Background/Objectives: Right heart catheterization (RHC) is the diagnostic gold standard for pulmonary hypertension (PH), defined as mean pulmonary arterial pressure (mPAP) greater than 20 mmHg at rest. It is invasive and carries procedural risk. Machine learning (ML) and deep learning (DL) applied to non-invasive modalities may provide a non-invasive adjunct for screening, triage, and earlier identification. Methods: Methodological quality was assessed using QUADAS-2. Primary non-comparative pooling was restricted to RHC-confirmed studies using Reitsma hierarchical bivariate random-effects models. Comparative studies were analyzed using a paired hierarchical bivariate model, with between-method differences assessed using paired Wald tests. Sensitivity, specificity, likelihood ratios, and diagnostic odds ratios were estimated; predictive values were evaluated as secondary outcomes. GRADE certainty was assessed separately for non-comparative ML/DL, comparative ML/DL, and traditional methods. Results: Nine studies involving multiple pulmonary hypertension subtypes met the inclusion criteria: five non-comparative (single-arm) studies including approximately 26,530 participants and four comparative (double-arm) studies including 330 paired participants per arm. In the primary synthesis restricted to RHC-confirmed single-arm studies, ML/DL models achieved a pooled sensitivity of 0.720 (95% CI: 0.647–0.783) and specificity of 0.883 (95% CI: 0.796–0.936), with a diagnostic odds ratio of 19.4 (95% CI: 13.6–27.7). Estimates were similar when all five single-arm studies were included (sensitivity 0.716, 95% CI: 0.654–0.771; specificity 0.891, 95% CI: 0.820–0.937). In comparative studies analyzed with a paired hierarchical bivariate model, ML/DL outperformed traditional methods for both sensitivity (0.838, 95% CI: 0.668–0.930 versus 0.707, 95% CI: 0.421–0.889; paired Wald p = 0.019) and specificity (0.849, 95% CI: 0.512–0.968 versus 0.640, 95% CI: 0.376–0.840; paired Wald p = 0.0076). At a 25% pre-test probability, ML/DL was projected to yield 34 additional true positives (95% CI: −30 to 109) and 142 fewer false positives (95% CI: −381 to 129) per 1000 patients tested, although all absolute difference intervals crossed zero. Certainty of evidence was very low across all outcomes. GRADE certainty ranged from low to very low depending on outcome and stratum. Conclusions: ML/DL-based methods showed promising non-invasive diagnostic accuracy for PH, with significantly higher pooled sensitivity and specificity than traditional methods in paired comparisons. However, evidence certainty ranged from low to very low, and projected absolute benefits remained imprecise. These findings are hypothesis-generating; ML/DL tools may serve as adjuncts in the diagnostic pathway but cannot replace RHC at this stage.

Background: Inherited arrhythmic syndromes (IAS) are an important but under-recognized cause of sudden cardiac death (SCD), particularly in younger individuals. Understanding long-term mortality trends is essential to evaluate their public health impact. Objective: To assess temporal trends and demographic disparities of IAS-related sudden cardiac death among individuals aged 5–44 years in the United States using CDC WONDER data. Methods: This retrospective observational study utilized the CDC WONDER Multiple Cause-of-Death database from 1999 to 2024. Deaths were identified using ICD-10 codes for non-ischemic arrhythmogenic conditions (I42, I44, I45, I47, I49) in combination with sudden cardiac arrest or unexplained death (I46, R96). Ischemic heart disease (I20–I25) was excluded to enhance specificity for inherited causes. Crude and age-adjusted mortality rates (AAMRs) per 1,000,000 population were calculated and stratified by age, sex, race/ethnicity, region, urbanization, and place of death. Joinpoint software helped us calculate the average annual percentage change (AAPC)/annual percent change (APC) in AAMRs and the 95% CIs for these changes. Results: A total of 8879 deaths were identified over the study period. The AAMR increased from 1.46 (95% CI: 1.27–1.64) in 1999 to 3.15 (95% CI: 2.89–3.42) in 2024, peaking at 4.54 in 2021, with an overall AAPC of 3.71% (p < 0.000001). Mortality was higher in males; however, females demonstrated a greater relative increase over time. Non-Hispanic Black individuals exhibited the highest mortality rates and fastest rise. The 25–44-year age group accounted for most deaths and showed the steepest increase. Regional and urban–rural disparities were observed, with higher mortality rates in the South and rural areas. Conclusions: It is concluded that mortality related to inherited arrhythmic syndromes and sudden cardiac death is rising among young individuals in the United States. The findings highlight a growing burden of potentially inherited arrhythmogenic conditions and underscore the need for early detection strategies, including genetic screening and targeted public health interventions, to reduce premature cardiovascular mortality.

