'Hammering nails with a screwdriver': how GPs perceive video consultations.

BACKGROUND: Early in the Covid-19 pandemic, the use of video consultation (VC) expanded considerably, with GPs indicating high satisfaction with it. However, use of VC declined as lock-down measures were eased. AIM: To explore reasons why VC use has declined in Norwegian general practice by investigating GPs' experiences with VC since the start of the pandemic and their attitudes towards it in a post-pandemic setting. DESIGN & SETTING: Qualitative study design. Semi-structured interviews with 13 GPs in southern Norway. METHOD: The method of data analysis was Braun & Clarke's reflexive thematic analysis. RESULTS: Although the implementation of VCs was unplanned, most participants were able to use this modality without much problem. Several GPs initially envisioned long-term VC use. However, despite certain positives, VCs were largely sidelined in favour of face-to-face and telephone consultations due to their practicality and VC's limited usefulness when considering the extra effort required. Nonetheless, GPs recognised ways of using VC that might exploit its strengths, but they highlighted how its sustained use would require them to replace other consultation modalities. They also identified extrinsic factors that might lead to the increased use of VC, including improved VC technology and patient demand. CONCLUSION: Although VC is now part of many GPs' consultation toolbox, its perceived relative lack of usefulness and extra effort compared to other remote consultation modalities mean that most GPs have chosen to abandon it as a routine consultation modality.

Isolation of the Antifungal Compound Alliodorin from the Heartwood of Cordia elaeagnoides A. DC. and the In Silico Analysis of the Laccase.

Cordia elaeagnoides A. DC. is an endemic species of Mexico valued for its timber. Renowned for its durability, resistance, and versatile applications in medicine, this tree holds significant commercial importance. Tetrahydrofuran (THF) extract from the heartwood of C. elaeagnoides was studied. Through chromatographic column purification, the compound 8-(2,5-Dihydroxyphenyl)-2,6-dimethylocta-2,6-dienal, also known as alliodorin, was successfully isolated. Identification of alliodorin was confirmed through comprehensive analysis utilizing NMR, IR, and mass spectrometry techniques. Inhibition tests were conducted using both the THF extract and alliodorin against the rotting fungus Trametes versicolor (L.) Lloyd, employing the agar well diffusion assay. Remarkably, alliodorin exhibited 100% inhibition with a median lethal concentration of 0.079 mg/mL and a total lethal concentration of 0.127 mg/mL, in comparison to the commercial fungicide benomyl, which requires a concentration of 1 mg/mL. In silico analysis through molecular docking on the laccase enzyme was proposed in order to explain the inhibitory activity against the fungus T. versicolor, as this enzyme is one of the main sources of nutrients and development for the fungus. Based on these findings, we deduced that alliodorin holds promise as a potent antifungal agent, potentially applicable in a wide array of technological and environmentally friendly initiatives.

Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets.

Effective population size (N e) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium (LD), in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software program based on the LD method, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the N e estimates obtained with GONE for the last generations with the contemporary N e estimates obtained with the programs currentNe and NeEstimator.

Effectiveness of Psychobiotics in the Treatment of Psychiatric and Cognitive Disorders: A Systematic Review of Randomized Clinical Trials.

In this study, a systematic review of randomized clinical trials conducted from January 2000 to December 2023 was performed to examine the efficacy of psychobiotics-probiotics beneficial to mental health via the gut-brain axis-in adults with psychiatric and cognitive disorders. Out of the 51 studies involving 3353 patients where half received psychobiotics, there was a notably high measurement of effectiveness specifically in the treatment of depression symptoms. Most participants were older and female, with treatments commonly utilizing strains of Lactobacillus and Bifidobacteria over periods ranging from 4 to 24 weeks. Although there was a general agreement on the effectiveness of psychobiotics, the variability in treatment approaches and clinical presentations limits the comparability and generalization of the findings. This underscores the need for more personalized treatment optimization and a deeper investigation into the mechanisms through which psychobiotics act. The research corroborates the therapeutic potential of psychobiotics and represents progress in the management of psychiatric and cognitive disorders.

