Artificial intelligence-assisted automated heart failure detection and classification from electronic health records.

AIMS: Electronic health records (EHR) linked to Digital Imaging and Communications in Medicine (DICOM), biological specimens, and deep learning (DL) algorithms could potentially improve patient care through automated case detection and surveillance. We hypothesized that by applying keyword searches to routinely stored EHR, in conjunction with AI-powered automated reading of DICOM echocardiography images and analysing biomarkers from routinely stored plasma samples, we were able to identify heart failure (HF) patients. METHODS AND RESULTS: We used EHR data between 1993 and 2021 from Tayside and Fife (~20% of the Scottish population). We implemented a keyword search strategy complemented by filtering based on International Classification of Diseases (ICD) codes and prescription data to EHR data set. We then applied DL for the automated interpretation of echocardiographic DICOM images. These methods were then integrated with the analysis of routinely stored plasma samples to identify and categorize patients into HF with reduced ejection fraction (HFrEF), HF with preserved ejection fraction (HFpEF), and controls without HF. The final diagnosis was verified through a manual review of medical records, measured natriuretic peptides in stored blood samples, and by comparing clinical outcomes among groups. In our study, we selected the patient cohort through an algorithmic workflow. This process started with 60 850 EHR data and resulted in a final cohort of 578 patients, divided into 186 controls, 236 with HFpEF, and 156 with HFrEF, after excluding individuals with mismatched data or significant valvular heart disease. The analysis of baseline characteristics revealed that compared with controls, patients with HFrEF and HFpEF were generally older, had higher BMI, and showed a greater prevalence of co-morbidities such as diabetes, COPD, and CKD. Echocardiographic analysis, enhanced by DL, provided high coverage, and detailed insights into cardiac function, showing significant differences in parameters such as left ventricular diameter, ejection fraction, and myocardial strain among the groups. Clinical outcomes highlighted a higher risk of hospitalization and mortality for HF patients compared with controls, with particularly elevated risk ratios for both HFrEF and HFpEF groups. The concordance between the algorithmic selection of patients and manual validation demonstrated high accuracy, supporting the effectiveness of our approach in identifying and classifying HF subtypes, which could significantly impact future HF diagnosis and management strategies. CONCLUSIONS: Our study highlights the feasibility of combining keyword searches in EHR, DL automated echocardiographic interpretation, and biobank resources to identify HF subtypes.

Exercise-based cardiac rehabilitation for adults with heart failure.

