| 1. |
- Holmes, Michael V., et al.
(författare)
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Secretory Phospholipase A(2)-IIA and Cardiovascular Disease
- 2013
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Ingår i: Journal of the American College of Cardiology. - : Elsevier. - 0735-1097 .- 1558-3597. ; 62:21, s. 1966-1976
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Tidskriftsartikel (refereegranskat)abstract
- Objectives This study sought to investigate the role of secretory phospholipase A(2) (sPLA(2))-IIA in cardiovascular disease. less thanbrgreater than less thanbrgreater thanBackground Higher circulating levels of sPLA(2)-IIA mass or sPLA(2) enzyme activity have been associated with increased risk of cardiovascular events. However, it is not clear if this association is causal. A recent phase III clinical trial of an sPLA(2) inhibitor (varespladib) was stopped prematurely for lack of efficacy. less thanbrgreater than less thanbrgreater thanMethods We conducted a Mendelian randomization meta-analysis of 19 general population studies (8,021 incident, 7,513 prevalent major vascular events [MVE] in 74,683 individuals) and 10 acute coronary syndrome (ACS) cohorts (2,520 recurrent MVE in 18,355 individuals) using rs11573156, a variant in PLA2G2A encoding the sPLA(2)-IIA isoenzyme, as an instrumental variable. less thanbrgreater than less thanbrgreater thanResults PLA2G2A rs11573156 C allele associated with lower circulating sPLA(2)-IIA mass (38% to 44%) and sPLA(2) enzyme activity (3% to 23%) per C allele. The odds ratio (OR) for MVE per rs11573156 C allele was 1.02 (95% confidence interval [CI]: 0.98 to 1.06) in general populations and 0.96 (95% CI: 0.90 to 1.03) in ACS cohorts. In the general population studies, the OR derived from the genetic instrumental variable analysis for MVE for a 1-log unit lower sPLA(2)-IIA mass was 1.04 (95% CI: 0.96 to 1.13), and differed from the non-genetic observational estimate (OR: 0.69; 95% CI: 0.61 to 0.79). In the ACS cohorts, both the genetic instrumental variable and observational ORs showed a null association with MVE. Instrumental variable analysis failed to show associations between sPLA2 enzyme activity and MVE. less thanbrgreater than less thanbrgreater thanConclusions Reducing sPLA(2)-IIA mass is unlikely to be a useful therapeutic goal for preventing cardiovascular events.
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| 2. |
- Cadrin-Tourigny, Julia, et al.
(författare)
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A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy
- 2019
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 1522-9645 .- 0195-668X. ; 40:23, s. 1850-1858
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Tidskriftsartikel (refereegranskat)abstract
- AIMS: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. METHODS AND RESULTS: Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.6% reduction of ICD placements with the same proportion of protected patients (P < 0.001). CONCLUSION: Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com).
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| 3. |
- Cadrin-Tourigny, Julia, et al.
(författare)
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A new prediction model for ventricular arrhythmias in arrhythmogenic right ventricular cardiomyopathy
- 2022
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Ingår i: European Heart Journal. - : Oxford University Press (OUP). - 0195-668X .- 1522-9645. ; 43:32, s. 1-9
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Tidskriftsartikel (refereegranskat)abstract
- Aims: Arrhythmogenic right ventricular dysplasia/cardiomyopathy (ARVC) is characterized by ventricular arrhythmias (VAs) and sudden cardiac death (SCD). We aimed to develop a model for individualized prediction of incident VA/SCD in ARVC patients. Methods and results: Five hundred and twenty-eight patients with a definite diagnosis and no history of sustained VAs/SCD at baseline, aged 38.2 ± 15.5 years, 44.7% male, were enrolled from five registries in North America and Europe. Over 4.83 (interquartile range 2.44-9.33) years of follow-up, 146 (27.7%) experienced sustained VA, defined as SCD, aborted SCD, sustained ventricular tachycardia, or appropriate implantable cardioverter-defibrillator (ICD) therapy. A prediction model estimating annual VA risk was developed using Cox regression with internal validation. Eight potential predictors were pre-specified: Age, sex, cardiac syncope in the prior 6 months, non-sustained ventricular tachycardia, number of premature ventricular complexes in 24 h, number of leads with T-wave inversion, and right and left ventricular ejection fractions (LVEFs). All except LVEF were retained in the final model. The model accurately distinguished patients with and without events, with an optimism-corrected C-index of 0.77 [95% confidence interval (CI) 0.73-0.81] and minimal over-optimism [calibration slope of 0.93 (95% CI 0.92-0.95)]. By decision curve analysis, the clinical benefit of the model was superior to a current consensus-based ICD placement algorithm with a 20.3% reduction of ICD placements with the same proportion of protected patients (P < 0.001). Conclusion: Using the largest cohort of patients with ARVC and no prior VA, a prediction model using readily available clinical parameters was devised to estimate VA risk and guide decisions regarding primary prevention ICDs (www.arvcrisk.com).
