Association of Beta-Blocker Use With Exercise Capacity in Participants With Heart Failure With Preserved Ejection Fraction: A Post Hoc Analysis of the RELAX Trial.

Patients with heart failure with preserved ejection fraction (HFpEF) often receive ß-blocker (BB) therapy for management of co-morbidities. However, the association of BB therapy with exercise capacity and health-related quality of life (HRQL) in HFpEF is not well-studied. In this post hoc analysis of the Phosphodiesterase-5 Inhibition to Improve Clinical Status and Exercise Capacity in HFpEF (RELAX) trial, which included patients with chronic stable HFpEF with peak exercise capacity assessment at baseline and at 12 and 24 weeks of follow-up, we evaluated the association of BB use with the measures of exercise capacity (peak exercise oxygen uptake), anaerobic threshold, and HRQL (Minnesota living with heart failure questionnaire). Separate linear mixed-effect models were constructed for each outcome with adjustment for treatment arm, demographics, medical history, left ventricular ejection fraction, and duration of heart failure. Of the 216 study participants (median age 69 years, 48.2% women), 76% reported BB use at baseline. Participants with (vs without) BB therapy were older (70 vs 63.5 years, p = 0.001) and had a higher prevalence of ischemic heart disease (44% vs 23%, p = 0.01). In the adjusted linear mixed model, BB use over time was not associated with peak exercise oxygen uptake (ß 95% confidence interval [CI] 0.2 (-0.31 to 0.7), p = 0.5) and 6-minute walk distance (ß 95% CI 14.69 [-14.25 to 43.63], p = 0.3). However, BB use was associated with a higher anaerobic threshold (ß 95% CI 0.32 (0.02 to 0.62), p = 0.036) and better HRQL (lower quality of life as assessed by Minnesota living with heart failure questionnaire score) (ß 95% CI -6.68 [-10.96 to -2.4], p = 0.002). Future trials are needed to better evaluate the effects of BB on exercise capacity in patients with chronic stable HFpEF.

Sex Disparities in Longitudinal Use and Intensification of Guideline-Directed Medical Therapy Among Patients With Newly Diagnosed Heart Failure With Reduced Ejection Fraction.

BACKGROUND: Guideline-directed medical therapies (GDMTs) are the mainstay of treatment for heart failure with reduced ejection fraction (HFrEF), but they are underused. Whether sex differences exist in the initiation and intensification of GDMT for newly diagnosed HFrEF is not well established. METHODS: Patients with incident HFrEF were identified from the 2016 to 2020 Optum deidentified Clinformatics Data Mart Database, which is derived from a database of administrative health claims for members of large commercial and Medicare Advantage health plans. The primary outcome was the use of optimal GDMT within 12 months of HFrEF diagnosis. Consistent with the guideline recommendations during the time period of the study, optimal GDMT was defined as ≥50% of the target dose of evidence-based beta-blocker plus ≥50% of the target dose of angiotensin-converting enzyme inhibitor or angiotensin receptor blocker, or any dose of angiotensin receptor neprilysin inhibitor plus any dose of mineralocorticoid receptor antagonist. The probability of achieving optimal GDMT on follow-up and predictors of optimal GDMT were evaluated with time-to-event analysis with adjusted Cox proportional hazard models. RESULTS: The study cohort included 63 759 patients (mean age, 71.3 years; 15.2% non-Hispanic Black race; 56.6% male). Optimal GDMT use was achieved by 6.2% of patients at 12 months after diagnosis. Female (compared with male) patients with HFrEF had lower use across every GDMT class and lower use of optimal GDMT at each time point at follow-up. In an adjusted Cox model, female sex was associated with a 23% lower probability of achieving optimal GDMT after diagnosis (hazard ratio [HR], 0.77 [95% CI, 0.71-0.83]; P<0.001). The sex disparities in GDMT use after HFrEF diagnosis were most pronounced among patients with commercial insurance (females compared with males; HR, 0.66 [95% CI, 0.58-0.76]) compared with Medicare (HR, 0.85 [95% CI, 0.77-0.92]); Pinteraction sex×insurance status=0.005) and for younger patients (age <65 years: HR, 0.65 [95% CI, 0.58-0.74]) compared with older patients (age ≥65 years: HR, 87 [95% CI, 80-96]) Pinteraction sex×age=0.009). CONCLUSIONS: Overall use of optimal GDMT after HFrEF diagnosis was low, with significantly lower use among female (compared with male) patients. These findings highlight the need for implementation efforts directed at improving GDMT initiation and titration.

Role of exercise therapy and cardiac rehabilitation in heart failure.