BACKGROUND: People with heart failure experience substantial disease burden that includes low exercise tolerance, poor health-related quality of life (HRQoL), increased risk of mortality and hospital admission, and high healthcare costs. The previous 2018 Cochrane review reported that exercise-based cardiac rehabilitation (ExCR) compared to no exercise control shows improvement in HRQoL and hospital admission amongst people with heart failure, as well as possible reduction in mortality over the longer term, and that these reductions appear to be consistent across patient and programme characteristics. Limitations noted by the authors of this previous Cochrane review include the following: (1) most trials were undertaken in patients with heart failure with reduced (< 45%) ejection fraction (HFrEF), and women, older people, and those with heart failure with preserved (≥ 45%) ejection fraction (HFpEF) were under-represented; and (2) most trials were undertaken in a hospital or centre-based setting. OBJECTIVES: To assess the effects of ExCR on mortality, hospital admission, and health-related quality of life of adults with heart failure. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, CINAHL, PsycINFO and Web of Science without language restriction on 13 December 2021. We also checked the bibliographies of included studies, identified relevant systematic reviews, and two clinical trials registers. SELECTION CRITERIA: We included randomised controlled trials (RCTs) that compared ExCR interventions (either exercise only or exercise as part of a comprehensive cardiac rehabilitation) with a follow-up of six months or longer versus a no-exercise control (e.g. usual medical care). The study population comprised adults (≥ 18 years) with heart failure - either HFrEF or HFpEF. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methods. Our primary outcomes were all-cause mortality, mortality due to heart failure, all-cause hospital admissions, heart failure-related hospital admissions, and HRQoL. Secondary outcomes were costs and cost-effectiveness. We used GRADE to assess the certainty of the evidence. MAIN RESULTS: We included 60 trials (8728 participants) with a median of six months' follow-up. For this latest update, we identified 16 new trials (2945 new participants), in addition to the previously identified 44 trials (5783 existing participants). Although the existing evidence base predominantly includes patients with HFrEF, with New York Heart Association (NYHA) classes II and III receiving centre-based ExCR programmes, a growing body of trials includes patients with HFpEF with ExCR undertaken in a home-based setting. All included trials employed a usual care comparator with a formal no-exercise intervention as well as a wide range of active comparators, such as education, psychological intervention, or medical management. The overall risk of bias in the included trials was low or unclear, and we mostly downgraded the certainty of evidence of outcomes upon GRADE assessment. There was no evidence of a difference in the short term (up to 12 months' follow-up) in the pooled risk of all-cause mortality when comparing ExCR versus usual care (risk ratio (RR) 0.93, 95% confidence interval (CI) 0.71 to 1.21; absolute effects 5.0% versus 5.8%; 34 trials, 36 comparisons, 3941 participants; low-certainty evidence). Only a few trials reported information on whether participants died due to heart failure. Participation in ExCR versus usual care likely reduced the risk of all-cause hospital admissions (RR 0.69, 95% CI 0.56 to 0.86; absolute effects 15.9% versus 23.8%; 23 trials, 24 comparisons, 2283 participants; moderate-certainty evidence) and heart failure-related hospital admissions (RR 0.82, 95% CI 0.49 to 1.35; absolute effects 5.6% versus 6.4%; 10 trials; 10 comparisons, 911 participants; moderate-certainty evidence) in the short term. Participation in ExCR likely improved short-term HRQoL as measured by the Minnesota Living with Heart Failure (MLWHF) questionnaire (lower scores indicate better HRQoL and a difference of 5 points or more indicates clinical importance; mean difference (MD) -7.39 points, 95% CI -10.30 to -4.77; 21 trials, 22 comparisons, 2699 participants; moderate-certainty evidence). When pooling HRQoL data measured by any questionnaire/scale, we found that ExCR may improve HRQoL in the short term, but the evidence is very uncertain (33 trials, 37 comparisons, 4769 participants; standardised mean difference (SMD) -0.52, 95% CI -0.70 to -0.34; very-low certainty evidence). ExCR effects appeared to be consistent across different models of ExCR delivery: centre- versus home-based, exercise dose, exercise only versus comprehensive programmes, and aerobic training alone versus aerobic plus resistance programmes. AUTHORS' CONCLUSIONS: This updated Cochrane review provides additional randomised evidence (16 trials) to support the conclusions of the previous 2018 version of the review. Compared to no exercise control, whilst there was no evidence of a difference in all-cause mortality in people with heart failure, ExCR participation likely reduces the risk of all-cause hospital admissions and heart failure-related hospital admissions, and may result in important improvements in HRQoL. Importantly, this updated review provides additional evidence supporting the use of alternative modes of ExCR delivery, including home-based and digitally-supported programmes. Future ExCR trials need to focus on the recruitment of traditionally less represented heart failure patient groups including older patients, women, and those with HFpEF.

Exercise-based cardiac rehabilitation for adults with heart failure - 2023 Cochrane systematic review and meta-analysis.

AIMS: Despite strong evidence, access to exercise-based cardiac rehabilitation (ExCR) remains low across global healthcare systems. We provide a contemporary update of the Cochrane review randomized trial evidence for ExCR for adults with heart failure (HF) and compare different delivery modes: centre-based, home-based (including digital support), and both (hybrid). METHODS AND RESULTS: Databases, bibliographies of previous systematic reviews and included trials, and trials registers were searched with no language restrictions. Randomized controlled trials, recruiting adults with HF, assigned to either ExCR or a no-exercise control group, with follow-up of ≥6 months were included. Two review authors independently screened titles for inclusion, extracted trial and patient characteristics, outcome data, and assessed risk of bias. Outcomes of mortality, hospitalization, and health-related quality of life (HRQoL) were pooled across trials using meta-analysis at short-term (≤12 months) and long-term follow-up (>12 months) and stratified by delivery mode. Sixty trials (8728 participants) were included. In the short term, compared to control, ExCR did not impact all-cause mortality (relative risk [RR] 0.93; 95% confidence interval [CI] 0.71-1.21), reduced all-cause hospitalization (RR 0.69; 95% CI 0.56-0.86, number needed to treat: 13, 95% CI 9-22), and was associated with a clinically important improvement in HRQoL measured by the Minnesota Living with Heart Failure Questionnaire (MLWHF) overall score (mean difference: -7.39; 95% CI -10.30 to -4.47). Improvements in outcomes with ExCR was seen across centre, home (including digitally supported), and hybrid settings. A similar pattern of results was seen in the long term (mortality: RR 0.87, 95% CI 0.72-1.04; all-cause hospitalization: RR 0.84, 95% CI 0.70-1.01, MLWHF: -9.59, 95% CI -17.48 to -1.50). CONCLUSIONS: To improve global suboptimal levels of uptake for HF patients, global healthcare systems need to routinely recommend ExCR and offer a choice of mode of delivery, dependent on an individual patient's level of risk and complexity.

Diagnosis and management of patients with left ventricular hypertrophy: Role of multimodality cardiac imaging. A scientific statement of the Heart Failure Association of the European Society of Cardiology.

Left ventricular (LV) hypertrophy consists in an increased LV wall thickness. LV hypertrophy can be either secondary, in response to pressure or volume overload, or primary, i.e. not explained solely by abnormal loading conditions. Primary LV hypertrophy may be due to gene mutations or to the deposition or storage of abnormal substances in the extracellular spaces or within the cardiomyocytes (more appropriately defined as pseudohypertrophy). LV hypertrophy is often a precursor to subsequent development of heart failure. Cardiovascular imaging plays a key role in the assessment of LV hypertrophy. Echocardiography, the first-line imaging technique, allows a comprehensive assessment of LV systolic and diastolic function. Cardiovascular magnetic resonance provides added value as it measures accurately LV and right ventricular volumes and mass and characterizes myocardial tissue properties, which may provide important clues to the final diagnosis. Additionally, scintigraphy with bone tracers is included in the diagnostic algorithm of cardiac amyloidosis. Once the diagnosis is established, imaging findings may help predict future disease evolution and inform therapy and follow-up. This consensus document by the Heart Failure Association of the European Society of Cardiology provides an overview of the role of different cardiac imaging techniques for the differential diagnosis and management of patients with LV hypertrophy.

Inflammation as a therapeutic target in heart failure with preserved ejection fraction.

Heart failure with preserved ejection fraction (HFpEF) accounts for around half of all cases of heart failure and may become the dominant type of heart failure in the near future. Unlike HF with reduced ejection fraction there are few evidence-based treatment strategies available. There is a significant unmet need for new strategies to improve clinical outcomes in HFpEF patients. Inflammation is widely thought to play a key role in HFpEF pathophysiology and may represent a viable treatment target. In this review focusing predominantly on clinical studies, we will summarise the role of inflammation in HFpEF and discuss potential therapeutic strategies targeting inflammation.

Amino acid homeostasis is a target of metformin therapy.

OBJECTIVE: Unexplained changes in regulation of branched chain amino acids (BCAA) during diabetes therapy with metformin have been known for years. Here we have investigated mechanisms underlying this effect. METHODS: We used cellular approaches, including single gene/protein measurements, as well as systems-level proteomics. Findings were then cross-validated with electronic health records and other data from human material. RESULTS: In cell studies, we observed diminished uptake/incorporation of amino acids following metformin treatment of liver cells and cardiac myocytes. Supplementation of media with amino acids attenuated known effects of the drug, including on glucose production, providing a possible explanation for discrepancies between effective doses in vivo and in vitro observed in most studies. Data-Independent Acquisition proteomics identified that SNAT2, which mediates tertiary control of BCAA uptake, was the most strongly suppressed amino acid transporter in liver cells following metformin treatment. Other transporters were affected to a lesser extent. In humans, metformin attenuated increased risk of left ventricular hypertrophy due to the AA allele of KLF15, which is an inducer of BCAA catabolism. In plasma from a double-blind placebo-controlled trial in nondiabetic heart failure (trial registration: NCT00473876), metformin caused selective accumulation of plasma BCAA and glutamine, consistent with the effects in cells. CONCLUSIONS: Metformin restricts tertiary control of BCAA cellular uptake. We conclude that modulation of amino acid homeostasis contributes to therapeutic actions of the drug.

