Housing and Community Partner Views on the Benefits of Housing with Services: The Right Care, Right Place, Right Time Program.

BACKGROUND AND OBJECTIVES: Older adult-focused housing with services programs seek to improve access to supportive services, particularly among individuals residing in subsidized housing. The Right Care, Right Place, Right Time (R3) program comprises two on-site wellness teams responsible for 400 participants across seven housing sites in Greater Boston. These embedded teams work directly with residents to address health-related needs and access to services. This study reports on the perceived benefits of participating in the R3 program from the perspective of housing staff and community partners. RESEARCH DESIGN AND METHODS: Data were derived from 24 semi-structured interviews conducted as part of a program evaluation. Participants described resident, housing, and system-related reasons for deciding to participate in the R3 program and experiences of their participation. RESULTS: In addition to positive overall assessments, housing partner interviewees reported concrete and psychosocial benefits for housing residents (e.g., connecting with resources, enabling longer stays, empowering residents, alleviating distress) and staffing and resident-related benefits. Community partners perceived more appropriate utilization of services by residents (e.g., reducing emergency transports). DISCUSSION AND IMPLICATIONS: Findings elucidate why housing and community partners might be motivated to integrate housing, health, and supportive care to affordable housing for older adults using a wellness team.

The Updated Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT 2.0).

The Registry of Fast Myocardial Perfusion Imaging with Next-Generation SPECT (REFINE SPECT) has been expanded to include more patients and CT attenuation correction imaging. We present the design and initial results from the updated registry. Methods: The updated REFINE SPECT is a multicenter, international registry with clinical data and image files. SPECT images were processed by quantitative software and CT images by deep learning software detecting coronary artery calcium (CAC). Patients were followed for major adverse cardiovascular events (MACEs) (death, myocardial infarction, unstable angina, late revascularization). Results: The registry included scans from 45,252 patients from 13 centers (55.9% male, 64.7 ± 11.8 y). Correlating invasive coronary angiography was available for 3,786 (8.4%) patients. CT attenuation correction imaging was available for 13,405 patients. MACEs occurred in 6,514 (14.4%) patients during a median follow-up of 3.6 y (interquartile range, 2.5-4.8 y). Patients with a stress total perfusion deficit of 5% to less than 10% (unadjusted hazard ratio [HR], 2.42; 95% CI, 2.23-2.62) and a stress total perfusion deficit of at least 10% (unadjusted HR, 3.85; 95% CI, 3.56-4.16) were more likely to experience MACEs. Patients with a deep learning CAC score of 101-400 (unadjusted HR, 3.09; 95% CI, 2.57-3.72) and a CAC of more than 400 (unadjusted HR, 5.17; 95% CI, 4.41-6.05) were at increased risk of MACEs. Conclusion: The REFINE SPECT registry contains a comprehensive set of imaging and clinical variables. It will aid in understanding the value of SPECT myocardial perfusion imaging, leverage hybrid imaging, and facilitate validation of new artificial intelligence tools for improving prediction of adverse outcomes incorporating multimodality imaging.

In vivo Antibody Painting for Next Generation Weight Loss Drugs.

Peptide-based therapeutics are currently in great demand but often suffer from rapid clearance and accumulation in off-target tissues which continue to present barriers in their clinical translation. Here, we developed an electrophilic peptide for the attachment of therapeutics to native immunoglobulin (IgG) in vivo, enabling the bioorthogonal covalent linkage, or 'painting', of peptide drugs of choice to circulating IgGs directly in live animals. Native IgG painting with glucagon-like peptide-1 (GLP-1) results in sustained body weight loss and prolonged blood glucose management after one dose. Such technology might revolutionize the next generation of long-acting peptide-based medicines.

Tracking the pre-clinical progression of transthyretin amyloid cardiomyopathy using artificial intelligence-enabled electrocardiography and echocardiography.

