N-Beats as an EHG signal forecasting method for labour prediction in full term pregnancy

The early prediction of onset labour is critical for avoiding the risk of death due to pregnancy delay. Low-income countries often struggle to deliver timely service to pregnant women due to a lack of infrastructure and healthcare facilities, resulting in pregnancy complications and, eventually, death. In this regard, several artificial-intelligence-based methods have been proposed based on the detection of contractions using electrohysterogram (EHG) signals. However, the forecasting of pregnancy contractions based on real-time EHG signals is a challenging task. This study proposes a novel model based on neural basis expansion analysis for interpretable time series (N-BEATS) which predicts labour based on EHG forecasting and contraction classification over a given time horizon. The publicly available TPEHG database of Physiobank was exploited in order to train and test the model, where signals from full-term pregnant women and signals recorded after 26 weeks of gestation were collected. For these signals, the 30 most commonly used classification parameters in the literature were calculated, and principal component analysis (PCA) was utilized to select the 15 most representative parameters (all the domains combined). The results show that neural basis expansion analysis for interpretable time series (N-BEATS) forecasting can forecast EHG signals through training after few iterations. Similarly, the forecasting signal’s duration is determined by the length of the recordings. We then deployed XG-Boost, which achieved the classification accuracy of 99 percent, outperforming the state-of-the-art approaches using a number of classification features greater than or equal to 15

A review about Technology in mental health sensing and assessment

Information and communication technologies (ICT) such as smart devices, the Internet of Things and wireless sensor networks are gradually being introduced into the health system for early diagnosis and management of certain diseases. The state of the art of the use of these technologies in mental health identified 37 articles published in indexed high impact journals in the period 2003-2021. The snowball sampling method was used to select these papers. From this literature review, it appears that several of these technologies are used to support the early detection of mental disorders. Various systems based on wearable sensor networks, the Internet of Things and pervasive and ubiquitous computing have been designed and implemented in this sense. However, most of the applications are designed for academic purposes. 29% of the papers deal with the use of mobile technology in the detection of mental illness, while 67% have studied other technologies such as wearable sensor networks. 4% of the papers concern the use of web platforms in the detection and assessment of mental health disorders

Moroccans’ ethnobotanical knowledge about medicinal tar

International audienceTar has been employed by humans since antiquity due to its importance and benefits. Up until now, it is still used in traditional medicine in different countries including Morocco. Using a quantitative research method, this study sheds light on the traditional properties and usage of tar from various social class perspectives in Morocco. To collect data about the general knowledge about tar, three groups of people were given an ethnobotanical questionnaire: general population, herbalists, and tar producers. An online survey was delivered to the general population, while a semi-structured questionnaire was employed to interview the other groups.The online participants were evenly split into two groups according to their gender. Also, there were twelve males for every one female for the herbalists, whereas the producers were entirely males. Tar usage was roughly the same across all three categories. Participants mentioned Juniperus sp., Cedrus sp., and more, herbalists mentioned Eucalyptus sp., Olea sp., and the producers mentioned Yew. For tar production, the online participants and herbalists knew the procedure with a percentage of 21% and 40% respectively, followed by 100% for producers. In this study, producers have more information and understanding about tar production than herbalists, who have a better knowledge about tar usage. Furthermore, medicinal tar is an intriguing product that deserves to be respected

Safety of Nonsteroidal Anti-inflammatory Drugs in Major Gastrointestinal Surgery: A Prospective, Multicenter Cohort Study

