Background: To assess the quality of life (QoL) and treatment satisfaction with intermittently-scanned continuous glucose monitoring (isCGM) in women with gestational diabetes mellitus (GDM). Methods: This prospective observational study included 189 women with GDM who completed the Korean version of the Audit of Diabetes-Dependent Quality of Life Questionnaire (K-ADDQoL). Among them, 25 women who utilized isCGM between gestational weeks 30 and 34 completed the Korean version of the Diabetes Treatment Satisfaction Questionnaire change version (K-DTSQc) to evaluate their satisfaction with isCGM during pregnancy. Results: GDM had a negative impact on the perceived QoL in 89.4% of the women. All 19 domains of the K-ADDQoL were adversely influenced by GDM, with the most significant impact on the freedom to eat (weighted impact score, −6.98 ± 2.49, P < 0.001) and the least impact on the sex life (−0.25 ± 0.80, P = 0.008). Younger women and those treated with insulin perceived themselves as being more affected in their QoL due to GDM. Women perceived to have less effect on their QoL attributed to GDM exhibited higher ΔHbA1c one year after delivery (ΔHbA1c, 0.3 ± 0.4% vs. 0.0 ± 0.4% in less affected vs. more affected women). The utilization of isCGM improved treatment satisfaction (overall satisfaction score, 10.36 ± 9.21, P < 0.001), independent of glycemic control during pregnancy. Conclusion Although GDM negatively affects the perceived QoL during pregnancy, attentiveness to GDM management may have a positive impact on long-term glycemic control.Moreover, employing isCGM can enhance treatment satisfaction in women with GDM.

Background: To assess the quality of life (QoL) and treatment satisfaction with intermittently-scanned continuous glucose monitoring (isCGM) in women with gestational diabetes mellitus (GDM). Methods: This prospective observational study included 189 women with GDM who completed the Korean version of the Audit of Diabetes-Dependent Quality of Life Questionnaire (K-ADDQoL). Among them, 25 women who utilized isCGM between gestational weeks 30 and 34 completed the Korean version of the Diabetes Treatment Satisfaction Questionnaire change version (K-DTSQc) to evaluate their satisfaction with isCGM during pregnancy. Results: GDM had a negative impact on the perceived QoL in 89.4% of the women. All 19 domains of the K-ADDQoL were adversely influenced by GDM, with the most significant impact on the freedom to eat (weighted impact score, −6.98 ± 2.49, P < 0.001) and the least impact on the sex life (−0.25 ± 0.80, P = 0.008). Younger women and those treated with insulin perceived themselves as being more affected in their QoL due to GDM. Women perceived to have less effect on their QoL attributed to GDM exhibited higher ΔHbA1c one year after delivery (ΔHbA1c, 0.3 ± 0.4% vs. 0.0 ± 0.4% in less affected vs. more affected women). The utilization of isCGM improved treatment satisfaction (overall satisfaction score, 10.36 ± 9.21, P < 0.001), independent of glycemic control during pregnancy. Conclusion Although GDM negatively affects the perceived QoL during pregnancy, attentiveness to GDM management may have a positive impact on long-term glycemic control.Moreover, employing isCGM can enhance treatment satisfaction in women with GDM.

Background: To assess the quality of life (QoL) and treatment satisfaction with intermittently-scanned continuous glucose monitoring (isCGM) in women with gestational diabetes mellitus (GDM). Methods: This prospective observational study included 189 women with GDM who completed the Korean version of the Audit of Diabetes-Dependent Quality of Life Questionnaire (K-ADDQoL). Among them, 25 women who utilized isCGM between gestational weeks 30 and 34 completed the Korean version of the Diabetes Treatment Satisfaction Questionnaire change version (K-DTSQc) to evaluate their satisfaction with isCGM during pregnancy. Results: GDM had a negative impact on the perceived QoL in 89.4% of the women. All 19 domains of the K-ADDQoL were adversely influenced by GDM, with the most significant impact on the freedom to eat (weighted impact score, −6.98 ± 2.49, P < 0.001) and the least impact on the sex life (−0.25 ± 0.80, P = 0.008). Younger women and those treated with insulin perceived themselves as being more affected in their QoL due to GDM. Women perceived to have less effect on their QoL attributed to GDM exhibited higher ΔHbA1c one year after delivery (ΔHbA1c, 0.3 ± 0.4% vs. 0.0 ± 0.4% in less affected vs. more affected women). The utilization of isCGM improved treatment satisfaction (overall satisfaction score, 10.36 ± 9.21, P < 0.001), independent of glycemic control during pregnancy. Conclusion Although GDM negatively affects the perceived QoL during pregnancy, attentiveness to GDM management may have a positive impact on long-term glycemic control.Moreover, employing isCGM can enhance treatment satisfaction in women with GDM.

