JMIR Cardio最新文献

{"title":"Effectiveness of a Telehealth Intervention on Functional Status, Anxiety, Depression, and Rehospitalization Among Older Adults Undergoing Coronary Artery Bypass Grafting: Randomized Controlled Trial.","authors":"Jirawan Mala, Usavadee Asdornwised, Kessiri Wongkongkam, Natkamol Chansatitporn, Punnarerk Thongcharoen","doi":"10.2196/81777","DOIUrl":"10.2196/81777","url":null,"abstract":"<p><strong>Background: </strong>Telehealth has shown promise in enhancing care transitions and physical health outcomes in patients with cardiovascular disease. However, limited studies have explored its effect on functional status, psychological health, and rehospitalization, specifically in older patients undergoing coronary artery bypass grafting (CABG).</p><p><strong>Objective: </strong>This study aimed to evaluate the effectiveness of a telehealth intervention in improving functional status, reducing anxiety and depression, and decreasing rehospitalization rates compared with usual care among older patients undergoing CABG.</p><p><strong>Methods: </strong>The study was a 2-arm parallel randomized controlled trial. This was conducted in 2 phases. Phase 1 was conducted in the cardiac surgical units at a university hospital in Bangkok, Thailand. Phase 2 involved following up with the participant at home 30 and 90 days after discharge. A total of 84 older adults undergoing CABG were randomly assigned to either the control group (n=42), which received usual care (discharge planning), or the intervention group (n=42), which received a telehealth intervention based on the transitional care model in addition to usual care. The telehealth intervention included home monitoring via the \"Zip Heart\" app and scheduled video consultations. The primary outcome was functional status, measured using the Thai version of the Enforced Social Dependency Scale. Secondary outcomes included anxiety and depression, assessed using the Thai Hospital Anxiety and Depression Scale, and rates of rehospitalization. Data were collected at baseline, 30, and 90 days after discharge. Analyses were conducted using an intention-to-treat approach, with missing outcome data handled using multiple imputation. Two-way repeated-measures ANOVA was used to evaluate group, time, and group-by-time interaction effects.</p><p><strong>Results: </strong>A total of 84 participants were randomized and included in the intention-to-treat analysis (intervention group, n=42; control group, n=42). At baseline, there were no statistically significant differences between the two groups. Significant group-by-time interactions were observed for functional status scores (F2,164=32.09, ηp²=.28; P<.001), anxiety (F2, 164=20.22, ηp²=.2; P<.001), and depression (F2,164=16.81, ηp²=.17; P<.001). The intervention group demonstrated significantly greater improvements in functional status and greater reductions in anxiety and depression at both 30 and 90 days after discharge compared to the control group (all P<.001). Additionally, rehospitalization rates were significantly lower in the intervention group at 30 days (Z=2.77; P=.006) and between 31 and 90 days post discharge (Z=2.31; P=.02).</p><p><strong>Conclusions: </strong>The Telehealth intervention is effective in improving functional and psychological outcomes and reducing rehospitalization rates among older patients undergoing CABG. Integrating telehealth ","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e81777"},"PeriodicalIF":2.2,"publicationDate":"2026-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13152204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147838018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Large Language Models in Cardiology: Systematic Review.","authors":"Moran Gendler, Girish N Nadkarni, Karin Sudri, Michal Cohen-Shelly, Benjamin S Glicksberg, Orly Efros, Shelly Soffer, Eyal Klang","doi":"10.2196/76734","DOIUrl":"10.2196/76734","url":null,"abstract":"<p><strong>Background: </strong>Large language models (LLMs) are increasingly used in health care, but their role in cardiology has not yet been systematically evaluated.</p><p><strong>Objective: </strong>This review aimed to assess the applications, performance, and limitations of LLMs across diverse cardiology tasks, including chronic and progressive conditions, acute events, education, and diagnostic testing.</p><p><strong>Methods: </strong>A systematic search was conducted in PubMed and Scopus for studies published up to April 14, 2024, using keywords related to LLMs and cardiology. Studies evaluating LLM outputs in cardiology-related tasks were included. Data were extracted across 5 predefined domains and the risk of bias was assessed using an adapted QUADAS-2 tool (developed by Whiting et al at the University of Bristol). The review protocol was registered in PROSPERO (CRD42024556397).