European Heart Journal - Quality of Care and Clinical Outcomes最新文献

Objectives: This study aims to analyze the variation in mortality burden of aortic aneurysms (AA) and explore the associated risk factors based on Global Burden of Disease (GBD) 2019 data, investigating the mortality burden of AA in China.

Methods: Using GBD 2019 data, the mortality burden of AA in China from 1990 to 2019 was analyzed. The age-period-cohort model was utilized to analyze time trends, period, and cohort effects of 4 attributable risk factors of AA by age.

Results: In 2019, the total number of AA deaths in China increased by 136.1% compared to 1990, while the age-standardized mortality rate (ASMR) decreased by 6.8%. Male deaths and ASMR were higher than those of females, and ASMR increased with age. Whether viewed overall (Average Annual Percent Change (AAPC): -0.261, 95% Confidence Interval (CI): -0.383 to -0.138) or by sex (female AAPC: -0.812, 95% CI: -0.977 to -0.646; male AAPC: -0.011, 95% CI: -0.183 to 0.162), the ASMR for AA in China has shown a declining trend since 1990. Attributable risk factors such as high blood pressure, a diet high in sodium, smoking, and lead exposure increase AA mortality with age. Smoking mortality peaks between ages 80-85. The cyclical effect of high blood pressure on AA mortality significantly increases, while the cyclical effects of the other three risk factors decrease. For the population born after 1940, the cohort effect of high systolic blood pressure (SBP), a diet high in sodium, and smoking increased, while the cohort effect of lead exposure decreased. The local drift values of high SBP, a diet high in sodium, and smoking decreased, while the local drift value of lead exposure increased. High SBP was identified as the most significant attributable risk factor for AA mortality burden among both males and females, and smoking was another major attributable risk factor, particularly in males.

Conclusion: From 1990 to 2019, fatality due to AA in China increased notably, but the ASMR showed a decreasing trend. The mortality rate of AA was influenced by age, sex, and attributable risk factors, with elderly male smokers carrying a heavy burden of death. Moreover, tobacco control and treatment of hypertension should be strengthened to reduce the burden and its impact on AA.

Background: An estimated two-thirds of heart failure (HF) patients with reduced ejection fraction (HFrEF) hospitalized in the United States have a severely reduced left ventricular ejection fraction (LVEF < 30%). Few studies have categorized patients according to their severity of left ventricular dysfunction beyond an LVEF of < 30%.

Methods: Intermountain Health patients (≥18 years), with a primary HF diagnosis, ≥1 inpatient hospitalization with a primary discharge diagnosis of HF, a documented LVEF of < 30%, and a BNP > 100 pg/mL within one year of hospitalization were studied. Patients were stratified by LVEF levels (≤15%, 16-25%, and 26-29%) and evaluated for death, HF hospitalization, healthcare resource utilization, and medical costs.

Results: Overall, 2 184 patients (mean age 64.2 ± 15.5 years, 72.5% male) were stratified by LVEF (≤15%, n = 468 [21.4%]; 16-25%, n = 1399 [64.1%]; and 26-29%, n = 317 [14.5%]). Lower LVEF was associated with younger age, male sex, and fewer comorbidities. Although one-year mortality differed significantly between LVEF stratifications, which remained after adjustment by risk factors (vs. LVEF 26-29% [referent]): ≤15%, hazard ratio (HR)=1.92, p < 0.0001; and 16-25%, HR = 1.42, p = 0.01), mortality was similar by 3-years. HF hospitalizations at 1- and 3-years were similar among LVEF groups. Total HF costs-driven by increased HF outpatient costs-were significantly higher among LVEF of ≤ 15%.

Conclusions: Patients with an LVEF of ≤ 15% had a modestly increased risk of 1-year mortality, as well as significantly higher total HF costs. Patients with HFrEF and a severely reduced LVEF continue to face an increased clinicoeconomic burden, and novel therapies to treat this unmet medical need are warranted.

Background: Mortality after heart transplantation can be influenced by multiple factors. This study analyzed its variation across 4 regions of the United States.

Objective: Analyze the differences in mortality among patients receiving a heart transplant across 4 regions of the United States.

