Open Heart最新文献

Background: Constrictive pericarditis (CP) is a rare but significant pericardial disease resulting in impaired ventricular filling and heart failure symptoms, often following cardiac surgery. Its clinical presentation complicates diagnosis, mimicking other causes of heart failure. Recent technological advances, including artificial intelligence (AI)-based non-invasive pulse wave analysis (AI-PWA), have the potential for improved haemodynamic assessment and clinical decision-making.

Objectives: This study evaluates the clinical utility of AI-PWA in assessing central aortic blood pressure (CABP), arterial stiffness and cardiac function in CP.

Methods: This prospective case-control study enrolled 12 adult CP patients and 12 age- and sex-matched healthy controls. CABP and peripheral blood pressure (PBP) were measured using the VascAssist2. Haemodynamic parameters, including pulse wave velocity (PWV), augmentation index@75 (AIx@75), cardiac index, stroke volume and dP/dtmax, were assessed and compared between groups.

Results: CP patients showed significantly lower mean CABP than systolic PBP (101.8±23.4 mm Hg vs 112.3±22.9 mm Hg). PWV showed elevated values (>9 m/s) in nnn (42%) of cases, indicating increased arterial stiffness (8.88±1.94 m/s). AIx@75 was higher in CP patients (22.55±8.36%) compared with controls (16.38±6.53%), reflecting increased wave reflection, increased systemic vascular resistance or enhanced aortic compliance. Cardiac performance was notably impaired in the CP group, with reduced stroke volume (64.8±18.8 mL vs 94.9±25.0 mL, p=0.003) and dP/dtmax (724.9±228.2 mm Hg/s vs 1055.3±203.2 mmHg/s, p=0.0011), indicating impaired ventricular function. The heart failure index was significantly higher in CP patients (31.8±18.3% vs . 6.4±6.5%, p<0.001), indicating substantial functional compromise.

Conclusion: AI-PWA provides clinically relevant insights into central haemodynamics and arterial stiffness in CP patients. This non-invasive approach may enhance diagnosis and management of CP and should be considered for integration into routine cardiologic evaluation protocols.

Background: Severe aortic stenosis (AS) causes a pathophysiological cascade, which impairs myocardial blood flow. This effect is exacerbated in the presence of coronary disease (CAD). Treatment with transcatheter aortic valve implantation (TAVI) may promote reversal of these pathophysiological conditions.

Methods: We performed multimodality assessment of cardiac physiology in patients with AS and concurrent CAD requiring percutaneous coronary intervention, prior to and 6 months after undergoing TAVI. Techniques include: coronary angiography and bolus thermodilution-derived indices of microvascular function (coronary flow reserve (CFR); index of microcirculatory resistance (IMR)); stress perfusion cardiac magnetic resonance (CMR) imaging, which was used to measure changes in global myocardial blood flow (MBF) and left ventricular mass (LVM), and computed resting and hyperaemic vessel specific absolute coronary flow (aCBF) and microvascular resistance (MVR) using a computational model of coronary physiology.

Results: Data were obtained for seven patients (10 vessels). CFR increased from 1.53 (1.2-1.7) to 2.35 (2.0-2.7) (p=0.037) 6 months post-TAVI. There was a 33% reduction in resting aCBF from 218 mL/min to 146 mL/min (p=0.004). On CMR, resting MBF fell 37% from 3.0±0.98 mL/min/g to 1.9±0.7 mL/min/g (p=0.033) and stress MBF fell 25% from 3.6±0.57 mL/min/g to 2.7±0.7 mL/min/g (p=0.004). Indexed LVM regressed from 79±14 g/m² to 71±16 g/m² (p=0.006). MVR remained unchanged.

Conclusions: CFR increased following TAVI. The mechanism for this was a significant reduction in resting coronary blood flow measured with CMR and modelled computationally. The unchanged MVR and IMR suggest that resting blood flow reduces due to reduced myocardial demand and myocardial remodelling, rather than changes in resistance.

Background: Middle-aged men seem to be particularly susceptible to adverse cardiovascular effects of endurance exercise. The acute impact of training, marathon finishing and recovery on the heart has not been extensively investigated in such at-risk novice marathon runners.

Methods: We prospectively quantified cardiac changes in middle-aged men (41.2±4.5 years; n=17) who participated in their first marathon run at four time points: at baseline, after 16 weeks of training, within 10 hours after completing the 2021 Amsterdam Marathon run and after 4 weeks of recovery. Measurements included comprehensive 3-Tesla MRI examination, echocardiography, ECG and blood sample assays of high-sensitivity troponin-T (hs-TnT) and N-terminal pro-B-type natriuretic peptide (NT-proBNP).

Results: Acute effects associated with finishing the marathon run were a <10% reduction in left ventricular end-diastolic volume in absence of other morphological changes, and only minor changes in systolic contractile mechanics and diastolic filling patterns. Neither quantitative myocardial mapping with MRI nor late gadolinium enhancement revealed any signs of post-marathon myocardial injury. ECGs did not reveal any abnormalities. Circulating levels of hs-TnT and NT-proBNP had increased markedly after the marathon, with hs-TnT exceeding the clinical upper reference limit for all participants. All observed marathon running-induced effects were transient.

Conclusions: Extensive phenotyping using state-of-the-art quantitative imaging modalities paired with physical assessments and blood assays in this selected cohort offers no evidence to support the notion that first-time marathon running in healthy middle-aged men has a detrimental impact on the heart.

Background: Amyloid transthyretin (ATTR) amyloidosis is a rare, life-threatening disease frequently manifesting with cardiomyopathy (ATTR-CM), polyneuropathy (ATTR-PN) or both (ATTR-mixed). We retrospectively analysed US electronic health records and claims data to provide up-to-date estimates of ATTR amyloidosis epidemiology (overall and by phenotype).

Methods: Data were extracted from the Clarivate Real-World Data repository (2016-2023). Given the lack of established coding for ATTR amyloidosis, we used different combinations of diagnostic codes to obtain narrow and broad estimates of incident and prevalent cases in the USA in 2022. Temporal trends (2019-2022) were also assessed.

Results: Using narrow definitions, the 2022 estimated incidence of ATTR amyloidosis overall, ATTR-CM, ATTR-PN and ATTR-mixed was 16.6, 12.7, 3.5 and 1.9 cases per million people, respectively; the corresponding prevalence estimates were 59.8, 41.1, 15.1 and 9.8 cases per million people. Estimates were consistently lower with the narrow (vs broad) definitions. Over time, the incidence and prevalence of ATTR amyloidosis overall increased, driven by ATTR-CM cases. No major changes were reported for the other phenotypes.

Conclusion: This study provides comprehensive and up-to-date epidemiological data for ATTR amyloidosis in the USA. Our findings corroborate the need for appropriate differential diagnostic coding and standardised criteria.

Background: Depression is a risk factor and complication of coronary artery disease (CAD) that is associated with poor cardiovascular outcomes. This may be related to medication non-adherence; a topic on which considerable new evidence has emerged. We aim to assess the relationship between depression and medication adherence in patients with CAD.

Methods: The Cochrane Library, Medline and Embase databases were searched for relevant studies published until January 2023. Studies were included if they reported the prevalence of adherence to cardiovascular medications in depressed versus non-depressed participants aged >18 years with CAD, including acute and chronic coronary syndromes and those undergoing percutaneous coronary intervention. The primary outcome was the OR of non-adherence to cardiovascular medications in depressed versus non-depressed patients.

Results: Included studies (n=30) comprised mainly of cohort or cross-sectional studies, most of which involved US participants. Nine tools were used to measure medication adherence, the majority of which relied on participant self-report. Nine depression diagnostic tools were used, including the Patient Health Questionnaire, Beck Depression Inventory and International Classification of Diseases (ICD-9/10) diagnostic codes. The prevalence of depression ranged widely (1.7-76.6%), as did medication non-adherence (5.9-72.9%). A meta-analysis of 17 studies and 82 059 patients showed that depression was associated with increased medication non-adherence (OR 1.48, 95% CI 1.23 to 1.78, p<0.001) using a random effects model. However, there was considerable heterogeneity between studies (I²=91%, τ²=0.17, p<0.001), and the association was absent under a fixed effects model (OR 0.99 95% CL 0.98 to 1.01, p=0.58).

