Automated Machine Learning Predicts Necessary Upcoming Therapy Changes in Patients With Psoriasis Vulgaris et Arthritis And Uncovers New Influences On Disease Progression: Retrospective Study.

BACKGROUND: Psoriasis vulgaris (PsV) and Psoriatic arthritis (PsA) are intertwined multifactorial diseases with significant impact on health and quality of life, which can be debilitating due to chronicity and treatment complexity. Predicting treatment response and disease progression in these conditions is challenging, but crucial for optimising therapeutic interventions. The advancing technology of automated machine learning (AutoML) holds great promise for rapidly building highly accurate predictive models based on patient features and treatment data. OBJECTIVE: The study aimed to develop highly accurate ML models using AutoML to address key clinical questions in PsV and PsA patients, including predicting therapy changes and identifying reasons for therapy changes, factors influencing skin lesion progression or factors associated with an abnormal BASDAI score. METHODS: After extensive dataset preparation of clinical study data from 309 PsV and PsA patients, a secondary dataset was created and ultimately analysed using AutoML to build a variety of predictive models and select the most accurate one for each variable of interest. RESULTS: "Therapy change at 24 weeks follow-up" was modelled using the eXtreme Gradient Boosted Trees Classifier with Early Stopping model (AUC of 0.9078 and LogLoss of 0.3955 for the holdout partition) to gain insight into the factors influencing therapy change, such as the initial systemic therapeutic agent, the score achieved in the CASPAR classification criteria at baseline, and changes in quality of life. An AVG blender of 3 models (Gradient Boosted Trees Classifier, ExtraTrees Classifier, Eureqa Generalised Additive Model Classifier) with an AUC of 0.8750 and a LogLoss of 0.4603 was used to predict therapy changes on two hypothetical patients to highlight the importance of such influencing factors. Notably, treatments such as MTX or specific biologicals showed a lower propensity for change. A further AVG Blender of RandomForest Classifier, eXtreme Gradient Boosted Trees Classifier and Eureqa Classifier (AUC of 0.9241 and LogLoss of 0.4498) was then used to estimate "PASI change after 24 weeks" with the primary predictors being the initial PASI score, change in pruritus and change in therapy. A lower initial PASI score, and consistently low pruritus were associated with better outcomes. Finally, "BASDAI classification at baseline" was analysed using an AVG Blender of Eureqa Generalised Additive Model Classifier, eXtreme Gradient Boosted Trees Classifier with Early Stopping and Dropout Additive Regression Trees Classifier with an AUC of 0.8274 and LogLoss of 0.5037. Factors influencing BASDAI scores included initial pain, disease activity and HADS scores for depression and anxiety. Increased pain, disease activity and psychological distress were generally likely to lead to higher BASDAI scores. CONCLUSIONS: The practical implications of these models for clinical decision making in PsV and PsA have the potential to guide early investigation and treatment, contributing to improved patient outcomes.

Correction: Telehealth Education in Allied Health Care and Nursing: Web-Based Cross-Sectional Survey of Students' Perceived Knowledge, Skills, Attitudes, and Experience.

[This corrects the article DOI: 10.2196/51112.].

Evaluation of a hybrid telehealth care pathway for patients with axial spondyloarthritis including self-sampling at home: results of a longitudinal proof-of-concept mixed-methods study (TeleSpactive).

Patients with axial spondyloarthritis (axSpA) require close monitoring to achieve the goal of sustained disease remission. Telehealth can facilitate continuous care while relieving scarce healthcare resources. In a mixed-methods proof-of-concept study, we investigated a hybrid telehealth care axSpA pathway in patients with stable disease over 6 months. Patients used a medical app to document disease activity (BASDAI and PtGA bi-weekly, flare questionnaire weekly). To enable a remote ASDAS-CRP (TELE-ASDAS-CRP), patients used a capillary self-sampling device at home. Monitoring results were discussed and a decision was reached via shared decision-making whether a pre-planned 3-month on-site appointment (T3) was necessary. Ten patients completed the study, and eight patients also completed additional telephone interviews. Questionnaire adherence was high; BASDAI (82.3%), flares (74.8%) and all patients successfully completed the TELE-ASDAS-CRP for the T3 evaluation. At T3, 9/10 patients were in remission or low disease activity and all patients declined the offer of an optional T3 on-site appointment. Patient acceptance of all study components was high with a net promoter score (NPS) of +50% (mean NPS 8.8 ± 1.5) for self-sampling, +70% (mean NPS 9.0 ± 1.6) for the electronic questionnaires and +90% for the T3 teleconsultation (mean NPS 9.7 ± 0.6). In interviews, patients reported benefits such as a better overview of their condition, ease of use of telehealth tools, greater autonomy, and, most importantly, travel time savings. To our knowledge, this is the first study to investigate a hybrid approach to follow-up axSpA patients including self-sampling. The positive results observed in this scalable proof-of-concept study warrant a larger confirmatory study.

