JMIR Cardio最新文献

Background: Atrial fibrillation (AF) is a chronic cardiovascular condition that requires long-term adherence to medications and self-monitoring. Clinical trials for AF have had limited diversity by sex, race and ethnicity, and rural residence, thereby compromising the integrity and generalizability of trial findings. Digital technology coupled with remote strategies has the potential to increase recruitment of individuals from underrepresented demographic and geographic populations, resulting in increased trial diversity, and improvement in the generalizability of interventions for complex diseases such as AF.

Objective: This study aimed to summarize the architecture of a research program using remote methods to enhance geographic and demographic diversity in mobile health trials to improve medication adherence.

Methods: We developed a programmatic architecture to conduct remote recruitment and assessments of individuals with AF in 2 complementary randomized clinical trials, funded by the National Institutes of Health, to test the effectiveness of a smartphone-based relational agent on adherence to oral anticoagulation. The study team engaged individuals with either rural or metropolitan residences receiving care for AF at health care settings who then provided consent, and underwent baseline assessments and randomization during a remotely conducted telephone visit. Participants were randomized to receive the relational agent intervention or control and subsequently received a study smartphone with installed apps by mail. Participants received a telephone-based training session on device and app usage accompanied by a booklet with pictures and instructions accessible for any level of health or digital literacy. The program included remote methods by mail and telephone to promote retention at 4-, 8-, and 12-month visits and incentivized return of the smartphone following study participation. The program demonstrated excellent participant engagement and retention throughout the duration of the clinical trials.

Results: The trials enrolled 513 participants, surpassing recruitment goals for the rural (n=270; target n=264) and metropolitan (n=243; target n=240) studies. A total of 62% (319/513) were women; 31% (75/243) of participants in the metropolitan study were African American, Asian, American Indian or Alaskan native or other races or ethnicities, in contrast to 5% (12/270) in the rural study. Among all participants, 56% (286/513) had less than an associate's degree and 44% (225/513) were characterized as having limited health literacy. Intervention recipients receiving the relational agent used the agent median of 95-98 (IQR, 56-109) days across both studies. Retention exceeded 89% (457/513) at 12 months with study phones used for median 3.3 (IQR, 1-5) participants.

Conclusions: We report here the development and implementation of a p

Background: Home blood pressure telemonitoring (HBPT) has been proposed to enhance adherence and optimize health care delivery, yet its prerequisites for cost-effective implementation remain unclear.

Objective: This study aims to quantify the potential cost-effectiveness of HBPT and identify prerequisites for cost-effective implementation of HBPT in comparison to standard hypertension management, using an early health economic analysis from a societal perspective.

Methods: A decision-analytic Markov model with a lifetime horizon (30 years) and a willingness-to-pay threshold of €20,000 (€1=US $1.09) per quality-adjusted life year (QALY) was developed to assess the cost-effectiveness of HBPT compared to standard of care (SOC). The HBPT intervention was based on an existing HBPT program applied by the Maasstad Hospital, Rotterdam, the Netherlands. The model incorporated 12 health states: 7 blood pressure states, 1 cardiovascular (CV) event, 1 recurrent CV event, 1 postrecurrent CV event, 1 all-cause death, and 1 CV disease-related death. A hypothetical cohort of 1000 patients (average age 65.3 years) was modeled, and results were reported in costs, QALYs, and the incremental cost-effectiveness ratio (ICER). The model assumed 3 in-person outpatient department (OPD) consultations in the SOC group and 1.5 in the HBPT group. Extensive sensitivity analyses were performed to identify important variables for the cost-effective implementation of HBPT.

Results: Following the base-case analysis, HBPT was not cost-effective with an ICER of €20,386 per QALY. Sensitivity analyses indicated that reducing the number of in-person OPD consultations resulted in a more favorable ICER. Specifically, reducing the number of in-person OPD consultations to 1.48 annually resulted in an ICER below the willingness-to-pay threshold. Reducing the in-person OPD consultations to an average of 1.18 per year would make HBPT cost-saving. Scenario analyses revealed that extending the duration of HBPT's clinical effect to 2 or 3 years substantially improved the ICER. Additionally, targeting HBPT toward patients aged 64 years or below further improved the ICER.

Conclusions: HBPT could result in cost-effective or cost-saving outcomes with only minor reductions in in-person OPD consultations. These findings highlight the potential of HBPT to transform hypertension management by replacing traditional hypertension management with more efficient care using remote patient monitoring.

