Potassium and the use of renin-angiotensin-aldosterone system inhibitors in heart failure with reduced ejection fraction: data from BIOSTAT-CHF.

BACKGROUND: Hyperkalaemia is a common co-morbidity in patients with heart failure with reduced ejection fraction (HFrEF). Whether it affects the use of renin-angiotensin-aldosterone system inhibitors and thereby negatively impacts outcome is unknown. Therefore, we investigated the association between potassium and uptitration of angiotensin-converting enzyme inhibitors (ACEi)/angiotensin receptor blockers (ARB) and its association with outcome. METHODS AND RESULTS: Out of 2516 patients from the BIOSTAT-CHF study, potassium levels were available in 1666 patients with HFrEF. These patients were sub-optimally treated with ACEi/ARB or beta-blockers and were anticipated and encouraged to be uptitrated. Potassium levels were available at inclusion and at 9 months. Outcome was a composite of all-cause mortality and heart failure hospitalization at 2 years. Patients' mean age was 67 ± 12 years and 77% were male. At baseline, median serum potassium was 4.3 (interquartile range 3.9-4.6) mEq/L. After 9 months, 401 (24.1%) patients were successfully uptitrated with ACEi/ARB. During this period, mean serum potassium increased by 0.16 ± 0.66 mEq/L (P  0.5 for all). CONCLUSION: Higher potassium levels are an independent predictor of enduring lower dosages of ACEi/ARB. Higher potassium levels do not attenuate the beneficial effects of ACEi/ARB uptitration

Potassium and the use of renin-angiotensin-aldosterone system inhibitors in heart failure with reduced ejection fraction: data from BIOSTAT-CHF.

BACKGROUND: Hyperkalaemia is a common co-morbidity in patients with heart failure with reduced ejection fraction (HFrEF). Whether it affects the use of renin-angiotensin-aldosterone system inhibitors and thereby negatively impacts outcome is unknown. Therefore, we investigated the association between potassium and uptitration of angiotensin-converting enzyme inhibitors (ACEi)/angiotensin receptor blockers (ARB) and its association with outcome. METHODS AND RESULTS: Out of 2516 patients from the BIOSTAT-CHF study, potassium levels were available in 1666 patients with HFrEF. These patients were sub-optimally treated with ACEi/ARB or beta-blockers and were anticipated and encouraged to be uptitrated. Potassium levels were available at inclusion and at 9 months. Outcome was a composite of all-cause mortality and heart failure hospitalization at 2 years. Patients' mean age was 67 ± 12 years and 77% were male. At baseline, median serum potassium was 4.3 (interquartile range 3.9-4.6) mEq/L. After 9 months, 401 (24.1%) patients were successfully uptitrated with ACEi/ARB. During this period, mean serum potassium increased by 0.16 ± 0.66 mEq/L (P  0.5 for all). CONCLUSION: Higher potassium levels are an independent predictor of enduring lower dosages of ACEi/ARB. Higher potassium levels do not attenuate the beneficial effects of ACEi/ARB uptitration

Biomarker-Guided Versus Guideline-Based Treatment of Patients With Heart Failure: Results From BIOSTAT-CHF

Background: Heart failure guidelines recommend up-titration of angiotensin-converting enzyme (ACE) inhibitor/angiotensin receptor blockers (ARBs), beta-blockers, and mineralocorticoid receptor antagonists (MRAs) to doses used in randomized clinical trials, but these recommended doses are often not reached. Up-titration may, however, not be necessary in all patients. Objectives: This study sought to establish the role of blood biomarkers to determine which patients should or should not be up-titrated. Methods: Clinical outcomes of 2,516 patients with worsening heart failure from the BIOSTAT-CHF (BIOlogy Study to Tailored Treatment in Chronic Heart Failure) were compared between 3 theoretical treatment scenarios: scenario A, in which all patients are up-titrated to >50% of recommended doses; scenario B, in which patients are up-titrated according to a biomarker-based treatment selection model; and scenario C, in which no patient is up-titrated to >50% of recommended doses. The study conducted multivariable Cox regression using 161 biomarkers and their interaction with treatment, weighted for treatment-indication bias to estimate the expected number of deaths or heart failure hospitalizations at 24 months for all 3 scenarios. Results: Estimated death or hospitalization rates in 1,802 patients with available (bio)markers were 16%, 16%, and 26%, respectively, in the ACE inhibitor/ARB up-titration scenarios A, B, and C. Similar rates for beta-blocker and MRA up-titration scenarios A, B, and C were 23%, 19%, and 24%, and 12%, 11%, and 24%, respectively. If up-titration was successful in all patients, an estimated 9.8, 1.3, and 12.3 events per 100 treated patients could be prevented at 24 months by ACE inhibitor/ARB, beta-blocker, and MRA therapy, respectively. Similar numbers were 9.9, 4.7, and 13.1 if up-titration treatment decision was based on a biomarker-based treatment selection model. Conclusions: Up-titrating patients with heart failure based on biomarker values might have resulted in fewer deaths or hospitalizations compared with a hypothetical scenario in which all patients were successfully up-titrated

Biomarker-Guided Versus Guideline-Based Treatment of Patients With Heart Failure: Results From BIOSTAT-CHF

