Smartwatches in healthcare medicine: assistance and monitoring; a scoping review.

Smartwatches have become increasingly popular in recent times because of their capacity to track different health indicators, including heart rate, patterns of sleep, and physical movements. This scoping review aims to explore the utilisation of smartwatches within the healthcare sector. According to Arksey and O'Malley's methodology, an organised search was performed in PubMed/Medline, Scopus, Embase, Web of Science, ERIC and Google Scholar. In our search strategy, 761 articles were returned. The exclusion/inclusion criteria were applied. Finally, 35 articles were selected for extracting data. These included six studies on stress monitoring, six on movement disorders, three on sleep tracking, three on blood pressure, two on heart disease, six on covid pandemic, three on safety and six on validation. The use of smartwatches has been found to be effective in diagnosing the symptoms of various diseases. In particular, smartwatches have shown promise in detecting heart diseases, movement disorders, and even early signs of COVID-19. Nevertheless, it should be emphasised that there is an ongoing discussion concerning the reliability of smartwatch diagnoses within healthcare systems. Despite the potential advantages offered by utilising smartwatches for disease detection, it is imperative to approach their data interpretation with prudence. The discrepancies in detection between smartwatches and their algorithms have important implications for healthcare use. The accuracy and reliability of the algorithms used are crucial, as well as high accuracy in detecting changes in health status by the smartwatches themselves. This calls for the development of medical watches and the creation of AI-hospital assistants. These assistants will be designed to help with patient monitoring, appointment scheduling, and medication management tasks. They can educate patients and answer common questions, freeing healthcare providers to focus on more complex tasks.

Crossover design in triage education: the effectiveness of simulated interactive vs. routine training on student nurses' performance in a disaster situation.

INTRODUCTION: This study investigates the effectiveness of incorporating simulated interactive guidelines in nursing students' performance during disaster situations, compared to routine training. METHOD: This study was a crossover design with pre-and post-tests for two groups. Each group consisted of 60 students selected using the census method. SIG and routine (Face-to-Face) training sessions were conducted as a crossover design. Triage knowledge questionnaires were used in the pretest to assess triage knowledge. An OSCE test was administered in the posttest to assess student performance, followed by a triage skills questionnaire. Both questionnaires were highly reliable, as indicated by Cronbach's alpha coefficients (0.9 and 0.95, respectively). Statistical analysis was performed using SPSS version 26 software at a significance level 0.05. RESULT: The chi-square test showed that the two groups were homogeneous regarding age. Regarding knowledge level, both groups were homogeneous before the intervention (P = 0.99). Nevertheless, the results of the OSCE test showed that the students in Group A had a higher level of skill than the students in Group B (93% versus 70%). Also, 18% of the students in group B had low skills. DISCUSSION: The study found that student outcomes improved in both groups receiving SIG, suggesting that interaction and simulation improve learning. However, gamification is an ideal precursor to learning and not a substitute for education. Therefore, gamification should not be used as a stand-alone teaching method. CONCLUSIONS: The crossover study found that simulators and games should not be considered stand-alone teaching methods but can contribute to learning sustainability when used alongside instruction.

Augmentation of left atrial contractile function: a herald of iron overload in patients with beta thalassemia major.

Early detection of myocardial iron overload is crucial for optimal management of patients with beta thalassemia major, which could lead to intensification of iron chelating therapy. In this study, we evaluate the conventional echocardiography and tissue Doppler imaging measurements in patients with beta thalassemia major and further introduce the assessment of atrial ejection force as a feasible price-saving approach for early detection of myocardial iron overload. During a 1-year period, 42 cases of beta thalassemia major aged <21 years and with preserved systolic function were evaluated with magnetic resonance T2* imaging (MRI T2*), conventional echocardiography, and tissue Doppler imaging techniques. Patients were classified into two groups according to their myocardial MRI T2* values, with and without critical iron loading. All patients with echocardiographic evidence of moderate and severe stages of diastolic dysfunction showed critical iron loading in their MRI T2*. After excluding those patients with severe and moderate ventricular diastolic filling abnormality, the atrial ejection force index (P = 0.002) and a number of volume indexes of the left atrium showed a significant difference between the two groups. None of the tissue Doppler imaging measurements showed a statistically significant difference between the two groups. The atrial ejection force index of 7.41, with a sensitivity of 93% and a specificity of 74%, was suggested to detect critical cardiac iron loading. These results imply that combining the atrial ejection force index with the transmitral-derived echocardiographic assessment is a feasible way to detect early stages of myocardial iron overload in patients with beta thalassemia major.