Shady Abohashem

Background: Cardiovascular disease (CVD) remains the leading cause of morbidity and death worldwide. Risk scores such as the pooled cohort equations often underpredict risk in individuals with low socioeconomic status. Methods: We used the Centers for Disease Control and Prevention Population Level Analysis and Community Estimates data set to obtain zip code–level prevalence of hypertension, obesity, stroke, diabetes, and coronary artery disease. The Distressed Communities Index (DCI) collates community socioeconomic status and social determinants/drivers of health metrics into a numerical score. Linear regression adjusted for region and rurality assessed associations between DCI and CVD prevalence. Results: We included 26 058 US zip codes (2016–2020). The median DCI was 50.9 (interquartile range, 25.4–75.9). Each 1‐unit increase in DCI was associated with increased prevalence of obesity (β=0.10 [95% CI, 0.09–0.10]), hypertension (β=0.08 [95% CI, 0.08–0.09]), diabetes (β=0.06 [95% CI, 0.06–0.06]), coronary artery disease (β=0.03 [95% CI, 0.03–0.03]), and stroke (β=0.02 [95% CI, 0.02–0.02]; all P <0.001). Rurality and region were independently associated with CVD and risk factor prevalence, with rural and southern zip codes having the highest prevalence. Conclusions: DCI, geographic region, and rurality are independently associated with greater prevalence of CVD and its risk factors in the United States. The DCI is a practical, scalable surrogate for socioeconomic status and social determinants/drivers of health that may enhance CVD risk stratification on the basis of an area's economic resilience or disadvantage. Using DCI with the Preventing Cardiovascular Events score may capture economic and social challenges it omits, warranting further study.

BACKGROUND: Recent advances in artificial intelligence enable fully automated 3-dimensional computed tomography (CT)-based body composition quantification. We investigated whether automated CT-derived thoraco-abdominopelvic body composition measures are associated with mortality after transcatheter aortic valve replacement. METHODS: In this retrospective multicenter study, consecutive patients undergoing transcatheter aortic valve replacement with preprocedural CT imaging were included between 2014 and 2023. A deep learning-based pipeline performed automated 3-dimensional segmentation of thoraco-abdominopelvic noncontrast CT scans to quantify volumes (L/m ² ) and attenuations (Hounsfield units) of subcutaneous adipose tissue, visceral adipose tissue, muscular adipose tissue, and lean skeletal muscle, indexed to body surface area. Associations with mortality were evaluated using Cox models and Harrell C statistics, adjusting for demographics (age, sex, body mass index) and cardiometabolic risk factors (hypertension, diabetes, chronic renal failure). RESULTS: Among 915 patients (median age, 84 years [interquartile range, 77–90]; 58% men), 160 (17.5%) died over a median follow-up of 22 months (interquartile range, 14–36). Restricted cubic spline analyses demonstrated that lower subcutaneous adipose tissue volume and higher adipose tissue attenuation were associated with increased mortality, whereas higher skeletal muscle volume and attenuation were associated with improved survival. Addition of body composition measures provided incremental discriminatory value beyond demographics and cardiometabolic risk factors (Harrell C, 0.66 versus 0.71; P <0.001). CONCLUSIONS: Automated 3-dimensional CT-derived body composition measures provide independent prognostic information and improve risk stratification for mortality after transcatheter aortic valve replacement. Low subcutaneous adipose tissue volume and higher adipose tissue attenuation identify patients at increased risk, whereas higher skeletal muscle volume and attenuation are associated with lower mortality.

