Pregnancy related anxiety and general anxious or depressed mood and the choice for birth setting:A secondary data-analysis of the DELIVER study

BACKGROUND: In several developed countries women with a low risk of complications during pregnancy and childbirth can make choices regarding place of birth. In the Netherlands, these women receive midwife-led care and can choose between a home or hospital birth. The declining rate of midwife-led home births alongside the recent debate on safety of home births in the Netherlands, however, suggest an association of choice of birth place with psychological factors related to safety and risk perception. In this study associations of pregnancy related anxiety and general anxious or depressed mood with (changes in) planned place of birth were explored in low risk women in midwife-led care until the start of labour. METHODS: Data (n = 2854 low risk women in midwife-led care at the onset of labour) were selected from the prospective multicenter DELIVER study. Women completed the Pregnancy Related Anxiety Questionnaire-Revised (PRAQ-R) to assess pregnancy related anxiety and the EuroQol-6D (EQ-6D) for an anxious and/or depressed mood. RESULTS: A high PRAQ-R score was associated with planned hospital birth in nulliparous (aOR 1.92; 95% CI 1.32–2.81) and parous women (aOR 2.08; 95% CI 1.55–2.80). An anxious or depressed mood was associated with planned hospital birth (aOR 1.58; 95% CI 1.20–2.08) and with being undecided (aOR 1.99; 95% CI 1.23–2.99) in parous women only. The majority of women did not change their planned place of birth. Changing from an initially planned home birth to a hospital birth later in pregnancy was, however, associated with becoming anxious or depressed after 35 weeks gestation in nulliparous women (aOR 4.17; 95% CI 1.35–12.89) and with pregnancy related anxiety at 20 weeks gestation in parous women (aOR 3.91; 95% CI 1.32–11.61). CONCLUSION: Low risk women who planned hospital birth (or who were undecided) more often reported pregnancy related anxiety or an anxious or depressed mood. Women who changed from home to hospital birth during pregnancy more often reported pregnancy related anxiety or an anxious or depressed mood in late pregnancy. Anxiety should be adequately addressed in the process of informed decision-making regarding planned place of birth in low risk women

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works recognize surgical activities at a coarse-grained level, such as phases, steps or events, leaving out fine-grained interaction details about the surgical activity; yet those are needed for more helpful AI assistance in the operating room. Recognizing surgical actions as triplets of ‹instrument, verb, target› combination delivers more comprehensive details about the activities taking place in surgical videos. This paper presents CholecTriplet2021: an endoscopic vision challenge organized at MICCAI 2021 for the recognition of surgical action triplets in laparoscopic videos. The challenge granted private access to the large-scale CholecT50 dataset, which is annotated with action triplet information. In this paper, we present the challenge setup and the assessment of the state-of-the-art deep learning methods proposed by the participants during the challenge. A total of 4 baseline methods from the challenge organizers and 19 new deep learning algorithms from the competing teams are presented to recognize surgical action triplets directly from surgical videos, achieving mean average precision (mAP) ranging from 4.2% to 38.1%. This study also analyzes the significance of the results obtained by the presented approaches, performs a thorough methodological comparison between them, in-depth result analysis, and proposes a novel ensemble method for enhanced recognition. Our analysis shows that surgical workflow analysis is not yet solved, and also highlights interesting directions for future research on fine-grained surgical activity recognition which is of utmost importance for the development of AI in surgery