Citations

AbstractThe dystrophinopathies encompass the phenotypically variable forms of muscular dystrophy caused by pathogenic variants in the DMD gene. The dystrophinopathies include the most common inherited muscular dystrophy among 46,XY individuals, Duchenne muscular dystrophy, as well as Becker muscular dystrophy and other less common phenotypic variants. With increased access to and utilization of genetic testing in the diagnostic and carrier setting, genetic counselors and clinicians in diverse specialty areas may care for individuals with and carriers of dystrophinopathy. This practice resource was developed as a tool for genetic counselors and other health care professionals to support counseling regarding dystrophinopathies, including diagnosis, health risks and management, psychosocial needs, reproductive options, clinical trials, and treatment. Genetic testing efforts have enabled genotype/phenotype correlation in the dystrophinopathies, but have also revealed unexpected findings, further complicating genetic counseling for this group of conditions. Additionally, the therapeutic landscape for dystrophinopathies has dramatically changed with several FDA‐approved therapeutics, an expansive research pathway, and numerous clinical trials. Genotype–phenotype correlations are especially complex and genetic counselors' unique skill sets are useful in exploring and explaining this to families. Given the recent advances in diagnostic testing and therapeutics related to dystrophinopathies, this practice resource is a timely update for genetic counselors and other healthcare professionals involved in the diagnosis and care of individuals with dystrophinopathies.

Background: Cardiac amyloidosis (CA) is associated with sinus node dysfunction (SND) and conduction system disease (CSD) yet data on pacing indications and outcomes is scarce. Methods: Retrospective review of patients (pts) with CA who had device implantation due to pacing indication at our institution. Results: At total of 51 (mean age 67.2±9.2 years, 90.2% male) pts with immunoglobulin light chain (n=27, 52.9%), hereditary transthyretin (n=7, 13.7%) and wild-type transthyretin (n=17, 33.3%) CA were included. Indication for pacing was exercise intolerance (n=16, 31.4%), syncope (n=16, 31.4%), congestive heart failure (n=5, 9.8%) and palpitation (n=2, 3.9%) with SND (n=23, 45.1%), CSD (17=33.3%) and uncontrolled atrial fibrillation (n=11, 21.6%). 16 (31.4%) pts received defibrillators (ICD) for primary prevention, of whom 8 (15.7%) had left ventricular ejection fraction (LVEF) ≤35%. Atrial (P wave: 1.7±1.2mV, threshold: 1.1±0.5mV/0.5±0.2ms) and right ventricular (RV) (R wave: 7.9±3.8mV, threshold: 0.8±0.4mV/0.4±0.1ms) lead parameters were satisfactory at implantation. During follow-up (mean 36.6±33.6 months), 26 (51%) pts reported symptomatic improvement (SI). Syncope was the only predictor of SI (OR 16.4, 95%CI 1.8-145.2, p=0.01) while exercise intolerance was not (OR 0.09, 95%CI 0.02-0.44, p=0.003). First-time life-threatening ventricular arrhythmias (VA) occurred in 6 (11.8%) pts, 3 (5.9%) had ICD implanted for LVEF ≤35%, 3 (5.9%) without ICD and LVEF ≥35%. Syncope was not predictive of first-time VA. RV lead noise led to inappropriate ICD shocks in 1 patient. Atrial lead sensing failure occurred in 6 (11.8%) and loss of capture in 5 (9.8%). Conclusion: Device implantation in patients with cardiac amyloidosis is safe but atrial lead failure is common. Syncope usually improves with pacing whereas other factors should be considered in those presented with exercise intolerance. Selection of pts who need pacing for prophylactic ICD implantation is challenging as neither left ventricular ejection fraction nor syncope are predictive of arrhythmic events.

Abstract Introduction Meta-analytic studies support that insomnia is a risk factor for cognitive decline and dementia, but limited accounting of confounders reduces their validity. Further, it is unclear whether these associations are driven by specific insomnia phenotypes. In this study, we aimed to assess the relationship between insomnia and longitudinal global cognitive decline in community-dwelling older adults after considering self-reported sleep duration changes and other important characteristics. Methods From the Mayo Clinic Study of Aging (MCSA) cohort, we identified all (age>=50yo) cognitively unimpaired participants at baseline without comorbid neurological disease with at least two previous comprehensive neuropsychological evaluations. Participants with at least two occurrences of insomnia ICD diagnosis (by EMR and Rochester Epidemiological Project data) at least 30 days apart were classified as having insomnia, and those without any instance of diagnosis were considered negative for insomnia. Changes in sleep duration were assessed using the question #16 of BDI-2 and categorized in reduced sleep (yes/no). We fit mixed-effect regression models to assess whether insomnia was associated with standardized global cognitive scores, after adjusting for age, sex, education, APOEe4, composite cardiovascular and metabolic conditions scores, anxiety/depression, reduced sleep, OSA (ICD diagnosis), alcoholism (CAGE≥2), and pain (NSAIDs use). Number of cognitive assessments and time from baseline were included as both fixed and random effects. Multiple interactions (e.g. insomnia*reduced sleep) were included. A backward stepwise procedure maintaining the hierarchical principal for interactions was utilized to reach the most parsimonious models. Results 3063 participants (50.24% males, aged 70±9.73 at baseline) were included. Insomnia alone was not associated with a decrease in global cognition, but when combined with subjective reduction in sleep duration at baseline it was associated with a -0.19 (95% CI: -0.32, -0.07; interaction p=0.01) reduction in global cognitive scores. This was equivalent to approximately 3 additional years of age or 6 cardiometabolic comorbidities at baseline. The effect size was greater than those associated with baseline cognition for having any APOE e4 allele (-0.12) and alcoholism (-0.15). Conclusion Insomnia with reduced sleep duration phenotype is a potentially modifiable risk factor for cognitive decline in older adults. Further studies with objective sleep measures are necessary for objective confirmation. Support (if any) NIA/NIH