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| 4. |
- Cadrin-Tourigny, Julia, et al.
(författare)
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Sudden Cardiac Death Prediction in Arrhythmogenic Right Ventricular Cardiomyopathy : A Multinational Collaboration
- 2021
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Ingår i: Circulation: Arrhythmia and Electrophysiology. - : Lippincott Williams & Wilkins. - 1941-3149 .- 1941-3084. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: Arrhythmogenic right ventricular cardiomyopathy (ARVC) is associated with ventricular arrhythmias (VA) and sudden cardiac death (SCD). A model was recently developed to predict incident sustained VA in patients with ARVC. However, since this outcome may overestimate the risk for SCD, we aimed to specifically predict life-threatening VA (LTVA) as a closer surrogate for SCD. Methods: We assembled a retrospective cohort of definite ARVC cases from 15 centers in North America and Europe. Association of 8 prespecified clinical predictors with LTVA (SCD, aborted SCD, sustained, or implantable cardioverter-defibrillator treated ventricular tachycardia >250 beats per minute) in follow-up was assessed by Cox regression with backward selection. Candidate variables included age, sex, prior sustained VA (≥30s, hemodynamically unstable, or implantable cardioverter-defibrillator treated ventricular tachycardia; or aborted SCD), syncope, 24-hour premature ventricular complexes count, the number of anterior and inferior leads with T-wave inversion, left and right ventricular ejection fraction. The resulting model was internally validated using bootstrapping. Results: A total of 864 patients with definite ARVC (40±16 years; 53% male) were included. Over 5.75 years (interquartile range, 2.77-10.58) of follow-up, 93 (10.8%) patients experienced LTVA including 15 with SCD/aborted SCD (1.7%). Of the 8 prespecified clinical predictors, only 4 (younger age, male sex, premature ventricular complex count, and number of leads with T-wave inversion) were associated with LTVA. Notably, prior sustained VA did not predict subsequent LTVA (P=0.850). A model including only these 4 predictors had an optimism-corrected C-index of 0.74 (95% CI, 0.69-0.80) and calibration slope of 0.95 (95% CI, 0.94-0.98) indicating minimal over-optimism. Conclusions: LTVA events in patients with ARVC can be predicted by a novel simple prediction model using only 4 clinical predictors. Prior sustained VA and the extent of functional heart disease are not associated with subsequent LTVA events.
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| 5. |
- Uijl, Alicia, et al.
(författare)
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A registry-based algorithm to predict ejection fraction in patients with heart failure
- 2020
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Ingår i: ESC Heart Failure. - : WILEY PERIODICALS, INC. - 2055-5822. ; 7:5, s. 2388-2397
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Tidskriftsartikel (refereegranskat)abstract
- Aims Left ventricular ejection fraction (EF) is required to categorize heart failure (HF) [i.e. HF with preserved (HFpEF), mid-range (HFmrEF), and reduced (HFrEF) EF] but is often not captured in population-based cohorts or non-HF registries. The aim was to create an algorithm that identifies EF subphenotypes for research purposes. Methods and results We included 42 061 HF patients from the Swedish Heart Failure Registry. As primary analysis, we performed two logistic regression models including 22 variables to predict (i) EF >= vs. <50% and (ii) EF >= vs. <40%. In the secondary analysis, we performed a multivariable multinomial analysis with 22 variables to create a model for all three separate EF subphenotypes: HFrEF vs. HFmrEF vs. HFpEF. The models were validated in the database from the CHECK-HF study, a cross-sectional survey of 10 627 patients from the Netherlands. The C-statistic (discrimination) was 0.78 [95% confidence interval (CI) 0.77-0.78] for EF >= 50% and 0.76 (95% CI 0.75-0.76) for EF >= 40%. Similar results were achieved for HFrEF and HFpEF in the multinomial model, but the C-statistic for HFmrEF was lower: 0.63 (95% CI 0.63-0.64). The external validation showed similar discriminative ability to the development cohort. Conclusions Routine clinical characteristics could potentially be used to identify different EF subphenotypes in databases where EF is not readily available. Accuracy was good for the prediction of HFpEF and HFrEF but lower for HFmrEF. The proposed algorithm enables more effective research on HF in the big data setting.
