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Aims: We aimed to determine the association between serum interleukin-6 (IL-6) concentrations and new-onset heart failure (HF) in persons with type 2 diabetes (T2D)., Methods and Results: We performed a case-control study nested in the Diabetes Care System Cohort, a prospective cohort of persons with T2D in primary care. We included 724 participants, of whom 141 developed HF during 5 years of follow-up and 583 were age- and sex-matched controls. IL-6 was measured at baseline and categorized into four groups: Group 1 was composed of participants with IL-6 below the detection limit of 1.5 pg/mL, and the remainder were divided into tertiles. We performed logistic regression analyses with categorized IL-6 or continuous IL-6 as the determinant and new-onset HF as the outcome adjusted for follow-up time, age, sex, glycated haemoglobin, estimated glomerular filtration rate, albumin/creatinine ratio, and cardiovascular disease at baseline. Effect modification by sex was tested. Participants were 70.7 ± 9.0 years, and 38% were women. In comparison with Group 1, all tertiles were associated with an increased risk of HF with odds ratios of 2.1 [95% confidence interval (CI): 1.2-2.9], 2.8 (95% CI: 2.0-3.7), and 2.1 (95% CI: 1.3-3.0), respectively, for Tertiles 1-3. Continuous IL-6 was associated with the development of HF with an odds ratio of 1.2 (95% CI: 1.0-1.5). No effect modification by sex was observed., Conclusions: Higher IL-6 levels are associated with the development of HF in persons with T2D. Further research should determine whether IL-6-lowering interventions could prevent the development of HF., (© 2024 The Authors. ESC Heart Failure published by John Wiley & Sons Ltd on behalf of European Society of Cardiology.)

Aims The HFA-PEFF score was developed to optimize diagnosis and to aid in early recognition of heart failure (HF) with preserved ejection fraction (HFpEF) in patients who present with HF-like symptoms. Recognizing early-HFpEF phenogroups is essential to better understand progression towards overt HFpEF and pave the way for early intervention and treatment. Whether the HFA-PEFF domain scores can identify ‘early-HFpEF’ phenogroups remains unknown. The aims of this pilot study are to (i) identify distinct phenogroups by cluster analysis of HFA-PEFF domain scores in subjects that present with HF-like symptoms and (ii) study whether these phenogroups may be associated with distinct blood proteome profiles. Methods and results Subjects referred to the Cardiology Centers of the Netherlands, location Utrecht, with non-acute possibly cardiac-related symptoms (such as dyspnoea or fatigue) were prospectively enrolled in the HELPFul cohort (N = 507) and were included in the current analysis. Inclusion criteria for this study were (i) age ≥ 45 years and (ii) a left ventricular ejection fraction (LVEF) ≥ 50%, in the absence of a history of HF, coronary artery disease, congenital heart disease, or any previous cardiac interventions. Multinominal-based clustering with latent class model using the HFA-PEFF domain scores (functional, structural, and biomarker scores) as input was used to detect distinct phenotypic clusters. For each bootstrapping run, the 92 Olink proteins were analysed for their association with the identified phenogroups. Four distinct phenogroups were identified in the current analysis (validated by bootstrapping 1000×): (i) no left ventricular diastolic dysfunction (no LVDD, N = 102); (ii) LVDD with functional left ventricular (LV) abnormalities (N = 204); (iii) LVDD with functional and structural LV abnormalities (N = 204); and (iv) LVDD with functional and structural LV abnormalities and elevated BNP (N = 107). The HFA-PEFF total score risk categories significantly differed between the phenogroups (P < 0.001), with an increase of the HFA-PEFF score from Phenogroup 1 to 4 (low/intermediate/high HFA-PEFF risk score: Phenogroup 1: 88%/12%/0%; Phenogroup 2: 9%/91%/0%; Phenogroup 3: 0%/92%/8%; Phenogroup 4: 5%/83%/12%). Thirty-two out of the 92 Olink protein biomarkers significantly differed among the phenogroups. The top eight biomarkers—N-terminal prohormone brain natriuretic peptide, growth differentiation factor-15, matrix metalloproteinase-2, osteoprotegerin, tissue inhibitor of metalloproteinase-4, chitinase-3-like protein 1, insulin-like growth factor-binding protein 2, and insulin-like growth factor-binding protein 7—are mainly involved in inflammation and extracellular matrix remodelling, which are currently proposed key processes in HFpEF pathophysiology. Conclusions This study identified distinct phenogroups by using the HFA-PEFF domain scores in ambulant subjects referred for HF-like symptoms. The newly identified phenogroups accompanied by their circulating biomarkers profile might aid in a better understanding of the pathophysiological processes involved during the early stages of the HFpEF syndrome. [ABSTRACT FROM AUTHOR]