Heart failure (HF) is a common cause of hospitalization and death, and the hallmark symptoms of HF, including dyspnea, fatigue, and exercise intolerance, contribute to poor patient quality of life (QoL). Cardiac rehabilitation (CR) is a comprehensive disease management program incorporating exercise training, cardiovascular risk factor management, and psychosocial support. CR has been demonstrated to effectively improve patient functional status and QoL among patients with HF. However, CR participation among patients with HF is poor. This review details the mechanisms of dyspnea and exercise intolerance among patients with HF, the physiologic and clinical improvements observed with CR, and the key components of a CR program for patients with HF. Furthermore, unmet needs and future strategies to improve patient participation and engagement in CR for HF are reviewed.

Frailty Status Modifies the Efficacy of ICD Therapy for Primary Prevention Among Patients With HF.

BACKGROUND: Implantable cardioverter-defibrillator (ICD) therapy is recommended to reduce mortality risk in patients with heart failure with reduced ejection fraction (HFrEF). Frailty is common among patients with HFrEF and is associated with increased mortality risk. Whether the therapeutic efficacy of ICD is consistent among frail and nonfrail patients with HFrEF remains unclear. OBJECTIVES: The aim of this study was to evaluate the effect modification of baseline frailty burden on ICD efficacy for primary prevention among participants of the SCD-HeFT (Sudden Cardiac Death in Heart Failure Trial). METHODS: Participants in SCD-HeFT with HFrEF randomized to ICD vs placebo were included. Baseline frailty was estimated using the Rockwood Frailty Index (FI), and participants were stratified into high (FI > median) vs low (FI ≤ median) frailty burden groups. Multivariable Cox models with multiplicative interaction terms (frailty × treatment arm) were constructed to evaluate whether baseline frailty status modified the treatment effect of ICD for all-cause mortality. RESULTS: The study included 1,676 participants (mean age: 59 ± 12 years, 23% women) with a median FI of 0.30 (IQR: 0.23-0.37) in the low frailty group and 0.54 (IQR: 0.47-0.60) in the high frailty group. In adjusted Cox models, baseline frailty status significantly modified the treatment effect of ICD therapy (Pinteraction = 0.047). In separate stratified analysis by frailty status, ICD therapy was associated with a lower risk of all-cause mortality among participants with low frailty burden (HR: 0.56; 95% CI: 0.40-0.78) but not among those with high frailty burden (HR: 0.86; 95% CI: 0.68-1.09). CONCLUSIONS: Baseline frailty modified the efficacy of ICD therapy with a significant mortality benefit observed among participants with HFrEF and a low frailty burden but not among those with a high frailty burden.

Prevalence and Predictors of Subclinical Cardiomyopathy in Patients With Type 2 Diabetes in a Health System.

INTRODUCTION: Diabetic cardiomyopathy (DbCM) is characterized by subclinical abnormalities in cardiac structure/function and is associated with a higher risk of overt heart failure (HF). However, there are limited data on optimal strategies to identify individuals with DbCM in contemporary health systems. The aim of this study was to evaluate the prevalence of DbCM in a health system using existing data from the electronic health record (EHR). METHODS: Adult patients with type 2 diabetes mellitus free of cardiovascular disease (CVD) with available data on HF risk in a single-center EHR were included. The presence of DbCM was defined using different definitions: (1) least restrictive: ≥1 echocardiographic abnormality (left atrial enlargement, left ventricle hypertrophy, diastolic dysfunction); (2) intermediate restrictive: ≥2 echocardiographic abnormalities; (3) most restrictive: 3 echocardiographic abnormalities. DbCM prevalence was compared across age, sex, race, and ethnicity-based subgroups, with differences assessed using the chi-squared test. Adjusted logistic regression models were constructed to evaluate significant predictors of DbCM. RESULTS: Among 1921 individuals with type 2 diabetes mellitus, the prevalence of DbCM in the overall cohort was 8.7% and 64.4% in the most and least restrictive definitions, respectively. Across all definitions, older age and Hispanic ethnicity were associated with a higher proportion of DbCM. Females had a higher prevalence than males only in the most restrictive definition. In multivariable-adjusted logistic regression, higher systolic blood pressure, higher creatinine, and longer QRS duration were associated with a higher risk of DbCM across all definitions. CONCLUSIONS: In this single-center, EHR cohort, the prevalence of DbCM varies from 9% to 64%, with a higher prevalence with older age and Hispanic ethnicity.

Risk factors for Coronavirus disease-associated mucormycosis.