Tensile Load-Bearing Behaviour of Concrete Components Reinforced with Flax Fibre Textiles.

In recent years, the use of natural flax fibres as a reinforcement in composite building structures has witnessed a growing interest amongst research communities due to their green, economical, and capable mechanical properties. Most of the previous investigations on the load-bearing behaviour of concrete components reinforced with natural flax fibres include inorganic impregnations (or even no impregnation) and exclude the use of textile fabrics. Also, the mechanical behaviour of textiles made of natural flax fibres produced as leno fabrics remains to be investigated. In this paper, the results of tensile tests on concrete components reinforced with bio-based impregnated leno fabrics are presented. For comparison, multilayer non-impregnated and impregnated textiles were considered. The results demonstrated that reinforced textiles yielded an increase in the failure loads compared to the concrete cross-sections without reinforcement. The stress-strain diagrams showed that the curves can be divided into three sections, which are typical for reinforced tensile test specimens. For the impregnated textiles, a narrowly distributed crack pattern was observed. The results showed that impregnated textiles tend to support higher failure stresses with less strains than non-impregnated textiles. Moreover, an increase in the reinforcement ratio alongside larger opening widths of the warp yarns enables higher failure loads.

[Orthopedics and trauma surgery in the digital age]. / Orthopädie und Unfallchirurgie im digitalen Zeitalter.

BACKGROUND: Digital transformation is shaping the future of orthopedics and trauma surgery. Telemedicine, digital health applications, electronic patient records and artificial intelligence play a central role in this. These technologies have the potential to improve medical care, enable individualized patient treatment plans and reduce the burden on the treatment process. However, there are currently challenges in the areas of infrastructure, regulation, reimbursement and data protection. REALISING THE TRANSFORMATION: Effective transformation requires a deep understanding of both technology and clinical practice. Orthopedic and trauma surgeons need to take a leadership role by actively engaging with new technologies, designing new treatment processes and enhancing their medical skills with digital and AI competencies. The integration of digital skills into medical education and specialist training will be crucial for actively shaping the digital transformation and exploiting its full potential.

Telehealth Education in Allied Health Care and Nursing: Web-Based Cross-Sectional Survey of Students' Perceived Knowledge, Skills, Attitudes, and Experience.

BACKGROUND: The COVID-19 pandemic has highlighted the growing relevance of telehealth in health care. Assessing health care and nursing students' telehealth competencies is crucial for its successful integration into education and practice. OBJECTIVE: We aimed to assess students' perceived telehealth knowledge, skills, attitudes, and experiences. In addition, we aimed to examine students' preferences for telehealth content and teaching methods within their curricula. METHODS: We conducted a cross-sectional web-based study in May 2022. A project-specific questionnaire, developed and refined through iterative feedback and face-validity testing, addressed topics such as demographics, personal perceptions, and professional experience with telehealth and solicited input on potential telehealth course content. Statistical analyses were conducted on surveys with at least a 50% completion rate, including descriptive statistics of categorical variables, graphical representation of results, and Kruskal Wallis tests for central tendencies in subgroup analyses. RESULTS: A total of 261 students from 7 bachelor's and 4 master's health care and nursing programs participated in the study. Most students expressed interest in telehealth (180/261, 69% very or rather interested) and recognized its importance in their education (215/261, 82.4% very or rather important). However, most participants reported limited knowledge of telehealth applications concerning their profession (only 7/261, 2.7% stated profound knowledge) and limited active telehealth experience with various telehealth applications (between 18/261, 6.9% and 63/261, 24.1%). Statistically significant differences were found between study programs regarding telehealth interest (P=.005), knowledge (P<.001), perceived importance in education (P<.001), and perceived relevance after the pandemic (P=.004). Practical training with devices, software, and apps and telehealth case examples with various patient groups were perceived as most important for integration in future curricula. Most students preferred both interdisciplinary and program-specific courses. CONCLUSIONS: This study emphasizes the need to integrate telehealth into health care education curricula, as students state positive telehealth attitudes but seem to be not adequately prepared for its implementation. To optimally prepare future health professionals for the increasing role of telehealth in practice, the results of this study can be considered when designing telehealth curricula.

