Résection laparoscopique d’une duplication gastrique chez l’adulte: traitement avec succès pour une pathologie rare

Les duplications de l'appareil digestif sont les malformations congénitales rares qui peuvent toucher tout  l'appareil digestive depuis la bouche jusqu' à l'anus. Certaines duplications sont asymptomatiques et sont diagnostiqués dans la plupart des cas pendant l'enfance. La prise en charge de la duplication gastrique est essentiellement chirurgicale. Le traitement de choix est l'exérèse complète de la duplication gastrique. Les auteurs rapportent un cas inhabituel de duplication gastrique complètement reséquée par laparoscopie. A notre connaissance, ceci est le premier cas d'une duplication gastrique traitée avec succès par laparoscopie dans la littérature Tunisienne. La Résection laparoscopique peut être ajoutée à l'arsenal thérapeutique dans le traitement chirurgical de duplications du tube digestif.Key words: Duplication, estomac, diagnostic, endoscopi

Does wet-cupping therapy improve repeated sprint ability, perceived wellness, and rating of perceived exertion in young active males?

Wet-cupping therapy (WCT) is one of the oldest known medical techniques, used as a traditional and complementary therapy with a wide application all around the world for general health. Research on the effects of WCT on sports performance are sparse and inconsistent. Thus, we aimed to explore the effects of WCT on repeated sprint ability, wellness, and exertion in young active males. Forty-nine active adult males (age: [28 ​± ​5] years; body height [177 ​± ​8] cm; body mass: [79 ​± ​7] kg; body mass index: [25.4 ​± ​1.8] kg/m2) were selected for the study. The participants performed a running-based sprint test on two separate occasions (Control and Post-WCT). WCT was performed 24 ​h before the testing session. They completed the Hooper questionnaire to assess their well-being (i.e., sleep, stress, fatigue, and soreness) before each session. The rating of perceived exertion (RPE) was collected after each testing session. A higher maximum power (p ​< ​0.05, effect size [ES] ​= ​0.6), mean power (p ​< ​0.01, ES ​= ​0.5) and minimum power (p ​< ​0.01, ES ​= ​0.6) were recorded post-WCT as compared to Control session along with a better perceived sleep (p ​< ​0.01, ES ​= ​0.85). Perceived stress (p ​< ​0.01, ES ​= ​0.6) and RPE (p ​< ​0.001; ES ​= ​1.1) were lower during the post-WCT compared to the Control session. The present findings demonstrated that WCT moderately enhanced repeated sprint ability and had positive effects on perceived sleep, stress, and exertion. WCT may be an effective ergogenic aid to improve repeated sprint ability and general well-being in young adult males. Future large-scale multicentric clinical studies are paramount to confirm the results of our study

Using artificial intelligence for exercise prescription in personalised health promotion: A critical evaluation of OpenAI’s GPT-4 model

The rise of artificial intelligence (AI) applications in healthcare provides new possibilities for personalized health management. AI-based fitness applications are becoming more common, facilitating the opportunity for individualised exercise prescription. However, the use of AI carries the risk of inadequate expert supervision, and the efficacy and validity of such applications have not been thoroughly investigated, particularly in the context of diverse health conditions. The aim of the study was to critically assess the efficacy of exercise prescriptions generated by OpenAI’s Generative Pre-Trained Transformer 4 (GPT-4) model for five example patient profiles with diverse health conditions and fitness goals. Our focus was to assess the model’s ability to generate exercise prescriptions based on a singular, initial interaction, akin to a typical user experience. The evaluation was conducted by leading experts in the field of exercise prescription. Five distinct scenarios were formulated, each representing a hypothetical individual with a specific health condition and fitness objective. Upon receiving details of each individual, the GPT-4 model was tasked with generating a 30-day exercise program. These AI-derived exercise programs were subsequently subjected to a thorough evaluation by experts in exercise prescription. The evaluation encompassed adherence to established principles of frequency, intensity, time, and exercise type; integration of perceived exertion levels; consideration for medication intake and the respective medical condition; and the extent of program individualization tailored to each hypothetical profile. The AI model could create general safety-conscious exercise programs for various scenarios. However, the AI-generated exercise prescriptions lacked precision in addressing individual health conditions and goals, often prioritizing excessive safety over the effectiveness of training. The AI-based approach aimed to ensure patient improvement through gradual increases in training load and intensity, but the model’s potential to fine-tune its recommendations through ongoing interaction was not fully satisfying. AI technologies, in their current state, can serve as supplemental tools in exercise prescription, particularly in enhancing accessibility for individuals unable to access, often costly, professional advice. However, AI technologies are not yet recommended as a substitute for personalized, progressive, and health condition specific prescriptions provided by healthcare and fitness professionals. Further research is needed to explore more interactive use of AI models and integration of real-time physiological feedback

