Daily Cardiology Research Analysis
Analyzed 333 papers and selected 3 impactful papers.
Summary
Three studies advance cardiology across mechanism, population outcomes, and diagnostics: single-cell and bulk transcriptomics identified lipid-associated macrophages as prognostic drivers of recurrent events after carotid endarterectomy; SGLT2 inhibitors were associated with reduced incident dementia in non-diabetic heart failure; and an on-site AI/fluid dynamics CT-FFR matched off-site FFRct and invasive FFR with rapid turnaround.
Research Themes
- Immunometabolic macrophage phenotypes predict secondary cardiovascular events
- SGLT2 inhibitors and neurocognitive outcomes in non-diabetic heart failure
- On-site AI-enabled CT-FFR for functional CAD assessment
Selected Articles
1. Carotid plaque macrophage burden and inflammatory lipid-associated macrophage markers predict secondary major adverse cardiovascular events after endarterectomy.
Single-cell and bulk transcriptomics in carotid plaques identified four macrophage archetypes and showed that macrophages—particularly lipid-associated macrophages (LAMs) and inflammatory LAMs—are linked to symptoms and independently predict 3-year MACE. LAM markers PLIN2 and TREM1 consistently associated with secondary events and were validated across cohorts.
Impact: This study bridges cellular mechanisms and clinical prognosis, pinpointing macrophage phenotypes and markers that forecast post-endarterectomy risk and offering tangible targets for risk stratification and potential intervention.
Clinical Implications: Quantifying LAM-related signatures (e.g., PLIN2, TREM1) could refine post-CEA risk stratification and surveillance. It motivates development of blood/imaging biomarkers and macrophage-targeted therapies to reduce secondary events.
Key Findings
- Identified four macrophage archetypes (inflammatory macrophages, LAMs, tissue-resident-like LAMs, inflammatory LAMs) in human carotid plaques.
- Macrophages were the only cell population significantly linked to symptoms at surgery and increased 3-year MACE in the AtheroExpress cohort.
- LAM/inflammatory LAM markers (e.g., PLIN2, TREM1) independently predicted secondary MACE and were validated in an external imaging cohort.
Methodological Strengths
- Integration of single-cell RNA-seq with bulk RNA deconvolution across a large cohort (n=656) and external validation (n=82).
- Trajectory and fate analyses delineating monocyte origins and differentiation into inflammatory LAMs.
Limitations
- Observational design limits causal inference despite validation.
- Plaque-level findings in carotid disease may not directly generalize to other vascular beds; deconvolution may be sensitive to batch and tissue heterogeneity.
Future Directions: Prospective studies to develop circulating/IMAGING biomarkers of LAM activity and to test macrophage- or TREM1-targeted interventions for secondary prevention.
BACKGROUND AND AIMS: Atherosclerosis is a chronic lipid-driven inflammatory disease... METHODS: Single-cell RNA sequencing on blood and plaques from 46 carotid endarterectomy patients... Deconvolution was done on bulk transcriptome data from 656 AtheroExpress patients, and findings were validated in 82 patients... RESULTS: Four major archetypes of plaque macrophages were identified... Macrophages were shown to be the only cell population significantly associated with both symptoms at time of surgery and increased risk of major adverse cardiovascular events during a 3-year follow-up period... LAM and inflammatory LAM foam cell markers such as PLIN2 and TREM1 were associated with an increased risk... CONCLUSIONS: ...show their clinical significance and risk prediction value...
2. Association of SGLT2 inhibitors and new-onset dementia in non-diabetic patients with heart failure.
In 39,979 matched pairs of non-diabetic HF patients, SGLT2 inhibitor use was associated with lower risks of incident dementia (HR 0.77), Alzheimer’s disease (0.58), vascular dementia (0.41), all-cause mortality (0.63), ischaemic stroke (0.67), and ESKD (0.75) over a median 1.2 years.
Impact: Findings extend SGLT2 inhibitor benefits to neurocognitive outcomes in non-diabetic HF, supporting broader therapeutic value and hypothesis generation for brain–heart–kidney mechanisms.
Clinical Implications: When selecting foundational HF therapy, SGLT2 inhibitors may confer cognitive and survival benefits even without diabetes, supporting earlier initiation and prioritization in appropriate patients.
