Catholic University College, Kensington

About: Catholic University College, Kensington is a based out in . It is known for research contribution in the topics: National Health and Nutrition Examination Survey & Population. The organization has 810 authors who have published 659 publications receiving 12845 citations.

Automated detection and classification of the proximal humerus fracture by using deep learning algorithm

Abstract: Background and purpose - We aimed to evaluate the ability of artificial intelligence (a deep learning algorithm) to detect and classify proximal humerus fractures using plain anteroposterior shoulder radiographs. Patients and methods - 1,891 images (1 image per person) of normal shoulders (n = 515) and 4 proximal humerus fracture types (greater tuberosity, 346; surgical neck, 514; 3-part, 269; 4-part, 247) classified by 3 specialists were evaluated. We trained a deep convolutional neural network (CNN) after augmentation of a training dataset. The ability of the CNN, as measured by top-1 accuracy, area under receiver operating characteristics curve (AUC), sensitivity/specificity, and Youden index, in comparison with humans (28 general physicians, 11 general orthopedists, and 19 orthopedists specialized in the shoulder) to detect and classify proximal humerus fractures was evaluated. Results - The CNN showed a high performance of 96% top-1 accuracy, 1.00 AUC, 0.99/0.97 sensitivity/specificity, and 0.97 Youden index for distinguishing normal shoulders from proximal humerus fractures. In addition, the CNN showed promising results with 65-86% top-1 accuracy, 0.90-0.98 AUC, 0.88/0.83-0.97/0.94 sensitivity/specificity, and 0.71-0.90 Youden index for classifying fracture type. When compared with the human groups, the CNN showed superior performance to that of general physicians and orthopedists, similar performance to orthopedists specialized in the shoulder, and the superior performance of the CNN was more marked in complex 3- and 4-part fractures. Interpretation - The use of artificial intelligence can accurately detect and classify proximal humerus fractures on plain shoulder AP radiographs. Further studies are necessary to determine the feasibility of applying artificial intelligence in the clinic and whether its use could improve care and outcomes compared with current orthopedic assessments.

Pathogenesis and antigenic characterization of a new East European subtype 3 porcine reproductive and respiratory syndrome virus isolate

Abstract: Background Porcine reproductive and respiratory syndrome virus (PRRSV) is divided into a European and North American genotype. East European PRRSV isolates have been found to be of the European genotype, but form different subtypes. In the present study, PRRSV was isolated from a Belarusian farm with reproductive and respiratory failure and designated "Lena". Analyses revealed that Lena is a new East European subtype 3 PRRSV isolate. The main purpose of this investigation was to study the pathogenesis and antigenic characteristics of PRRSV (Lena).

Effects of lifestyle intervention in obese pregnant women on gestational weight gain and mental health: a randomized controlled trial

Abstract: Lifestyle intervention could help obese pregnant women to limit their weight gain during pregnancy and improve their psychological comfort, but has not yet been evaluated in randomized controlled trials. We evaluated whether a targeted antenatal lifestyle intervention programme for obese pregnant women influences gestational weight gain (GWG) and levels of anxiety or depressed mood. This study used a longitudinal interventional design. Of the 235 eligible obese pregnant women, 205 (mean age (years): 29±4.5; body mass index (BMI, kg m−2): 34.7±4.6) were randomized to a control group, a brochure group receiving written information on healthy lifestyle and an experimental group receiving an additional four antenatal lifestyle intervention sessions by a midwife trained in motivational lifestyle intervention. Anxiety (State and Trait Anxiety Inventory) and feelings of depression (Edinburgh Depression Scale) were measured during the first, second and third trimesters of pregnancy. Socio-demographical, behavioural, psychological and medical variables were used for controlling and correcting outcome variables. We found a significant reduction of GWG in the brochure (9.5 kg) and lifestyle intervention (10.6 kg) group compared with normal care group (13.5 kg) (P=0.007). Furthermore, levels of anxiety significantly decreased in the lifestyle intervention group and increased in the normal care group during pregnancy (P=0.02); no differences were demonstrated in the brochure group. Pre-pregnancy BMI was positively related to levels of anxiety. Obese pregnant women who stopped smoking recently showed a significant higher GWG (β=3.04; P=0.01); those with concurrent gestational diabetes mellitus (GDM) (β=3.54; P=0.03) and those who consumed alcohol on a regular base (β=3.69; P=0.04) showed significant higher levels of state anxiety. No differences in depressed mood or obstetrical/neonatal outcomes were observed between the three groups. A targeted lifestyle intervention programme based on the principles of motivational interviewing reduces GWG and levels of anxiety in obese pregnant women.