorders relative to control subjects without these disorders.

METHODS

This study constitutes a preregistered systematic review and random-effects frequentist and Bayesian meta-analyses. Major databases were searched up until 27 June 2023.

RESULTS

Eighty-one original articles were included reporting 304 cross-sectional and prospective effect size estimates (median n per effect-size = 114837) regarding associations of interest. Infection risk was not significantly increased for any mental disorder that we investigated relative to samples of people without these disorders. The course of COVID-19, however, is relatively severe, and long COVID and COVID-19-related hospitalization are more likely in all patient samples that we investigated. The odds of dying from COVID-19 were high in people with most types of mental disorders, except for those with anxiety and neurodevelopmental disorders relative to non-patient samples (pooled ORs range, 1.26-2.57). Bayesian analyses confirmed the findings from the frequentist approach and complemented them with estimates of the strength of evidence.

CONCLUSIONS

Once infected, people with pre-existing mental disorders are at an elevated risk for a severe COVID-19 course and outcome, including long COVID and mortality, relative to people without pre-existing mental disorders, despite an infection risk not significantly increased.

Exploration of Molecular Targets and Mechanisms of Curcumin in the Treatment of COVID-19 with Depression by an Integrative Pharmacology Strategy

BACKGROUND

Coronavirus disease 2019 (COVID-19) not only causes a range of respiratory symptoms but also has a great impact on individual mental health. With the global pandemic of SARS-CoV-2, the incidence of COVID-19 comorbid with depression has increased significantly. Curcumin, a natural polyphenol compound, has been shown to have antidepressant and anti-coronavirus activities.

METHODS

This study aimed to explore the molecular targets and underlying biological mechanisms of curcumin in the treatment of COVID-19 with depression through an integrative pharmacology strategy, including target prediction, network analysis, PPI analysis, GO and KEGG enrichment analyses, and molecular docking.

RESULTS

After a comprehensive search and thorough analysis, 8 core targets (ALB, AKT1, CASP3, STAT3, EGFR, PTGS2, FOS, and SERPINE1) were identified. GO and KEGG enrichment analysis results revealed that the pathways related to viral infection, immune regulation, neuronal reorganization, apoptosis, and secretion of inflammatory cytokines were involved in the pathological process. Furthermore, molecular docking showed that curcumin could spontaneously bind to the SARS-CoV-2-related receptor proteins and the core targets with a strong binding force.

CONCLUSION

The potential pharmacological mechanisms of curcumin in COVID-19 comorbid depression were evaluated. Curcumin can be used as a therapeutic agent for COVID-19 comorbid depression. One of the potential mechanisms may be to reduce the inflammatory response and suppress the cytokine storm by regulating the JAK-STAT signaling pathway and MAPK signaling pathway. These findings may help to overcome the impact of the COVID-19 pandemic on psychological health.

Adjusting intervention strategies for mental health of COVID-19 patients: A network analysis based on a survey in Omicron-infected patients

Background

The COVID-19 pandemic had a major impact on people's mental health. As the SAS-Cov-2 evolves to become less virulent, the number of asymptomatic patients increases. It remains unclear if the mild symptoms are associated with mild perceived stress and mental illness, and the interventions to improve the mental health of the patients are rarely reported.

Methods

This cross-sectional study investigated the level of depression, anxiety and perceived stress of 1,305 COVID-19 patients who received treatment in the Fangcang shelter hospitals in Shanghai, China. Network analysis was used to explore the relationship among depression, anxiety and perceived stress.

Results

The prevalence of depression, anxiety and perceived stress in the patients with Omicron infection were 9.03, 4.60, and 17.03%, respectively, lower than the prevalence reported during the initial outbreak of COVID-19. "Restlessness (A5)," "Uncontrollable worry (A2)," "Trouble relaxing (A4)" and "Fatigue (D4)" had the highest expected influence values. "Irritability (A6)" and "Uncontrollable (S1)" were bridge symptoms in the network. Comparative analysis of the network identified differences in the network structures between symptomatic and asymptomatic patients.

Conclusion

This study investigated the prevalence of depression, anxiety and perceived stress and the correlation among them in Omicron-infected patients in Fangcang shelter hospital, in Shanghai, China. The core symptoms identified in the study provide insight into targeted clinical prevention and intervention of mental health in non-severe Omicron-infected patients.

Exploring changes in depression and radiology-related publications research focus: A bibliometrics and content analysis based on natural language processing

OBJECTIVE

This study aims to construct and use natural language processing and other methods to analyze major depressive disorder (MDD) and radiology studies' publications in the PubMed database to understand the historical growth, current state, and potential expansion trend.

METHODS

All MDD radiology studies publications from January 2002 to January 2022 were downloaded from PubMed using R, a statistical computing language. R and the interpretive general-purpose programming language Python were used to extract publication dates, geographic information, and abstracts from each publication's metadata for bibliometric analysis. The generative statistical algorithm "Latent Dirichlet allocation" (LDA) was applied to identify specific research focus and trends. The unsupervised Leuven algorithm was used to build a network to identify relationships between research focus.

RESULTS

A total of 5,566 publications on MDD and radiology research were identified, and there is a rapid upward trend. The top-cited publications were 11,042, and the highly-cited publications focused on improving diagnostic performance and establishing imaging standards. Publications came from 76 countries, with the most from research institutions in the United States and China. Hospitals and radiology departments take the lead in research and have an advantage. The extensive field of study contains 12,058 Medical Subject Heading (MeSH) terms. Based on the LDA algorithm, three areas were identified that have become the focus of research in recent years, "Symptoms and treatment," "Brain structure and imaging," and "Comorbidities research."

CONCLUSION

Latent Dirichlet allocation analysis methods can be well used to analyze many texts and discover recent research trends and focus. In the past 20 years, the research on MDD and radiology has focused on exploring MDD mechanisms, establishing standards, and constructing imaging methods. Recent research focuses are "Symptoms and sleep," "Brain structure study," and "functional connectivity." New progress may be made in studies on MDD complications and the combination of brain structure and metabolism.