Pre-assessment of patients with suspected axial spondyloarthritis combining student-led clinics and telemedicine: a qualitative study.

OBJECTIVE: Patients referred to rheumatologists are currently facing months of inefficient waiting time due to the increasing demand and rising workforce shortage. We piloted a pre-assessment of patients with suspected axial spondyloarthritis (axSpA) combining student-led clinics and telemedicine (symptom assessment, symptom monitoring and at-home capillary self-sampling) to improve access to rheumatology care. The aim of this study was to explore (1) current challenges accessing axSpA care and (2) patients' first-hand experiences. METHODS: Embedded within a clinical trial, this study was based on qualitative interviews with patients with suspected axSpA (n = 20). Data was analysed via qualitative content analysis. RESULTS: Student-led clinics were perceived as high-quality care, comparable to conventional rheumatologist-led visits. Patients expressed that their interactions with the students instilled a sense of trust. History-taking and examinations were perceived as comprehensive and meticulous. Telehealth tools were seen as empowering, offering immediate and continuous access to symptom assessment at home. Patients reported a lack of specificity of the electronic questionnaires, impeding accurate responses. Patients requested a comments area to supplement questionnaire responses. Some patients reported receiving help to complete the blood collection. CONCLUSION: Patients' access to rheumatology care is becoming increasingly burdensome. Pre-assessment including student-led clinics and telemedicine was highly accepted by patients. Patient interviews provided valuable in-depth feedback to improve the piloted patient pathway.

The Role of AI in Serious Games and Gamification for Health: Scoping Review.

BACKGROUND: Artificial intelligence (AI) and game-based methods such as serious games or gamification are both emerging technologies and methodologies in health care. The merging of the two could provide greater advantages, particularly in the field of therapeutic interventions in medicine. OBJECTIVE: This scoping review sought to generate an overview of the currently existing literature on the connection of AI and game-based approaches in health care. The primary objectives were to cluster studies by disease and health topic addressed, level of care, and AI or games technology. METHODS: For this scoping review, the databases PubMed, Scopus, IEEE Xplore, Cochrane Library, and PubPsych were comprehensively searched on February 2, 2022. Two independent authors conducted the screening process using Rayyan software (Rayyan Systems Inc). Only original studies published in English since 1992 were eligible for inclusion. The studies had to involve aspects of therapy or education in medicine and the use of AI in combination with game-based approaches. Each publication was coded for basic characteristics, including the population, intervention, comparison, and outcomes (PICO) criteria; the level of evidence; the disease and health issue; the level of care; the game variant; the AI technology; and the function type. Inductive coding was used to identify the patterns, themes, and categories in the data. Individual codings were analyzed and summarized narratively. RESULTS: A total of 16 papers met all inclusion criteria. Most of the studies (10/16, 63%) were conducted in disease rehabilitation, tackling motion impairment (eg, after stroke or trauma). Another cluster of studies (3/16, 19%) was found in the detection and rehabilitation of cognitive impairment. Machine learning was the main AI technology applied and serious games the main game-based approach used. However, direct interaction between the technologies occurred only in 3 (19%) of the 16 studies. The included studies all show very limited quality evidence. From the patients' and healthy individuals' perspective, generally high usability, motivation, and satisfaction were found. CONCLUSIONS: The review shows limited quality of evidence for the combination of AI and games in health care. Most of the included studies were nonrandomized pilot studies with few participants (14/16, 88%). This leads to a high risk for a range of biases and limits overall conclusions. However, the first results present a broad scope of possible applications, especially in motion and cognitive impairment, as well as positive perceptions by patients. In future, the development of adaptive game designs with direct interaction between AI and games seems promising and should be a topic for future reviews.

Industry perspective on a holistic container closure integrity approach to parenteral combination products.

