Cowie, Martin R

Hypertension is the single most important modifiable risk factor for preventable disability and death worldwide and disproportionately affects socially disadvantaged populations. We face a paradox—blood pressure control is low and recent trends suggest it is even declining, despite the availability of inexpensive and effective therapies. A variety of barriers on the system, patient, and healthcare provider side hinder effective drug-based risk factor management. Clinical inertia represents a major barrier on the clinician side, as well as workload and limited education. Common barriers on the patient side include limited English proficiency, low health literacy, and nonadherence with misaligned incentives, limited resources, lack of structured clinical pathways, and reimbursement issues. New innovations in the field of RNA-targeted therapies and device-based interventions could prevent and potentially even cure diseases previously designated as chronic health conditions, such as hypertension. Such novel therapies could potentially overcome several major barriers to effective treatment, including nonadherence. Drug development of novel, long-acting treatments requires consideration of specific clinical trial design aspects, including safety collection, benefit: risk assessment, the development and assessment of novel, qualitative surrogate end points, such as time-in-therapeutic range, the use of representative trial settings as well as the definition of standard of care in placebo-controlled trials, which should be of reasonably high-quality allowing for credible evaluation of effectiveness. Here, we provide an overview on barriers to effective treatment and a framework for trials assessing novel treatments for cardiovascular disease risk factors, including early and broad implementation programs.

SummaryThis SERVE‐HF (Treatment of Predominant Central Sleep Apnea by Adaptive Servo Ventilation in Patients With Heart Failure) sub study analysis evaluated polysomnography (PSG) data in patients with heart failure with reduced ejection fraction (HFrEF) and predominant central sleep apnea (CSA) randomised to guideline‐based medical therapy, with or without adaptive servo ventilation (ASV). Patients underwent full overnight PSG at baseline and at 12 months. All PSG recordings were analysed by a core laboratory. Only data for patients with baseline and 3‐ or 12‐month values were included. The sub study included 312 patients; the number with available PSG data differed for each variable (94–103 in the control group, 77–99 in the ASV group). After 12 months, baseline‐adjusted respiratory measures were significantly better in the ASV group versus control. Although some between‐group differences in sleep measures were seen at 12 months (e.g., better sleep efficiency in the ASV group), these were unlikely to be clinically significant. The number of periodic leg movements during sleep (PLMS) increased in the ASV group (p = 0.039). At 12 months, the respiratory arousal index was significantly lower in the ASV versus control group (p < 0.001), whilst the PLMS‐related arousal index was significantly higher in the ASV group (p = 0.04 versus control). ASV attenuated the respiratory variables characterising sleep apnea in patients with HFrEF and predominant CSA in SERVE‐HF. Sleep quality improvements during ASV therapy were small and unlikely to be clinically significant. The increase in PLMS and PLMS‐related arousals during ASV warrants further investigation, particularly relating to their potential association with increased cardiovascular risk.

Abstract Digital technology is now an integral part of medicine. Tools for detecting, screening, diagnosis, and monitoring health-related parameters have improved patient care and enabled individuals to identify issues leading to better management of their own health. Wearable technologies have integrated sensors and can measure physical activity, heart rate and rhythm, and glucose and electrolytes. For individuals at risk, wearables or other devices may be useful for early detection of atrial fibrillation or sub-clinical states of cardiovascular disease, disease management of cardiovascular diseases such as hypertension and heart failure, and lifestyle modification. Health data are available from a multitude of sources, namely clinical, laboratory and imaging data, genetic profiles, wearables, implantable devices, patient-generated measurements, and social and environmental data. Artificial intelligence is needed to efficiently extract value from this constantly increasing volume and variety of data and to help in its interpretation. Indeed, it is not the acquisition of digital information, but rather the smart handling and analysis that is challenging. There are multiple stakeholder groups involved in the development and effective implementation of digital tools. While the needs of these groups may vary, they also have many commonalities, including the following: a desire for data privacy and security; the need for understandable, trustworthy, and transparent systems; standardized processes for regulatory and reimbursement assessments; and better ways of rapidly assessing value.

