Abstract
Improved atrial fibrillation (AF) screening methods are required. We detected AF with pulse rate variability (PRV) parameters using a blood pressure device (BP+; Uscom, Sydney, Australia) ...and with a Kardia Mobile Cardiac Monitor (KMCM; AliveCor, Mountain View, CA). In 421 primary care patients (mean (range) age: 72 (31–99) years), we diagnosed AF (n = 133) from 12-lead electrocardiogram recordings, and performed PRV and KMCM measurements. PRV parameters detected AF with area under curve (AUC) values of up to 0.92. Using the mean of two sequential readings increased AUC to up to 0.94 and improved positive predictive value at a given sensitivity (by up to 18%). The KMCM detected AF with 83% sensitivity and 68% specificity. 89 KMCM recordings were “unclassified” or blank, and PRV detected AF in these with AUC values of up to 0.88. When non-AF arrhythmias (n = 56) were excluded, the KMCM device had increased specificity (73%) and PRV had higher discrimination performance (maximum AUC = 0.96). In decision curve analysis, all PRV parameters consistently achieved a positive net benefit across the range of clinical thresholds. In primary care, AF can be detected by PRV accurately and by KMCM, especially in the absence of non-AF arrhythmias or when combinations of measurements are used.
Currently, there is no generally accepted model to predict outcomes in stable coronary heart disease (CHD).
This study evaluated and compared the prognostic value of biomarkers and clinical variables ...to develop a biomarker-based prediction model in patients with stable CHD.
In a prospective, randomized trial cohort of 13,164 patients with stable CHD, we analyzed several candidate biomarkers and clinical variables and used multivariable Cox regression to develop a clinical prediction model based on the most important markers. The primary outcome was cardiovascular (CV) death, but model performance was also explored for other key outcomes. It was internally bootstrap validated, and externally validated in 1,547 patients in another study.
During a median follow-up of 3.7 years, there were 591 cases of CV death. The 3 most important biomarkers were N-terminal pro–B-type natriuretic peptide (NT-proBNP), high-sensitivity cardiac troponin T (hs-cTnT), and low-density lipoprotein cholesterol, where NT-proBNP and hs-cTnT had greater prognostic value than any other biomarker or clinical variable. The final prediction model included age (A), biomarkers (B) (NT-proBNP, hs-cTnT, and low-density lipoprotein cholesterol), and clinical variables (C) (smoking, diabetes mellitus, and peripheral arterial disease). This “ABC-CHD” model had high discriminatory ability for CV death (c-index 0.81 in derivation cohort, 0.78 in validation cohort), with adequate calibration in both cohorts.
This model provided a robust tool for the prediction of CV death in patients with stable CHD. As it is based on a small number of readily available biomarkers and clinical factors, it can be widely employed to complement clinical assessment and guide management based on CV risk. (The Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial STABILITY; NCT00799903)
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Background
Evaluation of cardiovascular prognosis in patients with stable coronary heart disease is based on clinical characteristics and biomarkers indicating dysglycemia, dyslipidemia, renal ...dysfunction, and possibly cardiac dysfunction. Inflammation plays a key role in atherosclerosis, but the association between inflammatory biomarkers and clinical outcomes is less studied in this population.
Methods and Results
Overall, 15 828 patients with coronary heart disease in the STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) trial were randomized to treatment with darapladib or placebo and observed for a median of 3.7 years. In 14 611 patients, levels of interleukin‐6 (IL‐6) and high‐sensitivity C‐reactive protein were measured in plasma samples: median levels were 2.1 (interquartile range, 1.4–3.2) ng/L and 1.3 (interquartile range, 0.6–3.1) mg/L, respectively. Associations between continuous levels or quartile groups and adjudicated outcomes were evaluated by spline graphs and Cox regression adjusted for clinical factors and cardiovascular biomarkers. IL‐6 was associated with increased risk of major adverse cardiovascular events (quartile 4 versus quartile 1 hazard ratio HR, 1.60; 95% confidence interval CI, 1.30–1.97; P<0.0001); cardiovascular death (HR, 2.15; 95% CI, 1.53–3.04; P<0.0001); myocardial infarction (HR, 1.53; 95% CI, 1.14–2.04; P<0.05); all‐cause mortality (HR, 2.11; 95% CI, 1.62–2.76; P<0.0001); and risk of hospitalization for heart failure (HR, 2.28; 95% CI, 1.34–3.89; P<0.001). Cancer death was doubled in the highest IL‐6 quartile group (HR, 2.34; 95% CI, 1.20–4.53; P<0.05). High‐sensitivity C‐reactive protein was associated with both cardiovascular and non‐cardiovascular events in the unadjusted model, but these did not remain after multivariable adjustments.
Conclusions
IL‐6, an upstream inflammatory marker, was independently associated with the risk of major adverse cardiovascular events, cardiovascular and all‐cause mortality, myocardial infarction, heart failure, and cancer mortality in patients with stable coronary heart disease. IL‐6 might reflect a pathophysiological process involved in the development of these events.
