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Background: Insomnia symptoms are prevalent in older adults and linked to cardiovascular disease (CVD), but the role of long-term symptom trajectories remains unclear. We investigated associations between insomnia symptoms, their trajectories over time and incident CVD in a population-based cohort.

Methods: This longitudinal study included 12 102 participants aged ≥50 years without baseline CVD from the US Health and Retirement Study (2002-2018). Insomnia symptoms (non-restorative sleep, difficulty initiating/maintaining sleep, early awakening) were assessed at baseline; trajectories were modelled over 4 years (2002-2006) using latent class analysis. Cox models estimated HRs for incident CVD (heart disease or stroke), adjusted for sociodemographics, lifestyle and comorbidities.

Results: During a median of 10.2-year follow-up, 3962 incident CVD events occurred. Compared with no symptoms, participants with one, two, or three to four symptoms had higher CVD risk (HR 1.16, 95% CI 1.05 to 1.27; HR 1.16, 95% CI 1.05 to 1.28; HR 1.26, 95% CI 1.15 to 1.38, respectively). Four trajectories were identified: persistent low (56.3%), decreasing (27.1%), increasing (7.2%) and persistent high (9.5%). Compared with persistent low, increasing (HR 1.28, 95% CI 1.10 to 1.50) and persistent high (HR 1.32, 95% CI 1.15 to 1.50) trajectories were associated with elevated CVD risk.

Conclusions: Greater burden of insomnia symptoms at baseline and trajectories over time were associated with higher CVD incidence in older adults.

Transthyretin amyloidosis (ATTR) is a condition caused by TTR protein misfolding and amyloid deposition, particularly in the heart and nervous system, leading to organ dysfunction. Advances in therapeutic strategies have revolutionised the management of ATTR amyloidosis. Treatments available in clinical practice include TTR stabilisers (tafamidis and acoramidis), which prevent the dissociation of TTR tetramer into monomers and oligomers that subsequently form amyloid fibrils, and gene-silencing therapies (patisiran, inotersen and vutrisiran), which suppress the hepatic synthesis of TTR, which is the amyloid precursor protein. Novel treatment strategies that are at various stages of development include Clustered Regularly Interspaced Short Palindromic Repeats-Cas9 gene-editing technology (nexiguran ziclumeran), which, if successful, offers the prospect of a single-dose treatment, and monoclonal (cormitug and ALXN220) and pan-amyloid antibodies (AT-02) that seek to target and remove amyloid fibrils that have deposited in the myocardium. Amyloid removal remains a significant unmet clinical need, and hence, the ability to promote amyloid degradation and clearance through the use of antiamyloid therapies would represent a groundbreaking advancement in the treatment of ATTR amyloidosis. The success of ATTR-specific disease-modifying therapies has already altered the treatment landscape and changed the perception of ATTR amyloidosis from a progressive and fatal disease to one that is treatable through the availability of highly effective disease-modifying therapies. However, important questions remain, including the long-term safety of these drugs, whether combining therapies with different mechanisms of action has an additive prognostic benefit and how best to monitor the treatment response.

Background: Baseline health and driving data might allow clinicians to personalise medical driving restrictions after implantable cardioverter-defibrillator (ICD) implantation.

Methods: Using 22 years of population-based administrative data from British Columbia, Canada, we identified licensed drivers with a first ICD implantation between 1998 and 2018. After stratifying by ICD indication (primary vs secondary prevention of sudden cardiac death), we used baseline health and driving data and logistic regression to estimate each driver's 1-year crash risk. We assessed optimism-corrected discrimination and calibration of the final model using 200 bootstrapped samples.

Results: In the first year after implantation, there were 352 crashes among 3652 primary prevention ICD recipients and 270 crashes among 3408 secondary prevention ICD recipients. Crash prediction models exhibited poor discrimination (c-statistics 0.60 and 0.61, respectively) but good calibration (calibration slopes 1.14 and 1.07). The strongest predictors of crash among primary prevention ICD recipients were male sex, active vehicle insurance in the past year and the number of crashes in the past year. The strongest predictors of crash among secondary prevention ICD recipients were male sex, no history of seizure, an active prescription for opioids and active vehicle insurance in the past year.

Conclusions: Crash prediction models based on health and driving data had a limited ability to distinguish individuals who subsequently crashed from individuals who did not. Observed crash risks are likely to be strongly influenced by unobserved changes in road exposure (the hours or miles of driving per week), limiting the application of these risk scores by clinicians and policy-makers.

Background: Bicuspid aortic regurgitation (AR) is common in younger patients who often do not meet guideline-based criteria for aortic valve (AV) surgery at diagnosis. However, identifying early predictors of disease progression may aid in risk stratification and surgical timing.

Methods: From a single-centre registry of 1927 patients with bicuspid AV, we identified 335 patients with moderate or severe AR, excluding those with severe aortic stenosis (AS), endocarditis or other major valvular diseases. Among them, 199 patients (mean age 52±14.0 years; 80% male) did not initially meet the surgical criteria and were included in the final analysis. Clinical data and echocardiographic parameters, including speckle-tracking-derived strain measurements, were analysed. The primary outcome was progression to AV surgery during follow-up.

Results: Over a mean follow-up of 4.9 years, 41 patients (21%) underwent AV surgery, primarily for symptom onset or left ventricular (LV) enlargement. In multivariable Cox regression, three independent predictors of future surgery were identified: LV mass index ≥113 g/m² (HR 4.49, 95% CI 1.74 to 11.6, p=0.002), left atrial (LA) reservoir strain <28% (HR 3.07, 95% CI 1.40 to 6.74, p=0.005) and concomitant moderate AS (HR 3.19, 95% CI 1.40 to 7.28, p=0.006).

Conclusion: In patients with significant bicuspid AR who do not initially meet indications for AV surgery, increased LV mass index, impaired LA reservoir strain and concomitant moderate AS are early predictors of surgical progression. These parameters may enhance surveillance strategies and inform earlier surgical referral in selected patients.

Background: Accurate pre-ablation differentiation between left (LVOT) and right (RVOT) ventricular outflow tract arrhythmias (OTVAs) using ECG algorithms is essential for decision on vascular access and treatment strategy. However, the most reliable ECG algorithm remains unclear. We conducted a systematic review and network meta-analysis (NMA) to compare the diagnostic accuracy of available algorithms.

Methods: We searched MEDLINE, EMBASE and Cochrane databases through 7 May 2025 for studies evaluating ECG algorithms against ablation-confirmed OTVA origin. A Bayesian diagnostic test accuracy NMA was performed to estimate pooled sensitivity, specificity, diagnostic odds ratios (DORs) and a superiority index (S) for each algorithm. Study quality was assessed using the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool.

Results: From 620 records, 22 studies (3483 patients; 2706 RVOT, 777 LVOT) evaluating 21 ECG algorithms were included. The 'Weighted hybrid score' algorithm showed the highest diagnostic accuracy (S=21.2 (0.3, 39.0); DOR=275.8 (7.1, 1642.5)), with pooled sensitivity of 0.83 (0.53, 0.98) and specificity of 0.92 (0.68, 0.99). Conversely, the 'Earliest onset or peak/nadir in lead V2' algorithm had the lowest accuracy.

Conclusions: Among existing ECG algorithms, the 'Weighted hybrid score' demonstrates superior diagnostic performance for differentiating LVOT from RVOT arrhythmias and is recommended for clinical application.

Prospero registration number: CRD42024567531.

Background: Non-dilated left ventricular cardiomyopathy (NDLVC), characterised by non-ischaemic scar/fatty replacement or isolated systolic dysfunction without dilatation, lacks validated risk stratification tools. We aimed to define cardiac magnetic resonance (CMR)-based phenotypes and evaluate their association with clinical outcomes.

Methods: In 515 patients with NDLVC (mean age 45 (16) years), three phenotypes were classified by CMR: late gadolinium enhancement (LGE+)/H- (LGE with preserved left ventricular ejection fraction (LVEF), n=130), LGE-/H+ (hypokinesia without LGE, n=226) and LGE+/H+ (LGE with reduced LVEF, n=159). The primary endpoint was all-cause death/heart transplantation; secondary endpoints included heart failure (HF) events and malignant ventricular arrhythmia (MVA).

Results: Over a mean follow-up of 6.5 (1.9) years, 29 patients (5.6%) reached the primary endpoint, while 81 (15.7%) and 19 (3.7%) experienced HF and MVA, respectively. The LGE+/H+ subgroup demonstrated the highest risk for composite clinical endpoints compared with other phenotypic groups (p<0.001). Multivariable analysis identified New York Heart Association class >II (HR 3.42, 95% CI 1.58 to 7.39, p=0.002), LVEF (HR 0.91 per 1% increase, 95% CI 0.88 to 0.95, p<0.001) and LGE extent (HR 1.14 per 3% increase, 95% CI 1.07 to 1.21, p<0.001) as independent predictors of the primary endpoint, with excellent discriminative power (C-statistic 0.862). In the adjusted model, LGE extent also independently predicted HF (HR 1.11 per 3%, 95% CI 1.06 to 1.17, p<0.001). The univariable Cox regression analysis indicated LGE extent was significantly associated with MVA (HR 1.12 per 3%, 95% CI 1.02 to 1.23, p=0.021).

Conclusion: CMR phenotyping enables risk stratification in NDLVC. LGE extent provides an objective marker to identify high-risk patients-even with preserved ejection fraction-supporting its integration into routine evaluation.