Trends in Postpartum Depression before and during the COVID-19 Pandemic and Correlates of Treatment Choices: A Population-Based Retrospective Cohort Study

Objectives: COVID-19-related stressors - including social distancing, material hardship, increased intimate partner violence, and loss of childcare, among others - may result in a higher prevalence of depression among postpartum individuals. This study examines trends in postpartum depression in the US from 2018 to 2022, as well as correlates of treatment choices among women with postpartum depression. Method(s): 1,108,874 women aged 14-64 in the Komodo Healthcare Map with 1+ live birth between April 2018 and December 2021 and had continuous enrollment 2+ years before and 4+ months after the delivery date were included. Prevalence of depression during postpartum (within 3 months after delivery) was calculated before (April 2018-March 2020) and during (April 2020-March 2022) COVID-19. Multinomial logistic regression was used to investigate correlates of treatment choices (no treatment, medication-only, psychotherapy-only, or both). Result(s): The prevalence of postpartum depression increased from 9.7% pre-pandemic to 12.0% during the pandemic (p < 0.001). Among 119,788 women with postpartum depression in 2018-2022, 47.0% received no treatment, 35.0% received medication-only, 10.0% received psychotherapy-only, and 7.4% received both within one month following their first depression diagnosis. Factors associated with an increase in the odds of receiving medication-psychotherapy treatment (vs. no treatment) included older ages;commercial insurance coverage;lower social vulnerability index;history of anxiety or mood disorder during and before pregnancy;and being diagnosed by a nurse practitioner, physician assistant, or behavioral care practitioner (vs. physician). Similar patterns were observed for medication-only and psychotherapy-only treatments. Conclusion(s): In this large, nationally representative sample of US insured population, the prevalence of postpartum depression increased significantly by 2.3 percentage-points during the pandemic (or a relative increase of 23.7%). Nonetheless, almost half of women with postpartum depression received no treatment, and only 7.5% received both medication and psychotherapy. The study highlighted potential socioeconomic and provider variation in postpartum depression treatment.Copyright © 2023

Trends of psychiatric emergencies during the COVID-19 health crisis in Italy

Background: Despite concerns on mental health problems related to lockdowns, recent reports revealed a reduction in psychiatric admissions in Emergency Departments (ED) during the lockdown period compared with the previous year in several countries. Most of the existing studies focused on the first lockdown not considering the different phases of the COVID-19 crisis. The present study aimed to analyse differences in ED admissions for psychiatric consultation during three different phases of the COVID-19 in Italy. Method(s): Information on ED admission the Santo Spirito Hospital in Rome for psychiatric consultations were retrospectively collected. The lockdown(March-June 2020) and the post-lockdown period (June 2020-June 2021) were compared to the pre-lockdown period(January 2019-March 2020). Multinomial logistic regression(MLR) was used to assess the risk of accessing ED for psychiatric consultation during the three periods. Result(s): 3871 ED psychiatric consultations were collected. A significant reduction of psychiatric consultations in ED during the lockdown period and the post-lockdown (H 762.45;p < .001) was documented. MLR showed that compared to pre-lockdown during the lockdown and post-lockdown patients were more likely to be men (RRR 1.52;95% CI 1.10-2.12) and more often diagnosed with non-severe mental illnesses (nSMI) (relative risk ratio [RRR] 1.53, 95% CI 1.10-2.15;and 1.72, 95% CI 1.42-2.08);during the lockdown, patients were also more often diagnosed with alcohol/substance abuse(RRR 1.70;95% CI 1.10-2.65). Conclusion(s): Several changes in the clinical characteristics of psychiatric consultations during and after the lockdown emerged;these may inform clinicians and future preventive strategies among community mental health services.

Changes in public bike usage after the COVID-19 outbreak: A survey of Seoul public bike sharing users.

When the COVID-19 pandemic swept across the world, people tended to seek more individualized and viable transportation modes, such as a bicycle. In this study, we examined the factors influencing changes in public bike sharing (PBS) in Seoul, to assess this trend post-pandemic. We conducted an online survey of 1,590 Seoul PBS users between July 30 and August 7, 2020. Using a difference-in-differences analysis, we found that participants who were affected by the pandemic used PBS 44.6 h more than unaffected individuals throughout the year. In addition, we used a multinomial logistic regression analysis to identify the factors affecting changes in PBS usage. In this analysis, the discrete dependent variables of increased, unchanged, and decreased were considered, representing the changes in PBS usage after the COVID-19 outbreak. Results revealed that PBS usage increased among female participants during weekday trips such as commuting to work and when there were perceived health benefits of using PBS. Conversely, PBS usage tended to decrease when the weekday trip purpose was for leisure or working out. Our findings offer insight into PBS user behaviors within the context of the COVID-19 pandemic and present policy implications to revitalize PBS usage.