Background and Aims: Socioeconomic and psychosocial factors (SPFs) are increasingly recognized as relevant to cardiovascular health. Their associations with length of stay, treatment use, and other diagnoses/outcomes in heart failure (HF) hospitalizations remain insufficiently studied. Methods: We analysed nationwide mandatory Diagnosis Related Groups (DRG) data from 6 601 082 HF hospitalizations of patients who were discharged alive in Germany 2005–2022. Hospitalizations were stratified according to coded SPFs and compared regarding clinical characteristics, length of stay, treatment use, and diagnoses recorded during hospitalization. The primary outcome was prolonged hospital stay (>10 days), and treatment use and diagnoses recorded during hospitalization were additional outcomes. Results: Of 6 601 082 HF hospitalizations, 49 565 (0.8%) had at least one coded SPF. These hospitalizations involved older patients, a higher proportion of women, and a greater comorbidity burden. In the fully adjusted model, coded SPFs were associated with prolonged hospital stay (>10 days; OR 1.59, 95% CI 1.56–1.62; P < .001), deep venous thrombosis and/or thrombophlebitis (OR 1.39, 95% CI 1.28–1.52; P < .001), pulmonary embolism (OR 1.18, 95% CI 1.02–1.37; P = .026), and stroke (OR 1.35, 95% CI 1.19–1.53; P < .001). No associations were observed for myocardial infarction (OR 1.05, 95% CI 0.99–1.12; P = .138) or pneumonia (OR 1.03, 95% CI 1.00–1.06; P = .084). Coded SPFs were also associated with lower odds of PCI use (OR 0.85, 95% CI 0.80–0.90; P < .001) and LVAD implantation (OR 0.23, 95% CI 0.11–0.49; P < .001). Conclusions: Among HF hospitalizations ending in live discharge, coded SPFs were associated with longer stays, lower use of selected therapies, and higher odds of selected diagnoses recorded during hospitalization. SPFs were markedly underrepresented in the German nationwide inpatient data.

Accurate cardiovascular risk assessment is essential in type 1 diabetes (T1D), but agreement between disease-specific prediction models remains insufficiently characterized. This retrospective, single-center, cross-sectional study compared 10-year cardiovascular risk estimates from the Steno Type 1 Risk Engine (ST1RE) and the Scottish/Swedish risk prediction model in 100 adults aged 20–35 years with T1D and no previous atherosclerotic cardiovascular disease or major cardiovascular event. Continuous and categorical agreement were assessed using Bland–Altman analysis and linearly weighted Cohen’s κ, respectively, with identical thresholds applied for risk classification. Risk estimates were strongly correlated (Spearman’s ρ = 0.849, p < 0.001), with no significant paired difference on the Wilcoxon signed-rank test (p = 0.893). However, categorical agreement was fair, with a weighted κ of 0.334 and a 95% confidence interval (CI) of 0.078–0.590. The mean difference (ST1RE − Scottish/Swedish) was −1.46 percentage points (95% CI: −2.48 to −0.44), with 95% limits of agreement from −11.54 to 8.62 percentage points. Significant proportional bias indicated progressively higher Scottish/Swedish estimates as mean predicted risk increased (β = 0.91, p < 0.001). Despite strong correlation, individual-level discrepancies and proportional bias suggest limited interchangeability of these models in this cohort. Larger prospective studies assessing cardiovascular outcomes are needed to establish their comparative predictive accuracy and clinical utility.