Background and Aims: Diagnosing transthyretin amyloid cardiomyopathy (ATTR-CM) requires advanced imaging, precluding large-scale testing for pre-clinical disease. We examined the application of artificial intelligence (AI) to echocardiography (TTE) and electrocardiography (ECG) as a scalable strategy to quantify pre-clinical trends in ATTR-CM. Methods: Across age/sex-matched case-control datasets in the Yale-New Haven Health System (YNHHS) we trained deep learning models to identify ATTR-CM-specific signatures on TTE videos and ECG images (area under the curve of 0.93 and 0.91, respectively). We deployed these across all studies of individuals referred for cardiac nuclear amyloid imaging in an independent population at YNHHS and an external population from the Houston Methodist Hospitals (HMH) to define longitudinal trends in AI-defined probabilities for ATTR-CM using age/sex-adjusted linear mixed models, and describe discrimination metrics during the early pre-clinical stage. Results: Among 984 participants referred for cardiac nuclear amyloid imaging at YNHHS (median age 74 years, 44.3% female) and 806 at HMH (69 years, 34.5% female), 112 (11.4%) and 174 (21.6%) tested positive for ATTR-CM, respectively. Across both cohorts and modalities, AI-defined ATTR-CM probabilities derived from 7,423 TTEs and 32,205 ECGs showed significantly faster progression rates in the years before clinical diagnosis in cases versus controls (p time × group interaction ≤0.004). In the one-to-three-year window before cardiac nuclear amyloid imaging sensitivity/specificity metrics were estimated at 86.2%/44.2% [YNHHS] vs 65.7%/65.5% [HMH] for AI-Echo, and 89.8%/40.6% [YNHHS] vs 88.5%/35.1% [HMH] for AI-ECG. Conclusions: We demonstrate that AI tools for echocardiographic videos and ECG images can enable scalable identification of pre-clinical ATTR-CM, flagging individuals who may benefit from risk-modifying therapies.

AI-based volumetric six-tissue body composition quantification from CT cardiac attenuation scans enhances mortality prediction: multicenter study.

Background: Computed tomography attenuation correction (CTAC) scans are routinely obtained during cardiac perfusion imaging, but currently only utilized for attenuation correction and visual calcium estimation. We aimed to develop a novel artificial intelligence (AI)-based approach to obtain volumetric measurements of chest body composition from CTAC scans and evaluate these measures for all-cause mortality (ACM) risk stratification. Methods: We applied AI-based segmentation and image-processing techniques on CTAC scans from a large international image-based registry (four sites), to define chest rib cage and multiple tissues. Volumetric measures of bone, skeletal muscle (SM), subcutaneous, intramuscular (IMAT), visceral (VAT), and epicardial (EAT) adipose tissues were quantified between automatically-identified T5 and T11 vertebrae. The independent prognostic value of volumetric attenuation, and indexed volumes were evaluated for predicting ACM, adjusting for established risk factors and 18 other body compositions measures via Cox regression models and Kaplan-Meier curves. Findings: End-to-end processing time was <2 minutes/scan with no user interaction. Of 9918 patients studied, 5451(55%) were male. During median 2.5 years follow-up, 610 (6.2%) patients died. High VAT, EAT and IMAT attenuation were associated with increased ACM risk (adjusted hazard ratio (HR) [95% confidence interval] for VAT: 2.39 [1.92, 2.96], p<0.0001; EAT: 1.55 [1.26, 1.90], p<0.0001; IMAT: 1.30 [1.06, 1.60], p=0.0124). Patients with high bone attenuation were at lower risk of death as compared to subjects with lower bone attenuation (adjusted HR 0.77 [0.62, 0.95], p=0.0159). Likewise, high SM volume index was associated with a lower risk of death (adjusted HR 0.56 [0.44, 0.71], p<0.0001). Interpretations: CTAC scans obtained routinely during cardiac perfusion imaging contain important volumetric body composition biomarkers which can be automatically measured and offer important additional prognostic value.

Evaluating Ischemic Heart Disease in Women: Focus on Angina With Nonobstructive Coronary Arteries (ANOCA).