Mitochondrial Dysfunction Is Associated with Post-Acute Sequelae of Covid-19

Background: Mitochondrial (mt) dysfunction has been described in acute severe SARS-CoV2 infection. It remains unclear whether the disturbances in mt are also present in post-acute sequelae of COVID-19 (PASC). Method(s): We analyzed cross-sectional data from participants without history of COVID and SARS-CoV2 antibody negative (COVID-), with documented prior COVID and full recovery (COVID+ PASC-), and with prior COVID with PASC as defined by the CDC (COVID+PASC+). Mt respiration was measured from peripheral blood mononuclear cells utilizing the Seahorse XFe96 analyzer. Generalized linear regression was used to compare estimates of mt and non-mt respirations, and unadjusted odds ratios using multinomial logistic regression to assess if mt respiration were associated with PASC. Result(s): For this analysis, 59 participants were enrolled, 71.19% (n=42) had a confirmed COVID-19 diagnosis. The overall mean age was 47.47 +/- 14.86 years, 69.49% (n=41) were females and 33.90% (n=20) were non-white race. There was no difference in demographics between participants with and without COVID (p>=0.72). Amongst all COVID+ participants, 19% (n=11) had hypertension and 8% (n=5) had diabetes. Among all COVID+, the median time between COVID diagnosis and study evaluation was 210 (IQR: 119, 453) days, and 50% (n=21) of COVID+ experienced persistent symptoms consistent with PASC. PASC participants had the highest observed values in non-mt respiration (21.57 +/- 10.77 pmol/min), basal respiration (38.95 +/- 17.58 pmol/min), proton leak (10.41 +/- 3.1), maximal respiration (103.91 +/- 58.63 pmol/min), spare respiratory capacity (64.96 +/- 41.82 pmol/min), and ATP production (28.55 +/-14.85 pmol/min). Basal respiration, ATP production, maximal respiration, and non-mt respiration were highest in PASC compared to COVID- (p<=0.02). There was marginal evidence (p=0.05) of a mean difference (8.09 pmol/min) in ATP production between COVID+PASC+ and COVID+PASC-, without differences in proton leak (p=0.23) or spare respiration capacity (p=0.07). Every unit increase in non-mt respiration, basal respiration, maximal respiration, and ATP production increased the predicted odds of PASC by 10.99, 5.6, 1.6 and 6.2%, respectively (Figure). Conclusion(s): Individuals with PASC are consuming more oxygen and producing more ATP in the PBMCs compared to controls. There also appears to be increased PBMC ATP production between PASC and COVID+. We hypothesize that this may reflect a crucial pathogenic mechanism in PASC that may be associated with ongoing inflammation. (Figure Presented).

Class prediction of the prevalent transmission mode of COVID-19 within a geographic area

This research developed a multinomial classification model that predicts the prevalent mode of transmission of the coronavirus from person to person within a geographic area, using data from the World Health Organization (WHO). The WHO defines four transmission modes of the coronavirus disease 2019 (COVID-19);namely, community transmission, pending (unknown), sporadic cases, and clusters of cases. The logistic regression was deployed on the COVID-19 dataset to construct a multinomial model that can predict the prevalent transmission mode of coronavirus within a geographic area. The k-fold cross validation was employed to test predictive accuracy of the model, which yielded 73% accuracy. This model can be adopted by local authorities such as regional, state, local government, and cities, to predict the prevalent transmission mode of the virus within their territories. The outcome of the prediction will determine the appropriate strategies to put in place or re-enforced to curtail further transmission.Copyright © 2023 Inderscience Enterprises Ltd.

Trends and factors associated with daily number of new cases of COVID-19 in the early stage of the pandemic: A worldwide opendata study

Objectives: We analyzed global trends in the daily number of new cases during the first wave of COVID-19 and factors associated with these trends. Methods: Data from 151 countries were analyzed. The index date for each country was set with consideration for a 7-day moving average (MA7) of ≥100 people. Data were collected for 60 and 90 days from the index date. Time-series hierarchical clustering was used to analyze the trends in the number of new cases in each country on the basis of their MA7 values. Multinomial logistic regression was performed to identify factors associated with these trends. Results: The trends in the daily number of new cases in the early stage of COVID-19 were classified into growth, declines, and smooth declines. The number of cases in countries with ≥25.60% residents with obesity (odds ratio = 6.69;p = 0.004) was more likely to exhibit growth than were those with obesity of 9.60-20.79%. The number in countries with a GDP of ≥US$34,341 (odds ratio = 0.10;p = 0.001) was more likely to exhibit a decline than were those with a GDP of US$5,277–14,932. Conclusions: COVID-19 epidemic prevention policies should account for country-specific characteristics such as the proportion of residents with obesity and GDP. © 2022, Taiwan Public Health Association. All rights reserved.

Trends and factors associated with daily number of new cases of COVID-19 in the early stage of the pandemic: A worldwide opendata study

Objectives: We analyzed global trends in the daily number of new cases during the first wave of COVID-19 and factors associated with these trends. Methods: Data from 151 countries were analyzed. The index date for each country was set with consideration for a 7-day moving average (MA7) of ≥100 people. Data were collected for 60 and 90 days from the index date. Time-series hierarchical clustering was used to analyze the trends in the number of new cases in each country on the basis of their MA7 values. Multinomial logistic regression was performed to identify factors associated with these trends. Results: The trends in the daily number of new cases in the early stage of COVID-19 were classified into growth, declines, and smooth declines. The number of cases in countries with ≥25.60% residents with obesity (odds ratio = 6.69;p = 0.004) was more likely to exhibit growth than were those with obesity of 9.60-20.79%. The number in countries with a GDP of ≥US$34,341 (odds ratio = 0.10;p = 0.001) was more likely to exhibit a decline than were those with a GDP of US$5,277–14,932. Conclusions: COVID-19 epidemic prevention policies should account for country-specific characteristics such as the proportion of residents with obesity and GDP. © 2022, Taiwan Public Health Association. All rights reserved.

Inflammation profiling and recovery clusters five months post-hospitalisation for COVID-19

Background Understanding the underlying mechanisms of post-COVID sequelae (Long COVID) is urgently needed to guide interventions. Aim To compare the inflammation profiles of four recovery clusters post-hospitalisation. Methods Post-Hospitalisation COVID-19 (PHOSP-COVID) is a prospective, multi-centre study across UK. Four recovery clusters previously identified using clinical data (symptoms, mental health, cognitive impairment, and physical function) at 5 months post-discharge were used based on severity of on-going health impairments: very severe, severe, moderate (cognitive), and mild. Inflammatory profiling performed from plasma samples using the Olink Explore 384 inflammation panel. Multinomial logistic regression for each protein was undertaken comparing the mild cluster with each of the remaining clusters with FDR of 0.1 to adjust p values. Results 626 participants (clusters: very severe n=111, severe n=173, moderate/cognitive n=73 and mild n=269). Proteomic results from 296 proteins were included. After adjustment for age, BMI, and comorbidity count, 13 proteins were significantly elevated in the very severe cluster, and 2 proteins in the moderate/cognitive cluster, compared to the mild cluster (Figure 1). Conclusion Inflammatory mediators consistent with persistent lung and systemic inflammation were associated with the severity of ongoing health impairments highlighting potential therapeutic pathways to be tested.

The Effects of the Covid-Pandemic on the Career Goal Feedbacks of University Students

Bu çalışmanın amacı pandemi korkusunun üniversite öğrencilerinin kariyer hedefleri üzerindeki etkisini ortaya koymaktır. Çalışmada nicel araştırma yöntemi kullanılmıştır. Araştırmada, 352 katılımcıya online olarak anket yöntemi uygulanmıştır. Ölçeklere geçerlilik ve güvenirlik testi yapılmıştır. Kariyer Hedefi Geribildirim Ölçeği (KHGBÖ) için güvenirlik 0.909 ve pandemi korkusu için ise 0.861 olarak bulunmuştur. Değişkenlerimiz kategorik olduğu için KHGB ile bağımsız değişkenler arasındaki ilişki ki-kare ile test edilmiştir. 24 maddeden oluşan KHGBÖ ile 6 maddeden oluşan pandemi korkusu ölçeği kullanılmıştır. Demografik özelliklerle pandemi korkusu ve KHGBÖ arasında istatistiksel olarak anlamlı bir fark olup olmadığı test edilmiştir. Faktör analizi kullanılarak KHGBÖ ne ait alt boyutları oluşturulmuş olup ve multinominal lojistik regresyon analizi ile pandemi korkusunun kariyer bildirimi geri bildirimi Kariyer Hedefi Geri Bildirimi (KHGB) üzerindeki etkisi analiz edilmiştir. Analiz sonrasında eğitim düzeyi, programı ve pandemi korkusu ile KHGB arasında istatistiksel olarak anlamlı bir farklılık çıkmıştır. Multinominal lojistik regresyon analizi sonrasında pandemi korkusunun KHGB üzerinde istatistiksel olarak etkili olduğu sonucuna ulaşılmıştır.Alternate abstract: This study aims to reveal the effects of the fear of the Covid-19 pandemic on university students' career goals. The quantitative method was utilized in the research, and an online survey method was applied to 352 participants. The scales were tested for validity and reliability. Reliability was found to be 0.909 for the Career Goal Feedback Scale (CGFS) and 0.861 for the fear of pandemic. Since our variables were categorical, the relationships between Career Goal Feedback (CGF) and independent variables were examined with the chi-square test. The CGF Scale composed of 24 items and the Fear of Pandemic Scale composed of six items were employed. It was examined whether statistically significant differences existed between demographic characteristics and the fear of pandemic and CGFS. Subdimensions of CGFS were constructed using exploratory factor analysis (EFA), and the effect of the fear of pandemic on Career Goal Feedback (CGF) was analyzed by multinomial logistic regression analysis. As a result of the analysis, the differences found between education level, program, and fear of pandemic and CGF were statistically significant. According to the multinomial logistic regression analysis, it was concluded that the fear of pandemic had a statistically significant effect on CGF.

APPLICATION OF INFORMATION TECHNOLOGIES AND METHODS FOR PROCESSING BIG DATA TO THE MANAGEMENT OF THE EDUCATIONAL PROCESS DURING THE PANDEMIC

The spread of coronavirus infection has changed all spheres of human life, forcing a new look at traditional forms of activity. Education as the most important social sphere has taken the blow of the pandemic transformation, resulting in a significant spread of distance forms of interaction between the teacher and the learner, involving the reliance on digital learning tools. Due to the need for participants in the educational process in these conditions to operate with large amounts of data and process information electronically, the use of the potential of artificial intelligence in education. The article deals with new opportunities and problems of integration of education and artificial intelligence under conditions of Covid-19 pandemic. The object of the research is education in the epoch of Covid19. The article describes fundamental changes, which took place in the educational system during the pandemic period, outlines promising directions of artificial intelligence usage in the modern educational process and corresponding problems. The necessity of further research of possibilities of integration of education and big data under conditions of acceleration of processes of digitalization of society is marked. COVID-19 epidemic caused a great number of human casualties and destruction of economic, social, public and health systems all over the world. Combating such an epidemic requires an understanding of its characteristics and behavior, which can be determined by collecting and analyzing relevant big data. Big data analysis tools play a vital role in generating the knowledge necessary for decision-making and precautionary measures. However, because of the vast amount of COVID-19 data available from various sources, there is a need to review the role of big data analysis in controlling the spread of COVID-19 by presenting the main challenges and directions of COVID-19 data. analysis, as well as providing a framework for relevant existing applications and research to facilitate future research on COVID-19 analysis. Therefore, in this paper, we conduct a literature review to highlight the contributions of several studies in the field of COVID-19-based big data analysis. © 2023 Little Lion Scientific.

Effects of Covid-19 pandemic on mode choice behavior of working Filipinos in Metro Manila

The COVID-19 pandemic and the resulting control measures by the government impacted the travel behavior of Filipinos. With work trips being a major part of trips generated, this study aimed to investigate the effects of the pandemic on working Filipinos' mode choice. Data were collected from employed residents of Metro Manila using an online survey. About 48% of the respondents preferred using public transportation for work pre-pandemic. This decreased to 22% during the transport lockdown and increased slightly to 25% after the lockdown was lifted. Active transport share increased by 3% during the lockdown but went back down after it was lifted. Using multinomial logistic regression, the significant factors that influence the pre-pandemic respondents' mode choice were age, household income, travel cost, and vehicle ownership. During the lockdown, travel distance, travel time, and sex assigned at birth became significant also. After the lockdown, the significant factors reverted to that pre-pandemic.

Household level determinants of food security in the City of Tshwane, South Africa

Food security has always been a contemporary issue in urban South Africa, which is gripped by high inequality. This has recently been exacerbated by risks and hazards pertaining to climate change and the more recent COVID-19 pandemic. The objective of the study was to ascertain the food security status and the determinants thereof for urban households in the City of Tshwane. The Household Food Insecurity Access Scale (HFIAS) and Multinomial Logistic Regression were used to scale the patterns of household-level determinants of food security of 775 households, distributed in 73 clusters, from the 7 regions of the City of Tshwane, South Africa. The study found that 39.2% of the households were food secure, 16.6% suffered from mild food insecurity, 12.1% were moderately food insecure, and 32.1% were severely food insecure. Food security was significantly more prevalent in male-headed households, households with younger members, households with educated heads, and those that are employed. Household size and income were also determinants of food security. The results indicate that age, gender (male), education, employment, household size, income, and grant type were significant at the 1% level in extreme changes in food insecurity, while only the grant was insignificant in mild changes in food security, with none of the variables being significant in slight food security changes. Government social grants were inadequate to guarantee food security status. The study concludes that there are extremes of food security and severe food insecurity indicating inequality, with various socio-economic factors affecting food security. Copyright © 2022 The Authors. Published by Rynnye Lyan Resources.

Sentiment Analysis of Tweets During the COVID-19 Pandemic Using Multinomial Logistic Regression

Recently, the research on sentimental analysis has been growing rapidly. The tweets of social media are extracted to analyze the user sentiments. Many of the studies prefer to apply machine learning algorithms for performing sentiment analysis. In the current pandemic, there is an utmost importance to analyze the sentiments or behavior of a person to make the decisions as the whole world is facing lockdowns in multiple phases. The lockdown is psychologically affecting the human behavior. This study performs a sentimental analysis of Twitter tweets during lockdown using multinomial logistic regression algorithm. The proposed system framework follows the pre-processing, polarity and scoring, and feature extracting before applying the machine learning model. For validating the performance of proposed framework, other three majorly used machine learning based models- namely decision tree, naïve Bayes, and K-nearest neighbors- are implemented. Experimental results prove that the proposed framework provides improved accuracy over other models. © 2022 Taru Publications. All rights reserved.

Risk factors for loneliness in family caregivers of people with dementia and enduring mental health conditions during the COVID-19 pandemic in Latin America

Background: During the COVID-19 pandemic, loneliness has increased in the general population due to government measures to contain the spread of the disease. In Latin America (LA), caregiving is most often delivered informally by family members Family caregivers often face mental health challenges linked to their caregiving role and their social context. Pandemic-related social restrictions have been especially detrimental for older people with dementia or other brain health challenges, as well as their family caregivers. We aimed to investigate the associations of loneliness, social isolation and care burden in these family caregivers. Method(s): We undertook a cross-sectional survey of over 300 informal caregivers of people with dementia or enduring mental health problems living in 4 Latin American countries, Mexico, Brazil, Chile, and Peru. We categorized loneliness into 3 groups 'low', 'moderate' and 'severe loneliness'. Here, we analyzed factors related to changes in the prevalence of moderate and severe loneliness before and during the pandemic using a longitudinal multinomial logistic regression model. Result(s): During the pandemic, there was a significant increase in loneliness prevalence (p<.001) among caregivers in Latin America, with more people having moderate (6.25% pre-pandemic;17.67% mid-pandemic) and severe loneliness (2.78% pre-pandemic;15.19% mid-pandemic). Gender differences in the prevalence of loneliness or higher levels of loneliness among dementia caregivers compared to caregivers of other conditions were not seen. The regression model revealed that the increment in risk for moderate loneliness during the pandemic was related to caregivers' age, level of education, and social contact/isolation. Increased risk for severe loneliness was related to caregivers' social contact during the pandemic and perceived mental health. Conclusion(s): Public health interventions regarding COVID-19 pandemic should consider increased loneliness in Latin-American caregivers. This population will need both, short and long-term mental health and practical support. Next steps include gathering more evidence on specific risk factors for loneliness and its impact on caregivers' physical and mental health. Copyright © 2022 the Alzheimer's Association.

Optimal anticoagulation intensity for patients with COVID-19 treated with Tocilizumab

Background: Tocilizumab reduces the need and the duration of organ support and provides a survival benefit for patients at the early stages of COVID-19 (Coronavirus Disease 2019) that have increasing oxygen needs and a significant inflammatory response. Contrary to expectations that this treatment would, also, break the vicious cycle of immunothrombosis of COVID-19, it has been debated whether it is associated with a conversely increased venous thromboembolism (VTE) incidence. In the interim, society guidelines have updated their recommendations advising a prophylactic over that of an intermediate or treatment dose of anticoagulation but there is a lack of evidence based for this group of patients. Aim(s): The purpose of this study was to compare the incidence of VTEs in patients with COVID-19 treated with Tocilizumab in relationship to the thromboprophylaxis dose determined by NICE guidelines. Method(s): A retrospective, cohort study was performed including all patients with COVID-19 admitted at NHS Hillingdon Hospital (UK) who required Tocilizumab between December 2020 and September 2021. Result(s): Sixty-three patients (20 females;43 males) with a median age of 63 y.o. (17-83) were analysed (Table 1). A Spearman's rank correlation was run to determine the relationship between the anticoagulation strategy and the thromboembolic risk in this context. A moderate negative correlation was found between the anticoagulation intensity and the risk of a VTE, r (61) = -0.470, p = 0.000. Binary logistic regression was then used to determine the relationship between anticoagulation intensity and VTEs and Multinomial Logistic Regression for the opposite relationship. Treatment dose thromboprophylaxis is related with more VTEs however this is likely a reflection that patients with VTEs receive appropriate antithrombotic therapy (Table 2). Conclusion(s): The present study suggests that patients with COVID-19 that receive Tocilizumab are not at increased thromboembolic risk and thus standard thromboprophylaxis should suffice. Findings should be confirmed in randomized controlled trials. (Table Presented).

EXTRACORPOREAL MEMBRANE OXYGENATION (ECMO) VS CONVENTIONAL MECHANICAL VENTILATION FOR SEVERE ACUTE RESPIRATORY FAILURE DUE TO COVID-19: A MULTICENTER MATCHED COHORT STUDY

SESSION TITLE: Critical Care Management of COVID-19 SESSION TYPE: Original Investigations PRESENTED ON: 10/17/2022 01:30 pm - 02:30 pm PURPOSE: Extracorporeal membrane oxygenation (ECMO), typically veno-venous, is used to treat COVID19 patients with severe acute respiratory distress syndrome (ARDS) and is associated with decreased mortality in some reports. This study sought to determine the effect of ECMO versus conventional invasive mechanical ventilation (IMV) on hospital mortality for ARDS due to COVID19, and to compare functional status at discharge. METHODS: This was a retrospective, multicenter cohort study of adult patients admitted for COVID19 within a large US hospital network between March 1, 2020 and October 31, 2021. Patients were included if they required IMV with a fraction of inspired oxygen (FiO2) of at least 80% or VV ECMO. Patients were excluded if they were not independent, had a history of severe neurologic impairment, chronic obstructive pulmonary disease, chronic systolic heart failure, end stage renal disease, cirrhosis, metastatic malignancy, or a length of stay <24 hours. ECMO criteria and management were at the discretion of the treating center. Conventional IMV patients were assigned a randomized pseudo-baseline, and coarsened exact matching was used to match ECMO to conventional IMV patients based on age, sex, body mass index, pre-baseline severity of hypoxemia, prone positioning, receipt of corticosteroids, Tocilizumab, Baricitinib, acute renal replacement therapy, and vasopressors. Differences in hospital mortality and discharge destination were assessed through weighted logistic regression and weighted multinomial logit regression, respectively. RESULTS: We identified 207,965 patients across 168 hospitals for review, and 10,571 patients met study criteria. After matching, 275 ECMO patients and 5,808 conventional IMV patients were available for comparison. ECMO was associated with a significant mortality reduction, 36% versus 61% (odds ratio [OR] 0.44, 95% confidence interval [CI] 0.34-0.57). Compared to conventional IMV survivors, ECMO survivors were significantly more likely to be discharged to acute rehabilitation than long term acute care (relative risk ratio (RRR) 2.23, 95% CI 1.16-4.32). ECMO survivors were also significantly more likely to be discharged to another acute care hospital for further management (RRR 3.21, 95% CI 1.75-5.92). CONCLUSIONS: This study demonstrates that ECMO support is significantly associated with reduced mortality in patients with severe ARDS due to COVID19 compared to conventional invasive mechanical ventilation. Further studies are needed to aid in prognostication, patient selection, and timing of intervention to maximize the benefit of this limited resource. CLINICAL IMPLICATIONS: These findings illustrate the importance of timely referral to an ECMO center for severely ill COVID19 patients, and may influence ECMO-capable centers to expand the use of ECMO in appropriate patients for this indication. DISCLOSURES: No relevant relationships by Elliott Cohen No relevant relationships by Katherine Cyr No relevant relationships by Jeffrey DellaVolpe No relevant relationships by Jamie Jarzembowski No relevant relationships by Chandra Kunavarapu no disclosure on file for Thomas Mcrae;Employee relationship with HCA Healthcare Please note: 6/1/2017 to current Added 04/04/2022 by Daniel Schlauch, value=Salary No relevant relationships by Owen Stell No relevant relationships by sage whitmore

Statistical methods for assessing drug interactions using observational data

With advances in medicine, many drugs and treatments become available. On the one hand, polydrug use (i.e. using more than one drug at a time) has been used to treat patients with multiple morbid conditions, and polydrug use may cause severe side effects. On the other hand, combination treatments have been successfully developed to treat severe diseases such as cancer and chronic diseases. Observational data, such as electronic health record data, may provide useful information for assessing drug interactions. In this article, we propose using marginal structural models to assess the average treatment effect and causal interaction of two drugs by controlling confounding variables. The causal effect and the interaction of two drugs are assessed using the weighted likelihood approach, with weights being the inverse probability of the treatment assigned. Simulation studies were conducted to examine the performance of the proposed method, which showed that the proposed method was able to estimate the causal parameters consistently. Case studies were conducted to examine the joint effect of metformin and glyburide use on reducing the hospital readmission for type 2 diabetic patients, and to examine the joint effect of antecedent statins and opioids use on the immune and inflammatory biomarkers for COVID-19 hospitalized patients. [ FROM AUTHOR] Copyright of Journal of Applied Statistics is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Socioeconomic status for predicting COVID-19-related changes in cancer prevention behaviors

Background: Disruptions of daily life activities during the CVOID-19 pandemic have adversely affected cancer-prevention behaviors. Socioeconomic status (SES) impacts on changes in cancer prevention behaviors have not been fully investigated. To tackle this gap, we examined the effects of SES on COVID- 19 related changes in cancer prevention behaviors. Methods: We invited participants from previous studies conducted at the Ohio State University Comprehensive Cancer Center who agreed to be re-contacted to participate in a survey assessing the impact of COVID-19 on various behaviors between June and November 2020. Participants reported current cancer prevention behaviors, including physical activity, daily fruit and vegetable intake, alcohol consumption, and tobacco use. In addition, participants reported qualitative changes in current behaviors relative to pre-COVID levels. We combined current behaviors with COVID-related changes to construct a 24-point cancer prevention score. Participants were classified into low, middle, or high SES based on household income, education, and employment status. Adjusted multinomial logistic regression was used to examine the association between SES and COVID-19 related changes in cancer prevention behaviors. Results: The study sample included 6136 eligible participants. The average age was 57 years, 67% were female, 89% were non-Hispanic White, and 33% lived in non-metro counties. The proportion of participants in the lowest cancer prevention behavior quartile decreased significantly with higher SES [low SES vs. high SES;32% vs. 28%;P-value <.001]. Relative to pre-COVID-19 levels, higher SES was significantly associated with increases in post-COVID-19 prevalence of more physical activity [low SES vs. high SES;12% vs. 28%;P-value <.001], higher fruit and vegetable intake [low SES vs. high SES;12% vs. 14%;P-value <.001], and more alcohol consumption [low SES vs. high SES;15% vs. 22%;P-value <.001]. Higher SES was associated with lower tobacco use prevalence [low SES vs. high SES;5% vs. 2%;P-value <.001]. Relative to the highest prevention score quartile, the adjusted odds of scoring in the lowest prevention score quartile were: adjusted odds ratio (aOR) 1.55 (95% CI: 1.27 - 1.89) and aOR 1.40 (95% CI: 1.19 - 1.66), respectively higher for low and middle SES. Low SES was significantly associated with higher odds of less frequent physical activity (aOR = 1.87;95% CI: 1.49 - 2.35) and less fruit and vegetable consumption (aOR = 1.56;95% CI: 1.15 - 2.12). Middle SES relative to high SES was associated with lower odds of more alcohol consumption (aOR = 0.64;95% CI: 0.49 - 0.85) and higher odds of binge drinking (aOR = 1.32;95% CI: 1.09 - 1.59). Conclusions: The adverse impacts of COVID- 19 on cancer prevention behaviors were seen most in those with lower SES. Public health efforts are currently needed to promote cancer prevention behaviors, especially amongst lower SES adults.

Depression, anxiety and stress among people infected with COVID-19 in Dhaka and Chittagong cities.

Background: Covid-19 is an acute respiratory infectious disease caused by novel coronavirus 2019. Many individuals have suffered or are experiencing psychological symptoms due to feelings of isolation, insecurity and instability triggered by Covid-19. This study aimed to explore the perceived psychological distress and associated factors among people infected with Covid-19 in Dhaka and Chittagong cities. Methods: Using the face-to-face interview method, a survey was conducted from 23 April to 22 May 2021 on a questionnaire on depression, anxiety and stress scale (DASS-21), socio-demographic, economic and health factors. Among those who had ever been infected with Covid-19, a total of 2092 respondents (1180 from Dhaka and 912 from Chittagong) were randomly selected and interviewed. χ 2 test for independence of attributes was employed to observe the association of various socioeconomic, cultural, demographic and health factors with psychological distress. Moreover, multinomial logistic regression analysis was performed to explore the factors that contributed to psychological distress. Results: Among participants from Dhaka, of three mental health conditions, the prevalence was higher for anxiety (80.0%), followed by stress (64.2%) and depression (59.8%), respectively. Anxiety was also more prevalent (57.3) among respondents in Chittagong, followed by depression (47.7%) and stress (39.5%). As the coexistence of symptoms, 52.8% of respondents in Dhaka, 34.4% in Chittagong experienced depression, anxiety and stress simultaneously. Moreover, in both Dhaka and Chittagong, all three psychological symptoms were strongly correlated in pairs. Multivariate analysis revealed that the most consistent factors associated with mild to moderate (MM), and severe to extremely severe (SES) depression were respondents from Chittagong who were illiterate or primary educated (OR = 0.166, CI: 0.076-0.364 for MM and OR = 0.041, CI: 0.013-0.131 for SES), male (OR = 0.999, CI: 0.666-1.496 for MM and OR = 0.395, CI: 0.249-0.625 for SES), single (OR = 0.393, CI: 0.157-0.982 for MM and OR = 0.121, CI: 0.049-0.303 for SES) and married (OR = 0.403, CI: 0.177-0.916 for MM and OR = 0.075, CI: 0.033-0.167 for SES), had a family of size ≤ 4 (OR = 0.253, CI: 0.140-0.458 for MM and OR = 0.114, CI: 0.059-0.218 for SES) and a family of size 5-6 (OR = 0.151, CI: 0.084-0.272), and no family members at risk being infected with Covid-19 (OR = 0.699, CI: 0.487-1.002 for MM and OR = 0.332, CI: 0.199-0.522 for SES). The analysis yielded similar findings for the other two mental health subscales, such as anxiety and stress. For respondents in Dhaka, the effect of factors other than sex on psychological distress was the opposite in Chittagong. Overall, psychological distress during the outbreak was greater among respondents in Dhaka than in Chittagong if respondents were not classified based on various characteristics. Conclusion: This study showed that in both Dhaka and Chittagong, a substantially large portion of Covid-19-infected respondents experienced all three psychological distress (e.g., depression, anxiety and stress). Regardless of the dissimilarity between the results in Dhaka and Chittagong, better mental health support was needed for women in both cities.

EFFECTIVENESS OF COVID-19 VIRAL VECTOR JANSSEN AD.26.COV2.S VACCINE AND COMPARISON WITH MRNA VACCINES IN CIRRHOSIS

commonly worldwide but their effectiveness in participants with cirrhosis is unknown. We explored the effectiveness of vaccination with the Janssen Ad.26.COV2.S compared to the mRNA Pfizer BNT162b2 or Moderna 1273-mRNA vaccine in participants with cirrhosis. Method: This was a test-negative case control study among participants with cirrhosis. This study design is widely used in evaluations of vaccine effectiveness and has the advantage of minimizing biases associated with access to vaccination or health care. Cases were those who were SARS CoV2 PCR positive, controls were those who tested negative during the study period between March 15, 2021 and October 3, 2021. Participants who did not undergo SARS CoV2 PCR testing, who had COVID-19 before the study period, or received a liver transplant, were excluded. COVID-19 was classified based on individual chart review using the National Institute of Health (NIH) COVID-19 severity scale as asymptomatic, mild, moderate, severe or critical illness. Propensity score matching was used to match test positive cases and test negative controls. The propensity score of having COVID-19 were derived from a logistic regression that adjusted for the participant's sex, age, date of testing, race/ethnicity, location, alcohol as the etiology of liver disease, body mass index (BMI), diabetes mellitus, current tobacco use, current alcohol use, co-morbidities, and the Child Turcotte Pugh score. Multinomial logistic regression models were fit for COVID-19, to assess the adjusted effect from vaccination with either the Ad.26.COV2.S or the mRNA-1273 or BNT162b2 vaccines. Results: A total of 955 cases and 955 matched controls were included in the study population. The two groups were well matched to all baseline characteristics. The Ad.26.COV2.S vaccine had an effectiveness of 64% against COVID-19 (adjusted Odds Ratio [aOR] 0.36, 95% CI 0.20-0.62, p=0.005). Effectiveness was lowest with asymptomatic illness (aOR 0.42, 0.18-0.73, p=0.03), and higher against mild (aOR 0.36, 0.15-0.63, p= 0.006), moderate (aOR 0.33, 0.14-0.49, p=0.002) and severe/critical (aOR 0.24, 0.08-0.83, p=0.04) COVID-19. In the same period, mRNA vaccines had a 73% effectiveness against overall COVID-19 (aOR 0.27, 0.19-0.37, p<0.0001), progressively higher from asymptomatic (aOR 0.38, 0.23-0.59, p=0.0004) to mild (aOR 0.29, 0.18-0.42, p<0.0001), moderate (aOR 0.27, 0.18-0.36, p<0.0001), and severe or critical illness (aOR 0.17, 0.06-0.32, p<0.0001). There were no statistically significant differences between the viral vector and mRNA vaccines. Conclusion: In participants with cirrhosis, the Ad.26.COV2.S demonstrated a 64% effectiveness against COVID-19, and a 74% effectiveness against severe or critical COVID-19, similar to that associated with mRNA vaccines. (Figure Presented)