Effect on cardiovascular risk of high density lipoprotein targeted drug treatments niacin, fibrates, and CETP inhibitors: meta-analysis of randomised controlled trials including 117 411 patients

Objective To investigate the effects on cardiovascular outcomes of drug interventions that increase high density lipoprotein levels. Design Meta-analysis. Studies reviewed Therapeutic benefit of niacin, fibrates, and cholesteryl ester transfer protein (CETP) inhibitors on cardiovascular events (all cause mortality, coronary heart disease mortality, non-fatal myocardial infarction, and stroke). Results 117 411 patients were randomised in a total of 39 trials. All interventions increased the levels of high density lipoprotein cholesterol. No significant effect was seen on all cause mortality for niacin (odds ratio 1.03, 95% confidence interval 0.92 to 1.15, P=0.59), fibrates (0.98, 0.89 to 1.08, P=0.66), or CETP inhibitors (1.16, 0.93 to 1.44, P=0.19); on coronary heart disease mortality for niacin (0.93, 0.76 to 1.12, P=0.44), fibrates (0.92, 0.81 to 1.04, P=0.19), or CETP inhibitors (1.00, 0.80 to 1.24, P=0.99); or on stroke outcomes for niacin (0.96, 0.75 to 1.22, P=0.72), fibrates (1.01, 0.90 to 1.13, P=0.84), or CETP inhibitors (1.14, 0.90 to 1.45, P=0.29). In studies with patients not receiving statins (before the statin era), niacin was associated with a significant reduction in non-fatal myocardial infarction (0.69, 0.56 to 0.85, P=0.0004). However, in studies where statins were already being taken, niacin showed no significant effect (0.96, 0.85 to 1.09, P=0.52). A significant difference was seen between these subgroups (P=0.007). A similar trend relating to non-fatal myocardial infarction was seen with fibrates: without statin treatment (0.78, 0.71 to 0.86, P<0.001) and with all or some patients taking statins (0.83, 0.69 to 1.01, P=0.07); P=0.58 for difference. Conclusions Neither niacin, fibrates, nor CETP inhibitors, three highly effective agents for increasing high density lipoprotein levels, reduced all cause mortality, coronary heart disease mortality, myocardial infarction, or stroke in patients treated with statins. Although observational studies might suggest a simplistic hypothesis for high density lipoprotein cholesterol, that increasing the levels pharmacologically would generally reduce cardiovascular events, in the current era of widespread use of statins in dyslipidaemia, substantial trials of these three agents do not support this concept

Evidence that conflict regarding size of haemodynamic response to interventricular delay optimization of cardiac resynchronization therapy may arise from differences in how atrioventricular delay is kept constant.

Aims: Whether adjusting interventricular (VV) delay changes haemodynamic efficacy of cardiac resynchronization therapy (CRT) is controversial, with conflicting results. This study addresses whether the convention for keeping atrioventricular (AV) delay constant during VV optimization might explain these conflicts. / Method and results: Twenty-two patients in sinus rhythm with existing CRT underwent VV optimization using non-invasive systolic blood pressure. Interventricular optimization was performed with four methods for keeping the AV delay constant: (i) atrium and left ventricle delay kept constant, (ii) atrium and right ventricle delay kept constant, (iii) time to the first-activated ventricle kept constant, and (iv) time to the second-activated ventricle kept constant. In 11 patients this was performed with AV delay of 120 ms, and in 11 at AV optimum. At AV 120 ms, time to the first ventricular lead (left or right) was the overwhelming determinant of haemodynamics (13.75 mmHg at ±80 ms, P < 0.001) with no significant effect of time to second lead (0.47 mmHg, P = 0.50), P < 0.001 for difference. At AV optimum, time to first ventricular lead again had a larger effect (5.03 mmHg, P < 0.001) than time to second (2.92 mmHg, P = 0.001), P = 0.02 for difference. / Conclusion: Time to first ventricular activation is the overwhelming determinant of circulatory function, regardless of whether this is the left or right ventricular lead. If this is kept constant, the effect of changing time to the second ventricle is small or nil, and is not beneficial. In practice, it may be advisable to leave VV delay at zero. Specifying how AV delay is kept fixed might make future VV delay research more enlightening

Discrepancies in autologous bone marrow stem cell trials and enhancement of ejection fraction (DAMASCENE): weighted regression and meta-analysis

Objective To investigate whether discrepancies in trials of use of bone marrow stem cells in patients with heart disease account for the variation in reported effect size in improvement of left ventricular function. Design Identification and counting of factual discrepancies in trial reports, and sample size weighted regression against therapeutic effect size. Meta-analysis of trials that provided sufficient information. Data sources PubMed and Embase from inception to April 2013. Eligibility for selecting studies Randomised controlled trials evaluating the effect of autologous bone marrow stem cells for heart disease on mean left ventricular ejection fraction. Results There were over 600 discrepancies in 133 reports from 49 trials. There was a significant association between the number of discrepancies and the reported increment in EF with bone marrow stem cell therapy (Spearman’s r=0.4, P=0.005). Trials with no discrepancies were a small minority (five trials) and showed a mean EF effect size of −0.4%. The 24 trials with 1-10 discrepancies showed a mean effect size of 2.1%. The 12 with 11-20 discrepancies showed a mean effect of size 3.0%. The three with 21-30 discrepancies showed a mean effect size of 5.7%. The high discrepancy group, comprising five trials with over 30 discrepancies each, showed a mean effect size of 7.7%. Conclusions Avoiding discrepancies is difficult but is important because discrepancy count is related to effect size. The mechanism is unknown but should be explored in the design of future trials because in the five trials without discrepancies the effect of bone marrow stem cell therapy on ejection fraction is zero