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| 6. |
- Uijl, Alicia, et al.
(författare)
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Identification of distinct phenotypic clusters in heart failure with preserved ejection fraction
- 2021
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Ingår i: European Journal of Heart Failure. - : Wiley. - 1388-9842 .- 1879-0844. ; 23:6, s. 973-982
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Tidskriftsartikel (refereegranskat)abstract
- Aims We aimed to derive and validate clinically useful clusters of patients with heart failure with preserved ejection fraction (HFpEF; left ventricular ejection fraction >= 50%). Methods and results We derived a cluster model from 6909 HFpEF patients from the Swedish Heart Failure Registry (SwedeHF) and externally validated this in 2153 patients from the Chronic Heart Failure ESC-guideline based Cardiology practice Quality project (CHECK-HF) registry. In SwedeHF, the median age was 80 [interquartile range 72-86] years, 52% of patients were female and most frequent comorbidities were hypertension (82%), atrial fibrillation (68%), and ischaemic heart disease (48%). Latent class analysis identified five distinct clusters: cluster 1 (10% of patients) were young patients with a low comorbidity burden and the highest proportion of implantable devices; cluster 2 (30%) patients had atrial fibrillation, hypertension without diabetes; cluster 3 (25%) patients were the oldest with many cardiovascular comorbidities and hypertension; cluster 4 (15%) patients had obesity, diabetes and hypertension; and cluster 5 (20%) patients were older with ischaemic heart disease, hypertension and renal failure and were most frequently prescribed diuretics. The clusters were reproduced in the CHECK-HF cohort. Patients in cluster 1 had the best prognosis, while patients in clusters 3 and 5 had the worst age- and sex-adjusted prognosis. Conclusions Five distinct clusters of HFpEF patients were identified that differed in clinical characteristics, heart failure drug therapy and prognosis. These results confirm the heterogeneity of HFpEF and form a basis for tailoring trial design to individualized drug therapy in HFpEF patients.
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| 7. |
- Brons, Maaike, et al.
(författare)
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Patterns in the Use of Heart Failure Telemonitoring: Post Hoc Analysis of the e-Vita Heart Failure Trial
- 2023
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Ingår i: JMIR cardio. - : JMIR Publications. - 2561-1011. ; 7
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Tidskriftsartikel (refereegranskat)abstract
- Background: Research on the use of home telemonitoring data and adherence to it can provide new insights into telemonitoring for the daily management of patients with heart failure (HF). Objective: We described the use of a telemonitoring platform—including remote patient monitoring of blood pressure, pulse, and weight—and the use of the electronic personal health record. Patient characteristics were assessed in both adherent and nonadherent patients to weight transmissions. Methods: We used the data of the e-Vita HF study, a 3-arm parallel randomized trial performed in stable patients with HF managed in outpatient clinics in the Netherlands. In this study, data were analyzed from the participants in the intervention arm (ie, e-Vita HF platform). Adherence to weight transmissions was defined as transmitting weight ≥3 times per week for at least 42 weeks during a year. Results: Data from 150 patients (mean age 67, SD 11 years; n=37, 25% female; n=123, 82% self-assessed New York Heart Association class I-II) were analyzed. One-year adherence to weight transmissions was 74% (n=111). Patients adherent to weight transmissions were less often hospitalized for HF in the 6 months before enrollment in the study compared to those who were nonadherent (n=9, 8% vs n=9, 23%; P=.02). The percentage of patients visiting the personal health record dropped steadily over time (n=140, 93% vs n=59, 39% at one year). With univariable analyses, there was no significant correlation between patient characteristics and adherence to weight transmissions. Conclusions: Adherence to remote patient monitoring was high among stable patients with HF and best for weighing; however, adherence decreased over time. Clinical and demographic variables seem not related to adherence to transmitting weight.Trial Registration: ClinicalTrials.gov NCT01755988; https://clinicaltrials.gov/ct2/show/NCT01755988
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| 8. |
- Meijs, Claartje, et al.