</p><p><strong>Results: </strong>A total of 33 studies contributed quantitative outcome data to a descriptive synthesis. Across chronic conditions, ChatGPT-3.5 (OpenAI) answered 91% (43/47) heart failure questions accurately, although readability often required college-level comprehension. In acute scenarios, Bing Chat omitted key myocardial infarction first aid steps in 25% (5/20) to 45% (9/20) of cases, while cardiac arrest information was rated highly (mean 4.3/5, SD 0.7) but written above recommended reading levels. In physician education tasks, ChatGPT-4 (OpenAI) demonstrated higher accuracy than ChatGPT-3.5, improving from 38% (33/88) to 66% (58/88). In patient education studies, ChatGPT-4 provided scientifically adequate explanations (5.0-6.0/7) comparable to hospital materials but at higher reading levels (11th vs 7th grade). In diagnostic testing, ChatGPT-4 interpreted 91% (36/40) electrocardiogram vignettes correctly, significantly better than emergency physicians (31/40, 77%; P< .001), but showed lower performance in echocardiography.</p><p><strong>Conclusions: </strong>LLMs show meaningful potential in cardiology, especially for education and electrocardiogram interpretation, but performance varies across clinical tasks. Limitations in emergency guidance and readability, as well as small in silico study designs, highlight the need for multimodal models and prospective validation.</p>","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e76734"},"PeriodicalIF":2.2,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13085985/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147698695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Heart Rate Estimation Using the Galaxy Watch During Maximal Cardiopulmonary Exercise Testing: Cross-Sectional Validation Study.","authors":"Allan Inoue, João Paulo Ferreira Soares, Felipe Antunes-Santos, Alexandre Ferreira, Alberto Gonçalves, João Arthur Alcântara, Marcelo Rodrigues Dos Santos","doi":"10.2196/81917","DOIUrl":"10.2196/81917","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Photoplethysmography-based smartwatches are increasingly used for continuous heart rate (HR) monitoring. Their accuracy has been demonstrated at rest or during low-intensity activity, but data are scarce for maximal-intensity exercise, when motion artifacts and rapid hemodynamic changes can degrade the photoplethysmography signal. Validating these devices under such demanding conditions is essential before they are applied to clinical exercise testing, athletic training, or remote health monitoring.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to evaluate the validity of the Samsung Galaxy Watch 6 (GW6) in estimating HR throughout a graded, maximal ramp cardiopulmonary exercise test performed on a treadmill. A secondary aim was to explore whether measurement error varies across 5 predefined intensity zones (50%-60%, 60%-70%, 70%-80%, 80%-90%, and 90%-100% of the maximum HR determined individually for each participant).&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Overall, 55 healthy adults (30 men, 25 women; mean age 30.3, SD 8.2 years) completed a symptom-limited incremental treadmill protocol to volitional exhaustion. Simultaneous HR recordings were obtained from the GW6 (left arm) and a Polar H10 chest strap monitor, which served as the reference standards. For each intensity zone, the following agreement indices were computed: intraclass correlation coefficient (ICC), median absolute error, median absolute percentage error, and root mean squared error. Bland-Altman analysis was performed to quantify the mean bias and 95% limits of agreement between the GW6 and the Polar H10. Statistical significance was set at P&lt;.05.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Agreement between the GW6 and Polar H10 varied across exercise intensities. ICC indicated moderate to good agreement at low to moderate intensities (ICC=0.71 at 50%-60%; ICC=0.89 at 60%-70%; ICC=0.54 at 70%-80%; and ICC=0.64 at 80%-90% HRmax), and at 90%-100% of HRmax the agreement was good-to-excellent (ICC=0.90). Absolute error metrics showed stable or reduced errors with increasing intensity, with median absolute error consistently around 1-3 bpm and median absolute percentage error declining from 2.90% at 50%-60% HRmax to 0.60%-0.75% at ≥70% HRmax. Root mean squared error ranged from 4.62 to 4.88 bpm across intensity zones. Bland-Altman analysis showed that the GW6 consistently underestimated HR compared with the Polar H10, with an overall mean bias of -2.67 bpm and wide limits of agreement (-16.90 to 11.57 bpm). This negative bias was present across all HR zones. The agreement was adequate for group-level comparisons but displayed substantial individual variability.