[Medical nutrition therapy in amyotrophic lateral sclerosis - Do we act or react? A case report and multidisciplinary review]. / Tratamiento médico nutricional en la esclerosis lateral amiotrófica: ¿Actuamos o reaccionamos? Un caso clínico y revisión multidisciplinar.

BACKGROUND: amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease with a progressive course. The current prevalence is between 3 and 6 cases/100,000. Malnutrition is closely related to patient prognosis in ALS. The implications of this conditions have been that we should recommend patient care in a multidisciplinary unit. CASE REPORT: the case presented shows the evolution of a patient with ALS. The patient was referred to different clinical departments after neurological evaluation and her nutritional, functional and respiratory status were assessed. There was no nutritional deterioration at diagnosis; however, intake was below energy-protein requirements. The clinical evolution of the patient showed a decrease in muscle mass with preservation of weight and fat mass. "Aggressive" measures to control nutritional status such as gastrostomy were rejected in the initial stages of the disease, but had to be carried out after development of dysphagia and associated malnutrition. This situation of progressive morphofunctional deterioration and the development of disease-related complications made essential the participation of different health services and professionals in its control. DICUSSION: the management of ALS in a multidisciplinary manner allows to improve the course of the disease and the quality of life of both the patients and their families. Patient follow-up is based on the adjustment and management of complications. The basis of the relationship with these patients includes maintaining an adequate communication with them and their families, and ensuring joint decision-making about their condition.

The Utilization Of Virtual Reality In Training Tactical Decision-Making In Argentinian Rugby

This study investigates the possible advantages and uses of virtual reality (VR) technology in developing rugby players from Argentina's ability to make tactical decisions. Rugby is becoming an even more dynamic and strategic sport. Thus, there's a growingneed for creative training techniques. The research was based on secondary data analysis to determine the data using E-views software and generate results, including descriptive statistics, and equality test analysis, which also explains the model summaryrelated to dependent and independent variables. With virtual reality (VR), players can imitate actual game conditions in a secure setting, honing their strategic thinking and cognitive skills without the physical rigours of on-field practice. The overall research found significant utilization of virtual reality in training tactical decision-making in Argentinian rugby. Virtual reality (VR) can assist rugby players in improving their decision-making process, collaboration, communication abilities, and overall effectiveness on the pitch through immersive and repetitive training experiences. The benefits of virtual reality training, its possible effects on player growth, and its ramifications for the future of rugby in Argentina are all covered in this essay. It also discusses factors to consider when integrating virtual reality technology into rugby training programs. It offers areas for more study to optimize its ability to improve tactical competence in Argentine rugby players. (AU)

The WHO atlas for female-genital schistosomiasis: Co-design of a practicable diagnostic guide, digital support and training.

Up to 56 million young and adult women of African origin suffer from Female Genital Schistosomiasis (FGS). The transmission of schistosomiasis happens through contact with schistosomiasis infested fresh water in rivers and lakes. The transmission vector is the snail that releases immature worms capable of penetrating the human skin. The worm then matures and mates in the blood vessels and deposits its eggs in tissues, causing urogenital disease. There is currently no gold standard for FGS diagnosis. Reliable diagnostics are challenging due to the lack of appropriate instruments and clinical skills. The World Health Organisation (WHO) recommends "screen-and-treat" cervical cancer management, by means of visual inspection of characteristic lesions on the cervix and point-of-care treatment as per the findings. FGS may be mistaken for cervical cancer or sexually transmitted diseases. Misdiagnosis may lead to the wrong treatment, increased risk of exposure to other infectious diseases (human immunodeficiency virus and human papilloma virus), infertility and stigmatisation. The necessary clinical knowledge is only available to a few experts in the world. For an appropriate diagnosis, this knowledge needs to be transferred to health professionals who have minimal or non-existing laboratory support. Co-design workshops were held with stakeholders (WHO representative, national health authority, FGS experts and researchers, gynaecologists, nurses, medical doctors, public health experts, technical experts, and members of the public) to make prototypes for the WHO Pocket Atlas for FGS, a mobile diagnostic support tool and an e-learning tool for health professionals. The dissemination targeted health facilities, including remote areas across the 51 anglophone, francophone and lusophone African countries. Outcomes were endorsed by the WHO and comprise a practical diagnostic guide for FGS in low-resource environments.