Integrating oculomics with genomics reveals imaging biomarkers for preventive and personalized prediction of arterial aneurysms.

Objective: Arterial aneurysms are life-threatening but usually asymptomatic before requiring hospitalization. Oculomics of retinal vascular features (RVFs) extracted from retinal fundus images can reflect systemic vascular properties and therefore were hypothesized to provide valuable information on detecting the risk of aneurysms. By integrating oculomics with genomics, this study aimed to (i) identify predictive RVFs as imaging biomarkers for aneurysms and (ii) evaluate the value of these RVFs in supporting early detection of aneurysms in the context of predictive, preventive and personalized medicine (PPPM). Methods: This study involved 51,597 UK Biobank participants who had retinal images available to extract oculomics of RVFs. Phenome-wide association analyses (PheWASs) were conducted to identify RVFs associated with the genetic risks of the main types of aneurysms, including abdominal aortic aneurysm (AAA), thoracic aneurysm (TAA), intracranial aneurysm (ICA) and Marfan syndrome (MFS). An aneurysm-RVF model was then developed to predict future aneurysms. The performance of the model was assessed in both derivation and validation cohorts and was compared with other models employing clinical risk factors. An RVF risk score was derived from our aneurysm-RVF model to identify patients with an increased risk of aneurysms. Results: PheWAS identified a total of 32 RVFs that were significantly associated with the genetic risks of aneurysms. Of these, the number of vessels in the optic disc ('ntreeA') was associated with both AAA (ß = -0.36, P = 6.75e-10) and ICA (ß = -0.11, P = 5.51e-06). In addition, the mean angles between each artery branch ('curveangle_mean_a') were commonly associated with 4 MFS genes (FBN1: ß = -0.10, P = 1.63e-12; COL16A1: ß = -0.07, P = 3.14e-09; LOC105373592: ß = -0.06, P = 1.89e-05; C8orf81/LOC441376: ß = 0.07, P = 1.02e-05). The developed aneurysm-RVF model showed good discrimination ability in predicting the risks of aneurysms. In the derivation cohort, the C-index of the aneurysm-RVF model was 0.809 [95% CI: 0.780-0.838], which was similar to the clinical risk model (0.806 [0.778-0.834]) but higher than the baseline model (0.739 [0.733-0.746]). Similar performance was observed in the validation cohort, with a C-index of 0.798 (0.727-0.869) for the aneurysm-RVF model, 0.795 (0.718-0.871) for the clinical risk model and 0.719 (0.620-0.816) for the baseline model. An aneurysm risk score was derived from the aneurysm-RVF model for each study participant. The individuals in the upper tertile of the aneurysm risk score had a significantly higher risk of aneurysm compared to those in the lower tertile (hazard ratio = 17.8 [6.5-48.8], P = 1.02e-05). Conclusion: We identified a significant association between certain RVFs and the risk of aneurysms and revealed the impressive capability of using RVFs to predict the future risk of aneurysms by a PPPM approach. Our finds have great potential to support not only the predictive diagnosis of aneurysms but also a preventive and more personalized screening plan which may benefit both patients and the healthcare system. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00315-7.

Metformin: evidence from preclinical and clinical studies for potential novel applications in cardiovascular disease.