Background: To assess the quality of life (QoL) and treatment satisfaction with intermittently-scanned continuous glucose monitoring (isCGM) in women with gestational diabetes mellitus (GDM). Methods: This prospective observational study included 189 women with GDM who completed the Korean version of the Audit of Diabetes-Dependent Quality of Life Questionnaire (K-ADDQoL). Among them, 25 women who utilized isCGM between gestational weeks 30 and 34 completed the Korean version of the Diabetes Treatment Satisfaction Questionnaire change version (K-DTSQc) to evaluate their satisfaction with isCGM during pregnancy. Results: GDM had a negative impact on the perceived QoL in 89.4% of the women. All 19 domains of the K-ADDQoL were adversely influenced by GDM, with the most significant impact on the freedom to eat (weighted impact score, −6.98 ± 2.49, P < 0.001) and the least impact on the sex life (−0.25 ± 0.80, P = 0.008). Younger women and those treated with insulin perceived themselves as being more affected in their QoL due to GDM. Women perceived to have less effect on their QoL attributed to GDM exhibited higher ΔHbA1c one year after delivery (ΔHbA1c, 0.3 ± 0.4% vs. 0.0 ± 0.4% in less affected vs. more affected women). The utilization of isCGM improved treatment satisfaction (overall satisfaction score, 10.36 ± 9.21, P < 0.001), independent of glycemic control during pregnancy. Conclusion Although GDM negatively affects the perceived QoL during pregnancy, attentiveness to GDM management may have a positive impact on long-term glycemic control.Moreover, employing isCGM can enhance treatment satisfaction in women with GDM.

Background: Systolic murmur suggesting the association of aortic valve (AV) stenosis or obstructive pathology in the left ventricular outflow tract (LVOT) usually requires preoperative echocardiographic evaluation for elective surgery.Case: In a 63-year-old female patient undergoing elective thoracic surgery, the systolic murmur was auscultated on the right sternal border of the second intercostal space in the preoperative patient holding area. Point-of-care (POC) transthoracic echocardiography (TTE) demonstrated a systolic jet flow in the LVOT area. The peak systolic velocity of the continuous wave Doppler tracing, aligned to the LVOT and the AV, was approximately 1.5 m/s. The peak/mean pressure gradient was 11/6 mmHg for the AV and 9/5 mmHg for the LVOT. Anesthesia was induced under continuous TTE imaging. Intraoperative transesophageal echocardiography also confirmed the absence of any cardiac pathology. Conclusions POC echocardiography offered a thorough preoperative evaluation of an unexpectedly identified systolic murmur, avoiding a potential delay in the operation schedule for conventional preoperative echocardiographic evaluation.

Background: Ultrafiltration (UF) would enhance coagulation profiles by concentrating coagulation elements during cardiopulmonary bypass (CPB) for cardiac surgery. Methods: We retrospectively reviewed electronic medical records of 75 patients who had undergone cardiac surgery with rotational thromboelastometry-based coagulation management in a university hospital and analyzed the UF-induced changes in the maximum clot firmness (MCF) of extrinsically activated test with tissue factor (EXTEM) during CPB in 30 patients. Results: The median volume of filtered-free water was 1,350 ml, and median hematocrit was significantly increased from 22.5% to 25.5%. As the primary measure, UF significantly increased the median MCF-EXTEM from 48.0 mm to 50.5 mm (P = 0.015, effect size r = 0.44). The area under the receiver operating characteristic curve pre-UF MCF-EXTEM for discrimination of any increase of MCF-EXTEM after applying UF was 0.89 (95% CI [0.77, 1.00], P < 0.001), and its cut-off value was 50.5 mm (specificity of 81.8% and sensitivity of 84.2% in Youden’s J statistic). In the secondary analyses using the cut-off value, UF significantly increased the median MCF-EXTEM from 40.5 mm to 42.5 mm in 18 patients with pre-UF MCF-EXTEM ≤ 50.5 mm. However, it did not increase MCF-EXTEM in 12 patients with pre-UF MCF-EXTEM > 50.5 mm. There was a significant interaction between pre-UF MCF-EXTEM values and applying UF (P < 0.001 for the subgroup, P = 0.046 for UF, P = 0.003 for interaction). Conclusions Applying UF improved clot firmness, and the improvement was more pronounced when pre-UF MCF-EXTEM had been reduced during CPB.