Novel method for chlorine determination in biofuel lipid feedstock by coupling a total sample introduction system (hTISIS) to an inductively coupled plasma tandem mass spectrometry (ICP-MS/MS).

BACKGROUND: Chlorine concentrations above 1 mg kg-1 in lipid feedstocks for biofuel production can generate corrosion issues in the different refining units as well as catalyst deactivation by clogging or fouling. To reach accurate analyses by inductively coupled plasma (ICP) techniques at low concentration levels, dilution in organic solvents rises as a simpler and more straightforward sample preparation methodology than conventional sample decomposition procedures (e.g., microwave-assisted acid digestion). However, matrix effects and the impact of the Cl chemical form on the signal must be overcome to obtain accurate results. RESULTS: In this work, the high temperature torch integrated sample introduction system (hTISIS) operated at 350 °C is coupled to an inductively coupled plasma tandem mass spectrometry (ICP-MS/MS) for the determination of Cl in lipid biofuel feedstock samples diluted in xylene and these results are compared with those reported by a conventional sample introduction system. Under optimal conditions of the hTISIS-ICP-MS/MS configuration, matrix effects are efficiently overcome (recovery values ranged from 101 to 104%) as well as the effect of the Cl chemical form on the signal for 6 organochloride compounds. Thus, an external calibration approach can be set to carry out the quantification of this element in real samples. The method is successfully validated, obtaining a good agreement in the Cl concentration reported in a standard reference material (SRM NIST 1634c) and also by comparing the concentration results obtained by external calibration and standard addition approaches in two biofuel feedstock samples. SIGNIFICANCE AND NOVELTY: The hTISIS coupled to an ICP-MS/MS system is used for the first time to overcome not only matrix effects but also the impact of the Cl chemical form in biofuel feedstock samples. This novel method, with a limit of quantification (LOQ) of 7.1 µg kg-1, give access to an accurate Cl determination in all kind of lipid feedstocks for clean fuel production.

A Prospective, Multicenter, Real-World Registry of Coronary Lithotripsy in Calcified Coronary Arteries: The REPLICA-EPIC18 Study.

BACKGROUND: Intravascular lithotripsy (IVL) has demonstrated effectiveness in the treatment of calcified lesions in selected patients with stable coronary disease. OBJECTIVES: The authors sought to assess the performance of coronary IVL in calcified coronary lesions in a real-life, all comers, setting. METHODS: The REPLICA-EPIC18 study prospectively enrolled consecutive patients treated with IVL in 26 centers in Spain. An independent core laboratory performed the angiographic analysis and event adjudication. The primary effectiveness endpoint assessed procedural success (successful IVL delivery, final diameter stenosis <20%, and absence of in-hospital major adverse cardiovascular events [MACE]). The primary safety endpoint measured freedom from MACE at 30 days. A predefined substudy compared outcomes between acute coronary syndrome (ACS) and chronic coronary syndrome (CCS) patients. RESULTS: A total of 426 patients (456 lesions) were included, 63% of the patients presenting with ACS. IVL delivery was successful in 99% of cases. Before IVL, 49% of lesions were considered undilatable. The primary effectiveness endpoint was achieved in 66% of patients, with similar rates among CCS patients (68%) and ACS patients (65%). Likewise, there were no significant differences in angiographic success after IVL between CCS and ACS patients. The rate of MACE at 30 days (primary safety endpoint) was 3% (1% in CCS and 5% in ACS patients [P = 0.073]). CONCLUSIONS: Coronary IVL proved to be a feasible and safe procedure in a "real-life" setting, effectively facilitating stent implantation in severely calcified lesions. Patients with ACS on admission showed similar angiographic success rates but showed a trend toward higher 30-day MACE compared with patients with CCS. (REPLICA-EPIC18 study [Registry of Coronary Lithotripsy in Spain]; NCT04298307).

Semantic representation and comparative analysis of physical activity sensor observations using MOX2-5 sensor in real and synthetic datasets: a proof-of-concept-study.