Clinical Trial Registration
URL: http://www.clinicaltrials.gov. Unique identifier: NCT00799903.
The recommended duration of dual anti-platelet therapy (DAPT) following acute coronary syndrome (ACS) varies from 1 month to 1 year depending on the balance of risks of ischaemia and major bleeding. ...We designed paired ischaemic and major bleeding risk scores to inform this decision.
New Zealand (NZ) patients with ACS investigated with coronary angiography are recorded in the All NZ ACS Quality Improvement registry and linked to national health datasets. Patients were aged 18-84 years (2012-2020), event free at 28 days postdischarge and without atrial fibrillation. Two 28-day to 1-year postdischarge multivariable risk prediction scores were developed: (1) cardiovascular mortality/rehospitalisation with myocardial infarction or ischaemic stroke (ischaemic score) and (2) bleeding mortality/rehospitalisation with bleeding (bleeding score).
In 27 755 patients, there were 1200 (4.3%) ischaemic and 548 (2.0%) major bleeding events. Both scores were well calibrated with moderate discrimination performance (Harrell's c-statistic 0.75 (95% CI, 0.74 to 0.77) and 0.69 (95% CI, 0.67 to 0 .71), respectively). Applying these scores to the 2020 European Society of Cardiology ACS antithrombotic treatment algorithm, the 31% of the cohort at elevated (>2%) bleeding and ischaemic risk would be considered for an abbreviated DAPT duration. For those at low bleeding risk, but elevated ischaemic risk (37% of the cohort), prolonged DAPT may be appropriate, and for those with low bleeding and ischaemic risk (29% of the cohort) short duration DAPT may be justified.
We present a pair of ischaemic and bleeding risk scores specifically to assist clinicians and their patients in deciding on DAPT duration beyond the first month post-ACS.
Higher growth differentiation factor 15 (GDF-15) concentrations are associated with cardiovascular (CV) and non-CV morbidity and mortality. However, information on associations between GDF-15 and the ...risk of specific CV and non-CV events in stable coronary heart disease (CHD) patients is limited.
In 14 577 patients with stable CHD participating in the Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy Trial (STABILITY), GDF-15 and other prognostic biomarkers (N-terminal pro-B-type natriuretic peptide, high-sensitivity troponin T, cystatin C, and high-sensitivity C-reactive protein) were measured. In adjusted Cox regression models, the associations between GDF-15 and the composite CV end point CV death, myocardial infarction (MI), and stroke, as well as other CV and non-CV events, were assessed.
The median concentration (interquartile range) of GDF-15 at baseline was 1253 (915-1827) ng/L. The hazard ratio for the composite end point for the highest compared to the lowest quartile of GDF-15 was 1.8 (95% CI, 1.5-2.2); for CV death, 2.63 (1.9-3.6); for sudden death, 3.06 (1.9-4.8); for heart failure (HF) death, 4.3 (1.3-14); for cancer death, 2.5 (1.3-4.7); for hospitalization for HF, 5.8 (3.2-10); for MI 1.4 (95% CI, 1.1-1.9); and for stroke, 1.8 (95% CI, 1.1-2.8). After adjustment for other prognostic biomarkers, GDF-15 remained significantly associated with all outcomes except for MI.
In stable CHD, GDF-15 was independently associated with CV, non-CV, and cancer mortality, as well as with MI and stroke. When also adjusting for other prognostic biomarkers, the associations to all fatal and nonfatal events were maintained except for MI. Information on GDF-15, therefore, might be helpful when assessing the risk of adverse outcomes in patients with stable CHD. ClinicalTrials.gov Identifier: NCT00799903.
BACKGROUND The obesity paradox states that patients with higher body mass index (BMI) and cardiovascular disease may experience better prognosis. However, this is less clear in patients with coronary ...heart disease. METHODS AND RESULTS The prospective STABILITY (Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy) trial included 15 828 patients with stable coronary heart disease with 3 to 5 years' follow-up on optimal secondary preventive treatment. BMI was measured at baseline (n=15 785). Associations between BMI and cardiovascular outcomes were evaluated by Cox regression analyses with multivariable adjustments. Mean age was 64±9 years and 19% women. Most risk markers (diabetes, hypertension, inflammatory biomarkers, triglycerides) showed a graded association with higher BMI. The frequency of smoking, levels of high-density lipoprotein, growth differentiation factor 15, and NT-proBNP (N-terminal pro-B-type natriuretic peptide) were higher at lower BMI. Low BMI (<20 kg/m
; n=244 1.5%) was associated with doubled risk of total death (hazard ratio HR, 2.27; 95% CI, 1.60-3.22), cardiovascular death (HR, 2.26; 95% CI, 1.46-3.49), and heart failure (HR, 2.51; 95% CI, 1.35-4.68) compared with BMI of 25 to <30 kg/m
(n=6752 42.8%) as reference. Similarly, high BMI of ≥35 kg/m
(n=1768 11.2%) was associated with increased risk of the same outcomes. A BMI between 20 and <25 kg/m
was associated with increased risk of cardiovascular death (HR, 1.26; 95% CI, 1.03-1.54) and total death (HR, 1.21; 95% CI, 1.03-1.42). CONCLUSIONS Patients with stable coronary heart disease showed a graded increase in cardiometabolic and inflammatory risk factors with increasing BMI category >25 kg/m
. All-cause and cardiovascular mortality were lowest at BMI of 25 to 35 kg/m
. Underweight with BMI of <20 kg/m
and very high BMI of ≥35 kg/m
were strong risk markers for poor prognosis. REGISTRATION URL: https://clinicaltrials.gov/; Unique identifier NCT00799903.