Methods: Organ Procurement and Transplantation Network (OPTN)/United Network for Organ Sharing (UNOS) registry was analyzed for adult heart transplant recipients from 1987-2023. They were divided into 4 regions according to heart transplant recipients' residence: the Northeast, Midwest, South, and West. The endpoint was all-cause mortality.

Results: A total of 33,482 heart transplant recipients were included in the analysis. Baseline characteristics differed by region. The median survival (years) was lower in the South [Northeast 12.9 (6.1-17.9), Midwest 13.1 (6.5-18.1), South 11.6 (5.3-16.8), West 13.6 (7.0-18.6); p<0.0001]. Mortality incidence rate was greater in the South. When compared to the Northeast, in the unadjusted analysis, mortality was higher in the South [HR 1.13 (95%CI 1.07-1.19), p<0.001] and lower in the West [HR 0.89 (95%CI 0.83-0.94), p<0.001]. After adjusting for demographic and clinical variables, only the South retained significant differences [HR 1.17 (95%CI 1.10-1.24), p<0.001]. Mortality significantly increased in all regions after 2018.

Conclusion: Mortality of heart transplant recipients varies across region of residence in the United States. A significant increase in adjusted mortality was observed in the South. These findings suggest that there are regional disparities in the mortality rates of heart transplant recipients.

Aims: Coronary Computed Tomography Angiography (CCTA) is a first line investigation for chest pain in patients with suspected obstructive coronary artery disease (CAD). However, many acute cardiac events occur in the absence of obstructive CAD. We assessed the lifetime cost-effectiveness of integrating a novel artificial intelligence-enhanced image analysis algorithm (AI-Risk) that stratifies the risk of cardiac events by quantifying coronary inflammation, combined with the extent of coronary artery plaque and clinical risk factors, by analysing images from routine CCTA.

Methods and results: A hybrid decision-tree with population cohort Markov model was developed from 3,393 consecutive patients who underwent routine CCTA for suspected obstructive CAD and followed up for major adverse cardiac events over a median(IQR) of 7.7(6.4-9.1) years. In a prospective real-world evaluation survey of 744 consecutive patients undergoing CCTA for chest pain investigation, the availability of AI-Risk assessment led to treatment initiation or intensification in 45% of patients. In a further prospective study of 1,214 consecutive patients with extensive guideline recommended cardiovascular risk profiling, AI-Risk stratification led to treatment initiation or intensification in 39% of patients beyond the current clinical guideline recommendations. Treatment guided by AI-Risk modelled over a lifetime horizon could lead to fewer cardiac events (relative reductions of 4%, 4%, 11%, and 12% for myocardial infarction, ischaemic stroke, heart failure and cardiac death, respectively). Implementing AI-Risk classification in routine interpretation of CCTA is highly likely to be cost-effective (Incremental cost-effectiveness ratio £1,371-3,244), both in scenarios of current guideline compliance or when applied only to patients without obstructive CAD.

Conclusions: Compared with standard care, the addition of AI-Risk assessment in routine CCTA interpretation is cost effective, by refining risk guided medical management.

Background: There are currently no specialized risk-scoring systems for critically ill patients with coronary heart disease (CHD). Arterial stiffness, as measured by estimated pulse wave velocity (ePWV), has emerged as a potential indicator of mortality or adverse cardiovascular events in individuals with CHD. This study aimed to evaluate the association between ePWV and all-cause mortality among critically ill patients with CHD beyond traditional risk scores.

Methods: This study included 11 001 participants with CHD from the Medical Information Mart for Intensive Care IV, with a one-year follow-up. The primary endpoint was one-year all-cause mortality, and the secondary endpoint was in-hospital mortality.

Results: Elevated ePWV was significantly associated with higher risks of in-hospital (OR 1.15, 95% CI 1.12-1.17, p < 0.001) and one-year (HR 1.21, 95% CI 1.20-1.23, p < 0.001) mortality. These associations remained consistent when adjusted for traditional risk scores and potential confounders. When ePWV was integrated into traditional risk scoring models (OASIS, SOFA score, APSIII, SIRS score, SAPS II, and LODS score), the predictive accuracy (area under the curve: 64.55 to 70.56, 64.32 to 72.51, 72.35 to 75.80, 55.58 to 67.68, 71.27 to 73.53, 67.24 to 73.40, p < 0.001) and reclassification (net reclassification index: 0.230, 0.268, 0.257, 0.255, 0.221, 0.254; integrated discrimination improvement: 0.049, 0.072, 0.054, 0.068, 0.037, 0.061, p < 0.001) of these models significantly improved for one-year mortality. Similar results were also found for in-hospital mortality.

Conclusions: ePWV is a strong independent predictor of both short- and long-term mortality in critically ill patients with CHD. Importantly, integrating ePWV into traditional risk scores significantly boosts the predictive accuracy for one-year and in-hospital all-cause mortality.

Background and aims: In patients undergoing heart valve surgery, subsequent bacteremia and infective endocarditis are feared events. Data on the incidence and bacterial microbiological etiology following left-sided heart valve surgery are sparse.

Methods: Between 2010-2021, all patients undergoing left-sided valve surgery were identified using Danish nationwide registries. Incidence and type bacteremia within one-year post-surgery was analyzed. Secondary outcome of interest was infective endocarditis. Cumulative incidence curves were stratified for bacterial species and for subgroups of interest: type of valve surgery, age, and sex.

Results: A total of 14 935 patients were included, of which 69% were male and the median age was 70.4 years (25th-75th percentile 62.4-76.2 years). The one-year cumulative incidence of bacteremia was 6.1% (95% CI 5.7-6.5%), and the most frequent bacteremia was coagulase-negative staphylococci (27%). More than half of the bacteremia with coagulase-negative staphylococci occurred within 30 days of follow-up. Patients developing bacteremia had a significantly higher Charlson comorbidity score at baseline, more often underwent CABG concomitant to valve surgery, and more often had surgery on both valves. The one-year cumulative incidence of infective endocarditis was 1.5% (95% CI 1.3-1.7), of which 23% were caused by Enterococci, and 22% were blood culture negative. The median time from surgery to infective endocarditis was 109 days.

Conclusions: Bacteremia and infective endocarditis following left-sided heart valve surgery occurred in 6.1% and 1.5% of patients, respectively. The most frequent bacteremia was coagulase-negative staphylococci, and more than half of these occurred within 30 days of surgery. Optimization of prophylactic strategies are warranted.

Aims: Patient-reported outcome measures (PROMs) serve multiple purposes, including shared decision-making and patient communication, treatment monitoring, and health technology assessment. Patient monitoring using PROMs is constrained by recall and non-response bias, respondent burden, and missing data. We evaluated the potential of behavioural digital biomarkers obtained from a wearable accelerometer to achieve personalized predictions of PROMs.

Methods and results: Data from the multicentre, prospective SafeHeart study conducted at Amsterdam University Medical Center in the Netherlands and Copenhagen University Hospital, Rigshospitalet in Copenhagen, Denmark, were used. The study enrolled patients with an implantable cardioverter defibrillator between May 2021 and September 2022 who then wore wearable devices with raw acceleration output to capture digital biomarkers reflecting physical behaviour. To collect PROMs, patients received the Kansas City Cardiomyopathy Questionnaire (KCCQ) and EuroQoL 5-Dimensions 5-Level (EQ5D-5L) questionnaire at two instances: baseline and after six months. Multivariable Tobit regression models were used to explore associations between digital biomarkers and PROMs, specifically whether digital biomarkers could enable PROM prediction. The study population consisted of 303 patients (mean age 62.9 ± 10.9 years, 81.2% male). Digital biomarkers showed significant correlations to patient-reported physical and social limitations, severity and frequency of symptoms, and quality of life. Prospective validation of the Tobit models indicated moderate correlations between the observed and predicted scores for KCCQ [concordance correlation coefficient (CCC) = 0.49, mean difference: 1.07 points] and EQ5D-5L (CCC = 0.38, mean difference: 0.02 points).

Conclusion: Wearable digital biomarkers correlate with PROMs, and may be leveraged for real-time prediction. These findings hold promise for monitoring of PROMs through wearable accelerometers.

Background: Thirty-day readmission rate after heart failure (HF) hospitalization is widely used to evaluate healthcare quality. Methodology may substantially influence estimated rates. We assessed the impact of different definitions on HF and all-cause readmission rates.