Aim: Diagnosing heart failure with preserved ejection fraction (HFpEF) in the non‐acute setting remains challenging. Natriuretic peptides have limited value for this purpose, and a multitude of studies investigating novel diagnostic circulating biomarkers have not resulted in their implementation. This review aims to provide an overview of studies investigating novel circulating biomarkers for the diagnosis of HFpEF and determine their risk of bias (ROB). Methods and results: A systematic literature search for studies investigating novel diagnostic HFpEF circulating biomarkers in humans was performed up until 21 April 2020. Those without diagnostic performance measures reported, or performed in an acute heart failure population were excluded, leading to a total of 28 studies. For each study, four reviewers determined the ROB within the QUADAS‐2 domains: patient selection, index test, reference standard, and flow and timing. At least one domain with a high ROB was present in all studies. Use of case‐control/two‐gated designs, exclusion of difficult‐to‐diagnose patients, absence of a pre‐specified cut‐off value for the index test without the performance of external validation, the use of inappropriate reference standards and unclear timing of the index test and/or reference standard were the main bias determinants. Due to the high ROB and different patient populations, no meta‐analysis was performed. Conclusion: The majority of current diagnostic HFpEF biomarker studies have a high ROB, reducing the reproducibility and the potential for clinical care. Methodological well‐designed studies with a uniform reference diagnosis are urgently needed to determine the incremental value of circulating biomarkers for the diagnosis of HFpEF. [ABSTRACT FROM AUTHOR]

Carriers of multidrug-resistant bacteria are at risk of infections with these bacteria; the precise size of this risk is unclear. We aimed to quantify the effect of gut colonisation on subsequent risk of infection with multidrug-resistant bacteria. We performed a systematic review and meta-regression analysis. We searched PubMed, Embase, Web of Science Core Collection, and Google Scholar for follow-up studies published from Jan 1, 1995, to March 17, 2022, that measured the incidence of infections with multidrug-resistant Gram-negative bacteria (MDR-GNB) and from Jan 1, 1995, to March 15, 2022, that measured the incidence of infections with vancomycin-resistant enterococci (VRE). We included original cohort studies and case-control studies that used incidence-density sampling, included 50 or more patients with enteric colonisation or positive urinary samples as a surrogate marker of colonisation, or both, and analysed infections clearly preceded by colonisation. We did not use any language restrictions. We excluded studies not reporting length of follow-up. Summary data were extracted and independently cross-verified by two authors. Carriage was defined as MDR-GNB or VRE, detected in faecal or urinary cultures. Our primary outcomes were cumulative incidence and incidence density of infection in patients colonised by multidrug-resistant bacteria. To estimate pooled incidences, general linearised mixed-effects meta-regressions were used, adjusting for varying follow-up durations. This study is registered with PROSPERO, CRD42020222415. Of the 301 studies identified, 44 studies (26 on MDR-GNB, 14 on VRE, and four on both MDR-GNB and VRE) from 14 countries were retained for qualitative synthesis, 40 of which were analysed with meta-regression, comprising data for 14 049 patients colonised with multidrug-resistant bacteria. The pooled cumulative incidence of infection was 14% (95% CI 10–18; p<0·0001) at a median follow-up time of 30 days for MDR-GNB (845 cases of infection in 9034 patients colonised) and 8% (5–13; p<0·0001) at 30 days for VRE (229 cases of infection in 4747 patients colonised). Infection incidence density (4·26 infections per 1000 patient-days; 95% CI 1·69–6·82) and cumulative incidence of infection (19%, 95% CI 15–25; p<0·0001; 602 cases of infection in 4547 patients colonised) were highest for carbapenem-resistant Gram-negative bacteria at 30 days. Risk of bias was rated low to moderate. The risk of infection was substantial, with the highest risk for patients colonised with carbapenem-resistant Gram-negative bacteria and the lowest in patients with VRE. These data might help to guide prophylactic and treatment decisions and form a valuable resource for planning clinical trials on targeted prevention. The Netherlands Organization for Health Research and Development [ABSTRACT FROM AUTHOR]