Multiorgan Dysfunction and Associated Prognosis in Transthyretin Cardiac Amyloidosis.

BACKGROUND: Transthyretin cardiac amyloidosis (ATTR-CA) is a progressive and ultimately fatal cardiomyopathy. Biomarkers reflecting multiorgan dysfunction are of increasing importance in patients with heart failure; however, their significance in ATTR-CA remains largely unknown. The aims of this study were to characterize the multifaceted nature of ATTR-CA using blood biomarkers and assess the association between blood biomarkers and prognosis. METHODS AND RESULTS: This is a retrospective cohort study of 2566 consecutive patients diagnosed with ATTR-CA between 2007 and 2023. Anemia (39%), high urea (52%), hyperbilirubinemia (18%), increased alkaline phosphatase (16%), increased CRP (C-reactive protein; 27%), and increased troponin (98.2%) were common findings in the overall population, whereas hyponatremia (6%) and hypoalbuminemia (2%) were less common. These abnormalities were most common in patients with p.(V142I) hereditary ATTR-CA, and became more prevalent as the severity of cardiac disease increased. Multivariable Cox regression analysis demonstrated that anemia (hazard ratio [HR], 1.19 [95% CI, 1.04-1.37]; P=0.01), high urea (HR, 1.23 [95% CI, 1.04-1.45]; P=0.01), hyperbilirubinemia (HR, 1.32 [95% CI, 1.13-1.57; P=0.001), increased alkaline phosphatase (HR, 1.20 [95% CI, 1.01-1.42; P=0.04), hyponatremia (HR, 1.65 [95% CI, 1.28-2.11]; P<0.001), and troponin-T >56 ng/L (HR, 1.72 [95% CI, 1.46-2.03]; P<0.001) were all independently associated with mortality in the overall population. The association between biomarkers and mortality varied across the spectrum of genotypes and left ventricular ejection fraction, with anemia remining independently associated with mortality in p.(V142I) hereditary ATTR-CA (HR, 1.58 [95% CI, 1.17-2.12]; P=0.003) and in a subgroup of the overall population with a left ventricular ejection fraction ≤40% (HR, 1.39 [95% CI, 1.08-1.81]; P=0.01). CONCLUSIONS: Cardiac and noncardiac biomarker abnormalities were common and reflect the complex and multifaceted nature of ATTR-CA, with a wide range of biomarkers remaining independently associated with mortality. Clinical trials are needed to investigate whether biomarker abnormalities represent modifiable risk factors that if specifically targeted could improve outcomes.

Albuminuria in transthyretin cardiac amyloidosis: Prevalence, progression and prognostic importance.

AIMS: Transthyretin cardiac amyloidosis (ATTR-CA) is an infiltrative cardiomyopathy that commonly presents with concomitant chronic kidney disease. Albuminuria is common in heart failure and associated with worse outcomes, but its prevalence and relationship to outcome in ATTR-CA remains unclear. METHODS AND RESULTS: A total of 1181 patients with ATTR-CA were studied (mean age 78.1 ± 7.9 years; 1022 [86.5%] male; median estimated glomerular filtration rate 59 ml/min/1.73m2 [interquartile range: 47-74]). Albuminuria was present in 563 (47.7%) patients (499 [88.6%] with microalbuminuria and 64 [11.4%] with macroalbuminuria). Patients with albuminuria had a more severe cardiac phenotype evidenced by higher serum cardiac biomarkers (median N-terminal pro-B-type natriuretic peptide [NT-proBNP]: 4027 ng/L [2173-6889] vs. 1851 ng/L [997-3209], p < 0.001; median troponin T: 69 ng/L [46-101] vs. 48 ng/L [34-68], p < 0.001) and worse echocardiographic indices of systolic (longitudinal strain: -10.0 ± 3.6% vs. -11.6 ± 3.8%, p < 0.001) and diastolic function (E/e': 17.5 ± 6.4 vs. 16.4 ± 6.7, p < 0.001) than those with a normal urinary albumin to creatinine ratio (UACR). Microalbuminuria and macroalbuminuria were independently associated with mortality in the overall population (hazard ratio [HR] 1.47, 95% confidence interval [CI] 1.13-1.92, p = 0.005 and HR 1.87, 95% CI 1.15-3.05, p = 0.012, respectively). In a subgroup of patients (n = 349) without concomitant hypertension, diabetes mellitus or chronic kidney disease, albuminuria was also associated with mortality (HR 2.98, 95% CI 1.72-5.17, p < 0.001). At 12 months, 330 patients had a repeat UACR measurement; those in whom UACR increased by 30% or more (n = 148, 44.8%) had an increased risk of mortality (HR 1.84, 95% CI 1.06-3.19, p = 0.030). CONCLUSIONS: Albuminuria is common in patients with ATTR-CA, and more prevalent in those with a more severe cardiac phenotype. Albuminuria at diagnosis and a significant increase in UACR during follow-up are associated with mortality.

Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?

Software is vital for the advancement of biology and medicine. Through analysis of usage and impact metrics of software, developers can help determine user and community engagement. These metrics can be used to justify additional funding, encourage additional use, and identify unanticipated use cases. Such analyses can help define improvement areas and assist with managing project resources. However, there are challenges associated with assessing usage and impact, many of which vary widely depending on the type of software being evaluated. These challenges involve issues of distorted, exaggerated, understated, or misleading metrics, as well as ethical and security concerns. More attention to the nuances, challenges, and considerations involved in capturing impact across the diverse spectrum of biological software is needed. Furthermore, some tools may be especially beneficial to a small audience, yet may not have comparatively compelling metrics of high usage. Although some principles are generally applicable, there is not a single perfect metric or approach to effectively evaluate a software tool's impact, as this depends on aspects unique to each tool, how it is used, and how one wishes to evaluate engagement. We propose more broadly applicable guidelines (such as infrastructure that supports the usage of software and the collection of metrics about usage), as well as strategies for various types of software and resources. We also highlight outstanding issues in the field regarding how communities measure or evaluate software impact. To gain a deeper understanding of the issues hindering software evaluations, as well as to determine what appears to be helpful, we performed a survey of participants involved with scientific software projects for the Informatics Technology for Cancer Research (ITCR) program funded by the National Cancer Institute (NCI). We also investigated software among this scientific community and others to assess how often infrastructure that supports such evaluations is implemented and how this impacts rates of papers describing usage of the software. We find that although developers recognize the utility of analyzing data related to the impact or usage of their software, they struggle to find the time or funding to support such analyses. We also find that infrastructure such as social media presence, more in-depth documentation, the presence of software health metrics, and clear information on how to contact developers seem to be associated with increased usage rates. Our findings can help scientific software developers make the most out of the evaluations of their software so that they can more fully benefit from such assessments.

Myocardial Perfusion Imaging After Severe COVID-19 Infection Demonstrates Regional Ischemia Rather Than Global Blood Flow Reduction.

Background: Acute myocardial damage is common in severe COVID-19. Post-mortem studies have implicated microvascular thrombosis, with cardiovascular magnetic resonance (CMR) demonstrating a high prevalence of myocardial infarction and myocarditis-like scar. The microcirculatory sequelae are incompletely characterized. Perfusion CMR can quantify the stress myocardial blood flow (MBF) and identify its association with infarction and myocarditis. Objectives: To determine the impact of the severe hospitalized COVID-19 on global and regional myocardial perfusion in recovered patients. Methods: A case-control study of previously hospitalized, troponin-positive COVID-19 patients was undertaken. The results were compared with a propensity-matched, pre-COVID chest pain cohort (referred for clinical CMR; angiography subsequently demonstrating unobstructed coronary arteries) and 27 healthy volunteers (HV). The analysis used visual assessment for the regional perfusion defects and AI-based segmentation to derive the global and regional stress and rest MBF. Results: Ninety recovered post-COVID patients {median age 64 [interquartile range (IQR) 54-71] years, 83% male, 44% requiring the intensive care unit (ICU)} underwent adenosine-stress perfusion CMR at a median of 61 (IQR 29-146) days post-discharge. The mean left ventricular ejection fraction (LVEF) was 67 ± 10%; 10 (11%) with impaired LVEF. Fifty patients (56%) had late gadolinium enhancement (LGE); 15 (17%) had infarct-pattern, 31 (34%) had non-ischemic, and 4 (4.4%) had mixed pattern LGE. Thirty-two patients (36%) had adenosine-induced regional perfusion defects, 26 out of 32 with at least one segment without prior infarction. The global stress MBF in post-COVID patients was similar to the age-, sex- and co-morbidities of the matched controls (2.53 ± 0.77 vs. 2.52 ± 0.79 ml/g/min, p = 0.10), though lower than HV (3.00 ± 0.76 ml/g/min, p< 0.01). Conclusions: After severe hospitalized COVID-19 infection, patients who attended clinical ischemia testing had little evidence of significant microvascular disease at 2 months post-discharge. The high prevalence of regional inducible ischemia and/or infarction (nearly 40%) may suggest that occult coronary disease is an important putative mechanism for troponin elevation in this cohort. This should be considered hypothesis-generating for future studies which combine ischemia and anatomical assessment.

