ABSTRACT
Objective: This study aimed to explore the influencing factors of adverse outcomes in the offspring of women with epilepsy (WWE) and to analyze the changes brought about by the epilepsy knowledge popularization campaign in China (EKPCIC). Methods: This nested case-control study focused on WWE and their offspring from a female epilepsy cohort in mainland China. From January 2009 to August 2022, WWE was prospectively enrolled in 32 study centers. This study aimed to observe the health outcomes of their offspring within 1 year of age. The main outcome measure assessed the health status of the offspring within their first year of age. We aimed to analyze the effects of seizures, anti-seizure medicines (ASMs), and a lack of folic acid supplementation on adverse outcomes in the offspring of WWE and to explore the changes in perinatal management and adverse outcomes of the offspring after dissemination of the EKPCIC in 2015. Additionally, subgroup analyses were conducted to compare seizure control during pregnancy between the valproate and non-valproate groups. Results: In total, 781 pregnancies in 695 WWE were included, of which 186 (23.69%) had adverse outcomes. The National Hospital Epilepsy Severity Scale score, number of seizures, status epilepticus, ASM type, and valproate and folic acid doses were associated with a high risk of adverse outcomes. After the EKPCIC, the use of ASMs (P = 0.013) and folic acid (P < 0.001), the seizure-free rate during pregnancy (P = 0.013), and the breastfeeding rate (P < 0.001) increased, whereas the incidence of complications during pregnancy decreased (P = 0.013). However, there was no significant difference in the incidence of adverse outcomes between the analyzed offspring pre-/post-EKPCIC. Additionally, there was no association between the frequency of seizures at different time points during pregnancy and the use of valproate (F = 1.514, P = 0.221). Conclusion: Possible factors influencing adverse outcomes in the offspring of WWE include seizures, type and number of ASM usage, and a lack of folic acid supplementation. Although the management of WWE during pregnancy is now more standardized, further efforts are needed to reduce adverse outcomes in offspring.
ABSTRACT
Many biomedical applications require fine motor skill assessments; however, real-time and contactless fine motor skill assessments are not typically implemented. In this study, we followed the 2D-to-3D pipeline principle and proposed a transformer-based spatial-temporal network to accurately regress 3D hand joint locations by inputting infrared thermal video for eliminating need of multiple cameras or RGB-D devices. We also developed a dataset composed of infrared thermal videos and ground truth annotations for training. The label represents a set of 3D joint locations from infrared optical trackers, which is considered the gold standard for clinical applications. To demonstrate their potential, the proposed method was used to measure the finger motion angle, and we investigated its accuracy by comparing the proposal with the Azure Kinect system and Leap Motion system. On the proposed dataset, the proposed method achieved a 3D hand pose mean error of less than 14 mm and outperforms the other deep learning methods. When the error thresholds were larger than approximately 35 mm, our method first to achieved excellent performance (>80%) in terms of the fraction of good frames. For the finger motion angle calculation task, the proposed and commercial systems had comparable inter-system reliability (ICC2,1 ranging from 0.81 to 0.83) and excellent validity (Pearson's r-values ranging from 0.82 to 0.86). We believe that the proposed approaches can capture hand motion and measure finger motion angles and can be used in different biomedicine scenarios as an effective evaluation tool for fine motor skills.