It is currently not known whether dairy food influences the risk of cardiovascular disease or diabetes. This study evaluates effects of changing dairy intake on cardio-metabolic risk factors.
180 ...healthy volunteers were randomised to increase, reduce or not change their dairy intake for 1 month in response to dietary advice. Body weight, waist circumference, blood pressure, fasting plasma lipids, insulin resistance and C-reactive protein (CRP) were measured at baseline and after 1 month and compared by dietary group.
176 (98%) subjects completed the study. Average change in self-reported dairy fat intake for increased dairy food was +0.9 SD 1.1 g/day (+71%), no change was -2.1 SD 0.4 g/day (-15%) and decreased dairy food was -10.8 SD 1.2 g/day (-77%) respectively. There was no statistically significant change in LDL or HDL cholesterol, triglycerides, systolic or diastolic blood pressure, C-reactive protein, glucose or insulin with 95% CI standard mean differences <0.2 for all and CRP <0.3. There was a small increase in weight (+0.4 kg, SD 3.1) in those asked to increase dairy food.
In healthy volunteers, dietary advice to change dairy intake for 1 month did not have a clinically significant effect on cardio-metabolic risk factors. These observations suggest that dairy food can be included as part of a normal healthy diet without increasing cardio-metabolic risk.
ACTRN12612000574842.
Clinical Endpoint Classification (CEC) in clinical trials allows FOR standardized, systematic, blinded, and unbiased adjudication of investigator-reported events. We quantified the agreement rates in ...the STABILITY trial on 15,828 patients with stable coronary heart disease.
Investigators were instructed to report all potential events. Each reported event was reviewed independently by 2 reviewers according to prespecified processes and prespecified end point definitions. Concordance between reported and adjudicated cardiovascular (CV) events was evaluated, as well as event classification influence on final study results.
In total, CEC reviewed 7,096 events: 1,064 deaths (696 CV deaths), 958 myocardial infarctions (MI), 433 strokes, 182 transient ischemic attacks, 2,052 coronary revascularizations, 1,407 hospitalizations for unstable angina, and 967 hospitalizations for heart failure. In total, 71.8% events were confirmed by CEC. Concordance was high (>80%) for cause of death and nonfatal MI and lower for hospitalization for unstable angina (25%) and heart failure (50%). For the primary outcome (composite of CV death, MI, and stroke), investigators reported 2,086 events with 82.5% confirmed by CEC. The STABILITY trial treatment effect of darapladib versus placebo on the primary outcome was consistent using investigator-reported events (hazard ratio 0.96 95% CI 0.87–1.06) or adjudicated events (hazard ratio 0.94 95% CI 0.85–1.03).
The primary outcome results of the STABILITY trial were consistent whether using investigator-reported or CEC-adjudicated events. The proportion of investigator-reported events confirmed by CEC varied by type of event. These results should help improve event identification in clinical trials to optimize ascertainment and adjudication.
In patients with coronary heart disease (CHD), atrial fibrillation (AF) is associated with increased morbidity and mortality. We investigated the associations between clinical risk factors and ...biomarkers with incident AF in patients with CHD.
Around 13,153 patients with optimally treated CHD included in the STabilization of Atherosclerotic plaque By Initiation of darapLadIb TherapY (STABILITY) trial with plasma samples obtained at randomization. Mean follow-up time was 3.5 years. The association between clinical risk factors and biomarkers with incident AF was estimated with Cox-regression models. Validation was performed in 1,894 patients with non-ST-elevation acute coronary syndrome included in the FRISC-II trial.
The median (min-max) age was 64 years (range 26-92) and 2,514 (19.1%) were women. A total of 541 patients, annual incidence rate of 1.2%, developed AF during follow-up. In multivariable models, older age, higher levels of NT-proBNP, higher body mass index (BMI), male sex, geographic regions, low physical activity, and heart failure were independently associated with increased risk of incident AF with hazard ratios ranging from 1.04 to 1.79 (P ≤ .05). NT-proBNP improved the C-index from 0.70 to 0.71. In the validation cohort, age, BMI, and NT-proBNP were associated with increased risk of incident AF with similar hazard ratios.
In patients with optimally treated CHD, the incidence of new AF was 1.2% per year. Age, NT-proBNP as a marker of impaired cardiac function, and BMI were the strongest factors, independently and consistently associated with incident AF. Male sex and low physical activity may also contribute to the risk of AF in patients with CHD.
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