Lee CJ, et al. Int J Heart Fail. 2024 Apr;6(2):56-69. https://doi.org/10.36628/ijhf.2024.0010

Background: Cardiovascular disease is an important cause of mortality among survivors of breast cancer (BC). We developed a prediction model for major adverse cardiovascular events after BC therapy, which is based on conventional and BC treatment‐related cardiovascular risk factors. Methods and Results: The cohort of the study consisted of 1256 Asian female patients with BC from 4 medical centers in Korea and was randomized in a 1:1 ratio into the derivation and validation cohorts. The outcome measures comprised cardiovascular mortality, myocardial infarction, congestive heart failure, and transient ischemic attack/stroke. To correct overfitting, a penalized Cox proportional hazards regression was performed with a cross‐validation approach. Number of cardiovascular diseases (myocardial infarction, peripheral artery disease, heart failure, and transient ischemic attack/stroke), number of baseline cardiovascular risk factors (hypertension, age ≥60, body mass index ≥30 kg/m ² , estimated glomerular filtration rate <60 mL/min per 1.73 m ² , dyslipidemia, and diabetes mellitus), radiation to the left breast, and anthracycline dose per 100 mg/m ² were included in the risk prediction model. The time‐dependent C‐indices at 3 and 7 years after BC diagnosis were 0.876 and 0.842, respectively, in the validation cohort. Conclusions: A prediction score model, including BC treatment‐related risk factors and conventional risk factors, was developed and validated to predict major adverse cardiovascular events in patients with BC. The CHEMO‐RADIAT (congestive heart failure, hypertension, elderly, myocardial infarction/peripheral artery occlusive disease, obesity, renal failure, abnormal lipid profile, diabetes mellitus, irradiation of the left breast, anthracycline dose, and transient ischemic attack/stroke) score may provide overall cardiovascular risk stratification in survivors of BC and can assist physicians in multidisciplinary decision‐making regarding the BC treatment.

Youn JC, et al. Int J Heart Fail. 2023 Apr;5:e9. https://doi.org/10.36628/ijhf.2023.0011

Objective We aimed to identify the following in all age groups among individuals without known hypertension and CVD: (1) Whether a systolic blood pressure (SBP) of 130–139 mm Hg elevates cardiovascular disease (CVD) mortality. (2) Whether SBP shows a linear association with cause-specific CVD mortality. Methods We used the Korean National Health Insurance sample data (n=429 220). Participants were categorised into three groups by age (40–59 years, 60–69 years and 70–80 years). Results During 10.4 years of follow-up, 4319 cardiovascular deaths occurred. A positive and graded association was generally observed between SBP and overall and cause-specific CVD mortality regardless of age, except for ischaemic heart disease (IHD) mortality in those aged 70–80 years. Among those aged 70–80 years, the HRs (95% CIs) for overall CVD mortality were 1.08 (0.92–1.28), 1.14 (0.97–1.34) and 1.34 (1.14–1.58) for SBP values of 120–129 mm Hg, 130–139 mm Hg and 140–149 mm Hg, respectively, compared with SBP <120 mm Hg. For total stroke mortality, the corresponding HRs were 1.29 (1.02–1.64), 1.37 (1.09–1.72) and 1.52 (1.20–1.93), while for IHD mortality, the corresponding HRs were 0.90 (0.64–1.26), 0.86 (0.62–1.19) and 1.29 (0.93–1.78), respectively. Non-linear associations were significant for IHD. Conclusions In the elderly Korean population, SBPs of 130–139 mm Hg elevated total stroke mortality, but not IHD mortality, compared with normal blood pressure, and a linear association was not observed for IHD mortality in the range <140 mm Hg.

Cho JY, et al. Int J Heart Fail. 2023 Apr;5:e10. https://doi.org/10.36628/ijhf.2023.0009

Background: Current heart failure (HF) guidelines recommend a multidisciplinary approach, discharge education, and self-management for HF. However, the recommendations are challenging to implement in real-world clinical settings. Objective: We developed a mobile health (mHealth) platform for HF self-care to evaluate whether a smartphone app–based intervention with Bluetooth-connected monitoring devices and a feedback system can help improve HF symptoms. Methods: In this prospective, randomized, multicenter study, we enrolled patients 20 years of age and older, hospitalized for acute HF, and who could use a smartphone from 7 tertiary hospitals in South Korea. In the intervention group (n=39), the apps were automatically paired with Bluetooth-connected monitoring devices. The patients could enter information on vital signs, HF symptoms, diet, medications, and exercise regimen into the app daily and receive feedback or alerts on their input. In the control group (n=38), patients could only enter their blood pressure, heart rate, and weight using conventional, non-Bluetooth devices and could not receive any feedback or alerts from the app. The primary end point was the change in dyspnea symptom scores from baseline to 4 weeks, assessed using a questionnaire. Results: At 4 weeks, the change in dyspnea symptom score from baseline was significantly greater in the intervention group than in the control group (mean –1.3, SD 2.1 vs mean –0.3, SD 2.3; P=.048). A significant reduction was found in body water composition from baseline to the final measurement in the intervention group (baseline level mean 7.4, SD 2.5 vs final level mean 6.6, SD 2.5; P=.003). App adherence, which was assessed based on log-in or the percentage of days when symptoms were first observed, was higher in the intervention group than in the control group. Composite end points, including death, rehospitalization, and urgent HF visits, were not significantly different between the 2 groups. Conclusions: The mobile-based health platform with Bluetooth-connected monitoring devices and a feedback system demonstrated improvement in dyspnea symptoms in patients with HF. This study provides evidence and rationale for implementing mobile app–based self-care strategies and feedback for patients with HF. Trial Registration: ClinicalTrials.gov NCT05668000; https://clinicaltrials.gov/study/NCT05668000