INTRODUCTION: For a long time, metformin has been the first-line treatment for glycemic control in type 2 diabetes; however, the results of recent cardiovascular outcome trials of sodium-glucose co-transporter 2 inhibitors and glucagon-like peptide 1 receptor agonists have caused many to question metformin's position in the guidelines. Although there are several plausible mechanisms by which metformin might have beneficial cardiovascular effects, for example, its anti-inflammatory effects and metabolic properties, and numerous observational data suggesting improved cardiovascular outcomes with metformin use, the main randomized clinical trial data for metformin was published over 20 years ago. Nevertheless, the overwhelming majority of participants in contemporary type 2 diabetes trials were prescribed metformin. AREAS COVERED: In this review, we will summarize the potential mechanisms of cardiovascular benefit with metformin, before discussing clinical data in individuals with or without diabetes. EXPERT OPINION: Metformin may have some cardiovascular benefit in patients with and without diabetes, however the majority of clinical trials were small and are before the use SGLT2 inhibitors and GLP1-RAs. Larger contemporary randomized trials, with metformin evaluating its cardiovascular benefit are warranted.

Biomarker signature and pathophysiological pathways in patients with chronic heart failure and metabolic syndrome.

AIM: The comorbidities that collectively define metabolic syndrome are common in patients with heart failure. However, the role of metabolic syndrome in the pathophysiology of heart failure is not well understood. We therefore investigated the clinical and biomarker correlates of metabolic syndrome in patients with heart failure. METHODS AND RESULTS: In 1103 patients with heart failure, we compared the biomarker expression using a panel of 363 biomarkers among patients with (n = 468 [42%]) and without (n = 635 [58%]) metabolic syndrome. Subsequently, a pathway overrepresentation analysis was performed to identify key biological pathways. Findings were validated in an independent cohort of 1433 patients with heart failure of whom 615 (43%) had metabolic syndrome. Metabolic syndrome was defined as the presence of three or more of five criteria, including central obesity, elevated serum triglycerides, reduced high-density lipoprotein cholesterol, insulin resistance and hypertension. The most significantly elevated biomarkers in patients with metabolic syndrome were leptin (log2 fold change 0.92, p = 5.85 × 10-21 ), fatty acid-binding protein 4 (log2 fold change 0.61, p = 1.21 × 10-11 ), interleukin-1 receptor antagonist (log2 fold change 0.47, p = 1.95 × 10-13 ), tumour necrosis factor receptor superfamily member 11a (log2 fold change 0.35, p = 4.16 × 10-9 ), and proto-oncogene tyrosine-protein kinase receptor Ret (log2 fold change 0.31, p = 4.87 × 10-9 ). Network analysis identified 10 pathways in the index cohort and 6 in the validation cohort, all related to inflammation. The primary overlapping pathway in both the index and validation cohorts was up-regulation of the natural killer cell-mediated cytotoxicity pathway. CONCLUSION: Metabolic syndrome is highly prevalent in heart failure and is associated with biomarkers and pathways relating to obesity, lipid metabolism and immune responses underlying chronic inflammation.

Plasma desmosine for prediction of outcomes after acute myocardial infarction.

Background: Elastin degradation is implicated in the pathology of vulnerable plaque. Recent studies show promising results for plasma desmosine (pDES), an elastin-specific degradation product, as a marker of cardiovascular disease (CVD) outcomes. The aim of this study was to investigate the potential role of pDES as a marker of clinical outcome in patients with acute myocardial infarction (AMI). Materials and methods: In this case-control study, we studied 236 AMI patients: 79 patients who had death and/or myocardial infarction (MI) at 2 years, and 157 patients who did not have an event at 2 years. pDES was measured using a validated liquid chromatography-tandem mass spectrometry method. Association of pDES with adverse outcomes, and the incremental value of pDES to global registry of acute coronary events (GRACE) score for risk stratification was assessed. Results: pDES levels were elevated in patients with the composite outcome of death/MI at 2 years (p = 0.002). Logistic regression analyses showed pDES to be associated with death/MI at 2 years [Odds ratio (OR) 5.99 (95% CI 1.81-19.86) p = 0.003]. pDES remained a significant predictor of death/MI at 2 years even after adjustment for age, sex, history of CVD, revascularisation, blood pressure, medications on discharge, Troponin I, and NT-proBNP levels.[OR 5.60 (95% CI 1.04-30.04) p = 0.044]. In another multivariable model including adjustment for eGFR, pDES was significantly associated with the composite outcome at 6 months, but not at 2 years follow up. DES was also able to reclassify risk stratification for death/MI at 6 months, when added to the GRACE risk model [Net Reclassification Index (NRI) 41.2 (95% CI 12.0-70.4) p = 0.006]. Conclusion: pDES concentrations predict clinical outcomes in patients with AMI, demonstrating its potential role as a prognostic marker in AMI.

Glucose-Lowering and Metabolic Effects of SGLT2 Inhibitors.

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have consistently demonstrated improved outcomes in patients with heart failure with or without type 2 diabetes; however, the mechanisms contributing to these benefits remain poorly understood. Although SGLT2 inhibitors do have glucose-lowering effects, it is unlikely that their cardiovascular benefits are solely due to improved glycemic control. This improved glycemia leads to consequent metabolic effects that could provide further explanation for their action. This review discusses the glucose-lowering and metabolic effects of SGLT2 inhibitors and how these might lead to improved cardiovascular outcomes in patients with heart failure.

Associations of Polymorphisms in the Peroxisome Proliferator-Activated Receptor Gamma Coactivator-1 Alpha Gene With Subsequent Coronary Heart Disease: An Individual-Level Meta-Analysis.

Background: The knowledge of factors influencing disease progression in patients with established coronary heart disease (CHD) is still relatively limited. One potential pathway is related to peroxisome proliferator-activated receptor gamma coactivator-1 alpha (PPARGC1A), a transcription factor linked to energy metabolism which may play a role in the heart function. Thus, its associations with subsequent CHD events remain unclear. We aimed to investigate the effect of three different SNPs in the PPARGC1A gene on the risk of subsequent CHD in a population with established CHD. Methods: We employed an individual-level meta-analysis using 23 studies from the GENetIcs of sUbSequent Coronary Heart Disease (GENIUS-CHD) consortium, which included participants (n = 80,900) with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. Three variants in the PPARGC1A gene (rs8192678, G482S; rs7672915, intron 2; and rs3755863, T528T) were tested for their associations with subsequent events during the follow-up using a Cox proportional hazards model adjusted for age and sex. The primary outcome was subsequent CHD death or myocardial infarction (CHD death/myocardial infarction). Stratified analyses of the participant or study characteristics as well as additional analyses for secondary outcomes of specific cardiovascular disease diagnoses and all-cause death were also performed. Results: Meta-analysis revealed no significant association between any of the three variants in the PPARGC1A gene and the primary outcome of CHD death/myocardial infarction among those with established CHD at baseline: rs8192678, hazard ratio (HR): 1.01, 95% confidence interval (CI) 0.98-1.05 and rs7672915, HR: 0.97, 95% CI 0.94-1.00; rs3755863, HR: 1.02, 95% CI 0.99-1.06. Similarly, no significant associations were observed for any of the secondary outcomes. The results from stratified analyses showed null results, except for significant inverse associations between rs7672915 (intron 2) and the primary outcome among 1) individuals aged ≥65, 2) individuals with renal impairment, and 3) antiplatelet users. Conclusion: We found no clear associations between polymorphisms in the PPARGC1A gene and subsequent CHD events in patients with established CHD at baseline.

Prediction of Major Adverse Cardiovascular Events From Retinal, Clinical, and Genomic Data in Individuals With Type 2 Diabetes: A Population Cohort Study.

OBJECTIVE: Improved identification of individuals with type 2 diabetes at high cardiovascular (CV) risk could help in selection of newer CV risk-reducing therapies. The aim of this study was to determine whether retinal vascular parameters, derived from retinal screening photographs, alone and in combination with a genome-wide polygenic risk score for coronary heart disease (CHD PRS) would have independent prognostic value over traditional CV risk assessment in patients without prior CV disease. RESEARCH DESIGN AND METHODS: Patients in the Genetics of Diabetes Audit and Research Tayside Scotland (GoDARTS) study were linked to retinal photographs, prescriptions, and outcomes. Retinal photographs were analyzed using VAMPIRE (Vascular Assessment and Measurement Platform for Images of the Retina) software, a semiautomated artificial intelligence platform, to compute arterial and venous fractal dimension, tortuosity, and diameter. CHD PRS was derived from previously published data. Multivariable Cox regression was used to evaluate the association between retinal vascular parameters and major adverse CV events (MACE) at 10 years compared with the pooled cohort equations (PCE) risk score. RESULTS: Among 5,152 individuals included in the study, a MACE occurred in 1,017 individuals. Reduced arterial fractal dimension and diameter and increased venous tortuosity each independently predicted MACE. A risk score combining these parameters significantly predicted MACE after adjustment for age, sex, PCE, and the CHD PRS (hazard ratio 1.11 per SD increase, 95% CI 1.04-1.18, P = 0.002) with similar accuracy to PCE (area under the curve [AUC] 0.663 vs. 0.658, P = 0.33). A model incorporating retinal parameters and PRS improved MACE prediction compared with PCE (AUC 0.686 vs. 0.658, P < 0.001). CONCLUSIONS: Retinal parameters alone and in combination with genome-wide CHD PRS have independent and incremental prognostic value compared with traditional CV risk assessment in type 2 diabetes.