Background: Resistant hypertension (RH) presents significant clinical challenges, often precipitating a spectrum of cardiovascular complications. Particular attention recently has focused on the role of matrix metalloproteinase-2 (MMP-2) gene polymorphisms, implicated in hypertensive target organ damage (TOD). Despite growing interest, the specific contribution of MMP-2 polymorphisms to such damage in RH remains inadequately defined.

Objective: This study is the first to examine the rs243865 (-1306C>T) polymorphism in the MMP-2 gene in the Vietnamese population and patients with RH, underscoring its critical role as a genetic determinant of TOD.

Methods: A cross-sectional study with both descriptive and analytical components was conducted with 78 patients with RH at the Can Tho Central General Hospital and Can Tho University of Medicine and Pharmacy Hospital from July 2023 to February 2024.

Results: More than three-quarters of patients with RH had carotid-femoral pulse wave velocity (PWV) >10 m/s and microalbuminuria at a prevalence of 79% (62/78) and 76% (59/78), respectively, and more than half of patients with RH had left ventricular mass index, relative wall thickness, and carotid artery stenosis with a prevalence of 56% (45/78), 55% (43/78), and 53% (41/78), respectively. Of the 78 studied patients with RH, the presence of genotype CC was 77% (60/78), genotype CT accounted for 21% (16/78), and genotype TT for 3% (2/78). The presence of single nucleotide polymorphism rs243865 (-1306C>T) with allele T was 23% (18/78). The MMP-2 gene polymorphism 1306C/T (rs243865) was significantly associated with ejection fraction and carotid artery stenosis with odds ratios (ORs) 8.1 (95% CI 1.3-51.4; P=.03) and 4.5 (95% CI 1.1-20.1; P=.048), respectively. The allele T was found to be significantly associated with arterial stiffness including brachial-ankle PWV and carotid-femoral PWV with the correlation coefficient of OR 2.2 (95% CI 0.6-3.8) and OR 1.8 (95% CI 0.5-3.2), respectively.

Conclusions: The MMP-2 gene polymorphism rs243865 (-1306C>T) may have an association with measurable TOD in RH.

Background: Nonadherence to medication is a key factor contributing to high heart failure (HF) rehospitalization rates. A conversational agent (CA) or chatbot is a technology that can enhance medication adherence by helping patients self-manage their medication routines at home.

Objective: This study outlines the conception of a design method for developing a CA to support patients in medication adherence, utilizing design thinking as the primary process for gathering requirements, prototyping, and testing. We apply this design method to the ongoing development of Medical Assistance and Rehabilitation Intelligent Agent (MARIA), a rule-based CA.

Methods: Following the design thinking process, at the ideation stage, we engaged a multidisciplinary group of stakeholders (patients and pharmacists) to elicit requirements for the early conception of MARIA. In collaboration with pharmacists, we structured MARIA's dialogue into a workflow based on Adlerian therapy, a psychoeducational theory. At the testing stage, we conducted an observational study using the Wizard of Oz (WoZ) research method to simulate the MARIA prototype with 20 patient participants. This approach validated and refined our application of Adlerian therapy in the CA's dialogue. We incorporated human-likeness and trust scoring into user satisfaction assessments after each WoZ session to evaluate MARIA's feasibility and acceptance of medication adherence. Dialogue data collected through WoZ simulations were analyzed using a coding analysis technique.

Results: Our design method for the CA revealed gaps in MARIA's conception, including (1) handling negative responses, (2) appropriate use of emoticons to enhance human-likeness, (3) system feedback mechanisms during turn-taking delays, and (4) defining the extent to which a CA can communicate on behalf of a health care provider regarding medication adherence.

Conclusions: The design thinking process provided interactive steps to involve users early in the development of a CA. Notably, the use of WoZ in an observational clinical protocol highlighted the following: (1) coding analysis offered guidelines for modeling CA dialogue with patient safety in mind; (2) incorporating human-likeness and trust in user satisfaction assessments provided insights into attributes that foster patient trust in a CA; and (3) the application of Adlerian therapy demonstrated its effectiveness in motivating patients with HF to adhere to medication within a CA framework. In conclusion, our method is valuable for modeling and validating CA interactions with patients, assessing system reliability, user expectations, and constraints. It can guide designers in leveraging existing CA technologies, such as ChatGPT or AWS Lex, for adaptation in health care settings.