The widespread use of devices like mobile phones and wearables allows for automatic monitoring of human daily activities, generating vast datasets that offer insights into long-term human behavior. A structured and controlled data collection process is essential to unlock the full potential of this information. While wearable sensors for physical activity monitoring have gained significant traction in healthcare, sports science, and fitness applications, securing diverse and comprehensive datasets for research and algorithm development poses a notable challenge. In this proof-of-concept study, we underscore the significance of semantic representation in enhancing data interoperability and facilitating advanced analytics for physical activity sensor observations. Our approach focuses on enhancing the usability of physical activity datasets by employing a medical-grade (CE certified) sensor to generate synthetic datasets. Additionally, we provide insights into ethical considerations related to synthetic datasets. The study conducts a comparative analysis between real and synthetic activity datasets, assessing their effectiveness in mitigating model bias and promoting fairness in predictive analysis. We have created an ontology for semantically representing observations from physical activity sensors and conducted predictive analysis on data collected using MOX2-5 activity sensors. Until now, there has been a lack of publicly available datasets for physical activity collected with MOX2-5 activity monitoring medical grade (CE certified) device. The MOX2-5 captures and transmits high-resolution data, including activity intensity, weight-bearing, sedentary, standing, low, moderate, and vigorous physical activity, as well as steps per minute. Our dataset consists of physical activity data collected from 16 adults (Male: 12; Female: 4) over a period of 30-45 days (approximately 1.5 months), yielding a relatively small volume of 539 records. To address this limitation, we employ various synthetic data generation methods, such as Gaussian Capula (GC), Conditional Tabular General Adversarial Network (CTGAN), and Tabular General Adversarial Network (TABGAN), to augment the dataset with synthetic data. For both the authentic and synthetic datasets, we have developed a Multilayer Perceptron (MLP) classification model for accurately classifying daily physical activity levels. The findings underscore the effectiveness of semantic ontology in semantic search, knowledge representation, data integration, reasoning, and capturing meaningful relationships between data. The analysis supports the hypothesis that the efficiency of predictive models improves as the volume of additional synthetic training data increases. Ontology and Generative AI hold the potential to expedite advancements in behavioral monitoring research. The data presented, encompassing both real MOX2-5 and its synthetic counterpart, serves as a valuable resource for developing robust methods in activity type classification. Furthermore, it opens avenues for exploration into research directions related to synthetic data, including model efficiency, detection of generated data, and considerations regarding data privacy.

Integrating Egocentric and Robotic Vision for Object Identification Using Siamese Networks and Superquadric Estimations in Partial Occlusion Scenarios.

This paper introduces a novel method that enables robots to identify objects based on user gaze, tracked via eye-tracking glasses. This is achieved without prior knowledge of the objects' categories or their locations and without external markers. The method integrates a two-part system: a category-agnostic object shape and pose estimator using superquadrics and Siamese networks. The superquadrics-based component estimates the shapes and poses of all objects, while the Siamese network matches the object targeted by the user's gaze with the robot's viewpoint. Both components are effectively designed to function in scenarios with partial occlusions. A key feature of the system is the user's ability to move freely around the scenario, allowing dynamic object selection via gaze from any position. The system is capable of handling significant viewpoint differences between the user and the robot and adapts easily to new objects. In tests under partial occlusion conditions, the Siamese networks demonstrated an 85.2% accuracy in aligning the user-selected object with the robot's viewpoint. This gaze-based Human-Robot Interaction approach demonstrates its practicality and adaptability in real-world scenarios.

Patients' perceptions of use, needs, and preferences related to a telemedicine solution for HIV care in a Norwegian outpatient clinic: a qualitative study.