Biologics are being developed more and more as parenteral combination products with drug delivery devices. The maintenance of sterility is imperative for such medical devices throughout their life cycle. Therefore, the container closure integrity (CCI) should, preferably, be built into the overall process, and not just demonstrated during the final testing of the combination product. The integrity is an important Critical Quality Attribute (CQA) and in the scope of specific considerations and studies during the combination product life cycle i.e., design robustness, assembly processes, storage (to end of shelf life), and shipping prior to patient use. The goal of this paper is to summarize an industry holistic approach to ensure CCI, for a combination product, and to build a scientifically based justification that Quality (in terms of CCI) is built into the overall process. Current analytical approaches used for characterization or Good Manufacturing Practice (GMP) CCI testing during combination product development will be described. However, the use of quality by design (QbD) during product development can reduce or eliminate routine batch level or stability testing of the combination product.

ChatGPT Versus Consultants: Blinded Evaluation on Answering Otorhinolaryngology Case-Based Questions.

BACKGROUND: Large language models (LLMs), such as ChatGPT (Open AI), are increasingly used in medicine and supplement standard search engines as information sources. This leads to more "consultations" of LLMs about personal medical symptoms. OBJECTIVE: This study aims to evaluate ChatGPT's performance in answering clinical case-based questions in otorhinolaryngology (ORL) in comparison to ORL consultants' answers. METHODS: We used 41 case-based questions from established ORL study books and past German state examinations for doctors. The questions were answered by both ORL consultants and ChatGPT 3. ORL consultants rated all responses, except their own, on medical adequacy, conciseness, coherence, and comprehensibility using a 6-point Likert scale. They also identified (in a blinded setting) if the answer was created by an ORL consultant or ChatGPT. Additionally, the character count was compared. Due to the rapidly evolving pace of technology, a comparison between responses generated by ChatGPT 3 and ChatGPT 4 was included to give an insight into the evolving potential of LLMs. RESULTS: Ratings in all categories were significantly higher for ORL consultants (P<.001). Although inferior to the scores of the ORL consultants, ChatGPT's scores were relatively higher in semantic categories (conciseness, coherence, and comprehensibility) compared to medical adequacy. ORL consultants identified ChatGPT as the source correctly in 98.4% (121/123) of cases. ChatGPT's answers had a significantly higher character count compared to ORL consultants (P<.001). Comparison between responses generated by ChatGPT 3 and ChatGPT 4 showed a slight improvement in medical accuracy as well as a better coherence of the answers provided. Contrarily, neither the conciseness (P=.06) nor the comprehensibility (P=.08) improved significantly despite the significant increase in the mean amount of characters by 52.5% (n= (1470-964)/964; P<.001). CONCLUSIONS: While ChatGPT provided longer answers to medical problems, medical adequacy and conciseness were significantly lower compared to ORL consultants' answers. LLMs have potential as augmentative tools for medical care, but their "consultation" for medical problems carries a high risk of misinformation as their high semantic quality may mask contextual deficits.

Recommendation to implementation of remote patient monitoring in rheumatology: lessons learned and barriers to take.

Remote patient monitoring (RPM) leverages advanced technology to monitor and manage patients' health remotely and continuously. In 2022 European Alliance of Associations for Rheumatology (EULAR) points-to-consider for remote care were published to foster adoption of RPM, providing guidelines on where to position RPM in our practices. Sample papers and studies describe the value of RPM. But for many rheumatologists, the unanswered question remains the 'how to?' implement RPM.Using the successful, though not frictionless example of the Southmead rheumatology department, we address three types of barriers for the implementation of RPM: service, clinician and patients, with subsequent learning points that could be helpful for new teams planning to implement RPM. These address, but are not limited to, data governance, selecting high quality cost-effective solutions and ensuring compliance with data protection regulations. In addition, we describe five lacunas that could further improve RPM when addressed: establishing quality standards, creating a comprehensive database of available RPM tools, integrating data with electronic patient records, addressing reimbursement uncertainties and improving digital literacy among patients and healthcare professionals.

Automated Machine Learning Analysis of Patients With Chronic Skin Disease Using a Medical Smartphone App: Retrospective Study.

BACKGROUND: Rapid digitalization in health care has led to the adoption of digital technologies; however, limited trust in internet-based health decisions and the need for technical personnel hinder the use of smartphones and machine learning applications. To address this, automated machine learning (AutoML) is a promising tool that can empower health care professionals to enhance the effectiveness of mobile health apps. OBJECTIVE: We used AutoML to analyze data from clinical studies involving patients with chronic hand and/or foot eczema or psoriasis vulgaris who used a smartphone monitoring app. The analysis focused on itching, pain, Dermatology Life Quality Index (DLQI) development, and app use. METHODS: After extensive data set preparation, which consisted of combining 3 primary data sets by extracting common features and by computing new features, a new pseudonymized secondary data set with a total of 368 patients was created. Next, multiple machine learning classification models were built during AutoML processing, with the most accurate models ultimately selected for further data set analysis. RESULTS: Itching development for 6 months was accurately modeled using the light gradient boosted trees classifier model (log loss: 0.9302 for validation, 1.0193 for cross-validation, and 0.9167 for holdout). Pain development for 6 months was assessed using the random forest classifier model (log loss: 1.1799 for validation, 1.1561 for cross-validation, and 1.0976 for holdout). Then, the random forest classifier model (log loss: 1.3670 for validation, 1.4354 for cross-validation, and 1.3974 for holdout) was used again to estimate the DLQI development for 6 months. Finally, app use was analyzed using an elastic net blender model (area under the curve: 0.6567 for validation, 0.6207 for cross-validation, and 0.7232 for holdout). Influential feature correlations were identified, including BMI, age, disease activity, DLQI, and Hospital Anxiety and Depression Scale-Anxiety scores at follow-up. App use increased with BMI >35, was less common in patients aged >47 years and those aged 23 to 31 years, and was more common in those with higher disease activity. A Hospital Anxiety and Depression Scale-Anxiety score >8 had a slightly positive effect on app use. CONCLUSIONS: This study provides valuable insights into the relationship between data characteristics and targeted outcomes in patients with chronic eczema or psoriasis, highlighting the potential of smartphone and AutoML techniques in improving chronic disease management and patient care.

Digital Approaches for Myositis.

PURPOSE OF REVIEW: This article serves as a comprehensive review, focusing on digital approaches utilized in the diagnosis, monitoring, and treatment of patients with idiopathic inflammatory myopathies (IIM). The authors critically assess the literature published in the last three years, evaluating the advancements and progress achieved in this specific domain. RECENT FINDINGS: Remarkable strides have been made in the realm of digital diagnostic support, particularly in image analysis and clinical prediction models, showing promise in aiding the diagnosis of IIM. The field of remote patient monitoring has also witnessed significant advancements, revolutionizing the care process by offering more convenient, data-driven, and continuous monitoring for IIM patients. Various digital tools, such as wearables, video- and voice consultations, and electronic patient-reported outcomes, have been extensively explored and implemented to enhance patient care. Survey studies consistently reveal a high acceptance of telehealth services among patients. Additionally, internet-based studies have facilitated the efficient and rapid recruitment of IIM patients for research purposes. Moreover, the integration of sensors and exoskeletons has shown great potential in significantly improving the functionality and quality of life for individuals with muscle weakness caused by IIM. The integration of digital health solutions in the care of IIM patients is steadily gaining attention and exploration. Although the existing evidence is limited, it does indicate that patients can be adequately and safely supported through digital means throughout their entire healthcare journey. The growing interest in digital health technologies holds the promise of improving the overall management and outcomes for individuals with idiopathic inflammatory myopathies.

Tailoring the Preformed Solid Electrolyte Interphase in Lithium Metal Batteries: Impact of Fluoroethylene Carbonate.

The film-forming electrolyte additive/co-solvent fluoroethylene carbonate (FEC) can play a crucial role in enabling high-energy-density lithium metal batteries (LMBs). Its beneficial impact on homogeneous and compact lithium (Li) deposition morphology leads to improved Coulombic efficiency (CE) of the resulting cell chemistry during galvanostatic cycling and consequently an extended cell lifetime. Herein, the impact of this promising additive/co-solvent on selected properties of LMBs is systematically investigated by utilizing an in-house developed lithium pretreatment method. The results reveal that as long as FEC is present in the organic carbonate-based electrolyte, a dense mosaic-like lithium morphology of Li deposits with a reduced polarization of only 20 mV combined with a prolonged cycle life is achieved. When the pretreated Li electrodes with an FEC-derived preformed SEI (pSEI) are galvanostatically cycled with the FEC-free electrolyte, the described benefits induced by the additive are not observable. These results underline that the favorable properties of the FEC-derived SEI are beneficial only if there is unreacted FEC in the electrolyte formulation left to constantly reform the interphase layer, which is especially important for anodes with high-volume changes and dynamic surfaces like lithium metal and lithiated silicon.