The fractal heart — embracing mathematics in the cardiology clinic

For clinicians grappling with quantifying the complex spatial and temporal patterns of cardiac structure and function (such as myocardial trabeculae, coronary microvascular anatomy, tissue perfusion, myocyte histology, electrical conduction, heart rate, and blood-pressure variability), fractal analysis is a powerful, but still underused, mathematical tool. In this Perspectives article, we explain some fundamental principles of fractal geometry and place it in a familiar medical setting. We summarize studies in the cardiovascular sciences in which fractal methods have successfully been used to investigate disease mechanisms, and suggest potential future clinical roles in cardiac imaging and time series measurements. We believe that clinical researchers can deploy innovative fractal solutions to common cardiac problems that might ultimately translate into advancements for patient care

Cardiovascular Risk Factors from Early Life Predict Future Adult Cardiac Structural and Functional Abnormalities: A Systematic Review of the Published Literature

Background: Clinical practice evaluates cardiovascular risk based on current risk factor (RF) levels [Blood pressure (BP), body mass index (BMI) and glycaemic control] largely disregarding previous risk-factor history over the totality of the life course. RFs are related to contemporaneous echocardiographic measures of cardiac structure and function which in turn are independently related to cardiovascular morbidity and mortality in cross-sectional studies. However, the effect of lifetime or earlier RF history on future echocardiographic changes has never been systematically examined. Methods: A systematic review of the published literature identified 24 studies relating either earlier BP, BMI, glycaemic control or a combination to future cardiac structure and/or function. Results: The majority of studies showed that elevated BP and BMI in earlier life and greater cumulative burden of these factors resulted in worse cardiac structure up to 24 years later. Studies examining glycaemic control as a RF were few, but poorer glycaemic control in young adults was associated with increased future left ventricular mass. While only 5 papers related RFs to future cardiac function, all RFs were positively associated with worse future diastolic function. Conclusions: BP, BMI and glycaemic control measures in childhood, adolescence and early adulthood and subsequent longitudinal trajectories of BP and BMI are predictive of future abnormalities in cardiac structure and function. Lifetime RF history should be used to inform clinical practice. Further research is required to enable the identification of any sensitive periods in the life course to enable prevention when it is most likely to be effective

How robust are recommended waiting times to pacing after cardiac surgery that are derived from observational data?

AIMS: For bradycardic patients after cardiac surgery, it is unknown how long to wait before implanting a permanent pacemaker (PPM). Current recommendations vary and are based on observational studies. This study aims to examine why this variation may exist. METHODS AND RESULTS: We conducted first a study of patients in our institution and second a systematic review of studies examining conduction disturbance and pacing after cardiac surgery. Of 5849 operations over a 6-year period, 103 (1.8%) patients required PPM implantation. Only pacing dependence at implant and time from surgery to implant were associated with 30-day pacing dependence. The only predictor of regression of pacing dependence was time from surgery to implant. We then applied the conventional procedure of receiver operating characteristic (ROC) analysis, seeking an optimal time point for decision-making. This suggested the optimal waiting time was 12.5 days for predicting pacing dependence at 30 days for all patients (area under the ROC curve (AUC) 0.620, P = 0.031) and for predicting regression of pacing dependence in patients who were pacing-dependent at implant (AUC 0.769, P < 0.001). However, our systematic review showed that recommended optimal decision-making time points were strongly correlated with the average implant time point of those individual studies (R = 0.96, P < 0.001). We further conducted modelling which revealed that in any such study, the ROC method is strongly biased to indicate a value near to the median time to implant as optimal. CONCLUSION: When commonly used automated statistical methods are applied to observational data with the aim of defining the optimal time to pacing after cardiac surgery, the suggested answer is likely to be similar to the average time to pacing in that cohort

Hierarchical statistical techniques are necessary to draw reliable conclusions from analysis of isolated cardiomyocyte studies

Aims It is generally accepted that post-MI heart failure (HF) changes a variety of aspects of sarcoplasmic reticular Ca2+ fluxes but for some aspects there is disagreement over whether there is an increase or decrease. The commonest statistical approach is to treat data collected from each cell as independent, even though they are really clustered with multiple likely similar cells from each heart. In this study, we test whether this statistical assumption of independence can lead the investigator to draw conclusions that would be considered erroneous if the analysis handled clustering with specific statistical techniques (hierarchical tests). Methods and results Ca2+ transients were recorded in cells loaded with Fura-2AM and sparks were recorded in cells loaded with Fluo-4AM. Data were analysed twice, once with the common statistical approach (assumption of independence) and once with hierarchical statistical methodologies designed to allow for any clustering. The statistical tests found that there was significant hierarchical clustering. This caused the common statistical approach to underestimate the standard error and report artificially small P values. For example, this would have led to the erroneous conclusion that time to 50% peak transient amplitude was significantly prolonged in HF. Spark analysis showed clustering, both within each cell and also within each rat, for morphological variables. This means that a three-level hierarchical model is sometimes required for such measures. Standard statistical methodologies, if used instead, erroneously suggest that spark amplitude is significantly greater in HF and spark duration is reduced in HF. Conclusion Ca2+ fluxes in isolated cardiomyocytes show so much clustering that the common statistical approach that assumes independence of each data point will frequently give the false appearance of statistically significant changes. Hierarchical statistical methodologies need a little more effort, but are necessary for reliable conclusions. We present cost-free simple tools for performing these analyses

Efficient labelling for efficient deep learning: the benefit of a multiple-image-ranking method to generate high volume training data applied to ventricular slice level classification in cardiac MRI

BACKGROUND: Getting the most value from expert clinicians' limited labelling time is a major challenge for artificial intelligence (AI) development in clinical imaging. We present a novel method for ground-truth labelling of cardiac magnetic resonance imaging (CMR) image data by leveraging multiple clinician experts ranking multiple images on a single ordinal axis, rather than manual labelling of one image at a time. We apply this strategy to train a deep learning (DL) model to classify the anatomical position of CMR images. This allows the automated removal of slices that do not contain the left ventricular (LV) myocardium. METHODS: Anonymised LV short-axis slices from 300 random scans (3,552 individual images) were extracted. Each image's anatomical position relative to the LV was labelled using two different strategies performed for 5 hours each: (I) 'one-image-at-a-time': each image labelled according to its position: 'too basal', 'LV', or 'too apical' individually by one of three experts; and (II) 'multiple-image-ranking': three independent experts ordered slices according to their relative position from 'most-basal' to 'most apical' in batches of eight until each image had been viewed at least 3 times. Two convolutional neural networks were trained for a three-way classification task (each model using data from one labelling strategy). The models' performance was evaluated by accuracy, F1-score, and area under the receiver operating characteristics curve (ROC AUC). RESULTS: After excluding images with artefact, 3,323 images were labelled by both strategies. The model trained using labels from the 'multiple-image-ranking strategy' performed better than the model using the 'one-image-at-a-time' labelling strategy (accuracy 86% vs. 72%, P=0.02; F1-score 0.86 vs. 0.75; ROC AUC 0.95 vs. 0.86). For expert clinicians performing this task manually the intra-observer variability was low (Cohen's κ=0.90), but the inter-observer variability was higher (Cohen's κ=0.77). CONCLUSIONS: We present proof of concept that, given the same clinician labelling effort, comparing multiple images side-by-side using a 'multiple-image-ranking' strategy achieves ground truth labels for DL more accurately than by classifying images individually. We demonstrate a potential clinical application: the automatic removal of unrequired CMR images. This leads to increased efficiency by focussing human and machine attention on images which are needed to answer clinical questions

Resonance as the Mechanism of Daytime Periodic Breathing in Patients with Heart Failure

Rationale: In patients with chronic heart failure, daytime oscillatory breathing at rest is associated with a high risk of mortality. Experimental evidence, including exaggerated ventilatory responses to CO2 and prolonged circulation time, implicates the ventilatory control system and suggests feedback instability (loop gain > 1) is responsible. However, daytime oscillatory patterns often appear remarkably irregular versus classic instability (Cheyne-Stokes respiration), suggesting our mechanistic understanding is limited. Objectives: We propose that daytime ventilatory oscillations generally result from a chemoreflex resonance, in which spontaneous biological variations in ventilatory drive repeatedly induce temporary and irregular ringing effects. Importantly, the ease with which spontaneous biological variations induce irregular oscillations (resonance “strength”) rises profoundly as loop gain rises toward 1. We tested this hypothesis through a comparison of mathematical predictions against actual measurements in patients with heart failure and healthy control subjects. Methods: In 25 patients with chronic heart failure and 25 control subjects, we examined spontaneous oscillations in ventilation and separately quantified loop gain using dynamic inspired CO2 stimulation. Measurements and Main Results: Resonance was detected in 24 of 25 patients with heart failure and 18 of 25 control subjects. With increased loop gain—consequent to increased chemosensitivity and delay—the strength of spontaneous oscillations increased precipitously as predicted (r = 0.88), yielding larger (r = 0.78) and more regular (interpeak interval SD, r = −0.68) oscillations (P < 0.001 for all, both groups combined). Conclusions: Our study elucidates the mechanism underlying daytime ventilatory oscillations in heart failure and provides a means to measure and interpret these oscillations to reveal the underlying chemoreflex hypersensitivity and reduced stability that foretells mortality in this population