Ischemic heart disease (IHD) is common in women, and cardiovascular disease is a leading cause of morbidity and mortality. While obstructive coronary artery disease is the most common form of IHD, millions of women suffer from angina with nonobstructive coronary arteries (ANOCA), an umbrella term encompassing multiple nonatherosclerotic disorders of the coronary tree. The underlying pathology leading to ischemia in these syndromes may be challenging to diagnose, leaving many women without a diagnosis despite persistent symptoms that impact quality of life and adversely affect long-term cardiovascular prognosis. In the last decade, there have been significant advances in the recognition and diagnostic evaluation of ANOCA. Despite these advances, the standard approach to evaluating suspected IHD in women continues to focus predominantly on the assessment of atherosclerotic coronary artery disease, leading to missed opportunities to accurately diagnose and treat underlying coronary vasomotor disorders. The goal of this review is to describe advances in diagnostic testing that can be used to evaluate angina in women and present a pragmatic diagnostic algorithm to guide evaluation of ANOCA in symptomatic patients. The proposed approach for the assessment of ANOCA is consistent with prior expert consensus documents and guidelines but is predicated on the medical interview and pretest probability of disease to inform a personalized diagnostic strategy.

Unpredictable Cyclosporine Clearance in a Korean Patient With Aplastic Anemia With Adverse Effects: A Case Study.

ABSTRACT: A 29-year-old Korean woman with chronic aplastic anemia presented with seizures due to cyclosporine-induced posterior reversible encephalopathy syndrome, caused by unpredictable oral cyclosporine (CS) accumulation and prolonged elimination. This case demonstrates the need to monitor CS drug levels with careful dose adjustments.

Behind the curtain of Australasian Psychiatry: The practice of a medical journal and a call for reviewers.

The process of medical scientific journal publishing merits further explanation for authors and readers. Prospective authors need to understand the scope of the journal and the article types that are published. We give an overview of the editorial process, including selection of reviewers, peer review and decisions regarding revision, acceptance and rejection of papers for Australasian Psychiatry. We encourage authors and readers to submit papers, and volunteer as peer reviewers, working together with the journal editorial team.

From transthyretin cardiac amyloidosis diagnosis to tafamidis treatment: Association of drop-off with patient sociodemographic characteristics.

DISCLAIMER: In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. PURPOSE: Compared to estimated population prevalence rates, relatively few patients at risk are diagnosed with and treated for transthyretin cardiac amyloidosis (ATTR-CA). Where along the clinical pathway patient drop-off occurs, as well as the association of drop-off with patient sociodemographic characteristics, remains unknown. METHODS: Using data from a healthcare system-wide cardiovascular imaging repository and specialty pharmacy, we characterized the clinical pathway from diagnosis with pyrophosphate scintigraphy (PYP) to tafamidis prescription, initiation, and adherence. Standardized differences (d values of ≥0.20, indicating at least a small effect size) were used to compare sociodemographics (age, sex, race, Area Deprivation Index) among patients with PYP-identified ATTR-CA by tafamidis prescription status and among patients prescribed tafamidis by initiation status. Tafamidis adherence was measured with the proportion of days covered (PDC). RESULTS: Of 97 patients with ATTR-CA, 58.8% were prescribed tafamidis, with 80.7% of those initiating therapy. Patients with ATTR-CA prescribed tafamidis were younger than those not prescribed tafamidis (d = -0.30). Utilization of a specialty pharmacy resulted in enrichment of treatment in subgroups traditionally undertreated in cardiovascular medicine, with higher rates of tafamidis initiation among women (100% initiation), patients of Black/African American race (d = 0.40), and those living in more economically disadvantaged areas (d ≥ 0.30). Adherence was high (PDC of >80%) in 88.4% of those initiating tafamidis. CONCLUSION: These findings highlight the tremendous opportunity for more robust ATTR-CA clinical programs, identifying potential patient subgroups that should be targeted to reduce disparities. For patients diagnosed with ATTR-CA, utilization of a specialty pharmacy process appears to ensure equitable provision of tafamidis therapy.

TAI-GAN: A Temporally and Anatomically Informed Generative Adversarial Network for early-to-late frame conversion in dynamic cardiac PET inter-frame motion correction.