Telomere length is independently associated with all-cause mortality in chronic heart failure.

OBJECTIVE: Patients with heart failure have shorter mean leucocyte telomere length (LTL), a marker of biological age, compared with healthy subjects, but it is unclear whether this is of prognostic significance. We therefore sought to determine whether LTL is associated with outcomes in patients with heart failure. METHODS: We measured LTL in patients with heart failure from the BIOSTAT-CHF Index (n=2260) and BIOSTAT-CHF Tayside (n=1413) cohorts. Cox proportional hazards analyses were performed individually in each cohort and the estimates combined using meta-analysis. Our co-primary endpoints were all-cause mortality and heart failure hospitalisation. RESULTS: In age-adjusted and sex-adjusted analyses, shorter LTL was associated with higher all-cause mortality in both cohorts individually and when combined (meta-analysis HR (per SD decrease in LTL)=1.16 (95% CI 1.08 to 1.24); p=2.66×10-5), an effect equivalent to that of being four years older. The association remained significant after adjustment for the BIOSTAT-CHF clinical risk score to account for known prognostic factors (HR=1.12 (95% CI 1.05 to 1.20); p=1.04×10-3). Shorter LTL was associated with both cardiovascular (HR=1.09 (95% CI 1.00 to 1.19); p=0.047) and non-cardiovascular deaths (HR=1.18 (95% CI 1.05 to 1.32); p=4.80×10-3). There was no association between LTL and heart failure hospitalisation (HR=0.99 (95% CI 0.92 to 1.07); p=0.855). CONCLUSION: In patients with heart failure, shorter mean LTL is independently associated with all-cause mortality.

Guideline Adherence of ß-blocker Initiating Dose and its Consequence in Hospitalized Patients With Heart Failure With Reduced Ejection Fraction.

Background: We aim to investigate the guideline adherence of ß-blocker (BB) initiating dose in Chinese hospitalized patients with heart failure with reduced ejection fraction (HFrEF) and whether the adherence affected the in-hospital outcomes. Methods: This was a retrospective study of patients hospitalized with HFrEF who had initiated BBs during their hospitalization. We defined adherence to clinical practice guidelines as initiating BB with standard dose and non-adherence to guidelines if otherwise, and examined the association between adherence to guidelines and in-hospital BB-related adverse events. Subgroup analyses based on sex, age, coronary heart disease, and hypertension were performed. Results: Among 1,104 patients with HFrEF initiating BBs during hospitalization (median length of hospitalization, 12 days), 304 (27.5%) patients received BB with non-adherent initiating dose. This non-adherence was related to a higher risk (hazard ratio [95% confidence interval]) of BB dose reduction or withdrawal (1.78 [1.42 to 2.22], P < 0.001), but not significantly associated with risks of profound bradycardia, hypotension, cardiogenic shock requiring intravenous inotropes, and severe bronchospasm requiring intravenous steroid during hospitalization. Conclusion: This study identified that over a fourth of patients had received BBs with an initiating dose that was not adherent to guidelines in Chinese hospitalized patients with HFrEF, and this non-adherence was associated with BB dose reduction or withdrawal during hospitalization.

Evidence of a Causal Relationship between Serum Thyroid-Stimulating Hormone and Osteoporotic Bone Fractures.

