Repeated Biomarker Measurements in Acquired Heart Disease: Values and Limitations

In this thesis, we investigated whether repeatedly measured blood biomarkers more prognostic information than a single baseline measurement. We have investigated this in patients with heart failure and patients who have had an acute coronary syndrome

Reproducibility of the Pleth Variability Index in premature infants

The aim was to assess the reproducibility of the Pleth Variability Index (PVI), developed for non-invasive monitoring of peripheral perfusion, in preterm neonates below 32 weeks of gestational age. Three PVI measurements were consecutively performed in stable, comfortable preterm neonates in the first 48 h of life. On each occasion, pulse oximeter sensors were attached to two different limbs for 5 min. Reproducibility was assessed with the intra-class correlation coefficient (ICC) and Bland–Altman analysis. A total of 25 preterm neonates were included. Inter-limb comparison showed fair to moderate ICC’s with 95%-confidence intervals (95%-CI). Left hand–right hand ICC = 0.498, 95%-CI (0.119–0.753); right foot–right hand ICC = 0.314 (−0.088–0.644); right foot–left foot ICC = 0.315 (−0.089–0.628). Intra-limb comparison showed fair to moderate ICC for right foot–right foot ICC = 0.380 (−0.014–0.677); and good ICC for right hand–right hand ICC = 0.646 (0.194–0.852). Bland–Altman plots showed moderate reproducibility of measurements between different limbs and of the same limb in consecutive time periods, with large biases and wide limits of agreement. The findings from this study indicate that PVI measurement is poorly reproducible when measured on different limbs and on the same limb in stable and comfortable preterm neonates

Health-related quality of life and cardiac rehabilitation: Does body mass index matter?

OBJECTIVE: To investigate the relation between body mass index class and changes in health-related quality of life in patients participating in cardiac rehabilitation. DESIGN: Prospective cohort study. PATIENTS: A total of 503 patients with acute coronary syndrome. METHODS: Data from the OPTICARE trial were used, in which health-related quality of life was measured with the MacNew Heart Disease HRQOL Instrument at the start, directly after, and 9 months after completion of cardiac rehabilitation. Patients were classed as normal weight, overweight, or obese. RESULTS: During cardiac rehabilitation, global health-related quality of life improved in patients in all classes of body mass index. Patients classed as overweight had a significantly greater improvement in social participation than those classed as normal weight (5.51-6.02 compared with 5.73-5.93, respectively; difference in change 0.30, p = 0.025). After completion of cardiac rehabilitation, health-related quality of life continued to improve similarly in patients in all classes of body mass index. CONCLUSION: Health-related quality of life improved during cardiac rehabilitation in patients of all classes of body mass index. Patients classed as overweight showed the greatest improvement. The beneficial effects were maintained during extended follow-up after completion of cardiac rehabilitation

Dataset on blood biomarkers and GRACE score measured at admission for myocardial infarction in a large secondary hospital

The GRACE score is currently the most widely used model to assess patient prognosis after myocardial infarction (MI). We have demonstrated that the prognostic performance of the GRACE score can be improved by adding blood biomarkers measured routinely at hospital admission in our study recently published in the International Journal of Cardiology: “Addition of routinely measured blood biomarkers significantly improves GRACE risk stratification in patients with myocardial infarction”. In this Data-in-Brief article we present additional original data from our dataset. This dataset consists of clinical and biomarker information and follow-up data of 2055 confirmed MI patients. In 143 of these patients the endpoint (all-cause mortality or reMI) occurred during six months follow-up. We describe the differences in baseline characteristics between ST-elevation MI (STEMI) patients and non-STEMI patients, differences in biomarker levels at admission between patients in whom the endpoint occurred and patients who remained endpoint-free, and associations of the biomarkers with the endpoint. Moreover, we show additional statistical results of analyses that compare the original GRACE-only model with our extended GRACE/biomarker model