BACKGROUND: Telemedicine in outpatient services for people living with human immunodeficiency virus (PLHIV) was scaled up during the COVID-19 pandemic as services transitioned to remote care. Many studies have reported on the challenges and advantages of telemedicine care during the pandemic. However, there is limited research on the provision of telemedicine human immunodeficiency virus (HIV) care beyond the COVID-19 pandemic, which entails different telemedicine components and focuses on ways to improve the telemedicine experience for patients. This study aimed to explore PLHIV's perceptions of use, needs, and preferences related to a telemedicine solution for HIV care in an outpatient clinic in Norway. The telemedicine solution included a pre-consultation questionnaire, asynchronous digital messages, and video consultation. METHODS: Qualitative interviews were conducted with 12 PLHIV. The interviews were analysed using thematic analysis. RESULTS: We identified four main themes that covered the participants' perceptions, needs, and preferences: (1) perceived usability, (2) maintaining confidentiality, (3) accommodating personal preferences, and (4) perceived usefulness. Some participants had difficulty logging into the telemedicine solution. Other participants suggested additional functionalities, such as picture sharing and access to test result. Telemedicine care enabled the avoidance of stigmatising clinic experiences, although a few participants reported concerns about confidentiality and data security. Accommodating personal preferences and needs in terms of the type of consultations (in-person or video) and frequency of visits was essential to the participants. With telemedicine care, participants felt more in control of their own lives, perceiving that it increased their perceived quality of life and saved them both time and money for travelling to the clinic. CONCLUSIONS: Our study identified several specific needs and preferences related to the assessed technical solution and the provision of current and future telemedicine care services. Nevertheless, the telemedicine solution was perceived as a usable, flexible, and person-centred approach to HIV care, contributing to accommodating the participants' personal preferences. However, healthcare professionals need to ensure that individual requirements and preferences are consistent with evidence-based follow-up and supported by person-centred care. Thus, the practice of shared decision making is important in telemedicine care.

Interleukin-6 Induces Stem Cell Propagation through Liaison with the Sortilin-Progranulin Axis in Breast Cancer.

Unraveling the complex network between cancer cells and their tumor microenvironment is of clinical importance, as it might allow for the identification of new targets for cancer treatment. Cytokines and growth factors secreted by various cell types present in the tumor microenvironment have the potential to affect the challenging subpopulation of cancer stem cells showing treatment-resistant properties as well as aggressive features. By using various model systems, we investigated how the breast cancer stem cell-initiating growth factor progranulin influenced the secretion of cancer-associated proteins. In monolayer cultures, progranulin induced secretion of several inflammatory-related cytokines, such as interleukin (IL)-6 and -8, in a sortilin-dependent manner. Further, IL-6 increased the cancer stem fraction similarly to progranulin in the breast cancer cell lines MCF7 and MDA-MB-231 monitored by the surrogate mammosphere-forming assay. In a cohort of 63 patient-derived scaffold cultures cultured with breast cancer cells, we observed significant correlations between IL-6 and progranulin secretion, clearly validating the association between IL-6 and progranulin also in human-based microenvironments. In conclusion, the interplay between progranulin and IL-6 highlights a dual breast cancer stem cell-promoting function via sortilin, further supporting sortilin as a highly relevant therapeutic target for aggressive breast cancer.

Advances of Nanotechnology in the Diagnosis and Treatment of Hepatocellular Carcinoma.

Nanotechnology has emerged as a promising technology in the field of hepatocellular carcinoma (HCC), specifically in the implementation of diagnosis and treatment strategies. Nanotechnology-based approaches, such as nanoparticle-based contrast agents and nanoscale imaging techniques, have shown great potential for enhancing the sensitivity and specificity of HCC detection. These approaches provide high-resolution imaging and allow for the detection of molecular markers and alterations in cellular morphology associated with HCC. In terms of treatment, nanotechnology has revolutionized HCC therapy by enabling targeted drug delivery, enhancing therapeutic efficacy, and minimizing off-target effects. Nanoparticle-based drug carriers can be functionalized with ligands specific to HCC cells, allowing for selective accumulation of therapeutic agents at the tumor site. Furthermore, nanotechnology can facilitate combination therapy by co-encapsulating multiple drugs within a single nanoparticle, allowing for synergistic effects and overcoming drug resistance. This review aims to provide an overview of recent advances in nanotechnology-based approaches for the diagnosis and treatment of HCC. Further research is needed to optimize the design and functionality of nanoparticles, improve their biocompatibility and stability, and evaluate their long-term safety and efficacy. Nonetheless, the integration of nanotechnology in HCC management holds great promise and may lead to improved patient outcomes in the future.

Low but significant evolutionary potential for growth, phenology and reproduction traits in European beech.