Aims Remote monitoring of pulmonary artery pressure has reduced heart failure (HF) hospitalizations in chronic HF as elevation of pulmonary artery pressure provides information that can guide treatment. The venous system is characterized by high capacitance, thus substantial increases in intravascular volume can occur before filling pressures increase. The inferior vena cava (IVC) is a highly compliant venous conduit and thus a candidate for early detection of change in intravascular volume. We aimed to compare IVC cross‐sectional area using a novel sensor with cardiac filling pressures during experimental manipulation of volume status, vascular tone, and cardiac function. Methods and results Experiments were conducted in sheep to manipulate volume status (colloid infusion), vascular tone (nitroglycerin infusion) and cardiac function (rapid cardiac pacing). A wireless implantable IVC sensor was validated ex‐vivo and in‐vivo , and then used to measure the cross‐sectional area of the IVC. Right‐ and left‐sided cardiac filling pressures were obtained via right heart catheterization. The IVC sensor provided highly accurate and precise measurements of cross‐sectional area in ex‐vivo and in‐vivo validation. IVC area changes were more sensitive than the corresponding changes in cardiac filling pressures during colloid infusion ( p < 0.001), vasodilatation ( p < 0.001) and cardiac dysfunction induced by rapid pacing ( p ≤ 0.02). Conclusions Inferior vena cava area can be remotely and accurately measured in real time with a wireless implantable sensor. Changes in IVC area are more sensitive than corresponding changes in filling pressures following experimental volume loading and fluid redistribution. Additional research is warranted to understand if remote monitoring of the IVC may have advantages over pressure‐based monitors in HF.

Abstract Aims The Treatment of Sleep-Disordered Breathing with Predominant Central Sleep Apnoea by Adaptive Servo Ventilation in Patients with Heart Failure trial investigated the effects of adaptive servo-ventilation (ASV) (vs. control) on outcomes of 1325 patients with heart failure and reduced ejection fraction (HFrEF) and central sleep apnoea (CSA). The primary outcome (a composite of all-cause death or unplanned HF hospitalization) did not differ between the two groups. However, all-cause and cardiovascular (CV) mortality were higher in the ASV group. Circulating biomarkers may help in better ascertain patients' risk, and this is the first study applying a large set of circulating biomarkers in patients with both HFrEF and CSA. Methods and results Circulating protein-biomarkers (n = 276) ontologically involved in CV pathways, were studied in 749 (57% of the trial population) patients (biomarker substudy), to investigate their association with the study outcomes (primary outcome, CV death and all-cause death). The mean age was 69 ± 10 years, and &gt; 90% were male. The groups (ASV vs. control and biomarker substudy vs. no biomarker) were well balanced. The “best” clinical prognostic model included male sex, systolic blood pressure &lt; 120 mmHg, diabetes, loop diuretic, cardiac device, 6-min walking test distance, and N-terminal pro BNP as the strongest prognosticators. On top of the “best” clinical prognostic model, the biomarkers that significantly improved both the discrimination (c-index) and the net reclassification index (NRI) of the model were soluble suppression of tumorigenicity 2 for the primary outcome; neurogenic locus notch homolog protein 3 (Notch-3) for CV-death and all-cause death; and growth differentiation factor 15 (GDF-15) for all-cause death only. Conclusions We studied 276 circulating biomarkers in patients with HFrEF and central sleep apnoea; of these biomarkers, three added significant prognostic information on top of the best clinical model: soluble suppression of tumorigenicity 2 (primary outcome), Notch-3 (CV and all-cause death), and GDF-15 (all-cause death).