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;The GW6 provides a good degree of validity for HR monitoring during a maximal treadmill cardiopulmonary exercise test in healthy young adults. Although measurement error increases modestly at near-maximal workloads, absolute errors remain well within clinically acceptable","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e81917"},"PeriodicalIF":2.2,"publicationDate":"2026-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13086260/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147698717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of a Cloud-Based Care Coordination Platform on False Activations of the Cardiac Catheterization Laboratory and Unnecessary Team Mobilization: A Retrospective Cohort Study.","authors":"William Gibson, Dawoud Al Kindi, François Brouillette, Ahmed Aldajani, Omar Chaabo, Yasmine Lachance, Elie Akl, Kshitij Badal Dandona, Giuseppe Martucci, Jean-Philippe Pelletier, Nicolo Piazza, Jeremy Levett, Tomer Moran, Marco Spaziano","doi":"10.2196/76932","DOIUrl":"https://doi.org/10.2196/76932","url":null,"abstract":"<p><strong>Background: </strong>Rapid activation of the cardiac catheterization laboratory (CCL) for ST-segment elevation myocardial infarction (STEMI) is essential to minimize time to reperfusion. However, system-wide efforts to reduce treatment delays have been accompanied by increased false activations (FA), defined as activations that do not result in emergent coronary intervention. False activations contribute to unnecessary team mobilization (UTM), staff fatigue, workflow disruption, and inefficient resource utilization.</p><p><strong>Objective: </strong>To evaluate whether implementation of a cloud-based care coordination platform (Stenoa) was associated with reductions in FA and UTM at a high-volume tertiary cardiac center.</p><p><strong>Methods: </strong>In September 2021, the McGill University Health Centre (MUHC) implemented Stenoa, a mobile cloud-based STEMI coordination platform enabling systematic case validation using electrocardiographic and clinical data. A retrospective cohort study was conducted including all CCL activations between September 2020 and December 2022. Activations were grouped as pre-implementation (Group 0: Sept 2020-Sept 2021) and post-implementation (Group 1: Sept 2021-Dec 2022). False activation was defined as CCL activation followed by case cancellation before any procedure was performed. The primary outcome was the rate of UTM.</p><p><strong>Results: </strong>A total of 632 activations were analyzed (overall: Group 0: n =288, Group 1: n =344; off- hours activations: Group 0: n =265, Group 1: n =316.) UTM decreased from 8.7% (23/265) to 4.4% (14/316) following platform implementation (P = .04). FA frequency decreased from 10.2% (27/265) to 7.0% (22/316), although this did not reach statistical significance (P = .16). Among false activations, the proportion resulting in UTM declined from 85% to 64% (P =.08).</p><p><strong>Conclusions: </strong>Implementation of a cloud-based STEMI coordination platform was associated with a significant reduction in unnecessary catheterization laboratory team mobilization. Structured digital communication may improve workflow efficiency and resource utilization in STEMI systems of care. Further multicenter evaluation is warranted.</p><p><strong>Clinicaltrial: </strong></p>","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":" ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2026-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147638800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multilingual Video Education for Hospitalized Patients With Myocardial Infarction (EDUCATE-MI): Single-Arm Implementation Study.","authors":"Aileen Zeng, Edel O'Hagan, Sul Ki Kim, Simone Marschner, Mitchell Sarkies, Marina Wassif, Meng Ji, Julie Ayre, Daniel McIntyre, Clara K Chow, Aravinda Thiagalingam, Liliana Laranjo","doi":"10.2196/82817","DOIUrl":"10.2196/82817","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Clinical guidelines recommend the early initiation of secondary prevention strategies prior to hospital discharge for patients with myocardial infarction (MI) to reduce morbidity and mortality, but implementation is resource-intensive. Multilingual videos can deliver information in diverse preferred languages and literacy levels, but their impact on MI knowledge among hospitalized patients remains unclear.