Inter-frame motion in dynamic cardiac positron emission tomography (PET) using rubidium-82 (82Rb) myocardial perfusion imaging impacts myocardial blood flow (MBF) quantification and the diagnosis accuracy of coronary artery diseases. However, the high cross-frame distribution variation due to rapid tracer kinetics poses a considerable challenge for inter-frame motion correction, especially for early frames where intensity-based image registration techniques often fail. To address this issue, we propose a novel method called Temporally and Anatomically Informed Generative Adversarial Network (TAI-GAN) that utilizes an all-to-one mapping to convert early frames into those with tracer distribution similar to the last reference frame. The TAI-GAN consists of a feature-wise linear modulation layer that encodes channel-wise parameters generated from temporal information and rough cardiac segmentation masks with local shifts that serve as anatomical information. Our proposed method was evaluated on a clinical 82Rb PET dataset, and the results show that our TAI-GAN can produce converted early frames with high image quality, comparable to the real reference frames. After TAI-GAN conversion, the motion estimation accuracy and subsequent myocardial blood flow (MBF) quantification with both conventional and deep learning-based motion correction methods were improved compared to using the original frames. The code is available at https://github.com/gxq1998/TAI-GAN.

Real-world evaluation of an algorithmic machine-learning-guided testing approach in stable chest pain: a multinational, multicohort study.

Aims: An algorithmic strategy for anatomical vs. functional testing in suspected coronary artery disease (CAD) (Anatomical vs. Stress teSting decIsion Support Tool; ASSIST) is associated with better outcomes than random selection. However, in the real world, this decision is rarely random. We explored the agreement between a provider-driven vs. simulated algorithmic approach to cardiac testing and its association with outcomes across multinational cohorts. Methods and results: In two cohorts of functional vs. anatomical testing in a US hospital health system [Yale; 2013-2023; n = 130 196 (97.0%) vs. n = 4020 (3.0%), respectively], and the UK Biobank [n = 3320 (85.1%) vs. n = 581 (14.9%), respectively], we examined outcomes stratified by agreement between the real-world and ASSIST-recommended strategies. Younger age, female sex, Black race, and diabetes history were independently associated with lower odds of ASSIST-aligned testing. Over a median of 4.9 (interquartile range [IQR]: 2.4-7.1) and 5.4 (IQR: 2.6-8.8) years, referral to the ASSIST-recommended strategy was associated with a lower risk of acute myocardial infarction or death (hazard ratioadjusted: 0.81, 95% confidence interval [CI] 0.77-0.85, P < 0.001 and 0.74 [95% CI 0.60-0.90], P = 0.003, respectively), an effect that remained significant across years, test types, and risk profiles. In post hoc analyses of anatomical-first testing in the Prospective Multicentre Imaging Study for Evaluation of Chest Pain (PROMISE) trial, alignment with ASSIST was independently associated with a 17% and 30% higher risk of detecting CAD in any vessel or the left main artery/proximal left anterior descending coronary artery, respectively. Conclusion: In cohorts where historical practices largely favour functional testing, alignment with an algorithmic approach to cardiac testing defined by ASSIST was associated with a lower risk of adverse outcomes. This highlights the potential utility of a data-driven approach in the diagnostic management of CAD.

Unlocking Diversity in Cardiovascular Clinical Research: Lessons from the Screening for Cardiac Amyloidosis With Nuclear Imaging in a Minority Populations Study.