Real-time deep artifact suppression using recurrent U-Nets for low-latency cardiac MRI.

PURPOSE: Real-time low latency MRI is performed to guide various cardiac interventions. Real-time acquisitions often require iterative image reconstruction strategies, which lead to long reconstruction times. In this study, we aim to reconstruct highly undersampled radial real-time data with low latency using deep learning. METHODS: A 2D U-Net with convolutional long short-term memory layers is proposed to exploit spatial and preceding temporal information to reconstruct highly accelerated tiny golden radial data with low latency. The network was trained using a dataset of breath-hold CINE data (including 770 time series from 7 different orientations). Synthetic paired data were created by retrospectively undersampling the magnitude images, and the network was trained to recover the target images. In the spirit of interventional imaging, the network was trained and tested for varying acceleration rates and orientations. Data were prospectively acquired and reconstructed in real time in 1 healthy subject interactively and in 3 patients who underwent catheterization. Images were visually compared to sliding window and compressed sensing reconstructions and a conventional Cartesian real-time sequence. RESULTS: The proposed network generalized well to different acceleration rates and unseen orientations for all considered metrics in simulated data (less than 4% reduction in structural similarity index compared to similar acceleration and orientation-specific networks). The proposed reconstruction was demonstrated interactively, successfully depicting catheters in vivo with low latency (39 ms, including 19 ms for deep artifact suppression) and an image quality comparing favorably to other reconstructions. CONCLUSION: Deep artifact suppression was successfully demonstrated in the time-critical application of non-Cartesian real-time interventional cardiac MR.

A simple echocardiographic score to rule out cardiac amyloidosis.

BACKGROUND: Early diagnosis of cardiac amyloidosis (CA) is warranted to initiate specific treatment and improve outcome. The amyloid light chain (AL) and inferior wall thickness (IWT) scores have been proposed to assess patients referred by haematologists or with unexplained left ventricular (LV) hypertrophy, respectively. These scores are composed of 4 or 5 variables, respectively, including strain data. METHODS: Based on 2 variables common to the AL and IWT scores, we defined a simple score named AMYLoidosis Index (AMYLI) as the product of relative wall thickness (RWT) and E/e' ratio, and assessed its diagnostic performance. RESULTS: In the original cohort (n = 251), CA was ultimately diagnosed in 111 patients (44%). The 2.22 value was selected as rule-out cut-off (negative likelihood ratio [LR-] 0.0). In the haematology subset, AL CA was diagnosed in 32 patients (48%), with 2.36 as rule-out cut-off (LR- 0.0). In the hypertrophy subset, ATTR CA was diagnosed in 79 patients (43%), with 2.22 as the best rule-out cut-off (LR- 0.0). In the validation cohort (n = 691), the same cut-offs proved effective: indeed, there were no patients with CA in the whole population or in the haematology or hypertrophy subsets scoring < 2.22, <2.36 or < 2.22, respectively. CONCLUSIONS: The AMYLI score (RWT*E/e') may have a role as an initial screening tool for CA. A < 2.22 value excludes the diagnosis in patients undergoing a diagnostic screening for CA, while a < 2.36 and a < 2.22 value may be better considered in the subsets with suspected cardiac AL amyloidosis or unexplained hypertrophy, respectively.

An unusual cause of polymorphic ventricular tachycardia: Acquired long QT syndrome from atypical variant of stress-induced cardiomyopathy.

A 55-year-old woman with a recent history of surgically and radioiodine treated thyroid cancer experienced a run of polymorphic ventricular tachycardia with hemodynamic perturbation during anaesthetic induction with propofol, fentanyl and rocuronium for elective surgical excision of right hip metastasis. Electrocardiography showed new T-wave inversion and QT prolongation that subsequently resolved. Cardiac enzymes were elevated but invasive coronary angiography showed unobstructed epicardial coronary arteries. Cardiovascular magnetic resonance showed not only normal biventricular size and systolic function but also a striking pattern of patchy myocardial oedema involving the basal-to-mid anterior, septal and inferior walls and some associated hypertrophy in the anteroseptum (representing focal myocardial swelling from the oedema) but no focal or diffuse myocardial fibrosis. All these abnormalities resolved on subsequent convalescent imaging. A diagnosis of multifactorial acquired long QT syndrome secondary to atypical variant stress-induced cardiomyopathy was made with the likely provoking factors in this case having been the female sex, understandable pre-operative anxiety, anaesthetic drugs, supraglottic airway placement and thyroid dysfunction. An implantable loop recorder during follow-up detected no further significant arrhythmias and she remains well and asymptomatic to date on a low dose of beta-blocker.