High-frequency metabolite profiling and the incidence of recurrent cardiac events in patients with post-acute coronary syndrome

Purpose: The aim of this study was to study temporal changes in metabolite profiles in patients with post-acute coronary syndrome (ACS), in particular prior to the development of recurrent ACS (reACS). Methods: BIOMArCS (BIOMarker study to identify the Acute risk of a Coronary Syndrome) is a prospective study including patients admitted for ACS, who underwent high-frequency blood sampling during 1-year follow-up. Within BIOMArCS, we performed a nested case-cohort analysis of 158 patients (28 cases of reACS). We determined 151 metabolites by nuclear magnetic resonance in seven (median) blood samples per patient. Temporal evolution of the metabolites and their relation with reACS was assessed by joint modelling. Results are reported as adjusted (for clinical factors) hazard ratios (aHRs). Results: Median age was 64 (25th–75th percentiles; 56–72) years and 78% were men. After multiple testing correction (p < 0.001), high concentrations of extremely large very low density lipoprotein (VLDL) particles (aHR 1.60/SD increase; 95%CI 1.25–2.08), very large VLDL particles (aHR 1.60/SD increase; 95%CI 1.25–2.08) and large VLDL particles (aHR 1.56/SD increase; 95%CI 1.22–2.05) were significantly associated with reACS. Moreover, these longitudinal particle concentrations showed a steady increase over time prior to reACS. Among the other metabolites, no significant associations were observed. Conclusion: Post-ACS patients with persistent high concentrations of extremely large, very large and large VLDL particles have increased risk of reACS within 1 year

Evolution of renal function and predictive value of serial renal assessments among patients with acute coronary syndrome: BIOMArCS study

Background: Impaired renal function predicts mortality in acute coronary syndrome (ACS), but its evolution immediately following index ACS and preceding next ACS has not been described in detail. We aimed to describe this evolution using serial measurements of creatinine, glomerular filtration rate [eGFRCr] and cystatin C [CysC]. Methods: F

IgM anti-malondialdehyde low density lipoprotein antibody levels indicate coronary heart disease and necrotic core characteristics in the Nordic Diltiazem (NORDIL) study and the Integrated Imaging and Biomarker Study 3 (IBIS-3)

Background: Certain immunoglobulins (Ig) are proposed to have protective functions in atherosclerosis. Objectives: We tested whether serum levels of IgG and IgM autoantibodies against malondialdehyde low density lipoprotein (MDA-LDL) are associated with clinical coronary heart disease (CHD) and unfavorable plaque characteristics. Methods: NORDIL was a prospective study investigating adverse cardiovascular outcomes in hypertensive patients. IBIS-3 analyzed lesions in a non-culprit coronary artery with <50% stenosis using radiofrequency intravascular ultrasound (RF-IVUS) and near-infrared spectroscopy (NIRS). Imaging was repeated after a median of 386 days on rosuvastatin. Associations of antibodies with incident CHD and imaging parameters were assessed in the two sub-studies respectively. Findings: From 10,881 NORDIL patients, 87 had serum sampled at baseline and developed CHD over 4.5 years, matched to 227 controls. Higher titers of IgM anti-MDA-LDL had a protective effect on adverse outcomes, with odds ratio 0.29 (0.11, 0.76; p = 0.012; p = 0.016 for trend). Therefore, the effect was explored at the lesional level in IBIS-3. 143 patients had blood samples and RF-IVUS measurements available, and NIRS was performed in 90 of these. At baseline, IgM anti-MDA-LDL levels had a strong independent inverse relationship with lesional necrotic core volume (p = 0.027) and percentage of plaque occupied by necrotic core (p = 0.011), as well as lipid core burden index (p = 0.024) in the worst 4 mm segment. Interpretation: Our study supports the hypothesis that lower circulating levels of IgM anti-MDA-LDL are associated with clinical CHD development, and for the first time relates these findings to atherosclerotic plaque characteristics that are linked to vulnerability

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost