Disruptions in Health Care among Mwccs Participants during the Covid-19 Pandemic

Background: The COVID-19 pandemic resulted in disruptions to health care services. Vulnerable populations, including people living with HIV (PLHIV), may have experienced unique challenges when accessing medical care. The objective of this study was to evaluate the impact of social disruptions on health care visits among Multicenter AIDS Cohort Study/Women's Interagency HIV Study Combined Cohort Study (MWCCS) participants. Method(s): A survey collecting data on missed health care visits and social disruptions (i.e., disruptions in employment, childcare, financial support, housing, and health insurance) during the pandemic was administered via telephone to MWCCS participants 1-3 times from March and September 2020. Logistic regression models adjusted for sociodemographics and HIV-status were used to test the association between social disruptions and three medical care interruption outcomes (i.e., missed healthcare appointment, interruption of mental health care, and interruption of substance use care). Result(s): Surveys (n=10,076) were conducted among 2238 PLHIV (61% women) and 1427 people living without HIV (PLWoH) (41% women). Overall, 42% of participants reported disruptions in health care with no significant difference by HIV status. Among participants receiving mental health care services and substance use treatment, 52% and 36% reported interruptions of care, respectively. Participants reporting >= 2 social disruptions were more likely to report missed health care appointments (adjusted odds ratio [aOR]: 1.81, 95% confidence interval [CI]: 1.54-2.13), and interruptions in mental health care [aOR: 2.42, 95%CI: 1.85-3.17) or substance use treatment (aOR: 1.97, 95%CI: 1.26-3.09), compared to those reporting no disruptions. Participants who were unemployed were more likely to miss health care appointments (aOR:1.46, 95% CI: 1.25-1.71) and report disruptions in mental health care (aOR: 2.02, 95% CI: 1.54-2.66) compared to those who were employed. PLHIV reporting >= 2 social disruptions were at increased risk for missed health care appointments (aOR 1.92, 95%CI: 1.56-2.36) and disruptions in mental health care (aOR: 2.54, 95%CI: 1.83-3.53 (Table 1). Conclusion(s): Social disruptions as a result of the COVID-19 pandemic have adversely impacted the receipt of health care among PLHIV and PLWoH, including the receipt of treatment for mental health and substance abuse. Providing childcare, financial support, housing, and health insurance may reduce disruptions in care and improve health outcomes.

Factors associated with response to a phone-administered alcohol and substance use survey during the COVID-19 pandemic among women in the MACS/WIHS Combined Cohort Study: Who are we missing?

Background. Early in the COVID-19 pandemic, many clinical studies pivoted to remote research visits, which have a higher non-response rate compared to in-person assessments. Survey non-response can bias estimates of alcohol and substance use prevalence. Our objective was to identify factors associated with responding to an alcohol and substance use phone survey administered during the COVID-19 pandemic to women enrolled in the MACS/WIHS Combined Cohort Study, a multicenter U.S. prospective cohort of adults living with and without HIV. Methods. We assessed associations of pre-pandemic (April-Sept. 2019) sociodemographic factors, HIV status, housing status, depressive symptoms, alcohol use, and substance use measures with response to a pandemic (Aug.-Sept. 2020) phone survey using multivariable logistic regression. Response probability weights generated from the regression model were applied to the sample and prevalence estimates of risky drinking (> 7 drinks/week or > 3 drinks/day) and substance use (opioids, stimulants, sedatives) in the COVID-19 pandemic were compared to the unweighted sample. Results. Of 1,834 women with pre-pandemic data, 62% were of Black race, 46% had an annual income < $12K, 71% were living with HIV and the mean age was 52.4 (SD 9.3) years. The phone survey response rate was 77.5%. In the adjusted model, the odds of responding were lower at research sites in the Western (aOR 0.35 95% CI 0.21-0.57) and Southern US (aOR 0.29 95% CI 0.19-0.44, ref=Midwest), in women of Hispanic ethnicity (aOR 0.47 95% CI 0.33-0.66, ref=Black race), and in those who reported substance use (aOR 0.62 95% CI 0.40-0.95). By contrast, the odds were higher for women of white race (aOR 1.63 95% CI 1.02-2.70) and those with stable housing (aOR 1.71 95% CI 1.22-2.39). Un weighted versus weighted prevalence estimates were 11.1% vs. 11.6% for risky drinking and 6.1% vs. 6.9% for substance use. Conclusion. Among a sample of socioeconomically disadvantaged women, women of Hispanic ethnicity, and those who were unstably housed and reported substance use at baseline had lower odds of responding to an alcohol and substance use phone survey conducted early in the COVID-19 pandemic. As remote survey methods become more common, investigators should ensure that data remain representative of the target population.

Towards Real-World Federated Learning in Medical Image Analysis Using Kaapana

The Radiological Cooperative Network (RACOON) is dedicated to strengthening Covid-19 research by establishing a standardized digital infrastructure across all university hospitals in Germany. Using a combination of structured reporting together with advanced image analysis methods, it is possible to train new models for a standardized and automated biomarker extraction that can be easily rolled out across the consortium. A major challenge consists in providing generic and robust tools that work well on relevant data from all hospitals, not just on those where the model was originally trained. Potential solutions are federated approaches that incorporate data from all sites for model generation. In this work, we therefore extend the Kaapana framework used in RACOON to enable real-world federated learning in clinical environments. In addition, we create a benchmark of the nnU-Net when applied in multi-site settings by conducting intra- and cross-site experiments on a multi-site prostate segmentation dataset. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Results of a factor analysis of items regarding COVID-19 pandemic-specific workload among medical staff in Germany

IntroductionEpidemics lead to an increase in occupational stress and psychological strain among medical staff (cf. Mulfinger et al. 2020). However, there are no validated questionnaires to measure stress caused by an epidemic such as Covid-19, instead self-constructed questions are used frequently.ObjectivesThe aim was to develop items for the assessment of specific workload in epidemics which can be used to obtain longitudinal data.MethodsA sample of N=8078 persons working in the health care sector in Germany participated in the VOICE, EviPan online survey addressing the burden of Covid-19 pandemic during the 2nd quarter of 2020. We used 15 self-constructed items to examine whether these items can represent Covid-19 specific topics. A total of N=7549 (24% males) had complete data to run a confirmatory factor analysis using SEM procedure in Stata 14.2.ResultsFive factors were identified a priory: Factor (F) 1: Workload due to Covid-19 pandemic (4 items;Cronbachs’ alpha (α))=0.740);F 2: Fear, uncertainty of SarsCoV-2infection (self and others) (3 items;α= 0.741);F 3: Patient safety (3 items;α=0.533;F 4: Perception of protection concepts (2 items;α=0.590);F 5: Dysfunctional coping strategies (3 items;α=0.447). Fit-Indices: χ²(73)= 1373.849, p<.001, CFI=.946, TLI=.923, RMSEA=.0049, SRMR=.037)ConclusionsWe identified 5 factors associated with problems occurring during the Covid-19 pandemic with acceptable to good internal consistency. Most of the constructed items could therefore be used in further surveys to monitor stress, as a basis for recommendations in the area of stress prevention and interventions for medical staff during epidemics.