Conclusion: Patients with CAD and depression may have increased odds of medication non-adherence; however, there was considerable clinical and statistical heterogeneity, underscoring the need for further research to better understand this relationship.

Background: Multiple long-term conditions (MLTCs) are common among individuals with heart failure (HF); however, the influence of sex on clinical characteristics and prognosis remains unclear. This study investigated sex-related differences in clinical characteristics and prognosis in individuals with HF and a high MLTC burden.

Methods: We conducted a multicentre retrospective study of 3004 hospitalised patients with HF who survived to discharge. Comorbid chronic conditions were defined using the Charlson Comorbidity Index (CCI), and MLTC burden was quantified using the age-adjusted CCI. Patients were stratified into high (CCI≥6; n=1514) and low (CCI<6; n=1490) MLTC burden groups based on the median age-adjusted CCI, and comparisons were made by sex. The primary outcome was a composite of all-cause death or HF readmission within 1 year.

Results: The prevalence of ≥2 comorbid conditions increased with age, peaking before age 85 and declining slightly thereafter. This trend differed by sex, with a steeper age-related increase observed in men. In the high MLTC burden group, females were older, had higher left ventricular ejection fraction and were prescribed fewer medications than men. Dementia and rheumatologic disease were more common in women. Although no significant sex differences in event-free survival were observed overall in either MLTC group, among individuals aged≥75 years with high MLTC burden, men had a significantly higher risk of adverse events than women (HR: 1.334; 95% CI 1.031 to 1.727). A spline-based three-way interaction analysis (age×sex×MLTC burden) demonstrated that male risk exceeded female risk after age 70, only in the high MLTC burden group.

Conclusion: In individuals with HF and a high MLTC burden, age-dependent sex differences in prognosis were evident. These findings highlight the importance of incorporating age-specific and sex-specific approaches into personalised HF care.

Trial registration number: UMIN000054854.

Background: Although chest X-rays (CXRs) are widely used, diagnosing mitral stenosis (MS) based solely on CXR findings remains challenging in some cases.

Objective: This study aimed to develop a deep learning-based artificial intelligence (AI) model to detect MS using CXR.

Methods: In this retrospective study, 515 posteroanterior CXR images were analysed, including 285 from patients with MS and 230 from healthy controls. The dataset was randomly divided into training, validation and test datasets at a 7:2:1 ratio. An AI model was formulated by using the training dataset, and model performance was evaluated on the validation and test datasets using the area under the receiver operating characteristic curve (AUC), precision, recall, F1-score and accuracy. Saliency maps were generated to visualise the regions prioritised by the model.

Results: The model achieved an AUC of 0.99 on the validation dataset, with a precision of 0.96, recall of 0.96, F1-score of 0.96 and accuracy of 0.96. On the test dataset, the model achieved an AUC of 0.99, with a precision of 0.95, recall of 0.94, F1-score of 0.94 and accuracy of 0.94. Saliency maps highlighted regions consistent with known radiographic features of MS.

Conclusion: The developed deep learning-based AI model demonstrated high performance in detecting MS from CXR. This approach may provide a convenient and accessible screening tool for MS, particularly in resource-limited areas.

Background: Despite anticoagulation, patients with atrial fibrillation (AF) experience persistent elevated cardiovascular risk, with conflicting evidence regarding sex-based outcome disparities. Social determinants of health (SDOH)-encompassing economic, psychosocial and environmental factors-demonstrate robust associations with cardiovascular outcomes and exhibit significant sex-specific patterns, yet remain understudied in AF populations. This study aimed to clarify sex differences in the association of SDOH and adverse cardiovascular outcomes in patients with AF.