Background Significant safety concerns remain surrounding the use of nonsteroidal anti-inflammatory drugs (NSAIDs) following gastrointestinal surgery, leading to wide variation in their use. This study aimed to determine the safety profile of NSAIDs after major gastrointestinal surgery. Methods Consecutive patients undergoing elective or emergency abdominal surgery with a minimum one-night stay during a 3-month study period were eligible for inclusion. The administration of any NSAID within 3 days following surgery was the main independent variable. The primary outcome measure was the 30-day postoperative major complication rate, as defined by the Clavien–Dindo classification (Clavien–Dindo III–V). Propensity matching with multivariable logistic regression was used to produce odds ratios (OR) and 95 % confidence intervals. Results From 9264 patients, 23.9 % (n = 2212) received postoperative NSAIDs. The overall major complication rate was 11.5 % (n = 1067). Following propensity matching and adjustment, use of NSAIDs were not significantly associated with any increase in major complications (OR 0.90, 0.60–1.34, p = 0.560). Conclusions Early use of postoperative NSAIDs was not associated with an increase in major complications following gastrointestinal surgery

Body mass index and complications following major gastrointestinal surgery: A prospective, international cohort study and meta-analysis

Aim Previous studies reported conflicting evidence on the effects of obesity on outcomes after gastrointestinal surgery. The aims of this study were to explore the relationship of obesity with major postoperative complications in an international cohort and to present a metaanalysis of all available prospective data. Methods This prospective, multicentre study included adults undergoing both elective and emergency gastrointestinal resection, reversal of stoma or formation of stoma. The primary end-point was 30-day major complications (Clavien\u2013Dindo Grades III\u2013V). A systematic search was undertaken for studies assessing the relationship between obesity and major complications after gastrointestinal surgery. Individual patient meta-analysis was used to analyse pooled results. Results This study included 2519 patients across 127 centres, of whom 560 (22.2%) were obese. Unadjusted major complication rates were lower in obese vs normal weight patients (13.0% vs 16.2%, respectively), but this did not reach statistical significance (P = 0.863) on multivariate analysis for patients having surgery for either malignant or benign conditions. Individual patient meta-analysis demonstrated that obese patients undergoing surgery formalignancy were at increased risk of major complications (OR 2.10, 95% CI 1.49\u20132.96, P < 0.001), whereas obese patients undergoing surgery for benign indications were at decreased risk (OR 0.59, 95% CI 0.46\u20130.75, P < 0.001) compared to normal weight patients. Conclusions In our international data, obesity was not found to be associated with major complications following gastrointestinal surgery. Meta-analysis of available prospective data made a novel finding of obesity being associated with different outcomes depending on whether patients were undergoing surgery for benign or malignant disease

Body mass index and complications following major gastrointestinal surgery: a prospective, international cohort study and meta-analysis.

AIM: Previous studies reported conflicting evidence on the effects of obesity on outcomes after gastrointestinal surgery. The aims of this study were to explore the relationship of obesity with major postoperative complications in an international cohort and to present a meta-analysis of all available prospective data. METHODS: This prospective, multicentre study included adults undergoing both elective and emergency gastrointestinal resection, reversal of stoma or formation of stoma. The primary end-point was 30-day major complications (Clavien-Dindo Grades III-V). A systematic search was undertaken for studies assessing the relationship between obesity and major complications after gastrointestinal surgery. Individual patient meta-analysis was used to analyse pooled results. RESULTS: This study included 2519 patients across 127 centres, of whom 560 (22.2%) were obese. Unadjusted major complication rates were lower in obese vs normal weight patients (13.0% vs 16.2%, respectively), but this did not reach statistical significance (P = 0.863) on multivariate analysis for patients having surgery for either malignant or benign conditions. Individual patient meta-analysis demonstrated that obese patients undergoing surgery for malignancy were at increased risk of major complications (OR 2.10, 95% CI 1.49-2.96, P < 0.001), whereas obese patients undergoing surgery for benign indications were at decreased risk (OR 0.59, 95% CI 0.46-0.75, P < 0.001) compared to normal weight patients. CONCLUSIONS: In our international data, obesity was not found to be associated with major complications following gastrointestinal surgery. Meta-analysis of available prospective data made a novel finding of obesity being associated with different outcomes depending on whether patients were undergoing surgery for benign or malignant disease