Challenging ChatGPT 3.5 in Senology-An Assessment of Concordance with Breast Cancer Tumor Board Decision Making.

With the recent diffusion of access to publicly available large language models (LLMs), common interest in generative artificial-intelligence-based applications for medical purposes has skyrocketed. The increased use of these models by tech-savvy patients for personal health issues calls for a scientific evaluation of whether LLMs provide a satisfactory level of accuracy for treatment decisions. This observational study compares the concordance of treatment recommendations from the popular LLM ChatGPT 3.5 with those of a multidisciplinary tumor board for breast cancer (MTB). The study design builds on previous findings by combining an extended input model with patient profiles reflecting patho- and immunomorphological diversity of primary breast cancer, including primary metastasis and precancerous tumor stages. Overall concordance between the LLM and MTB is reached for half of the patient profiles, including precancerous lesions. In the assessment of invasive breast cancer profiles, the concordance amounts to 58.8%. Nevertheless, as the LLM makes considerably fraudulent decisions at times, we do not identify the current development status of publicly available LLMs to be adequate as a support tool for tumor boards. Gynecological oncologists should familiarize themselves with the capabilities of LLMs in order to understand and utilize their potential while keeping in mind potential risks and limitations.

[Digital rheumatology]. / Digitale Rheumatologie.

Chronic inflammatory rheumatic diseases mostly run an undulating course and with unspecific symptoms. The initial clarification and timely initiation of treatment are challenging, which is additionally exacerbated by the lack of specialized physicians. Digital approaches, including artificial intelligence (AI), should be of assistance and enable an improved, personalized and needs-based treatment; however, the evidence is currently still very limited. This article provides a compact overview of the current state of digital rheumatology.

Barriers to Video Call-Based Telehealth in Allied Health Professions and Nursing: Scoping Review and Mapping Process.

BACKGROUND: Telehealth interventions have become increasingly important in health care provision, particularly during the COVID-19 pandemic. Video calls have emerged as a popular and effective method for delivering telehealth services; however, barriers limit the adoption among allied health professionals and nurses. OBJECTIVE: This review aimed to identify and map the perceived barriers to the use of video call-based telehealth interventions among allied health professionals and nurses. METHODS: A comprehensive literature search was conducted in the PubMed and CINAHL databases on June 22, 2022, and updated on January 3, 2023, following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) guidelines. Only original studies published in English or German since June 2017 that reported barriers to the use of video call-based telehealth interventions were eligible for inclusion. The studies had to involve interviews, focus groups, or questionnaires with physical therapists, occupational therapists, speech and language therapists, audiologists, orthoptists, dieticians, midwives, or nurses. Each publication was coded for basic characteristics, including country, health profession, and target group. Inductive coding was used to identify the patterns, themes, and categories in the data. Individual codings were analyzed and summarized narratively, with similarities and differences in barriers identified across health professions and target groups. RESULTS: A total of 56 publications were included in the review, with barriers identified and categorized into 8 main categories and 23 subcategories. The studies were conducted in various countries, predominantly the United States, Australia, the United Kingdom, Canada, Israel, and India. Questionnaires were the most commonly used evaluation method, with 10,245 health professionals involved. Interviews or focus groups were conducted with 288 health professionals. Most of the included publications focused on specific health care professions, with the highest number addressing barriers for physical therapists, speech and language therapists, and audiologists. The barriers were related to technology issues, practice issues, patient issues, environmental issues, attributions, interpersonal issues, policies and regulations, and administration issues. The most reported barriers included the lack of hands-on experience, unreliable network connection, the lack of technology access, diminished fidelity of observations and poor conditions for visual instructions, the lack of technology skills, and diminished client-practitioner interaction and communication. CONCLUSIONS: This review identified key barriers to video call-based telehealth use by allied health professionals and nurses, which can foster the development of stable infrastructure, education, training, guidelines, policies, and support systems to improve telehealth services. Further research is necessary to identify potential solutions to the identified barriers.