Methods: Data came from the UK Biobank. Participants with AF enrolled between 2006 and 2010 were included. SDOH comprised economic, psychosocial and neighbourhood environmental factors. The primary outcome was a composite of major adverse cardiovascular events (ie, stroke/transient ischaemic attack, arterial thromboembolic events, myocardial infarction and cardiovascular mortality) and all-cause mortality. Sex-stratified, Cox proportional hazards models were used.

Results: Among 3842 participants (mean age 62.5±6.1 years; 35.1% female), males demonstrated higher adverse outcome event rates than females (29.1% vs 21.3%) over median 11.6-year follow-up. Multivariate analyses revealed independent SDOH associations with adverse outcomes, with distinct sex-specific patterns. In male participants, low income (HR 1.30, 95% CI 1.08 to 1.55), unemployment (HR 1.28, 95% CI 1.06 to 1.55), living alone (HR 1.29, 95% CI 1.07 to 1.55) and housing insecurity (HR 1.26, 95% CI 1.01 to 1.57) were associated with adverse outcomes, while emotional distress was the only predictor (HR 1.33, 95% CI 1.04 to 1.69) in females.

Conclusions: SDOH demonstrate sex-specific associations with adverse cardiovascular outcomes in AF populations. Integration of SDOH into risk prediction algorithms may enhance cardiovascular risk stratification and inform targeted intervention strategies in AF management.

Contemporary cardiology faces a paradox: unprecedented technological capability coincides with declining scientific curiosity and clinical judgement. This manuscript examines the shift from question-driven, physiologic medicine to an approach dominated by procedural feasibility, commercial influence and algorithmic decision-making. Advances such as transcatheter interventions, advanced imaging and artificial intelligence have broadened therapeutic options but also encouraged action to precede reasoning, allowing anatomical suitability to overshadow clinical appropriateness and patient-centred values.The paper describes how industry pressures, guideline structures and training environments normalise interventionist reflexes and weaken the discipline of restraint, while research increasingly prioritises surrogate outcomes and validation of existing technologies. In response, the manuscript advocates for restoring the 'why' in cardiology through renewed critical thinking, meaningful outcomes and ethically grounded decisions. This requires cultural, educational and structural reform so that technology enhances rather than displaces the scientific and humanistic foundations of the field.

Background: Malnutrition influences prognosis in patients with heart failure, but current nutritional evaluation methods are excessively complex for routine clinical use. The role of the serum albumin concentration, a widely used surrogate marker, in acute heart failure remains unclear. We assessed whether changes in serum albumin during heart failure hospitalisation can serve as a prognostic marker.

Methods: Among 14 847 patients in a nationwide heart failure registry in 2013, 5836 eligible patients (mean age: 77.7 years, 51.2% men) were categorised into two groups: the albumin-increase group (n=2048) and the no-albumin-increase group (n=3788). The incidences of primary (all-cause mortality) and secondary (a composite of cardiovascular death and rehospitalisation for worsening heart failure) outcomes were compared between the groups. The prognostic impact of serum albumin changes was also evaluated.

Results: The median follow-up period was 1545 days (95% CI 1535 to 1557 days). Event-free survival rates for clinical outcomes were higher in the albumin-increase group than in the no-albumin-increase group (primary outcome: 54.5% vs 45.4%, 95% CI 51.4% to 57.6% vs 42.9% to 47.8%, p<0.005; secondary outcome: 40.5% vs 36.9%, 95% CI 36.4% to 44% vs 34.1% to 39.6%, p<0.005). A generalised additive model revealed a linear relationship between serum albumin changes and prognosis; declines had a stronger negative effect than the positive impact of increases, but the change rate better reflected the relationship with prognosis. Survival classification and regression tree analysis indicated that a 25% decrease in the serum albumin concentration identified the most vulnerable population; even a 3% decrease was associated with worse outcomes.

Conclusions: Serum albumin changes during hospitalisation can predict prognosis in patients with heart failure, indicating potential as a target for interventions.