Local survival of forest tree populations under climate change depends on existing genetic variation and their adaptability to changing environments. Responses to selection were studied in European beech (Fagus sylvatica) under field conditions. A total of 1087 adult trees, seeds, 1-year-old seedlings and established multiyear saplings were genotyped with 16 nuSSRs. Adult trees were assessed for phenotypic traits related to growth, phenology and reproduction. Parentage and paternity analyses were used to estimate effective female and male fecundity as a proxy of fitness and showed that few parents contributed to successful regeneration. Selection gradients were estimated from the relationship between traits and fecundity, while heritability and evolvability were estimated using mixed models and the breeder's equation. Larger trees bearing more fruit and early male flowering had higher total fecundity, while trees with longer growth season had lower total fecundity (directional selection). Stabilizing selection on spring phenology was found for female fecundity, highlighting the role of late frosts as a selection driver. Selection gradients for other traits varied between measurement years and the offspring cohort used to estimate parental fecundity. Compared to other studies in natural populations, we found low to moderate heritability and evolvability for most traits. Response to selection was higher for growth than for budburst, leaf senescence or reproduction traits, reflecting more consistent selection gradients across years and sex functions, and higher phenotypic variability in the population. Our study provides empirical evidence suggesting that populations of long-lived organisms such as forest trees can adapt locally, even at short-time scales.

Between but Not Within-Species Variation in the Distribution of Fitness Effects.

New mutations provide the raw material for evolution and adaptation. The distribution of fitness effects (DFE) describes the spectrum of effects of new mutations that can occur along a genome, and is, therefore, of vital interest in evolutionary biology. Recent work has uncovered striking similarities in the DFE between closely related species, prompting us to ask whether there is variation in the DFE among populations of the same species, or among species with different degrees of divergence, that is whether there is variation in the DFE at different levels of evolution. Using exome capture data from six tree species sampled across Europe we characterized the DFE for multiple species, and for each species, multiple populations, and investigated the factors potentially influencing the DFE, such as demography, population divergence, and genetic background. We find statistical support for the presence of variation in the DFE at the species level, even among relatively closely related species. However, we find very little difference at the population level, suggesting that differences in the DFE are primarily driven by deep features of species biology, and those evolutionarily recent events, such as demographic changes and local adaptation, have little impact.

Continuous Assessment of Function and Disability via Mobile Sensing: Real-World Data-Driven Feasibility Study.

BACKGROUND: Functional limitations are associated with poor clinical outcomes, higher mortality, and disability rates, especially in older adults. Continuous assessment of patients' functionality is important for clinical practice; however, traditional questionnaire-based assessment methods are very time-consuming and infrequently used. Mobile sensing offers a great range of sources that can assess function and disability daily. OBJECTIVE: This work aims to prove the feasibility of an interpretable machine learning pipeline for predicting function and disability based on the World Health Organization Disability Assessment Schedule (WHODAS) 2.0 outcomes of clinical outpatients, using passively collected digital biomarkers. METHODS: One-month-long behavioral time-series data consisting of physical and digital activity descriptor variables were summarized using statistical measures (minimum, maximum, mean, median, SD, and IQR), creating 64 features that were used for prediction. We then applied a sequential feature selection to each WHODAS 2.0 domain (cognition, mobility, self-care, getting along, life activities, and participation) in order to find the most descriptive features for each domain. Finally, we predicted the WHODAS 2.0 functional domain scores using linear regression using the best feature subsets. We reported the mean absolute errors and the mean absolute percentage errors over 4 folds as goodness-of-fit statistics to evaluate the model and allow for between-domain performance comparison. RESULTS: Our machine learning-based models for predicting patients' WHODAS functionality scores per domain achieved an average (across the 6 domains) mean absolute percentage error of 19.5%, varying between 14.86% (self-care domain) and 27.21% (life activities domain). We found that 5-19 features were sufficient for each domain, and the most relevant being the distance traveled, time spent at home, time spent walking, exercise time, and vehicle time. CONCLUSIONS: Our findings show the feasibility of using machine learning-based methods to assess functional health solely from passively sensed mobile data. The feature selection step provides a set of interpretable features for each domain, ensuring better explainability to the models' decisions-an important aspect in clinical practice.