Student-led clinics and ePROs to accelerate diagnosis and treatment of patients with axial spondyloarthritis: results from a prospective pilot study.

We aimed to investigate (1) student-led clinics and (2) electronic patient-reported outcomes (ePROs) to accelerate diagnosis and treatment of patients with axial spondyloarthritis (axSpA). Patients with suspected axSpA completed an initial student-led clinic visit (T-1) prior to their planned actual rheumatologist visit (T0). Acceleration of patient appointment and NSAID therapy start, availability of diagnostic findings, and treatment response at T0 were evaluated. Beginning at T-1, patients completed electronic BASDAI questionnaires every 2 weeks. Concordance of paper-based and electronic BASDAI was evaluated. Patient acceptance of ePRO reporting and student-led clinics was measured using the net promoter score (NPS). 17/36 (47.2%) included patients were diagnosed with axSpA. Student-led clinics (T-1) significantly accelerated patient appointments by more than 2 months (T0, T-1, p < 0.0001) and axSpA guideline-conform NSAID treatment (p < 0.0001). At T0, diagnostic workup was completed for all patients and 7/17 (41.2%) axSpA patients presented with a clinically important improvement or were in remission. 34/36 (94.4%) patients completed at least 80% of the ePROs between T-1 and T0. Electronic and paper-administered BASDAI correlated well (r = 0.8 p < 0.0001). Student-led clinics and ePROs were well accepted by patients with NPS scores of + 62.0% (mean ± SD 9.2/10.0 ± 0.9) and + 30.5% (mean ± SD 8.0/10.0 ± 1.7), respectively. In conclusion, student-led clinics and ePRO monitoring were well accepted, accelerated diagnostic workup and treatment in patients with axSpA.

Does participation in the European Trauma Course lead to new behaviours and organisational change? A Portuguese experience.

BACKGROUND: Medical educational courses can be successful from an immediate feedback perspective but not lead to new behaviour or organisational changes in the workplace. The aim of this study was to assess the self-perceived impact of the European Trauma Course (ETC) on Reanima trainees' behaviour and organisational change. METHODS: A 40-item questionnaire based on Holton's evaluation model was used to evaluate the candidate's perceptions. The results were analysed with descriptive and inferential statistical analysis using nonparametric tests with α = 0.05. RESULTS: Out of 295 participants, 126 responded to the survey. Of these, 94% affirmed that the ETC modified their approach to trauma patients, and 71.4% described a change in their behaviour. Postcourse responders changed their behaviour in their initial approach to trauma care in the nontechnical skills of communication, prioritisation and teamwork. Being an ETC instructor strongly influenced the acquisition of new material, and this group was able to implement changes in attitudes. Individuals with no previous trauma course experience identified lack of self-efficacy as a significant obstacle to introducing new work-based learning. In contrast, responders with ATLS training noted a lack of ETC colleagues as the main impediment for moving from conceptualisation to experimentation in the workplace. CONCLUSIONS: Participation in the ETC led to behavioural changes in the workplace. However, the ability to influence others and bring about wider organisational changes was more difficult to achieve. Major factors were the status of the person, their experience and self-efficacy. National organisational impact was obtained, which went far beyond our aspirations in acknowledging change in individual daily practice. Future research studies will include the effect of implementing the ETC methodology on the outcome of trauma patients.

Inflammation-Controlled Anti-Inflammatory Hydrogels.

While autoregulative adaptation is a common feature of living tissues, only a few feedback-controlled adaptive biomaterials are available so far. This paper herein reports a new polymer hydrogel platform designed to release anti-inflammatory molecules in response to the inflammatory activation of human blood. In this system, anti-inflammatory peptide drugs, targeting either the complement cascade, a complement receptor, or cyclophilin A, are conjugated to the hydrogel by a peptide sequence that is cleaved by elastase released from activated granulocytes. As a proof of concept, the adaptive drug delivery from the gel triggered by activated granulocytes and the effect of the released drug on the respective inflammatory pathways are demonstrated. Adjusting the gel functionalization degree is shown to allow for tuning the drug release profiles to effective doses within a micromolar range. Feedback-controlled delivery of covalently conjugated drugs from a hydrogel matrix is concluded to provide valuable safety features suitable to equip medical devices with highly active anti-inflammatory agents without suppressing the general immunosurveillance.