Background: Atherosclerotic heart disease (AHD) remains a leading cause of global mortality and a major driver of fatal cardiac syndromes. Ischemic myocardial injury from AHD can lead to ventricular remodeling and myocyte loss, progressing to heart failure (HF) and, in advanced stages, cardiogenic shock (CS). However, long-term national mortality trends for deaths involving the combined burden of AHD, HF, and CS remain insufficiently characterized. Methods: Mortality data from 1999 to 2023 were obtained from the CDC WONDER Multiple Cause of Death database. Deaths involving CS (ICD-10 R57.0), HF (I50, I50.1, I50.9), and AHD (I25.1) in adults were identified. Age-adjusted mortality rates (AAMRs) per 1,000,000 population were calculated and stratified by sex, race/ethnicity, and geographic region. Temporal trends were analyzed using Joinpoint regression to estimate annual percent changes (APCs) and average annual percent changes (AAPCs). Autoregressive integrated moving average (ARIMA) modeling was used to forecast mortality trends through 2035. Results: A total of 15,631 deaths were attributed to AHD-associated HF and CS during the study period. Overall AAMRs increased significantly (AAPC 3.75%; 95% CI 3.32–4.29; p < 0.01). Mortality rates declined between 1999 and 2006 (APC −7.55%; 95% CI −13.15 to −5.23; p < 0.01), increased modestly from 2006 to 2013 (APC 3.94%; 95% CI −1.47 to 8.91), and rose sharply from 2013 to 2023 (APC 12.33%; 95% CI 11.27–14.46; p < 0.01). Males had higher AAMRs than females in 2023 (9.26 vs. 3.39 per 1,000,000). Non-Hispanic White individuals accounted for the highest number of deaths (11,878), followed by non-Hispanic Black individuals (1708), while non-Hispanic American Indian populations had the lowest counts (39). Regionally, the West (7.31) and South (5.92) exhibited the highest final AAMRs. State-level AAMRs ranged from 2.49 in Minnesota to 8.27 in Nevada. Conclusions: Mortality involving AHD, HF, and CS has risen substantially in the United States since 2013, with marked demographic and geographic disparities. These findings highlight a growing burden of advanced ischemic heart disease and heart failure and underscore the need for earlier intervention and improved access to advanced HF therapies to prevent progression to cardiogenic shock and death.

Background: Cardiogenic shock (CS) and chronic ischemic heart disease (CIHD) remain major contributors to cardiovascular mortality in the United States. Although mortality related to ischemic disease declined in the early 2000s, recent trends suggest a resurgence. Methods: This population-based study utilized the Centers for Disease Control and Prevention’s Wide-Ranging OnLine Data for Epidemiologic Research (CDC WONDER) database from 1999 to 2023. Deaths were identified using ICD-10 codes R57.0 (CS) and I25 (CIHD). Adults aged ≥ 45 years were included. Crude mortality rates (CMRs) and age-adjusted mortality rates (AAMRs) were calculated, with temporal changes assessed using Joinpoint regression to estimate Annual Percent Change (APC) and Average Annual Percent Change (AAPC). Results: Between 1999 and 2023, deaths attributed to CS and CIHD accounted for 78,903 cases among adults ≥ 45 years. Overall AAMR ranged from 35.88 per million in 1999 to 37.44 per million in 2023, with a downward trend from 1999 to 2012 followed by an upward trend thereafter. Males (51,080 deaths) exhibited rising mortality (AAPC: +0.50, p < 0.001), while females (27,823 deaths) showed a decline (AAPC: − 0.91, p < 0.0004). Non-Hispanic Black adults demonstrated the steepest increase (AAPC: +1.85, p < 0.001). The burden was greatest in adults ≥ 65 years, but the 45–64 group showed the fastest rise (AAPC: +1.67, p < 0.001). Conclusion: Mortality from cardiogenic shock and chronic ischemic heart disease among U.S. adults ≥ 45 years declined initially but reversed after 2012. Rising mortality in middle-aged adults, persistent racial disparities, and geographic inequities highlight urgent gaps in prevention and acute care.

Background: Pulmonary hypertension (PH) is associated with increased pulmonary arterial pressure and impairment of right ventricular (RV) function. Reliable characterization of RV performance is important for prognosis, risk assessment, and therapeutic planning. Cardiac magnetic resonance (CMR) is considered the reference technique for quantifying RV volumes and function, but its expense and limited availability can restrict routine implementation. Echocardiography is more widely accessible; however, the extent to which individual echocardiographic indices correspond with CMR-derived RV ejection fraction (RVEF) remains incompletely defined. Objective: Our objective was to determine the correlation of RV fractional area change (RV-FAC), RV free-wall longitudinal strain (RV-FWLS), and RV global longitudinal strain (RV-GLS) with CMR-derived RVEF in individuals with PH. Methods: PubMed, Embase, ClinicalTrials.gov, Scopus, and the Cochrane Library were searched, yielding 404 records; six studies fulfilled the eligibility criteria. Studies were eligible when they enrolled patients with PH and provided extractable correlations between at least one prespecified echocardiographic measure and CMR-derived RVEF. Correlation coefficients were converted with Fisher’s z transformation, combined using common-effect and random-effects approaches, and then transformed back to correlation coefficients. Pooled mean RV-FAC was evaluated as a separate outcome. Between-study heterogeneity was quantified with I² and τ², with random-effects estimates emphasized for interpretation. Results: Each evaluated echocardiographic measure was positively correlated with CMR-derived RVEF. RV-FWLS had the largest pooled correlation and the greatest consistency (r = 0.79, 95% CI: 0.73–0.83; I² = 0.0%). The pooled correlation for RV-GLS was 0.75 (95% CI: 0.60–0.85; I² = 80.3%), while that for RV-FAC was 0.72 (95% CI: 0.61–0.80; I² = 61.8%). The random-effects pooled mean RV-FAC was 31.10% (95% CI: 26.77–35.43), with substantial heterogeneity (I² = 90.9%). Conclusions: RV-FWLS showed the highest numerical and most consistent association with CMR-derived RVEF, suggesting that it may serve as a useful non-invasive adjunct for RV assessment in PH, especially where CMR is not readily available. Larger studies using harmonized acquisition and analysis methods are required for confirmation.