Loneliness among Homeless Individuals during the First Wave of the COVID-19 Pandemic.

The feeling of loneliness is a major public health concern associated with multiple somatic and psychiatric illnesses. Studies have shown increasing incidence of loneliness in the general population during the first wave of the COVID-19 pandemic. Homeless individuals are a particularly vulnerable group; however, little is known about loneliness among homeless individuals. We therefore aimed to examine the prevalence of loneliness among homeless individuals during the pandemic. Furthermore, we estimated the association between loneliness and sociodemographic and lifestyle factors, as well as the self-perceived risk of contracting COVID-19. Data from the Hamburg survey of homeless individuals were used, including 151 homeless individuals that were recruited in spring of 2020. Loneliness was measured by the 3- item version of the UCLA-3 Loneliness Scale. To summarize, 48.5% of the participants experienced loneliness. Multiple linear regressions showed increased loneliness to be associated with male gender (β = 1.07, p = 0.01), being single (β = 1.33, p = 0.00), originating from Germany (β = 1.48, p = 0.00), high frequency of sharing a sleeping space with more than three people (β = 0.42, p = 0.02) and a higher self-perceived risk of contracting COVID-19 (β = 0.41, p = 0.02). On the contrary, there was no association of loneliness with age, educational level, chronic alcohol consumption or frequently sharing a sleeping space. In conclusion, the magnitude of loneliness among homeless individuals during the pandemic was highlighted. Description of factors determining loneliness may help to identify homeless individuals at risk

Matched-pair analysis of patients with female and male breast cancer: a comparative analysis

<p>Abstract</p> <p>Background</p> <p>Male breast cancer (MBC) is a rare disease accounting for approximately 1% of all breast carcinomas. Presently treatment recommendations are derived from the standards for female breast cancer. However, those approaches might be inadequate because of distinct gender specific differences in tumor biology of breast cancer. This study was planned in order to contrast potential differences between female and male breast cancer in both tumor biological behavior and clinical management.</p> <p>Methods</p> <p>MBC diagnosed between 1995-2007 (region Chemnitz/Zwickau, Saxony, Germany) was retrospectively analyzed. Tumor characteristics, treatment and follow-up of the patients were documented. In order to highlight potential differences each MBC was matched with a female counterpart (FBC) that showed accordance in at least eight tumor characteristics (year of diagnosis, age, tumor stage, nodal status, grade, estrogen- and progesterone receptors, HER2 status).</p> <p>Results</p> <p>108 male/female matched-pairs were available for survival analyses. In our study men and women with breast cancer had similar disease-free (DFS) and overall (OS) survival. The 5-years DFS was 53.4% (95% CI, range 54.1-66.3) in men respectively 62.6% (95% CI, 63.5-75.3) in women (p > 0.05). The 5-years OS was 71.4% (95% CI, 62.1-72.7%) and 70.3% (95% CI, 32.6-49.6) in women (p > 0.05). In males DFS analyses revealed progesterone receptor expression as the only prognostic relevant factor (p = 0.006). In multivariate analyses for OS both advanced tumor size (p = 0.01) and a lack of progesterone receptor expression were correlated (p = 0.01) with poor patients outcome in MBC.</p> <p>Conclusion</p> <p>Our comparative study revealed no survival differences between male and female breast cancer patients and gives evidence that gender is no predictor for survival in breast cancer. This was shown despite of significant gender specific differences in terms of frequency and intensity of systemic therapy in favor to female breast cancer.</p

Kenntnis und Einsatz Digitaler Medien in der Adipositasrehabilitation

Pankatz M, Gellhaus I, Kühn-Dost A, Sievers-Böckel B, Wulff H. Kenntnis und Einsatz Digitaler Medien in der Adipositasrehabilitation. Presented at the 27. Rehabilitationswissenschaftliches Kolloquium, München

Early Fusion of Camera and Lidar for robust road detection based on U-Net FCN

Automated vehicles rely on the accurate and robust detection of the drivable area, often classified into free space, road area and lane information. Most current approaches use monocular or stereo cameras to detect these. However, LiDAR sensors are becoming more common and offer unique properties for road area detection such as precision and robustness to weather conditions. We therefore propose two approaches for a pixel-wise semantic binary segmentation of the road area based on a modified U-Net Fully Convolutional Network (FCN) architecture. The first approach UView-Cam employs a single camera image, whereas the second approach UGrid-Fused incorporates a early fusion of LiDAR and camera data into a multi-dimensional occupation grid representation as FCN input. The fusion of camera and LiDAR allows for efficient and robust leverage of individual sensor properties in a single FCN. For the training of UView-Cam, multiple publicly available datasets of street environments are used, while the UGrid-Fused is trained with the KITTI dataset. In the KITTI Road/Lane Detection benchmark, the proposed networks reach a MaxF score of 94.23% and 93.81% respectively. Both approaches achieve realtime performance with a detection rate of about 10 Hz