Training during the COVID-19 lockdown : knowledge, beliefs, and practices of 12,526 athletes from 142 countries and six continents

OBJECTIVE Our objective was to explore the training-related knowledge, beliefs, and practices of athletes and the influence of lockdowns in response to the coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). METHODS Athletes (n = 12,526, comprising 13% world class, 21% international, 36% national, 24% state, and 6% recreational) completed an online survey that was available from 17 May to 5 July 2020 and explored their training behaviors (training knowledge, beliefs/attitudes, and practices), including specific questions on their training intensity, frequency, and session duration before and during lockdown (March–June 2020). RESULTS Overall, 85% of athletes wanted to “maintain training,” and 79% disagreed with the statement that it is “okay to not train during lockdown,” with a greater prevalence for both in higher-level athletes. In total, 60% of athletes considered “coaching by correspondence (remote coaching)” to be sufficient (highest amongst world-class athletes). During lockdown, < 40% were able to maintain sport-specific training (e.g., long endurance [39%], interval training [35%], weightlifting [33%], most (83%) training for “general fitness and health maintenance” during lockdown. Athletes trained alone (80%) and focused on bodyweight (65%) and cardiovascular (59%) exercise/training during lockdown. Compared with before lockdown, most athletes reported reduced training frequency (from between five and seven sessions per week to four or fewer), shorter training sessions (from ≥ 60 to < 60 min), and lower sport-specific intensity (~ 38% reduction), irrespective of athlete classification. CONCLUSIONS COVID-19-related lockdowns saw marked reductions in athletic training specificity, intensity, frequency, and duration, with notable within-sample differences (by athlete classification). Higher classification athletes had the strongest desire to “maintain” training and the greatest opposition to “not training” during lockdowns. These higher classification athletes retained training specificity to a greater degree than others, probably because of preferential access to limited training resources. More higher classification athletes considered “coaching by correspondence” as sufficient than did lower classification athletes. These lockdown-mediated changes in training were not conducive to maintenance or progression of athletes’ physical capacities and were also likely detrimental to athletes’ mental health. These data can be used by policy makers, athletes, and their multidisciplinary teams to modulate their practice, with a degree of individualization, in the current and continued pandemic-related scenario. Furthermore, the data may drive training-related educational resources for athletes and their multidisciplinary teams. Such upskilling would provide athletes with evidence to inform their training modifications in response to germane situations (e.g., COVID related, injury, and illness).A specific funding was provided by the National Sports Institute of Malaysia for this study.The National Sports Institute of Malaysia.https://www.springer.com/journal/40279am2023Sports Medicin

COVID-19 lockdown : a global study investigating athletes’ sport classification and sex on training practices

PURPOSE : To investigate differences in athletes’ knowledge, beliefs, and training practices during COVID-19 lockdowns with reference to sport classification and sex. This work extends an initial descriptive evaluation focusing on athlete classification. METHODS : Athletes (12,526; 66% male; 142 countries) completed an online survey (May–July 2020) assessing knowledge, beliefs, and practices toward training. Sports were classified as team sports (45%), endurance (20%), power/technical (10%), combat (9%), aquatic (6%), recreational (4%), racquet (3%), precision (2%), parasports (1%), and others (1%). Further analysis by sex was performed. RESULTS : During lockdown, athletes practiced body-weight-based exercises routinely (67% females and 64% males), ranging from 50% (precision) to 78% (parasports). More sport-specific technical skills were performed in combat, parasports, and precision (∼50%) than other sports (∼35%). Most athletes (range: 50% [parasports] to 75% [endurance]) performed cardiorespiratory training (trivial sex differences). Compared to prelockdown, perceived training intensity was reduced by 29% to 41%, depending on sport (largest decline: ∼38% in team sports, unaffected by sex). Some athletes (range: 7%–49%) maintained their training intensity for strength, endurance, speed, plyometric, change-of-direction, and technical training. Athletes who previously trained ≥5 sessions per week reduced their volume (range: 18%–28%) during lockdown. The proportion of athletes (81%) training ≥60 min/session reduced by 31% to 43% during lockdown. Males and females had comparable moderate levels of training knowledge (56% vs 58%) and beliefs/attitudes (54% vs 56%). CONCLUSIONS : Changes in athletes’ training practices were sport-specific, with few or no sex differences. Team-based sports were generally more susceptible to changes than individual sports. Policy makers should provide athletes with specific training arrangements and educational resources to facilitate remote and/or home-based training during lockdown-type events.https://journals.humankinetics.com/view/journals/ijspp/ijspp-overview.xmlhj2023Sports Medicin

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Un flot de conception pour générer automatiquement des moniteurs sur puce pendant la synthèse de haut niveau d'accélérateurs matériels