Background: Music therapy (MT) offers benefits of improved symptom relief and quality of life at the end of life, but its impact on hospice patients and caregivers needs more research. Objective: To assess the impact of MT intervention on symptom burden and well-being of hospice patients and caregivers. Methods: A total of 18 hospice patients, selected based on scores ≥4 on the revised Edmonton Symptom Assessment System (ESAS-r) items on pain, depression, anxiety, or well-being, participated in MT sessions provided by a board-certified music therapist. Over a period of 2-3 weeks, 3-4 MT sessions were conducted for each. Patient Quality of life (QOL) was assessed using the Linear Analogue Self-Assessment (LASA). Depression and anxiety were measured with the Patient Health Questionnaire-4 (PHQ-4). For the 7 caregivers enrolled, stress levels were measured using the Pearlin role overload measure and LASA. Results: Patients reported a reduction in symptom severity and emotional distress and an increase in QOL. All patients endorsed satisfaction with music therapy, describing it as particularly beneficial for stress relief, relaxation, spiritual support, emotional support, and well-being. Scores on overall QOL and stress were worse for caregivers. Conclusion: This study provides evidence that MT reduces symptom burden and enhances the quality of life for hospice patients. Hospice patients and their caregivers endorsed satisfaction with MT. Given the benefits observed, integrating MT into hospice care regimens could potentially improve patient and caregiver outcomes. Larger studies should be conducted to better assess the impact of MT in this population.

Abstract Aims Cardiac amyloidosis (CA) is common in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR). Cardiac amyloidosis has poor outcomes, and its assessment in all TAVR patients is costly and challenging. Electrocardiogram (ECG) artificial intelligence (AI) algorithms that screen for CA may be useful to identify at-risk patients. Methods and results In this retrospective analysis of our institutional National Cardiovascular Disease Registry (NCDR)-TAVR database, patients undergoing TAVR between January 2012 and December 2018 were included. Pre-TAVR CA probability was analysed by an ECG AI predictive model, with >50% risk defined as high probability for CA. Univariable and propensity score covariate adjustment analyses using Cox regression were performed to compare clinical outcomes between patients with high CA probability vs. those with low probability at 1-year follow-up after TAVR. Of 1426 patients who underwent TAVR (mean age 81.0 ± 8.5 years, 57.6% male), 349 (24.4%) had high CA probability on pre-procedure ECG. Only 17 (1.2%) had a clinical diagnosis of CA. After multivariable adjustment, high probability of CA by ECG AI algorithm was significantly associated with increased all-cause mortality [hazard ratio (HR) 1.40, 95% confidence interval (CI) 1.01–1.96, P = 0.046] and higher rates of major adverse cardiovascular events (transient ischaemic attack (TIA)/stroke, myocardial infarction, and heart failure hospitalizations] (HR 1.36, 95% CI 1.01–1.82, P = 0.041), driven primarily by heart failure hospitalizations (HR 1.58, 95% CI 1.13–2.20, P = 0.008) at 1-year follow-up. There were no significant differences in TIA/stroke or myocardial infarction. Conclusion Artificial intelligence applied to pre-TAVR ECGs identifies a subgroup at higher risk of clinical events. These targeted patients may benefit from further diagnostic evaluation for CA.

Summary: While the current approach to precursor hematologic conditions is to “watch and wait,” this may change with the development of therapies that are safe and extend survival or delay the onset of symptomatic disease. The goal of future therapies in precursor hematologic conditions is to improve survival and prevent or delay the development of symptomatic disease while maximizing safety. Clinical trial considerations in this field include identifying an appropriate at-risk population, safety assessments, dose selection, primary and secondary trial endpoints including surrogate endpoints, control arms, and quality-of-life metrics, all of which may enable more precise benefit–risk assessment.

AbstractINTRODUCTIONLittle is known regarding quality of life (QoL) in dementia with Lewy bodies (DLB), particularly in advanced stages.METHODSDyads of individuals with moderate–advanced DLB and their primary caregivers were recruited from specialty clinics, advocacy organizations, and research registries. The study collected demographics, disease‐related measures, and measures of patient/caregiver experiences.RESULTSThe Quality of Life in Alzheimer's Disease (QoL‐AD) was completed by the person with DLB and the caregiver (proxy) in 61 dyads; 85 dyads had only a proxy‐completed QoL‐AD. Patient‐ and proxy‐reported scores were moderately correlated (r = 0.57, P < 0.0001). Worse patient‐reported QoL correlated with daytime sleepiness, autonomic symptom burden, and behavioral symptoms. Proxy ratings correlated with dementia severity, daytime sleepiness, behavioral symptoms, dependence in activities of daily living, and caregiver experience measures.DISCUSSIONPatient‐ and proxy‐reported quality of life (QoL) should be assessed separately in advanced DLB. Some symptoms associated with QoL have available therapeutic options. Research is needed regarding strategies to optimally improve QoL in DLB.Highlights Patient and proxy quality of life (QoL) ratings had moderate correlation in advanced dementia with Lewy bodies. Daytime sleepiness affected patient‐ and proxy‐reported QoL. Behavioral symptoms affected patient‐ and proxy‐reported QoL. Autonomic symptom burden affected patient‐reported QoL. Dementia severity, dependence, and caregiver experiences affected proxy ratings.