ABSTRACTBackground and objectiveIncreases in Cheyne–Stokes respiration (CSR) cycle length (CL), lung‐to‐periphery circulation time (LPCT) and time to peak flow (TTPF) may reflect impaired cardiac function. This retrospective analysis used an automatic algorithm to evaluate baseline CSR‐related features and then determined whether these could be used to identify patients with systolic heart failure (HF) who experienced serious adverse events in the Treatment of Sleep‐Disordered Breathing with Predominant Central Sleep Apnea by Adaptive Servo Ventilation in Patients with Heart Failure (SERVE‐HF) substudy.MethodsA total of 280 patients had overnight diagnostic polysomnography data available; an automated algorithm was applied to quantify CSR‐related features.ResultsMedian baseline CL, LPCT and TTPF were similar in the control (n = 152) and adaptive servo‐ventilation (ASV, n = 156) groups. In both groups, CSR‐related features were significantly longer in patients who did (n = 129) versus did not (n = 140) experience a primary endpoint event (all‐cause death, life‐saving cardiovascular intervention or unplanned hospitalization for worsening HF): CL, 61.1 versus 55.1 s (P = 0.002); LPCT, 36.5 versus 31.5 s (P < 0.001); TTPF, 15.20 versus 13.35 s (P < 0.001), respectively. This finding was independent of treatment allocation.ConclusionPatients with systolic HF and central sleep apnoea who experienced serious adverse events had longer CSR CL, LPCT and TTPF. Future studies should examine an independent role for CSR‐related features to enable risk stratification in systolic HF.

Abstract Aims The SERVE-HF trial investigated the impact of treating central sleep apnoea (CSA) with adaptive servo-ventilation (ASV) in patients with systolic heart failure. A preplanned substudy was conducted to provide insight into mechanistic changes underlying the observed effects of ASV, including assessment of changes in left ventricular function, ventricular remodelling, and cardiac, renal and inflammatory biomarkers. Methods and results In a subset of the 1325 randomised patients, echocardiography, cardiac magnetic resonance imaging (cMRI) and biomarker analysis were performed at baseline, and 3 and 12 months. In secondary analyses, data for patients with baseline and 12-month values were evaluated; 312 patients participated in the substudy. The primary endpoint, change in echocardiographically determined left ventricular ejection fraction from baseline to 12 months, did not differ significantly between the ASV and the control groups. There were also no significant between-group differences for changes in left ventricular dimensions, wall thickness, diastolic function or right ventricular dimensions and ejection fraction (echocardiography), and on cMRI (in small patient numbers). Plasma N-terminal pro B-type natriuretic peptide concentration decreased in both groups, and values were similar at 12 months. There were no significant between-group differences in changes in cardiac, renal and systemic inflammation biomarkers. Conclusion In patients with systolic heart failure and CSA, addition of ASV to guideline-based medical management had no statistically significant effect on cardiac structure and function, or on cardiac biomarkers, renal function and systemic inflammation over 12 months. The increased cardiovascular mortality reported in SERVE-HF may not be related to adverse remodelling or worsening heart failure.

Objective Implantable cardioverter defibrillators (ICD), cardiac resynchronisation therapy pacemakers (CRT-P) and the combination therapy (CRT-D) have been shown to reduce all-cause mortality compared with medical therapy alone in patients with heart failure and reduced EF. Our aim was to synthesise data from major randomised controlled trials to estimate the comparative mortality effects of these devices and how these vary according to patients’ characteristics. Methods Data from 13 randomised trials (12 638 patients) were provided by medical technology companies. Individual patient data were synthesised using network meta-analysis. Results Unadjusted analyses found CRT-D to be the most effective treatment (reduction in rate of death vs medical therapy: 42% (95% credible interval: 32–50%), followed by ICD (29% (20–37%)) and CRT-P (28% (15–40%)). CRT-D reduced mortality compared with CRT-P (19% (1–33%)) and ICD (18% (7–28%)). QRS duration, left bundle branch block (LBBB) morphology, age and gender were included as predictors of benefit in the final adjusted model. In this model, CRT-D reduced mortality in all subgroups (range: 53% (34–66%) to 28% (−1% to 49%)). Patients with QRS duration ≥150 ms, LBBB morphology and female gender benefited more from CRT-P and CRT-D. Men and those <60 years benefited more from ICD. Conclusions These data provide estimates for the mortality benefits of device therapy conditional upon multiple patient characteristics. They can be used to estimate an individual patient's expected relative benefit and thus inform shared decision making. Clinical guidelines should discuss age and gender as predictors of device benefits.