Key Findings
- SGLT2 inhibitor therapy was associated with reduced incident dementia (HR 0.77), Alzheimer’s disease (HR 0.58), and vascular dementia (HR 0.41).
- All-cause mortality (HR 0.63), ischaemic stroke (HR 0.67), and ESKD (HR 0.75) were also reduced among SGLT2i users.
- Results were derived from 39,979 propensity-matched pairs over a median follow-up of 1.2 years.
Methodological Strengths
- Large-scale real-world dataset with 39,979 matched pairs controlling for measured confounding.
- Multiple clinically relevant neurological, cardiovascular, and renal outcomes assessed with consistent benefit.
Limitations
- Observational design with potential residual confounding and misclassification from EHR coding.
- Relatively short median follow-up (1.2 years) limits assessment of long-term cognitive trajectories.
Future Directions: Randomized trials evaluating cognitive outcomes in HF without diabetes, mechanistic studies (neurovascular, glymphatic, inflammation), and longer-term real-world follow-up.
AIMS: Patients with heart failure (HF) are at increased risk of developing dementia... METHODS: Retrospective cohort using TriNetX (2016-2025) including adults with HF and no prior dementia or diabetes; SGLT2i initiators (n = 46,049) vs non-users (n = 205,010). After 1:1 propensity matching, 39,979 pairs analyzed. RESULTS: Median follow-up 1.2 years; SGLT2i use associated with lower new-onset dementia (HR 0.77, 95% CI 0.68-0.87; P < .001), Alzheimer's (HR 0.58), vascular dementia (HR 0.41), all-cause mortality (HR 0.63), ischaemic stroke (HR 0.67) and ESKD (HR 0.75). CONCLUSION: ...
3. Deep Learning and Fluid Dynamics On-Site CT-FFR Solution Compared to Off-Site FFRct and Invasive FFR.
An on-site deep learning/fluid dynamics CT-FFR (xFFR) achieved high diagnostic accuracy (AUC 0.91), comparable to off-site FFRct and with superior performance for LAD lesions (AUC 0.96 vs 0.84). Sensitivity/specificity were 95%/81%, with rapid analysis (~8 minutes), and good agreement with invasive FFR.
Impact: Demonstrates clinically viable, rapid, and accurate on-site functional CAD assessment, reducing dependence on off-site platforms and potentially streamlining care pathways.
Clinical Implications: Hospitals can integrate on-site CT-FFR to expedite decision-making, reduce delays and costs tied to off-site processing, and improve patient throughput—especially useful for LAD assessment.
Key Findings
- On-site xFFR achieved AUC 0.91 vs invasive FFR and matched off-site FFRct (AUC 0.89; P=0.274).
- Superior performance in LAD (AUC 0.96 vs 0.84; P=0.001) with sensitivity 95% and specificity 81%.
- Good correlation with invasive FFR (ρ=0.67) and fast analysis (mean 8±3.4 minutes).
Methodological Strengths
- Prospective head-to-head comparison with both invasive FFR and off-site FFRct in symptomatic patients.
- Comprehensive vessel-level performance metrics with predefined analysis times.
Limitations
- Single-center study may limit generalizability; not powered for clinical outcomes.
- Diagnostic advantage in LAD may not extend to all territories; vendor-specific workflows need broader validation.
Future Directions: Multicenter studies to validate generalizability, cost-effectiveness analyses, and workflow integration across vendors and care settings.
BACKGROUND: On-site computed tomography (CT)-derived fractional flow reserve (FFR) solutions are increasingly needed... METHODS: Single-center prospective study of 250 symptomatic patients undergoing CTA, xFFR (on-site), FFRct (off-site), and invasive angiography with iFFR. RESULTS: Functionally significant CAD detected in 56.6% (xFFR), 54% (FFRct), 48% (iFFR); xFFR sensitivity, specificity, accuracy were 95%, 81%, 88%; AUC comparable to FFRct (0.91 vs 0.89; P=0.274), superior in LAD (0.96 vs 0.84; P=0.001). Agreement with iFFR (ρ=0.67). Mean analysis time 8±3.4 minutes. CONCLUSIONS: xFFR is a robust and efficient on-site tool...