Background: Heart failure guidelines recommend up-titration of angiotensin-converting enzyme (ACE) inhibitor/angiotensin receptor blockers (ARBs), beta-blockers, and mineralocorticoid receptor antagonists (MRAs) to doses used in randomized clinical trials, but these recommended doses are often not reached. Up-titration may, however, not be necessary in all patients. Objectives: This study sought to establish the role of blood biomarkers to determine which patients should or should not be up-titrated. Methods: Clinical outcomes of 2,516 patients with worsening heart failure from the BIOSTAT-CHF (BIOlogy Study to Tailored Treatment in Chronic Heart Failure) were compared between 3 theoretical treatment scenarios: scenario A, in which all patients are up-titrated to >50% of recommended doses; scenario B, in which patients are up-titrated according to a biomarker-based treatment selection model; and scenario C, in which no patient is up-titrated to >50% of recommended doses. The study conducted multivariable Cox regression using 161 biomarkers and their interaction with treatment, weighted for treatment-indication bias to estimate the expected number of deaths or heart failure hospitalizations at 24 months for all 3 scenarios. Results: Estimated death or hospitalization rates in 1,802 patients with available (bio)markers were 16%, 16%, and 26%, respectively, in the ACE inhibitor/ARB up-titration scenarios A, B, and C. Similar rates for beta-blocker and MRA up-titration scenarios A, B, and C were 23%, 19%, and 24%, and 12%, 11%, and 24%, respectively. If up-titration was successful in all patients, an estimated 9.8, 1.3, and 12.3 events per 100 treated patients could be prevented at 24 months by ACE inhibitor/ARB, beta-blocker, and MRA therapy, respectively. Similar numbers were 9.9, 4.7, and 13.1 if up-titration treatment decision was based on a biomarker-based treatment selection model. Conclusions: Up-titrating patients with heart failure based on biomarker values might have resulted in fewer deaths or hospitalizations compared with a hypothetical scenario in which all patients were successfully up-titrated

Reproducibility of telomere length assessment: an international collaborative study

BACKGROUND: Telomere length is a putative biomarker of ageing, morbidity and mortality. Its application is hampered by lack of widely applicable reference ranges and uncertainty regarding the present limits of measurement reproducibility within and between laboratories. METHODS: We instigated an international collaborative study of telomere length assessment: 10 different laboratories, employing 3 different techniques [Southern blotting, single telomere length analysis (STELA) and real-time quantitative PCR (qPCR)] performed two rounds of fully blinded measurements on 10 human DNA samples per round to enable unbiased assessment of intra- and inter-batch variation between laboratories and techniques. RESULTS: Absolute results from different laboratories differed widely and could thus not be compared directly, but rankings of relative telomere lengths were highly correlated (correlation coefficients of 0.63-0.99). Intra-technique correlations were similar for Southern blotting and qPCR and were stronger than inter-technique ones. However, inter-laboratory coefficients of variation (CVs) averaged about 10% for Southern blotting and STELA and more than 20% for qPCR. This difference was compensated for by a higher dynamic range for the qPCR method as shown by equal variance after z-scoring. Technical variation per laboratory, measured as median of intra- and inter-batch CVs, ranged from 1.4% to 9.5%, with differences between laboratories only marginally significant (P = 0.06). Gel-based and PCR-based techniques were not different in accuracy. CONCLUSIONS: Intra- and inter-laboratory technical variation severely limits the usefulness of data pooling and excludes sharing of reference ranges between laboratories. We propose to establish a common set of physical telomere length standards to improve comparability of telomere length estimates between laboratories

Genetic variants previously associated with resting heart rate used for Mendelian randomization.

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S2 Checklist -

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Association of resting heart rate polygenic risk score and incident AF adjusted for resting heart rate in the AFGen consortium.

The results of a regression analyses of the Heart rate PRS and incident AF adjusted for heart rate is shown. The Heart rate PRS should not be associated with incident AF if adjusted for heart rate; this would be evidence for pleiotropic effects of the Heart rate PRS. Fig 3A shows the results of the regression performed in the strata with instrumental variable-free resting heart rate below 65 bpm of the strata (p = 0.052), Fig 3B shows the results of the regression performed in the strata with instrumental variable-free resting heart rate between 65 and 75 bpm (p = 0.111), and Fig 3C shows the results of the regression performed in the strata with instrumental variable-free resting heart rate of and above 75 bpm (p = 0.778). I2 reflects heterogeneity between studies, higher values reflect greater heterogeneity. Abbreviations: ARIC = Atherosclerosis Risk in Communities study, bpm = beats per minute, FHS = Framingham Heart Study, I2 = heterogeneity, MESA = Multi-Ethnic Study of Atherosclerosis, PREVEND = Prevention of Renal and Vascular End-stage Disease study, PROSPER = PROspective Study of Pravastatin in the Elderly at Risk study, PRS = polygenic risk score, RS = Rotterdam Study, se = standard error of the effect size, SHIP = Study of Health in Pomerania, t2 = between study variance. (PNG)</p

Characteristics of individuals of European ancestry included in the participating cohorts of AFGen.

Characteristics of individuals of European ancestry included in the participating cohorts of AFGen.</p

Visualization of the ratio estimator.

Visualization of the ratio estimator.</p