Methods: Readmission rates were examined in 1835 patients discharged following HF hospitalization using 64 unique definitions derived from five methodological factors: (1) International Classification of Diseases-10 codes (broad vs. narrow), (2) index admission selection (single admission only first-in-year vs. random sample; or multiple admissions in year with vs. without 30-day blanking period), (3) variable denominator (number alive at discharge vs. number alive at 30 days), (4) follow-up period start (discharge date vs. day following discharge), and (5) annual reference period (calendar vs. fiscal). The impact of different factors was assessed using linear regression.

Results: The calculated 30-day readmission rate for HF varied more than two-fold depending solely on the methodological approach (6.5-15.0%). All-cause admission rates exhibited similar variation (18.8-29.9%). The highest rates included all consecutive index admissions (HF 11.1-15.0%, all-cause 24.0-29.9%), and the lowest only one index admission per patient per year (HF 6.5-11.3%, all-cause 18.8-22.7%). When including multiple index admissions and compared with blanking the 30-day post-discharge, not blanking was associated with 2.3% higher readmission rates. Selecting a single admission per year with a first-in-year approach lowered readmission rates by 1.5%, while random-sampling admissions lowered estimates further by 5.2% (P < 0.001).

Conclusion: Calculated 30-day readmission rates varied more than two-fold by altering methods. Transparent and consistent methods are needed to ensure reproducible and comparable reporting.

Aims: Previous studies on disparities in healthcare and outcomes have shown conflicting results. The aim of this study was to assess differences in baseline characteristics, management, and outcomes in myocardial infarction (MI) patients, by country of birth.

Methods and results: In total, 194 259 MI patients (64% male, 15% foreign-born) from the nationwide SWEDEHEART (The Swedish Web-system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies) registry were included and compared by geographic region of birth. The primary outcome was 1-year major adverse cardiovascular events (MACEs) including all-cause death, MI, and stroke. Secondary outcomes were long-term MACE (up to 12 years), the individual components of MACE, 30-day mortality, management, and risk factors. Logistic regression, Cox proportional hazard models, and propensity score match (PSM), accounting for baseline differences, were used. Foreign-born patients were younger, often male, and had a higher cardiovascular (CV) risk factor burden, including smoking, diabetes, and hypertension. In PSM analyses, Asia-born patients had higher likelihood of revascularization [odds ratio 1.16, 95% confidence interval (CI) 1.04-1.30], statins and beta-blocker prescription at discharge, and a 34% lower risk of 30-day mortality. Furthermore, no statistically significant differences were found in primary outcomes except for Asia-born patients having lower risk of 1-year MACE [hazard ratio (HR) 0.85, 95% CI 0.73-0.98], driven by lower mortality (HR 0.72, 95% CI 0.57-0.91). The results persisted over the long-term follow-up.

Conclusion: This study shows that in a system with universal healthcare coverage in which acute and secondary preventive treatments do not differ by country of birth, foreign-born patients, despite higher CV risk factor burden, will do at least as well as native-born patients.

Aims: To explore the relationship between remnant cholesterol (RC) and the risk of premature mortality as well as life expectancy in the general population.

Methods: We included a total of 428 804 participants from the UK Biobank for analyses. Equivalent population percentiles approach based on the low-density lipoprotein cholesterol cut-off points was performed to categorize participants into three RC groups: low (with a mean RC of 0.34 mmol/L), moderate (0.53 mmol/L), and high (1.02 mmol/L). We used multivariable Cox proportional hazards models to evaluate the relationship between RC groups and the risk of premature mortality (defined as death before age 75 years). Life table methods were used to estimate life expectancy by RC groups.

Results: During a median follow-up of 12.1 years (Q1-Q3 11.0-13.0), there were 23 693 all-cause premature deaths documented, with an incidence of 4.83 events per 1000 person-years [95% confidence interval (CI): 4.77-4.89]. Compared with the low RC group, the moderate RC group was associated with a 9% increased risk of all-cause premature mortality [hazard ratio (HR) = 1.09, 95% CI: 1.05-1.14], while the high RC group had an 11% higher risk (HR = 1.11, 95% CI: 1.07-1.16). At the age of 50 years, high RC group was associated with an average 2.2 lower years of life expectancy for females, and an average 0.1 lower years of life expectancy for males when compared with their counterparts in the low RC group.

Conclusions: Elevated RC was significantly related to an increased risk of premature mortality and a reduced life expectancy. Premature death in the general population would benefit from measurement to aid risk stratification and proactive management of RC to improve cardiovascular risk prevention efforts.