Despite suppressive antiretroviral therapy (ART), people with HIV (PWH) remain at increased risk of cardiovascular disease (CVD), likely driven, at least in part, by persistent immune activation and vascular inflammation. Mechanistic pathways may include ongoing low-level HIV transcription within immune cells, particularly peripheral blood mononuclear cells (PBMCs), which may contribute to chronic inflammatory signaling. Persistent viral transcription and inflammatory signaling may also be associated with an interferon-responsive cellular environment conducive to APOBEC3 activation and mutational editing of viral transcripts. APOBEC3 enzymes, which are interferon (IFN)-inducible cytidine deaminases, generate characteristic premature stop codons (PSCs) within retroviral genomes and may reflect interferon-associated inflammatory states relevant to vascular pathology. We investigated whether APOBEC3-associated PSC signatures and reservoir-associated drug resistance mutations (RA-DRMs) in viral reservoirs, as markers of persistent reservoir transcriptional activity, are associated with vascular inflammation in ART-suppressed individuals. PBMCs from ART-suppressed PWH (n=36) were analyzed for long HIV-1 gag/pol transcripts (>4.2 kb) and PSCs as a surrogate marker of APOBEC3 activity, with RA-DRMs assessed by Oxford Nanopore sequencing. Arterial inflammation was quantified using PET imaging of the aorta and carotid arteries. Additionally, an exploratory panel of >60 cardiometabolic, clinical, and inflammatory biomarkers was profiled to identify host immune signatures associated with reservoir PSC burden, with focused analyses on circulating inflammatory biomarkers sCD14, sCD163, and IP-10. Long HIV-1 transcripts were detected in 67% (24/36) despite ART. Higher PSC frequency within these transcripts was significantly associated with increased aortic inflammation, but not carotid inflammation, in univariable analysis (β = 0.00834, p = 0.013). RA-DRMs were detected in 50% (12/24), including triple-class resistance, but were not associated with vascular inflammation or soluble biomarkers. In multivariable models, PSCs remained independently associated with aortic inflammation after adjustment for sCD14 and sCD163 (β = 0.0075, p = 0.023), and remained the only significant predictor when IP-10 was included (β = 0.0073, p = 0.036). These findings suggest that APOBEC3-associated PSC signatures in long HIV transcripts identify transcriptionally active HIV reservoir states associated with aortic inflammation during suppressive ART. Rather than reflecting ongoing mutational accumulation or direct pathogenic effects of PSCs themselves, these signatures may serve as biomarkers of an interferon-associated inflammatory reservoir state related to cardiovascular risk. Graphical Highlights: Interferon-inducible APOBEC3-associated PSC signatures in HIV reservoirs and vascular inflammation: APOBEC3-associated premature stop codon (PSC) signatures were identified in transcriptionally active HIV reservoir-derived RNA despite suppressive ART. Higher PSC burden was significantly associated with increased aortic vascular inflammation measured by FDG-PET. Reservoir-associated drug resistance mutations (RA-DRMs) showed no association with arterial inflammation. PSC burden remained independently associated with aortic vascular inflammation in multivariable analyses. PSC-enriched reservoir states were associated with inflammatory biomarker patterns consistent with monocyte–macrophage activation and vascular immune activation. These findings are consistent with an interferon-inducible APOBEC3-edited reservoir state associated with persistent arterial inflammation during suppressive ART. APOBEC3-associated mutational signatures may represent a candidate biomarker of vascular inflammation and cardiovascular risk in people with HIV.

Aims: Glucagon-like peptide-1 receptor agonists (GLP-1 RAs) are widely used for type 2 diabetes and obesity and produce significant weight loss. However, concerns have emerged about potential loss of skeletal muscle mass (SMM) with pharmacologic weight reduction, particularly in older adults at risk for sarcopaenia. The effects of GLP-1 RA therapy on SMM among patients participating in intensive cardiac rehabilitation (ICR) remain incompletely characterized. Methods and results: A retrospective cohort study of 468 patients enrolled in a structured Pritikin ICR programme at UC San Diego Health between 2017 and 2024 was performed. At programme initiation, 67 patients were taking GLP-1 RAs with a median duration of 231 days (IQR 144–400). Body composition was assessed using bioelectrical impedance analysis at baseline and programme completion. Outcomes included SMM and fat mass (FM). Multivariable regression models adjusted for age, sex, baseline body mass index (BMI), diabetes status, and baseline fitness (measured in metabolic equivalents of tasks [METs]). Both groups improved in METs with ICR (P < 0.001). At baseline, patients on GLP-1 RAs had higher BMI and percent FM compared with non-users, but no differences were observed in SMM. In adjusted analyses, GLP-1 RA use was not associated with significantly different per cent change in SMM from baseline to ICR programme completion compared with no GLP-1 RA use (β = 0.62%, 95% CI −0.62 to 1.86; P = 0.326). Similarly, there was no significant between-group difference in per cent change in FM (β = 3.01%, 95% CI −1.64 to 7.66; P = 0.204). Conclusion: GLP-1 RA use during ICR was not associated with significantly different SMM changes after adjustment for measured covariates. These findings support the integration of GLP-1 based pharmacotherapy with structured exercise programmes.