Objectives: Artificial intelligence (AI) technologies are developing very rapidly in the medical field, but have yet to be actively used in actual clinical settings. Ensuring reliability is essential to disseminating technologies, necessitating a wide range of research and subsequent social consensus on requirements for trustworthy AI. Methods: This review divided the requirements for trustworthy medical AI into explainability, fairness, privacy protection, and robustness, investigated research trends in the literature on AI in healthcare, and explored the criteria for trustworthy AI in the medical field. Results: Explainability provides a basis for determining whether healthcare providers would refer to the output of an AI model, which requires the further development of explainable AI technology, evaluation methods, and user interfaces. For AI fairness, the primary task is to identify evaluation metrics optimized for the medical field. As for privacy and robustness, further development of technologies is needed, especially in defending training data or AI algorithms against adversarial attacks. Conclusions In the future, detailed standards need to be established according to the issues that medical AI would solve or the clinical field where medical AI would be used. Furthermore, these criteria should be reflected in AI-related regulations, such as AI development guidelines and approval processes for medical devices.

Aged people are challenged by serious complications from chronic diseases, such as mood disorder, diabetes, heart disease, and infectious diseases, which are also the most common causes of death in older people. Therefore, elderly care facilities are more important than ever. The most common causes of death in elderly care facilities were reported to be diabetes, cardiovascular disease, and pneumonia. Recently, the coronavirus disease 2019 (COVID-19) pandemic have a great impact on blind spots of safety where aged people were isolated from society. Elderly care facilities were one of the blind spots in the midst of the pandemic, where major casualties were reported from COVID-19 complications because most people had one or two mortality risk factors, such as diabetes or cardiovascular disease. Therefore, medical governance of public health center and hospital, and elderly care facility is becoming important issue of priority. Thus, remote health monitoring service by the Internet of Medical Things (IoMT) sensors is more important than ever. Recently, technological breakthroughs have enabled healthcare professionals to have easy access to patients in medical blind spots through the use of IoT sensors. These sensors can detect medically urgent situations in a timely fashion and make medical decisions for aged people in elderly care facilities. Real-time electrocardiograms and blood sugar monitoring sensors are approved by the medical insurance service. Real-time monitoring services in medical blind spots, such as elderly care facilities, has been suggested. Heart rhythm monitoring could play a role in detecting early cardiovascular disease events and monitoring blood glucose levels in the management of chronic diseases, such as diabetes, in aged people in elderly care facilities. This review presents the potential usefulness of remote monitoring with IoMT sensors in medical blind spots and clinical suggestions for applications.

Purpose: This study is an integrated literature review to analyze health problems and social determinants of multicultural adolescents in South Korea. Methods: An integrative review was conducted according to Whittemore & Knafl’s guideline. An electronic search that included publications from 2018 to 2020 in the PubMed, EMBASE, Cochrane Library, CINAHL, RISS, and KISS databases was conducted. Of a total of 67 records that were identified, 13 finally met full inclusion criteria. Text network analysis was also conducted to identify keywords network trends using NetMiner program. Results: The health problems of multicultural adolescents were classified into mental health (depression, anxiety, suicide and acculturative stress) and health risk behaviors (smoking, risky drinking, smartphone dependence and sexual behavior). As social determinants affecting the health of multicultural adolescents, the biological factors such as gender, age, and visible minority, and the psychological factors such as acculturative stress, self-esteem, family support, and ego-resiliency were identified. The sociocultural factors were identified as family economic status, residential area, parental education level, and parents' country of birth. As a result of text network analysis, a total of 41 words were identified. Conclusion Based on these results, mental health and health risk behaviors should be considered as interventions for health promotion of multicultural adolescents. Our findings suggest that further research should be conducted to broaden the scope of health determinants to account for the effects of the physical environment and health care system.