Tag: Medical device

Duchenne muscular dystrophy (DMD) is a progressive, multisystem disease requiring long-term monitoring of respiratory, cardiac, and functional status. Advances in care have extended survival, increasing the need for continuous, coordinated management. In parallel, digital health technologies have enabled remote monitoring and data collection outside traditional clinical settings. This Viewpoint examines the role of device-based remote monitoring in DMD and argues that it should be understood as an emerging multisystem digital surveillance framework rather than a collection of isolated technologies. This Viewpoint is based on a synthesis of published literature on device-based remote monitoring and digital health technologies in DMD and experiences at our center. The aim was to outline the current clinical and technological landscape and support an interpretive perspective. Device-based monitoring in DMD encompasses a range of technologies, including home spirometry, ventilator-integrated telemonitoring, wearable activity sensors, cardiac rhythm monitoring, and interactive rehabilitation systems. These approaches enable longitudinal assessment of physiological and functional parameters in real-world settings. However, the current evidence base is heterogeneous and largely limited to feasibility studies, small cohorts, and extrapolated data. While data acquisition is technically feasible and increasingly available, integration into clinical workflows remains constrained by the lack of validated digital biomarkers, standardized monitoring frameworks, and interoperable data systems. Remote monitoring in DMD is evolving toward a connected, multisystem model of disease surveillance. Its clinical impact will depend on the validation of digital end points, development of decision support frameworks, and integration into multidisciplinary care pathways. Bridging the gap between data generation and clinical decision-making remains a key priority for future research and implementation. These findings support a shift from isolated technologies toward a coordinated, clinically integrated model of multisystem care in DMD.
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Background: Residents in pediatric endocrinology subspecialty units encounter diverse educational scenarios spanning theory, skills, and attitudes; yet, brief residencies frequently limit their exposure to certain clinical cases. Research in medical education demonstrates that e-learning can address such challenges efficiently. We implemented a blended learning model grounded in the Kolb learning cycle that uses structured, case-based e-learning. Objective: We aimed to evaluate the utility and usability of blended learning using a novel e-learning tool. Methods: We used a problem-solving approach and used the physical separation of case-based e-learning (interactive, patient scenario–based online modules) and theoretical content delivery as the educational model for residents in a pediatric endocrinology and diabetology unit. Residents worked asynchronously (on their own time, not simultaneously with others) on clinical scenarios and completed formative assessments (practice tests designed to provide feedback for learning rather than grades) with immediate feedback using a flipped classroom teaching method, in which students review material before group instruction. In addition, all cases could be discussed with specialists during face-to-face learning opportunities through a blended learning approach that combines online and in-person elements. We evaluated Kirkpatrick level 1 (reaction, how participants respond to training) and level 2 (learning, measured as an increase in knowledge or capability) outcomes using the postgraduate Medical E-learning Evaluation Survey (MEES) and the User Experience Questionnaire (UEQ), which assesses users’ perceptions of e-learning platforms. Results: Questionnaires from 12 pediatric residents and 1 questionnaire from a fourth-year medical student were evaluated. The main strengths identified were the tool’s support for applying content to daily clinical work (12/13, 92% users), provision of timely summaries (n=9, 69% users), access to reliable information sources (n=9, 69% users), and immediate feedback on responses (n=8, 62% users). Key weaknesses included device compatibility for e-learning (n=5, 38% users), limited content personalization (n=4, 31% users), and a lack of a navigation aid (n=4, 31% users). No significant functional issues were reported. The UEQ evaluation showed that dependability received the lowest rating, while attractiveness and stimulation received the highest rating. Conclusions: Our e-learning proposal provides a practical way to apply theoretical knowledge through interactive clinical cases. Evaluations show that users are highly motivated to engage with e-learning, highlighting our tool’s adaptability and effectiveness for postgraduate medical education in pediatric endocrinology. Identifying strengths and weaknesses will guide future improvements. Evaluating various aspects of e-learning remains crucial, as these aspects can affect learning outcomes. However, more longitudinal evaluations of e-learning are necessary to achieve a comprehensive understanding of its effectiveness.
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