Use of Telemonitoring for CPAP Therapy Control in OSA Patients: Impact on Cost and Process Improvements.

Introduction: In Spain, 2 million people are treated for obstructive sleep apnoea. Continuous positive airway pressure, the gold-standard therapy, requires regular follow-up and periodic evaluation of the efficacy of the treatment via a titration examination, i.e. autoCPAP test. Telemonitoring use is increasing and this study aims to evaluate the cost impact of its use for therapy evaluation instead of the standard ambulatory autoCPAP test. Methods: This prospective observational study includes 100 OSA patients under CPAP therapy who volunteered to test telemonitoring as an alternative therapy control tool. Costs for both the patients and the Sleep Unit were calculated and compared for the standard of care (ambulatory autoCPAP (SoC)), vs alternative telemonitoring option (TM). Results: More than half (54%) of the patients preferred the TM option vs only 47.5% of the SoC patients. Patients inclining towards telemonitoring option were mainly reported to be more than 10 years youngers, mainly active workers (63%), travelling more distance to the Sleep Unit (16 vs 8 km) and spending more expenses in travel than those who preferred SoC (median 30€). 29% of active workers left their jobs to attend the SoC. The costs related to the use of the Sleep Unit resources were found to be lower in the TM option compared to the SoC option (0.47 vs 3.09 euros per patient attended). Conclusions: The use of TM for follow-up CPAP therapy enables the patient to save travel costs and to reduce absenteeism but also to save assistential burden and therefore to reduce the Sleep Unit workload and optimize the care activity.

Postoperative pain management in the elderly. Literature review

Timely post-operative pain management in elderly patients is critically important. Given their physiological changes and comorbidities, management in this group of patients is different from the rest of the population. Knowledge of potentially inappropriate medications (Beers criteria) is relevant because of the presence of comorbidities in this population. Although acetaminophen continues to be safe, non-steroidal anti-inflammatory agents produce several adverse effects which need to be considered before they are used. On the other hand, opioids continue to be one of the pillars in analgesia, with due consideration of their adverse affects and interactions, and the need for dose adjustments. Adequate postoperative pain management prevents adverse effects and the risk of developing chronic pain.

El manejo oportuno del dolor en la población anciana durante el periodo posoperatorio es de vital importancia. Este grupo de pacientes, dado sus cambios fisiológicos y comorbilidades, requieren un manejo diferente al resto de la población. Es relevante conocer cuáles medicamentos son potencialmente inapropiados para su uso (criterios de Beers) ante las comorbilidades de esta población. Si bien el acetaminofén continúa siendo seguro, los antiinflamatorios no esteroideos causan varios efectos adversos que ameritan consideración antes de su uso; por su parte, los opioides siguen siendo uno de los pilares analgésicos, teniendo en cuenta sus efectos adversos y valorando la necesidad de ajuste de dosis e interacciones. El adecuado manejo del dolor posoperatorio previene desenlaces adversos y el riesgo de cronificación.

Automatic patient functionality assessment from multimodal data using deep learning techniques - Development and feasibility evaluation.

Wearable devices and mobile sensors enable the real-time collection of an abundant source of physiological and behavioural data unobtrusively. Unlike traditional in-person evaluation or ecological momentary assessment (EMA) questionnaire-based approaches, these data sources open many possibilities in remote patient monitoring. However, defining robust models is challenging due to the data's noisy and frequently missing observations. This work proposes an attention-based Long Short-Term Memory (LSTM) neural network-based pipeline for predicting mobility impairment based on WHODAS 2.0 evaluation from such digital biomarkers. Furthermore, we addressed the missing observation problem by utilising hidden Markov models and the possibility of including information from unlabelled samples via transfer learning. We validated our approach using two wearable/mobile sensor data sets collected in the wild and socio-demographic information about the patients. Our results showed that in the WHODAS 2.0 mobility impairment prediction task, the proposed pipeline outperformed a prior baseline while additionally providing interpretability with attention heatmaps. Moreover, using a much smaller cohort via task transfer learning, the same model could learn to predict generalised anxiety severity accurately based on GAD-7 scores.