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aims to assess whether the delivery of a multilingual educational video to hospitalized patients with MI can improve patient MI knowledge before hospital discharge.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a single-arm pre-post study with embedded formative implementation evaluation from December 2023 to October 2024 in a tertiary hospital. The intervention was a video on post-MI management, available in English, Arabic, Hindi, and Mandarin (with Simplified Chinese subtitles). The intervention was delivered via a tablet provided by the research assistant. The primary outcome was the change in patient knowledge of MI, measured by comparing the mean number of correct responses before and after the intervention using a 2-tailed paired t test. We assessed early-stage implementation using 2 prespecified elements from the Proctor implementation outcomes framework: acceptability and fidelity of the video delivery. We performed content analysis on the notes taken from participants' feedback to improve the video.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;We recruited 129 participants (mean age of 59.4, SD 12.6 years) for this study. English was the preferred language (n=96, 74.4%) and Hindi was the predominant non-English language (n=17, 13.2%). Of the 129 participants enrolled, 128 completed follow-up immediately postintervention (1 lost interest). The average number of correct responses out of 10 was 5.4 (SD 2.7) at baseline and 7.2 (SD 2.5) postintervention (mean difference=1.9, 95% CI 1.6-2.2; P&lt;.001; Cohen drm for paired change=0.72). The educational video was well-accepted, with 83.6% (107/128) of participants finding it easy to understand, 74.2% (95/128) engaging, and 87.5% (112/128) useful. Participants' feedback for improvement highlighted content complexity and a preference for conversational language and dialects. Fidelity of the intervention was subjectively assessed as reasonably achieved, given that the core components of the intervention (ie, animations and educational content conveyed through the audio and subtitles) were delivered as intended. Fidelity of the implementation strategy was similarly assessed as reasonably achieved because there were no technology issues preventing delivery of the intervention as intended, through video display from a weblink embedded in REDCap, using a tablet with internet connection.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;A short educational video may improve patient knowledge of MI before discharge. Further scaled research is needed to e","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e82817"},"PeriodicalIF":2.2,"publicationDate":"2026-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13020905/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147521007","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Short-Term Arrhythmia Prediction Using AI Based on Daily Data From Implantable Devices: Multicenter Prospective Observational Study.","authors":"Ignacio Fernández Lozano, Joaquín Fernández de la Concha, Javier Ramos Maqueda, Nicasio Pérez Castellano, Rafael Salguero Bodes, F Javier García-Fernández, Juan Benezet Mazuecos, Javier Jiménez Candil, Tomás Datino, Sem Briongos Figuero, Javier Paniagua Olmedillas, Miguel Nicolás Font de la Fuente, Juan López-Dóriga Costales, Sarai Paz Fernández, Vicente Copoví Lucas","doi":"10.2196/85841","DOIUrl":"10.2196/85841","url":null,"abstract":"<p><strong>Background: </strong>Predictive medicine relies on algorithms to determine clinical treatments tailored to each patient's individual characteristics. Predictive models based on artificial intelligence have shown promise in identifying atrial fibrillation episodes; however, they rarely focus on short-term dynamic prediction.</p><p><strong>Objective: </strong>This study aimed to evaluate the use of an artificial intelligence model and remote monitoring data extracted from pacemaker devices to predict the onset or worsening of arrhythmias in the short term.</p><p><strong>Methods: </strong>This was a multicenter prospective observational study in which data from 314 patients were analyzed. A total of 65,243 data sequences were collected, of which 55,532 (85.1%) were used to train the algorithm. This model used 31-day records to predict whether the number of arrhythmic episodes would increase, decrease, or remain the same in the following 14 days.