Comparison of interleukin-6 and high-sensitivity C-reactive protein for cardiovascular risk assessment: Findings from the MESA study.

BACKGROUND AND AIMS: Inflammation is a risk factor for major adverse cardiovascular events (MACE). Elevated levels of both high-sensitivity C-reactive protein (hsCRP) and interleukin-6 (IL6) have been associated with MACE. However, few studies have compared IL6 to hsCRP for cardiovascular risk assessment. Using the MESA (Multi-Ethnic Study of Atherosclerosis) study cohort, we aim to compare IL6 to hsCRP. METHODS: We divided IL6 and hsCRP by their median values and created 4 groups i.e., low-low, high-low, low-high and high-high. The median follow-up was 14 years. RESULTS: 6614 (97 %) participants had complete baseline IL6 and hsCRP data. The correlation between hsCRP and IL6 was modest (Rho = 0.53). IL6 ≥1.2 pg/mL (median) was present in 3309 participants, and hsCRP ≥1.9 mg/L (median) was present in 3339 participants. Compared to participants with low IL6 and low hsCRP, those with high IL6 and high hsCRP were older (64 vs. 60 years), more frequently women (63 % vs. 45 %), and with more cardiovascular co-morbidities. hsCRP outcome associations lost statistical significance when adjusting for IL6: MACE HR (95 %CI) 1.06 (0.93-1.20), p =0.39, whereas IL6 associations remained significant after adjusting for hsCRP: HR (95 %CI) 1.44 (1.25-1.64), p <0.001. The C-index of Framingham score for did not improve with hsCRP but improved with IL6. Compared to participants with low IL6 and low hsCRP, those with high IL6, regardless of hsCRP, experienced an increased risk of MACE, heart failure and mortality. CONCLUSIONS: In a diverse and asymptomatic population, IL6 showed a stronger association with atherosclerotic, heart failure and fatal outcomes than hsCRP.

Missed opportunities in the diagnosis of heart failure: a real-world assessment.

AIMS: Heart failure (HF) is a leading cause of hospitalization worldwide. An early HF diagnosis is key to reducing hospitalizations. We used electronic health records (EHRs) to characterize HF pathways at the primary care physician (PCP) level prior to a first HF hospitalization (hHF). This study aimed to identify missed opportunities for HF diagnosis and management at the PCP level before a first hHF. METHODS AND RESULTS: This cohort study used EHRs of a large health care organization in Portugal. Patients with incident hHF between 2017 and 2020 were identified. Missed opportunities were defined by the absence of any of the following work-up in the 6 months after signs or symptoms had been recorded: lab results and electrocardiogram, natriuretic peptides, echocardiogram, referral to HF specialist, or HF medication initiation. A total of 2436 patients with a first hHF were identified. The median (interquartile range) age at the time of hospitalization was 81 (14) years, and 1361 (56%) were women. Most patients were treated with cardiovascular drugs prior or at index event. A total of 720 (30%) patients had records of HF signs or symptoms, 94% (n = 674) within 6 months prior to hHF. Among patients with recorded HF signs or symptoms, 410 (57%) had clinical management considered adequate before signs and symptoms were recorded. Of the 310 remaining patients, 155 (50%) had a follow-up that was considered inadequate. CONCLUSIONS: Relatively few patients with a first hHF had primary care records of signs or symptoms prior to admission. Of these, nearly half had inadequate management considering diagnosis and treatment. These data suggest the need to improve PCP HF awareness.

StatelO - Open Source Economic Input-Output Models for the 50 States of the United States of America.

Subnational input-output (IO) tables capture industry- and region-specific production, consumption, and trade of commodities and serve as a common basis for regional and multi-regional economic impact analysis. However, subnational IO tables are not made available by national statistical offices, especially in the United States (US), nor have they been estimated with transparent methods for reproducibility or updated regularly for public availability. In this article, we describe a robust StateIO modeling framework to develop state and two-region IO models for all 50 states in the US using national IO tables and state industry and trade data from reliable public sources such as the US Bureau of Economic Analysis. We develop 2012-2017 state IO models and two-region IO models at the BEA summary level. The two regions are state of interest and rest of the US. All models are validated by a series of rigorous checks to ensure the results are balanced at state and national levels. We then use these models to calculate a 2012-2017 time series of macro economic indicators and highlight results for I I states that have distinct economies with respect to size, geography, and industry structure. We also compare selected indicators to state IO models created by popular licensed and open-source software. Our StateIO modeling framework is consolidated in an open-source R package, stateior, to ensure transparency and reproducibility. Our StateIO models are US-focused, which may not be transferrable to international accounts, and form the economic base of state versions of the US environmentally-extended IO models.

Biomarker-based assessment of collagen cross-linking identifies patients at risk of heart failure more likely to benefit from spironolactone effects on left atrial remodelling. Insights from the HOMAGE clinical trial.

AIMS: The HOMAGE randomized trial found that spironolactone reduced left atrial volume index (LAVI), E:A ratio, and a marker of collagen type I synthesis (procollagen type I C-terminal propeptide) in patients at risk of heart failure (HF). Previous trials showed that patients with HF, preserved ejection fraction and low serum collagen type I C-terminal telopeptide to matrix metalloproteinase-1 ratio (CITP:MMP-1), associated with high collagen cross-linking, had less improvement in diastolic function with spironolactone. We evaluated the interaction between serum CITP:MMP-1 and spironolactone on cardiac function in the HOMAGE trial. METHODS AND RESULTS: Patients at risk of HF were randomized to spironolactone (n = 260) or not (n = 255). Blood sampling and echocardiography were done at baseline, one and nine months. CITP:MMP-1 was used as an indirect measure of collagen cross-linking. Higher baseline CITP:MMP-1 (i.e. lower collagen cross-linking) was associated with greater reductions in LAVI with spironolactone at both one (p = 0.003) and nine (p = 0.01) months, but no interaction was observed for E:A ratio. Spironolactone reduced LAVI after one and nine months only for those patients in the third tertile of CITP:MMP-1 (estimated lowest collagen cross-linking) [mean differencesspiro/control : -1.77 (95% confidence interval, CI -2.94 to -0.59) and -2.52 (95% CI -4.46 to -0.58) mL/m2 ; interaction pacross-tertiles  = 0.005; interaction pthird tertile  = 0.008] with a similar trend for N-terminal pro-B-type natriuretic peptide which was consistently reduced by spironolactone only in the lowest collagen cross-linking tertile [mean differencesspiro/control : -0.47 (95% CI -0.66 to -0.28) and -0.31 (95% CI -0.59 to -0.04) ng/L; interaction pacross-tertiles  = 0.09; interaction pthird tertile < 0.001]. CONCLUSIONS: These findings suggest that, for patients at risk of HF, the effects of spironolactone on left atrial remodelling may be more prominent in patients with less collagen cross-linking (indirectly assessed by serum CITP:MMP-1).

The Future of Meat: Health Impact Assessment with Randomized Evidence.

Massive animal farming for meat production poses major problems in terms of resource use, environmental impact, and biodiversity. Furthermore, excessive meat consumption has been associated with multiple deleterious health consequences. However, more and better-designed randomized trials are needed to increase the level of evidence on the health impacts of meat. Novel meat alternatives, such as plant- and cell-based meat, are much less impactful to the environment and might replace traditional animal meat in the future, but, despite promising early data, the health consequences of these novel products need further study. This manuscript focuses on the health impacts of meat over 3 main sections: 1) overview of the evidence highlighting the association of meat consumption with health; 2) novel alternatives to meat, including plant-based and cell-based alternatives; and 3) examine the rationale for randomized studies to evaluate the effects of the novel meat alternatives compared with the standard animal meat.

Income level and inequality as complement to geographical differences in cardiovascular trials.

BACKGROUND: Analyses of country or regional differences in cardiovascular (CV) trials are based on geographical subgroup analyses. However, apart from map location and related racial, ethnic, and genetic variations, identified differences may also depend on social structure and provision and access to health care, for which country income and income inequality are indicators. The aim of the study was to examine the association between country per capita income and income inequality and prognosis in patients with heart failure or an acute coronary syndrome in 3 international trials (EMPHASIS-HF, EPHESUS, and EXAMINE). METHODS: Countries were classified into high income or low-middle income (LMICs) and into low, middle, or high inequality using the Gini index. The main outcome measures were all-cause and CV death. RESULTS: Patients from LMICs and countries with higher inequality were younger, were less often white, had fewer comorbid conditions, and were less often treated with guideline-recommended therapies, including devices. These patients had higher adjusted mortality rates (+15% to +70%) compared with patients from high-income countries and countries with less inequality. Patients from countries with the combination of greater inequality and low-middle income had particularly high mortality rates (+80% to +190%) compared with those that did not have both characteristics. Living in a country that is poor and has inequality had more impact on death rates than any comorbidity. These findings were reproduced in 3 trials. CONCLUSIONS: Patients from LMICs and countries with greater inequality had the highest mortality rates. The prognostic impact of income and inequality is substantial and should be considered when looking into subgroup differences in CV trials.

Income Inequality and Outcomes in Heart Failure: A Global Between-Country Analysis.

OBJECTIVES: This study examined the relationship between income inequality and heart failure outcomes. BACKGROUND: The income inequality hypothesis postulates that population health is influenced by income distribution within a society, with greater inequality associated with worse outcomes. METHODS: This study analyzed heart failure outcomes in 2 large trials conducted in 54 countries. Countries were divided by tertiles of Gini coefficients (where 0% represented absolute income equality and 100% represented absolute income inequality), and heart failure outcomes were adjusted for standard prognostic variables, country per capita income, education index, hospital bed density, and health worker density. RESULTS: Of the 15,126 patients studied, 5,320 patients lived in Gini coefficient tertile 1 countries (coefficient: <33%), 6,124 patients lived in tertile 2 countries (33% to 41%), and 3,772 patients lived in tertile 3 countries (>41%). Patients in tertile 3 were younger than tertile 1 patients, were more often women, and had less comorbidity and several indicators of less severe heart failure, yet the tertile 3-to-1 hazard ratios (HRs) for the primary composite outcome of cardiovascular death or heart failure hospitalization were 1.57 (95% confidence interval [CI]: 1.38 to 1.79) and 1.48 for all-cause death (95% CI: 1.29 to 1.71) after adjustment for recognized prognostic variables. After additional adjustments were made for per capita income, education index, hospital bed density, and health worker density, these HRs were 1.46 (95% CI: 1.25 to 1.70) and 1.30 (95% CI: 1.10 to 1.53), respectively. CONCLUSIONS: Greater income inequality was associated with worse heart failure outcomes, with an impact similar to those of major comorbidities. Better understanding of the societal and personal bases of these findings may suggest approaches to improve heart failure outcomes.

Relationship Between Enrolling Country Income Level and Patient Profile, Protocol Completion, and Trial End Points.

BACKGROUND: Globalization of clinical trials fosters inclusion of higher and lower income countries, but the influence of enrolling country income level on heart failure trial performance is unclear. This study sought to evaluate associations between enrolling country income level, acute heart failure patient profile, protocol completion, and trial end points. METHODS AND RESULTS: The ASCEND-HF (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) trial included 7141 patients with acute heart failure from 30 countries. Country income data in gross national income per capita in current US dollars from the year 2007 (ie, the year trial enrollment began) were abstracted from the World Bank. Patients were grouped by enrolling country income level (ie, high [>$11 455], upper middle [$3706-$11 455], lower middle [$936-$3705], and low [<$936]). Income data were available for 29 (97%) countries (N=7064). There were 3996 (57%), 1518 (21%), and 1550 (22%) patients from high-income, upper-middle-income, and lower-middle-income countries, respectively. There were no patients from low-income countries. Patients from lower-middle-income countries tended to be younger with fewer comorbidities and lower utilization of guideline-directed therapies. Rates of adverse events (13.8%) and protocol noncompletion (4.9%) during 180-day follow-up were highest among high-income countries (all P <0.01). After adjustment for race, geographic region, and clinical characteristics, compared with lower-middle-income countries, enrollment from higher income countries was associated with increased 30-day mortality or rehospitalization (high income: odds ratio, 1.70; 95% CI, 1.02-2.85; upper-middle-income: odds ratio, 2.16; 95% CI, 1.23-3.81), driven by higher rates of rehospitalization. Mortality was similar at 30 and 180 days. The association between higher country income and the 30-day composite end point was similar across geographic regions, with exception of Latin America ( P for interaction, 0.03). CONCLUSIONS: In this global acute heart failure trial, patients from higher income countries had lower rates of protocol completion, higher rates of adverse events, and similar mortality rates. After adjustment for race, geographic region, and clinical factors, enrollment from a higher income country was associated with worse clinical outcomes, driven by higher rates of rehospitalization. Variation in enrolling country income level may influence study end points and trial performance independent of geographic region. CLINICAL TRIAL REGISTRATION: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00475852.

Geographic differences in heart failure trials.

Randomized controlled trials (RCTs) are essential to develop advances in heart failure (HF). The need for increasing numbers of patients (without substantial cost increase) and generalization of results led to the disappearance of international boundaries in large RCTs. The significant geographic differences in patients' characteristics, outcomes, and, most importantly, treatment effect observed in HF trials have recently been highlighted. Whether the observed regional discrepancies in HF trials are due to trial-specific issues, patient heterogeneity, structural differences in countries, or a complex interaction between factors are the questions we propose to debate in this review. To do so, we will analyse and review data from HF trials conducted in different world regions, from heart failure with preserved ejection fraction (HF-PEF), heart failure with reduced ejection fraction (HF-REF), and acute heart failure (AHF). Finally, we will suggest objective and actionable measures in order to mitigate regional discrepancies in future trials, particularly in HF-PEF where prognostic modifying treatments are urgently needed and in which trials are more prone to selection bias, due to a larger patient heterogeneity.