Diagnosis and assessment of dilated cardiomyopathy: a guideline protocol from the British Society of Echocardiography.

Heart failure (HF) is a debilitating and life-threatening condition, with 5-year survival rate lower than breast or prostate cancer. It is the leading cause of hospital admission in over 65s, and these admissions are projected to rise by more than 50% over the next 25 years. Transthoracic echocardiography (TTE) is the first-line step in diagnosis in acute and chronic HF and provides immediate information on chamber volumes, ventricular systolic and diastolic function, wall thickness, valve function and the presence of pericardial effusion, while contributing to information on aetiology. Dilated cardiomyopathy (DCM) is the third most common cause of HF and is the most common cardiomyopathy. It is defined by the presence of left ventricular dilatation and left ventricular systolic dysfunction in the absence of abnormal loading conditions (hypertension and valve disease) or coronary artery disease sufficient to cause global systolic impairment. This document provides a practical approach to diagnosis and assessment of dilated cardiomyopathy that is aimed at the practising sonographer.

Implementation of a patient perception survey in a pharmacist-managed primary care clinic and analysis with a unique HFMEA method.

OBJECTIVES: To develop and implement a patient-based pilot survey that measures patient perceptions regarding the quality of education given to them by clinical pharmacists in primary care clinics and to incorporate a unique method for analyzing the survey data. METHODS: The survey addressed 12 components of education within three categories: medication-related education, disease-related education, and delivery of education provided. The 12 components were repeated in two sections of the survey. Section 1 assessed patients' perceptions of pharmacist performance in each component, while section 2 measured patients' perceptions regarding the importance of each component of education. Results were analyzed with standard statistical techniques and an adaptation of the health care failure mode and effect analysis (HFMEA) process to identify areas of improvement that patients value most. RESULTS: The survey was successfully developed and implemented, and results were analyzed with the HFMEA tool. A total of 60 patients completed surveys, with 75% (45 of 60) scoring an overall rating of excellent. Initial results from the HFMEA identified no areas of improvement. A secondary analysis was used to identify five areas for improvement, including (1) discussing adverse effects of medications, (2) discussing resources available, (3) providing benefits of treating medical problems, (4) answering questions completely, and (5) discussing goals of treatment. CONCLUSION: A survey focused on pharmacist-driven education with primary care patients was successfully developed and implemented. The unique HFMEA tool implemented provided a means of prioritizing results for future quality improvements.

Pharmacist screening for depression among patients with diabetes in an urban primary care setting.

OBJECTIVES: To identify possible undiagnosed and undertreated depression in patients with diabetes in an urban primary care setting using screening by a student pharmacist, to develop a better understanding of the influence of comorbid depression on diabetes control, and to identify predictors of increased risk for comorbid depression. METHODS: Patients from an underserved, low-income, inner-city setting who were receiving primary follow-up diabetes care at five Cincinnati Health Department clinics were evaluated for depression using the Zung Self-rating Depression Scale (SDS). A student pharmacist questioned patients on their medical history and documented the information. After the appointment, the student pharmacist also gathered information from patient medical charts, including patient characteristics, age, social history, pertinent laboratory results (glycosylated hemoglobin [A1C], fasting blood glucose, lipid panel information), and documented comorbidities. A positive screen for depression was defined as an SDS score of 50 or more, and the result of the screening was documented as a clinical note in the patient's medical chart. Based on SDS scores, severity of depressive symptoms was categorized as mild (50-59), moderate (60-69), or severe (> or = 70). RESULTS: 45 patients (2 with type 1 diabetes and 43 with type 2 diabetes, 41 aged > 40 years, 35 black, 31 women, and 31 uninsured) were enrolled in the study. Based on the data collected and SDS results, 12 patients (27%) had a current diagnosis of depression from their primary care physician. For this group of 12, the SDS acted as a quality-assurance tool, identifying 3 patients (25%) as adequately treated (SDS scores < 50), 6 (50%) as undertreated (SDS scores > or = 50 with pharmacologic and/or nonpharmacologic therapy), and 3 (25%) as not treated at all (SDS scores > or = 50 without pharmacologic or nonpharmacologic therapy). Of the 33 patients (73%) without a current diagnosis of depression, 16 (48%) screened positive for depression and 17 were not depressed (52%). No significant differences were observed between nondepressed and depressed participants in mean A1C or fasting blood glucose. CONCLUSION: Poorly controlled depression in patients with diabetes can be identified by pharmacists in the primary care setting via use of a brief screening tool such as the SDS.