</p><p><strong>Results: </strong>The sensitivity and specificity of the generated predictions were calculated from 9711 prediction-observation pairs. The global sensitivity was 66.4% (95% CI 64.3%-68.3%), and specificity was 77.4% (95% CI 76.4%-78.4%). For patients with baseline arrhythmia, sensitivity was 76.8% (95% CI 74.6%-78.8%), and specificity was 39.6% (95% CI 35.8%-43.5%). The prediction for patients with no baseline arrhythmia showed a sensitivity of 39% (95% CI 35.1%-43%) and a specificity of 81% (95% CI 80.0%-81.9%). The analysis for the patient subgroup without history of atrial fibrillation (232/314, 73.9%) yielded a 69% sensitivity (95% CI 66.5%-71.5%) and an 80% specificity (95% CI 79.3%-81.3%).</p><p><strong>Conclusions: </strong>This model was capable of predicting short-term increases or decreases in arrhythmic episodes with reasonable sensitivity and specificity using data collected through remote monitoring of implantable devices. The model's performance is expected to improve progressively as more data samples become available, including demographic data and clinical records.</p>","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e85841"},"PeriodicalIF":2.2,"publicationDate":"2026-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12998600/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147480711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The HeartHealth Program: A Mixed Methods Study of a Community-Based Text Messaging Support Program for Patients With Cardiovascular Disease From 2020 to 2024.","authors":"Brodie Sheahen, Liliana Laranjo, Ritu Trivedi, Tim Shaw, Gopal Sivagangabalan, James Chong, Aravinda Thiagalingam, Sarah Zaman, Pierre Qian, Anupama Balasuriya Indrawansa, Clara Kayei Chow","doi":"10.2196/68896","DOIUrl":"10.2196/68896","url":null,"abstract":"<p><strong>Background: </strong>The HeartHealth program is a 6-month SMS text messaging-based support program offered to patients with a recent cardiovascular hospitalization or recent cardiovascular clinic visit in Western Sydney, Australia. Its customized content focuses on cardiovascular risk factors, lifestyle, treatments, and general heart health information.</p><p><strong>Objective: </strong>This study aimed to evaluate the implementation of the HeartHealth program.</p><p><strong>Methods: </strong>A mixed methods study was conducted assessing program reach, effectiveness, implementation, and maintenance using program data, participant feedback surveys, and staff focus group discussions. Consecutive adult patients who had attended cardiology clinics or had been discharged from cardiology hospitalization at Westmead Hospital, between April 2020 and April 2024, were included in the analysis. Content analysis was used to interpret the qualitative data.</p><p><strong>Results: </strong>A total of 23,095 patients were invited, 8804 (38.1%) enrolled into the program, and 7964 out of 8804 (90.5%) completed the 6-month duration. Participants enrolled in the HeartHealth program had a mean age of 58.6 years, 60.3% (5302/8788) were male, and 62.4% (5382/8624) were recruited from an outpatient clinic setting. A total of 851,058 SMS text messages were sent, with 99.41% (846,009/851,058) delivered successfully. A total of 3533 out of 7964 (44.4% of program completers) participants completed the postintervention survey, and 4 HeartHealth staff members participated in a focus group discussion. Among the participants who completed the survey, 60.5% (2137/3533) reported that the program improved the healthiness of their diet, 53.6% (1894/3533) reported improved physical activity levels, and 56.1% (1982/3533) reported that it helped remind them to take their medications. Content analysis of participant feedback identified that the program was effective in prompting participants to change their diet, providing emotional support, reminding them of the importance of behavior change, improving their confidence in managing their health, and keeping participants focused. Key barriers included limited personalization, language options, and SMS text messaging scheduling flexibility. Recommended adaptations focused on enhancing personalization, greater engagement by local clinical teams, and expanding program dissemination.</p><p><strong>Conclusions: </strong>The program had a broad reach, translated to improved patient-reported health behaviors, and provided participants with needed support at low cost and low resource requirements. This analysis highlights the successful implementation and scalability of the HeartHealth program and provides key learnings for health systems that are looking to implement similar programs in the future.