BACKGROUND: The Screening for Cardiac Amyloidosis with Nuclear Imaging in Minority Populations study seeks to determine the prevalence of transthyretin cardiac amyloidosis (ATTR-CA) among older Black or Caribbean Hispanic individuals with heart failure and an increased wall thickness. We noticed varied recruitment percentages across the recruiting sites and sought to determine the factors associated with greater percentage enrollment of eligible participants. METHODS: The percentage of enrolled to eligible participants was calculated across study sites. Baseline demographic and clinical characteristics, health literacy, trust in providers, perceived discrimination, area deprivation index (ADI) and English proficiency were compared by site using Kruskal-Wallis's test or one-way ANOVA for continuous variables and the Chi-Square test or Fisher's exact test for categorical variables. Wilcoxon rank sum and Chi-Square tests, with multiple comparisons correction using the false discovery rate (FDR) method, were used as post-hoc analysis when results were statistically significant. RESULTS: Among the four recruiting sites, Boston Medical Center, Columbia University Irving Medical Center, Harlem Hospital and Yale University, which employed different recruitment approaches, the percentage of participants enrolled among eligible participants differed, with the highest rate at Harlem Hospital (n=149 of 310, 48%), followed by Yale University (n=27 of 67, 40%), Boston University (n=247 of 655, 38%), and Columbia University (n=137of 442, 32%), p <0.01. Direct recruitment by the primary cardiovascular care team providing clinical care was associated with higher percent enrolled across sites as were higher education levels and English proficiency. Enrollment differences across sites were not associated with the number of chronic diseases, physician trust, perceived discrimination, or health literacy. CONCLUSIONS: Recruitment of eligible under-represented minorities (URMs) in SCAN-MP was associated with approaches employed in recruitment, including direct initial contact by the primary cardiovascular care team providing the potential participant's clinical care. Such data may help improve approaches to more successful recruitment of URMs in clinical research.

Links Between Obstructive Sleep Apnea and Myocardial Blood Flow Changes Impacting Adverse Cardiovascular Disease-related Outcomes.

PURPOSE OF REVIEW: Recent studies have demonstrated an association between obstructive sleep apnea (OSA) and abnormal myocardial blood flow (MBF), myocardial flow reserve (MFR), and coronary microvascular dysfunction (CMD). Here, we review the evidence and describe the potential underlying mechanisms linking OSA to abnormal MBF. Examining relevant studies, we assess the impact of OSA-specific therapy, such as continuous positive airway pressure (CPAP), on MBF. RECENT FINDINGS: Recent studies suggest an association between moderate to severe OSA and abnormal MBF/MFR. OSA promotes functional and structural abnormalities of the coronary microcirculation. OSA also promotes the uncoupling of MBF to cardiac work. In a handful of studies with small sample sizes, CPAP therapy improved MBF/MFR. Moderate to severe OSA is associated with abnormal MFR, suggesting an association with CMD. Evidence suggests that CPAP therapy improves MBF. Future studies must determine the clinical impact of improved MBF with CPAP.

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.

Background: While low-dose computed tomography scans are traditionally used for attenuation correction in hybrid myocardial perfusion imaging (MPI), they also contain additional anatomic and pathologic information not utilized in clinical assessment. We seek to uncover the full potential of these scans utilizing a holistic artificial intelligence (AI)-driven image framework for image assessment. Methods: Patients with SPECT/CT MPI from 4 REFINE SPECT registry sites were studied. A multi-structure model segmented 33 structures and quantified 15 radiomics features for each on CT attenuation correction (CTAC) scans. Coronary artery calcium and epicardial adipose tissue scores were obtained from separate deep-learning models. Normal standard quantitative MPI features were derived by clinical software. Extreme Gradient Boosting derived all-cause mortality risk scores from SPECT, CT, stress test, and clinical features utilizing a 10-fold cross-validation regimen to separate training from testing data. The performance of the models for the prediction of all-cause mortality was evaluated using area under the receiver-operating characteristic curves (AUCs). Results: Of 10,480 patients, 5,745 (54.8%) were male, and median age was 65 (interquartile range [IQR] 57-73) years. During the median follow-up of 2.9 years (1.6-4.0), 651 (6.2%) patients died. The AUC for mortality prediction of the model (combining CTAC, MPI, and clinical data) was 0.80 (95% confidence interval [0.74-0.87]), which was higher than that of an AI CTAC model (0.78 [0.71-0.85]), and AI hybrid model (0.79 [0.72-0.86]) incorporating CTAC and MPI data (p<0.001 for all). Conclusion: In patients with normal perfusion, the comprehensive model (0.76 [0.65-0.86]) had significantly better performance than the AI CTAC (0.72 [0.61-0.83]) and AI hybrid (0.73 [0.62-0.84]) models (p<0.001, for all).CTAC significantly enhances AI risk stratification with MPI SPECT/CT beyond its primary role - attenuation correction. A comprehensive multimodality approach can significantly improve mortality prediction compared to MPI information alone in patients undergoing cardiac SPECT/CT.