Daily Cardiology Research Analysis
Analyzed 81 papers and selected 3 impactful papers.
Summary
Three studies stand out today: a double-blind RCT shows empagliflozin reduces left ventricular mass in older overweight adults at risk of heart failure; an end-to-end deep learning pipeline automates scar/microvascular obstruction quantification on LGE-CMR with prognostic performance comparable to experts; and right atrial reservoir strain robustly stratifies mortality risk in pulmonary arterial hypertension, outperforming other CMR metrics.
Research Themes
- Preventive cardiology with SGLT2 inhibition
- AI-enabled cardiovascular imaging and prognostication
- Atrial mechanics for risk stratification in pulmonary vascular disease
Selected Articles
1. The effect of empagliflozin on left ventricular mass and volumes in elderly individuals with overweight and high risk of heart failure: The Empire Prevent Cardiac Trial.
In a multicenter, double-blind RCT of 191 elderly, overweight individuals at high cardiovascular risk, empagliflozin 10 mg daily for 180 days significantly reduced left ventricular mass index versus placebo. This preventive remodeling effect was observed in a population without established heart failure.
Impact: This is a rigorously designed RCT showing structural cardiac benefits of SGLT2 inhibition in at-risk individuals without heart failure, supporting a preventive cardiology paradigm.
Clinical Implications: Empagliflozin may be considered for preventive cardiac remodeling in older overweight adults at risk of HF, pending confirmation of clinical outcomes in larger, longer trials.
Key Findings
- Double-blind, randomized, placebo-controlled multicenter trial (NCT05084235) enrolled 191 elderly, overweight individuals at risk of heart failure.
- Empagliflozin 10 mg daily for 180 days led to a significant reduction in left ventricular mass index versus placebo.
- Trial focused on a prevention population without established heart failure, indicating a potential role for SGLT2 inhibitors in early cardiac remodeling.
Methodological Strengths
- Investigator-initiated, double-blind, randomized, placebo-controlled, multicenter design
- Pre-registered clinical trial (NCT05084235) with standardized imaging endpoints
Limitations
- Short follow-up (180 days) and surrogate imaging outcomes without hard clinical endpoints
- Modest sample size may limit subgroup analyses and generalizability
Future Directions: Confirm findings in larger RCTs powered for clinical outcomes, assess durability of LV mass regression, and evaluate cost-effectiveness in preventive cardiology.
BACKGROUND AND AIM: Increased left ventricular (LV) mass is a predictor of HF. The preventive effect of sodium-glucose cotransporter 2 inhibitors remain unclear in subjects without heart failure (HF). The aim was to evaluate the effect of empagliflozin on LV mass index (LVMI) and LV volumes in individuals with overweight and considered at risk of HF. METHOD AND RESULTS: Investigator-initiated, double-blinded, randomized, placebo-controlled, multicenter superiority trial [NCT05084235] in 191 elderly (60-84 years), overweight (body mass index (BMI) >28 kg/m CONCLUSION: Among elderly individuals with overweight and cardiovascular disease Empagliflozin 10 mg daily compared to placebo for 180 days led to a significant reduction in LVMI.
2. Prognostic value of end-to-end deep learning assessment of myocardial scar and microvascular obstruction on late gadolinium enhancement cardiovascular magnetic resonance.
An end-to-end deep learning pipeline (LGE-CMRnet) combining YOLOv8 and nnU-Net achieved fast (0.05 s/image), accurate segmentation of scar and MVO on LGE-CMR with strong agreement to expert annotations. Automated scar/MVO quantification provided prognostic information for MACE comparable to expert analysis over a median 24.4 months.
Impact: This work offers a scalable, accurate, and prognostically meaningful AI solution to a core cardiac imaging task, reducing variability and workload while enabling broader risk stratification.
Clinical Implications: Automated LGE-CMR quantification of scar and MVO can standardize reporting and support routine prognostic assessment after AMI, potentially expediting clinical workflows and trial endpoints.
Key Findings
- LGE-CMRnet processed images rapidly (0.05 seconds per image) while maintaining high accuracy.
- External validation achieved mean DSC of 0.83 for scar and 0.88 for MVO with strong volumetric correlations (scar r=0.90; MVO r=0.98).
- Automated scar/MVO quantification conferred prognostic value for MACE comparable to expert analysis over a median 24.4 months.
Methodological Strengths
- External validation cohort and rigorous benchmarking (DSC, correlation, Bland–Altman) against expert annotations
- Integrated end-to-end pipeline (localization + multi-structure segmentation) with outcome-linked prognostic evaluation
Limitations
- Generalizability beyond AMI populations, vendors, and centers requires broader validation
- Data/code availability and prospective in-clinic deployment were not detailed
Future Directions: Prospective, multi-center deployment studies to assess clinical impact, integration with reporting systems, and extension to non-AMI diseases and multi-vendor datasets.
