ABSTRACT
Introduction: About one in 500 pregnant women requires a surgical intervention that is not pregnancy-related. One of the most common surgical interventions during pregnancy is appendectomy. The primary aim of this study was to assess surgical access of appendectomy during pregnancy and pregnancy outcome. Secondary outcomes were clinical symptoms and diagnostics as well as histopathological analysis. Methods and Material: This is a single-center retrospective data analysis conducted at a tertiary perinatal center. A digital search of the hospital record archive was conducted focusing on pregnant women beyond 24 0/7 weeks of pregnancy encoding appendectomy. Descriptive statistical analysis was performed. Results: Between January 2013 and January 2023, a total of 20 appendectomies were performed during pregnancy with gestational age beyond 24 0/7 weeks of pregnancy. All of them were performed as lower midline laparotomy. The rate of appendix perforation was 3/20 (15.0%). 19/20 patients (95.0%) delivered via cesarean. In 7/20 patients (35.0%) appendectomy was performed during cesarean delivery due to incidental finding of irritated or abnormal vermiform appendix. In the pathological work-up, only 2/7 (28.6%) of these subjects had inflammation. Conclusion: In this small monocentric cohort, only open appendectomies were performed. Our data indicate that it is safe to perform open appendectomy during pregnancy if necessary. In this small patient group, there was an increase in simultaneous cesarean deliveries.
ABSTRACT
Healthy adults and neurological patients show unique mobility patterns over the course of their lifespan and disease. Quantifying these mobility patterns could support diagnosing, tracking disease progression and measuring response to treatment. This quantification can be done with wearable technology, such as inertial measurement units (IMUs). Before IMUs can be used to quantify mobility, algorithms need to be developed and validated with age and disease-specific datasets. This study proposes a protocol for a dataset that can be used to develop and validate IMU-based mobility algorithms for healthy adults (18-60 years), healthy older adults (>60 years), and patients with Parkinson's disease, multiple sclerosis, a symptomatic stroke and chronic low back pain. All participants will be measured simultaneously with IMUs and a 3D optical motion capture system while performing standardized mobility tasks and non-standardized activities of daily living. Specific clinical scales and questionnaires will be collected. This study aims at building the largest dataset for the development and validation of IMU-based mobility algorithms for healthy adults and neurological patients. It is anticipated to provide this dataset for further research use and collaboration, with the ultimate goal to bring IMU-based mobility algorithms as quickly as possible into clinical trials and clinical routine.