</p>","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e68896"},"PeriodicalIF":2.2,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12978537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147432932","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association Between Type D Personality and Cardiovascular Disease History: Cross-Sectional Study.","authors":"Keren Grinberg, Yael Sela","doi":"10.2196/79159","DOIUrl":"https://doi.org/10.2196/79159","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Type D personality, characterized by high negative affectivity and social inhibition, has been linked to poorer mental health and heightened risk for adverse cardiovascular outcomes. Although previous studies have examined associations between type D personality, psychological distress, and cardiovascular disease (CVD), many have assessed these factors independently, relied on clinical samples, or overlooked the simultaneous assessment of psychological distress and CVD history. Consequently, less is known about how type D traits relate to emotional distress and CVD history within the general population. Understanding these relationships may support early identification of at-risk individuals and strengthen the integration of psychological screening into cardiovascular care.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to (1) examine associations between type D personality, emotional distress (depression, anxiety, and stress), and self-reported CVD history; (2) compare distress levels among participants with and without CVD history; and (3) determine whether type D personality predicts emotional distress independent of demographic factors and CVD history.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;A cross-sectional online survey was completed by 146 adults aged 30 to 85 years, recruited through convenience and snowball sampling on social media. Type D personality was assessed using the Type D Scale-14, and emotional distress was measured using the Depression Anxiety and Stress Scale-21 items. CVD history was captured through a single self-report question regarding prior diagnosis of a cardiovascular condition. Descriptive statistics characterized the sample. Two-tailed independent samples t tests compared distress between individuals with and without type D personality and between participants with and without CVD history. Pearson correlation coefficients examined associations among key variables. Hierarchical multiple regression assessed whether type D personality predicted emotional distress beyond age, gender, education, and CVD history.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of the 146 participants, 40 (27.4%) reported a history of CVD and 62 (42.5%) met criteria for type D personality. Individuals with type D personality exhibited significantly higher depression, anxiety, and stress levels than non-type D participants (all P&lt;.001). Participants with CVD history also reported greater distress compared with those without CVD history. Hierarchical regression analyses showed that type D personality remained a strong independent predictor of emotional distress (β=.46; P&lt;.001) after adjusting for demographics and CVD history. CVD history made an additional but smaller contribution to distress (β=.18; P=.008). These findings highlight the cumulative influence of personality traits and cardiovascular background on psychological well-being.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusions: &lt;/strong&gt;Type D personality traits have been associated with high","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e79159"},"PeriodicalIF":2.2,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12974995/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147432919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Applications of Smart Textiles for Ambulatory Electrocardiogram Monitoring: Scoping Review of the Literature.","authors":"Clarissa Pedrini Schuch, Gabriela Chaves, Bastien Moineau, Sarah Bennett, Meysam Pirbaglou, Edwin Martin Lobo, Milad Alizadeh-Meghrazi","doi":"10.2196/74261","DOIUrl":"10.2196/74261","url":null,"abstract":"<p><strong>Background: </strong>Smart textiles (ie, electronic textiles) offer a promising solution to ease continuous electrocardiogram (ECG) monitoring, but their real-world clinical application has been limited.</p><p><strong>Objective: </strong>This review comprehensively examines the current state of research on textile-based ECG monitoring systems, synthesizing current evidence with respect to performance (ie, signal quality, function under static and dynamic conditions), user experience, and current challenges.</p><p><strong>Methods: </strong>A systematic literature search across the PubMed, MEDLINE, and Embase databases from 2000 to 2025 identified 34 research papers eligible for inclusion.