BACKGROUND: Late gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) is the reference standard for assessing myocardial scar and microvascular obstruction (MVO), strong predictors of post-acute myocardial infarction (AMI) outcomes. However, manual segmentation is time-consuming and subject to inter-observer variability, limiting clinical scalability. This study develops and validates LGE-CMRnet, an end-to-end deep learning pipeline for automated scar and MVO segmentation on LGE CMR, and evaluates its prognostic value in AMI patients. METHODS: A total of 3,874 LGE images from 567 AMI patients (409 for training/internal stress-test cohort; 158 for external testing) were analyzed. LGE-CMRnet integrates YOLOv8 for heart localization and nnU-Net for simultaneous segmentation of myocardium, scar, and MVO. Performance was evaluated using Dice similarity coefficient (DSC), correlation, and Bland-Altman analysis against expert annotations. Prognostic value was assessed using Cox regression for major adverse cardiac events (MACE) over a median follow-up of 24.4 months. RESULTS: LGE-CMRnet achieved rapid processing (0.05seconds per image) and high segmentation accuracy. In the external validation cohort, the model achieved mean DSC of 0.83±0.11 for scar and 0.88±0.11 for MVO at the patient level, with strong volumetric correlations to expert reference segmentations (scar: r=0.90; MVO: r=0.98, both P<0.0001). Bland-Altman analysis showed minimal bias in volumetric measurements (scar: 2.5±8.9 cm
3. Right atrial phasic strain in risk stratification of patients with Pulmonary Arterial Hypertension.
In a prospective cohort of 348 PAH patients followed for a median of 41.5 months, right atrial reservoir strain independently predicted all-cause mortality (HR 0.950). Cutoffs at 16.1% and 36.8% produced high-, intermediate-, and low-risk strata with 1-year mortality of 24.0%, 5.5%, and 0.0%, outperforming other CMR metrics and enhancing REVEAL Lite 2.
Impact: The study establishes RA reservoir strain as a powerful, easily derivable CMR biomarker for mortality risk stratification in PAH, complementing and improving established clinical models.
Clinical Implications: Incorporating RA reservoir strain into multiparametric PAH assessment can refine risk stratification, guide therapy intensity, and potentially inform timing of advanced therapies or transplant evaluation.
Key Findings
- Prospective cohort of 348 PAH patients with median 41.5-month follow-up; RA reservoir strain independently predicted all-cause mortality (HR=0.950; P<0.001).
- Cutoffs at 16.1% and 36.8% delineated high-, intermediate-, and low-risk groups with 1-year mortality of 24.0%, 5.5%, and 0.0%, respectively.
- RA reservoir strain achieved the highest C-index (0.79) among CMR metrics and significantly improved REVEAL Lite 2 performance (P=0.03).
Methodological Strengths
- Prospective recruitment with pre-specified mortality risk strata and long median follow-up
- Trial registration and comprehensive comparison against CMR metrics and clinical risk model (REVEAL Lite 2)
Limitations
- Single-country cohort; external validation across centers and vendors is needed
- Observational nature limits causal inference; thresholds require prospective confirmation
Future Directions: External, multi-center validation; incorporation into clinical workflows and risk calculators; studies to test treatment guidance based on RA strain thresholds.
BACKGROUND: Right atrial (RA) phasic function is impaired in individuals with pulmonary arterial hypertension (PAH), evidence for the clinical significance of the RA strain in risk stratification for PAH patients is limited. METHODS: Participants with PAH from June 2013 to December 2022 were prospectively recruited. C-index, 1-year mortality, and annual event rates were used to evaluate prognostic performance. Risk groups were defined as low (<5%), intermediate (5-20%), and high (>20%) 1-year mortality. RESULTS: A total of 348 PAH patients were included (mean age: 40.0 ± 14.0 years; 93 males), with a median follow-up of 41.5 months (interquartile range: 24.9-61.9 months). RA reservoir strain independently predicted all-cause mortality (HR = 0.950, 95% CI: 0.922-0.979; P < 0.001). Based on cutoff values of 16.1% and 36.8%, RA reservoir strain stratified patients into high-, intermediate-, and low-risk groups with 1-year mortality rates of 24.0%, 5.5%, and 0.0%, demonstrating the highest discriminative ability among CMR-derived metrics (C-index: 0.79, 95% CI: 0.71-0.87). Incorporating RA reservoir strain significantly improved the performance of the REVEAL Lite 2 model (P = 0.03), with comparable prognostic value to that of the combined CMR parameters (both P > 0.05). Similar findings were observed in PAH patients without shunts. CONCLUSION: RA reservoir strain outperformed RV functional parameters in stratifying PAH patients into low-, intermediate-, and high-risk strata. RA reservoir strain has the potential to be part of the multiparametric evaluation of patients with PAH. TRIAL REGISTRATION: This study was registered in the Chinese clinical trial registry (ChiCTR1800019314 and ChiCTR1900025518). URL: https://www.chictr.org.cn/index.html.