OBJECTIVE: We aimed to validate the association of genome-wide association study (GWAS)-identified loci and polygenic risk score with serum thyroid-stimulating hormone (TSH) concentrations and the diagnosis of hypothyroidism. Then, the causal relationship between serum TSH and osteoporotic bone fracture risk was tested. METHODS: A cross-sectional study was done among patients of European Caucasian ethnicity recruited in Tayside (Scotland, UK). Electronic medical records (EMRs) were used to identify patients and average serum TSH concentration and linked to genetic biobank data. Genetic associations were performed by linear and logistic regression models. One-sample Mendelian randomization (MR) was used to test causality of serum TSH on bone fracture risk. RESULTS: Replication in 9,452 euthyroid individuals confirmed known loci previously reported. The 58 polymorphisms accounted for 11.08% of the TSH variation (p < 1e-04). TSH-GRS was directly associated with the risk of hypothyroidism with an odds ratio (OR) of 1.98 for the highest quartile compared to the first quartile (p = 2.2e-12). MR analysis of 5,599 individuals showed that compared with those in the lowest tertile of the TSH-GRS, men in the highest tertile had a decreased risk of osteoporotic bone fracture (OR = 0.59, p = 2.4e-03), while no difference in a similar comparison was observed in women (OR = 0.93, p = 0.61). Sensitivity analysis yielded similar results. CONCLUSIONS: EMRs linked to genomic data in large populations allow replication of GWAS discoveries without additional genotyping costs. This study suggests that genetically raised serum TSH concentrations are causally associated with decreased bone fracture risk in men.

Left Ventricular Hypertrophy in Diabetic Cardiomyopathy: A Target for Intervention.

Heart failure is an important manifestation of diabetic heart disease. Before the development of symptomatic heart failure, as much as 50% of patients with type 2 diabetes mellitus (T2DM) develop asymptomatic left ventricular dysfunction including left ventricular hypertrophy (LVH). Left ventricular hypertrophy (LVH) is highly prevalent in patients with T2DM and is a strong predictor of adverse cardiovascular outcomes including heart failure. Importantly regression of LVH with antihypertensive treatment especially renin angiotensin system blockers reduces cardiovascular morbidity and mortality. However, this approach is only partially effective since LVH persists in 20% of patients with hypertension who attain target blood pressure, implicating the role of other potential mechanisms in the development of LVH. Moreover, the pathophysiology of LVH in T2DM remains unclear and is not fully explained by the hyperglycemia-associated cellular alterations. There is a growing body of evidence that supports the role of inflammation, oxidative stress, AMP-activated kinase (AMPK) and insulin resistance in mediating the development of LVH. The recognition of asymptomatic LVH may offer an opportune target for intervention with cardio-protective therapy in these at-risk patients. In this article, we provide a review of some of the key clinical studies that evaluated the effects of allopurinol, SGLT2 inhibitor and metformin in regressing LVH in patients with and without T2DM.

Precision Medicine and Adverse Drug Reactions Related to Cardiovascular Drugs.

Cardiovascular disease remains the leading global cause of death. Early intervention, with lifestyle advice alongside appropriate medical therapies, is fundamental to reduce patient mortality among high-risk individuals. For those who live with the daily challenges of cardiovascular disease, pharmacological management aims to relieve symptoms and prevent disease progression. Despite best efforts, prescription drugs are not without their adverse effects, which can cause significant patient morbidity and consequential economic burden for healthcare systems. Patients with cardiovascular diseases are often among the most vulnerable to adverse drug reactions due to multiple co-morbidities and advanced age. Examining a patient's genome to assess for variants that may alter drug efficacy and susceptibility to adverse reactions underpins pharmacogenomics. This strategy is increasingly being implemented in clinical cardiology to tailor patient therapies. The identification of specific variants associated with adverse drug effects aims to predict those at greatest risk of harm, allowing alternative therapies to be given. This review will explore current guidance available for pharmacogenomic-based prescribing as well as exploring the potential implementation of genetic risk scores to tailor treatment. The benefits of large databases and electronic health records will be discussed to help facilitate the integration of pharmacogenomics into primary care, the heartland of prescribing.