BACKGROUND: The epidemiology of the Coronavirus-disease associated mucormycosis (CAM) syndemic is poorly elucidated. We aimed to identify risk factors that may explain the burden of cases and help develop preventive strategies. METHODS: We performed a case-control study comparing cases diagnosed with CAM and taking controls as recovered COVID 19 patients who did not develop mucormycosis. Information on comorbidities, glycemic control, and practices related to COVID-19 prevention and treatment was recorded. Multivariate regression analysis was used to identify independent predictors. RESULTS: A total of 352 patients (152 cases and 200 controls) diagnosed with COVID-19 during April-May 2021 were included. In the CAM group, symptoms of mucormycosis began a mean of 18.9 (SD 9.1) days after onset of COVID-19, and predominantly rhino-sinus and orbital involvement was present. All, but one, CAM cases had conventional risk factors of diabetes and steroid use. On multivariable regression, increased odds of CAM were associated with the presence of diabetes (adjusted OR 3.5, 95% CI 1.1-11), use of systemic steroids (aOR 7.7, 95% CI 2.4-24.7), prolonged use of cloth and surgical masks (vs. no mask, aOR 6.9, 95%CI 1.5-33.1), and repeated nasopharyngeal swab testing during the COVID-19 illness (aOR 1.6, 95% CI 1.2-2.2). Zinc therapy was found to be protective (aOR 0.05, 95%CI 0.01-0.19). Notably, the requirement of oxygen supplementation or hospitalization did not affect the risk of CAM. CONCLUSION: Judicious use of steroids and stringent glycemic control are vital to preventing mucormycosis. Use of clean masks, preference for N95 masks if available, and minimizing swab testing after the diagnosis of COVID-19 may further reduce the incidence of CAM.

A machine learning application for raising WASH awareness in the times of COVID-19 pandemic.

The COVID-19 pandemic has revealed the power of internet disinformation in influencing global health. The deluge of information travels faster than the epidemic itself and is a threat to the health of millions across the globe. Health apps need to leverage machine learning for delivering the right information while constantly learning misinformation trends and deliver these effectively in vernacular languages in order to combat the infodemic at the grassroot levels in the general public. Our application, WashKaro, is a multi-pronged intervention that uses conversational Artificial Intelligence (AI), machine translation, and natural language processing to combat misinformation (NLP). WashKaro uses AI to provide accurate information matched against WHO recommendations and delivered in an understandable format in local languages. The primary aim of this study was to assess the use of neural models for text summarization and machine learning for delivering WHO matched COVID-19 information to mitigate the misinfodemic. The secondary aim of this study was to develop a symptom assessment tool and segmentation insights for improving the delivery of information. A total of 5026 people downloaded the app during the study window; among those, 1545 were actively engaged users. Our study shows that 3.4 times more females engaged with the App in Hindi as compared to males, the relevance of AI-filtered news content doubled within 45 days of continuous machine learning, and the prudence of integrated AI chatbot "Satya" increased thus proving the usefulness of a mHealth platform to mitigate health misinformation. We conclude that a machine learning application delivering bite-sized vernacular audios and conversational AI is a practical approach to mitigate health misinformation.

Cerebellar progressive multifocal leukoencephalopathy associated with pulmonary sarcoidosis.

Progressive multifocal leukoencephalopathy can complicate the course of a patient with sarcoidosis. Here we present a rare case of a 35-year-old patient with pulmonary sarcoidosis whose course was complicated by progressive multifocal leukoencephalopathy involving the cerebellum. Neuroimaging and cerebrospinal fluid PCR played a crucial role in the diagnosis.

Patient Experience of a Neurology Tele-Follow-Up Program Initiated During the Coronavirus Disease 2019 Pandemic: A Questionnaire-Based Study.

Background: Teleneurology consultations can be highly advantageous since neurological diseases and disabilities often limit patient's access to health care, particularly in a setting where they need to travel long distances for specialty consults. Patient satisfaction is an important outcome assessing success of a telemedicine program. Materials and Methods: A cross-sectional study was conducted to determine satisfaction and perception of patients toward an audio call based teleneurology follow-up initiated during the coronavirus disease 2019 pandemic. Primary outcomes were satisfaction to tele-consult, and proportion of patients preferring telemedicine for future follow-up. Results: A total of 261 patients who received tele-consult were enrolled. Satisfaction was highest for domain technological quality, followed by patient-physician dialogue (PPD) and least to quality of care (QoC). Median (interquartile range) patient satisfaction on a 5-point Likert scale was 4 (3-5). Eighty-five (32.6%; 95% confidence interval 26.9-38.6%) patients preferred telemedicine for future follow-up. Higher overall satisfaction was associated with health condition being stable/better, change in treatment advised on tele-consult, diagnosis not requiring follow-up examination, higher scores on domains QoC and PPD (p < 0.05). Future preference for telemedicine was associated with patient him-/herself consulting with doctor, less duration of follow-up, higher overall satisfaction, and higher scores on domain QoC (p < 0.05). On thematic analysis, telemedicine was found convenient, reduced expenditure, and had better physician attention; in-person visits were comprehensive, had better patient-physician relationship, and better communication. Discussion: Patient satisfaction was lower in our study than what has been observed earlier, which may be explained by the primitive nature of our platform. Several variables related to the patients' disease process have an effect on patient satisfaction. Conclusion: Development of robust, structured platforms is necessary to fully utilize the potential of telemedicine in developing countries.