Embedded systems are increasingly used in various fields like transportation, industrial automation, telecommunication or healthcare to execute critical applications and manipulate sensitive data. These systems often involve financial and industrial interests but also human lives which imposes strong safety constraints.Hence, a key issue lies in the ability of such systems to respond safely when errors occur at runtime and prevent unacceptable behaviors. Errors can be due to natural causes such as particle hits as well as internal noise, integrity problems, but also due to malicious attacks. Embedded system architecture typically includes processor (s), memories, Input / Output interface, bus controller and hardware accelerators that are used to improve both energy efficiency and performance. With the evolution of applications, the design cycle of hardware accelerators becomes more and more complex. This complexity is partly due to the specification of hardware accelerators traditionally based on handwritten Hardware Description Language (HDL) files. However, High-Level Synthesis (HLS) that promotes automatic or semi-automatic generation of hardware accelerators according to software specification, like C code, allows reducing this complexity.The work proposed in this document targets the integration of verification support in HLS tools to generate On-Chip Monitors (OCMs) during the high-level synthesis of hardware accelerators (HWaccs). Three distinct contributions are proposed. The first one consists in checking the Input / Output timing behavior errors (synchronization with the whole system) as well as the control flow errors (illegal jumps or infinite loops). On-Chip Monitors are automatically synthesized and require no modification in their high-level specification. The second contribution targets the synthesis of high-level properties (ANSI-C asserts) that are added into the software specification of HWacc. Synthesis options are proposed to trade-off area overhead, performance impact and protection level. The third contribution improves the detection of data corruptions that can alter the stored values or/and modify the data transfers without causing assertions violations or producing illegal jumps. Those errors are detected by duplicating a subset of program’s data limited to the most critical variables. In addition, the properties over the evolution of loops induction variables are automatically extracted from the algorithmic description of HWacc. It should be noticed that all the proposed approaches, in this document, allow only detecting errors at runtime. The counter reaction i.e. the way how the HWacc reacts if an error is detected is out of scope of this work.Les systèmes embarqués sont de plus en plus utilisés dans des domaines divers tels que le transport, l’automatisation industrielle, les télécommunications ou la santé pour exécuter des applications critiques et manipuler des données sensibles. Ces systèmes impliquent souvent des intérêts financiers et industriels, mais aussi des vies humaines ce qui impose des contraintes fortes de sûreté. Par conséquent, un élément clé réside dans la capacité de tels systèmes à répondre correctement quand des erreurs se produisent durant l’exécution et ainsi empêcher des comportements induits inacceptables. Les erreurs peuvent être d’origines naturelles telles que des impacts de particules, du bruit interne (problème d’intégrité), etc. ou provenir d’attaques malveillantes. Les architectures de systèmes embarqués comprennent généralement un ou plusieurs processeurs, des mémoires, des contrôleurs d’entrées/sorties ainsi que des accélérateurs matériels utilisés pour améliorer l’efficacité énergétique et les performances. Avec l’évolution des applications, le cycle de conception d’accélérateurs matériels devient de plus en plus complexe. Cette complexité est due en partie aux spécifications des accélérateurs matériels qui reposent traditionnellement sur l’écriture manuelle de fichiers en langage de description matérielle (HDL).Cependant, la synthèse de haut niveau (HLS) qui favorise la génération automatique ou semi-automatique d’accélérateurs matériels à partir de spécifications logicielles, comme du code C, permet de réduire cette complexité.Le travail proposé dans ce manuscrit cible l’intégration d’un support de vérification dans les outils de HLS pour générer des moniteurs sur puce au cours de la synthèse de haut niveau des accélérateurs matériels. Trois contributions distinctes ont été proposées. La première contribution consiste à contrôler les erreurs de comportement temporel des entrées/sorties (impactant la synchronisation avec le reste du système) ainsi que les erreurs du flot de contrôle (sauts illégaux ou problèmes de boucles infinies). La synthèse des moniteurs est automatique sans qu’aucune modification de la spécification utilisée en entrée de la HLS ne soit nécessaire. La deuxième contribution vise la synthèse des propriétés de haut niveau (ANSI-C asserts) qui ont été ajoutées dans la spécification logicielle de l’accélérateur matériel. Des options de synthèse ont été proposées pour arbitrer le compromis entre le surcout matériel, la dégradation de la performance et le niveau de protection. La troisième contribution améliore la détection des corruptions des données qui peuvent modifier les valeurs stockées, et/ou modifier les transferts de données, sans violer les assertions (propriétés) ni provoquer de sauts illégaux. Ces erreurs sont détectées en dupliquant un sous-ensemble des données du programme, limité aux variables les plus critiques. En outre, les propriétés sur l’évolution des variables d’induction des boucles ont été automatiquement extraites de la description algorithmique de l’accélérateur matériel. Il faut noter que l’ensemble des approches proposées dans ce manuscrit, ne s’intéresse qu’à la détection d’erreurs lors de l’exécution. La contreréaction c.à.d. la manière dont le moniteur réagit si une erreur est détectée n’est pas abordée dans ce document