</p><p><strong>Results: </strong>Textile-based ECG electrodes demonstrated good signal quality and comfort, particularly under static conditions. Nonetheless, integration into clinical practice requires addressing critical issues, which include greater efforts at validating these technologies in clinical settings and populations, as well as ensuring data security, cost‑effectiveness, user‑friendliness, and data interoperability.</p><p><strong>Conclusions: </strong>Considering the prominence of feasibility research, the successful clinical integration of textile-based ECG monitoring systems requires comprehensive efforts at establishing a clinical evaluation research base (via clinical trials) and developing regulatory policies.</p>","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e74261"},"PeriodicalIF":2.2,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12954708/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147432845","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Digital Health Literacy in Elective Open-Heart Surgery Patients: Cross-Sectional Study.","authors":"Rikke Daugaard, Thomas Maribo, Britt Borregaard, Ditte Sommerlund Skydt, Kristina Hindhede Bech, Kjersti Alexandra Skovli, Ivy Susanne Modrau","doi":"10.2196/83454","DOIUrl":"10.2196/83454","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Digital health solutions play a key role in health care, but their safe and effective use depends on patients' digital health literacy. While digital health solutions are beneficial for patients with cardiac disease, disparities in digital health literacy may limit access, particularly for patients undergoing cardiac surgery with complex care and psychological challenges. Unaddressed, these disparities could exacerbate inequalities in accessing beneficial digital services. Denmark's advanced digital health care system provides a unique context to evaluate digital health literacy.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Objective: &lt;/strong&gt;This study aimed to assess digital health literacy levels in patients scheduled for elective open-heart surgery and examine associations with sociodemographic factors and concurrent health issues.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;We conducted a cross-sectional survey of consecutive patients scheduled for elective open-heart surgery at 3 university hospitals covering approximately two-thirds of Denmark's population. Patients with cognitive impairment or language barriers preventing completion of the questionnaire were excluded. The questionnaire was administered in paper form by medical staff during preoperative consultations. Digital health literacy was assessed using the validated 8-item eHealth Literacy Scale (eHEALS; range 8-40), along with 2 additional questions from the validated Danish version assessing the perceived importance and usefulness of online health information. Sociodemographic data collected included age, gender, cohabitation status, social support for technology use, educational level, and number of concurrent health issues. Descriptive and comparative analyses examined associations between eHEALS scores and sociodemographic variables and health issues. Exploratory subscale analyses evaluated the 3 eHEALS domains-awareness, skills, and ability to evaluate online health information-to identify areas in which patients may require additional support.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;Of 576 eligible patients, 313 (54.3%) completed the survey between February 2024 and July 2024. Response rates varied across sites: 71.1% (133/187), 58.5% (134/229), and 28.8% (46/160) in sites 1, 2, and 3, respectively. Nonresponse was primarily due to logistical challenges during preoperative consultations, with only a few patients excluded because of cognitive impairment, language barriers, or refusal. The median eHEALS score was 30 (IQR 27-32), indicating generally high digital health literacy scores (cutoff score ≥26). Scores were negatively correlated with age (Spearman ρ=-0.18; P=.002) and positively associated with educational level (Kruskal-Wallis test: χ22=17.0; P&lt;.001). No substantial associations were observed for gender, cohabitation status, social support for technology use, or number of concurrent health issues. Exploratory subscale analyses suggested that patients felt least confident in evaluating","PeriodicalId":14706,"journal":{"name":"JMIR Cardio","volume":"10 ","pages":"e83454"},"PeriodicalIF":2.2,"publicationDate":"2026-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12954704/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147344196","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}