(författare)
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Identifying distinct clinical clusters in heart failure with mildly reduced ejection fraction
- 2023
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Ingår i: International Journal of Cardiology. - : ELSEVIER IRELAND LTD. - 0167-5273 .- 1874-1754. ; 386, s. 83-90
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Heart failure (HF) is a heterogeneous syndrome, and the specific sub-category HF with mildly reduced ejection fraction (EF) range (HFmrEF; 41-49% EF) is only recently recognised as a distinct entity. Cluster analysis can characterise heterogeneous patient populations and could serve as a stratification tool in clinical trials and for prognostication. The aim of this study was to identify clusters in HFmrEF and compare cluster prognosis.Methods and results: Latent class analysis to cluster HFmrEF patients based on their characteristics was performed in the Swedish HF registry (n = 7316). Identified clusters were validated in a Dutch cross-sectional HF registrybased dataset CHECK-HF (n =1536). In Sweden, mortality and hospitalisation across the clusters were compared using a Cox proportional hazard model, with a Fine-Gray sub-distribution for competing risks and adjustment for age and sex. Six clusters were discovered with the following prevalence and hazard ratio with 95% confidence intervals (HR [95%CI]) vs. cluster 1: 1) low-comorbidity (17%, reference), 2) ischaemic-male (13%, HR 0.9 [95% CI 0.7-1.1]), 3) atrial fibrillation (20%, HR 1.5 [95% CI 1.2-1.9]), 4) device/wide QRS (9%, HR 2.7 [95% CI 2.2-3.4]), 5) metabolic (19%, HR 3.1 [95% CI 2.5-3.7]) and 6) cardio-renal phenotype (22%, HR 2.8 [95% CI 2.2-3.6]). The cluster model was robust between both datasets.Conclusion: We found robust clusters with potential clinical meaning and differences in mortality and hospitalisation. Our clustering model could be valuable as a clinical differentiation support and prognostic tool in clinical trial design.
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| 9. |
- Savarese, Gianluigi, et al.
(författare)
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Comorbidities and cause-specific outcomes in heart failure across the ejection fraction spectrum : A blueprint for clinical trial design
- 2020
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Ingår i: International Journal of Cardiology. - : Elsevier BV. - 0167-5273 .- 1874-1754. ; 313, s. 76-82
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundComorbidities may differently affect treatment response and cause-specific outcomes in heart failure (HF) with preserved (HFpEF) vs. mid-range/mildly-reduced (HFmrEF) vs. reduced (HFrEF) ejection fraction (EF), complicating trial design. In patients with HF, we performed a comprehensive analysis of type 2 diabetes (T2DM), atrial fibrillation (AF) chronic kidney disease (CKD), and cause-specific outcomes.Methods and resultsOf 42,583 patients from the Swedish HF registry (23% HFpEF, 21% HFmrEF, 56% HFrEF), 24% had T2DM, 51% CKD, 56% AF, and 8% all three comorbidities. HFpEF had higher prevalence of CKD and AF, HFmrEF had intermediate prevalence of AF, and prevalence of T2DM was similar across the EF spectrum. Patients with T2DM, AF and/or CKD were more likely to have also other comorbidities and more severe HF. Risk of cardiovascular (CV) events was highest in HFrEF vs. HFpEF and HFmrEF; non-CV risk was highest in HFpEF vs. HFmrEF vs. HFrEF. T2DM increased CV and non-CV events similarly but less so in HFpEF. CKD increased CV events somewhat more than non-CV events and less so in HFpEF. AF increased CV events considerably more than non-CV events and more so in HFpEF and HFmrEF.ConclusionHFpEF is distinguished from HFmrEF and HFrEF by more comorbidities, non-CV events, but lower effect of T2DM and CKD on events. CV events are most frequent in HFrEF. To enrich for CV vs. non-CV events, trialists should not exclude patients with lower EF, AF and/or CKD, who report higher CV risk.
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| 10. |
- Stolfo, Davide, et al.
(författare)
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Association between beta-blocker use and mortality/morbidity in older patients with heart failure with reduced ejection fraction. A propensity score-matched analysis from the Swedish Heart Failure Registry
- 2020
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Ingår i: European Journal of Heart Failure. - : WILEY. - 1388-9842 .- 1879-0844. ; 22:1, s. 103-112
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Tidskriftsartikel (refereegranskat)abstract
- Background Beta-blockers reduce mortality and morbidity in heart failure (HF) with reduced ejection fraction (HFrEF). However, patients older than 80 years are poorly represented in randomized controlled trials. We assessed the association between beta-blocker use and outcomes in HFrEF patients aged amp;gt;= 80 years. Methods and results We included patients with an ejection fraction amp;lt;40% and aged amp;gt;= 80 years from the Swedish HF Registry. The association between beta-blocker use, all-cause mortality and cardiovascular (CV) mortality/HF hospitalization was assessed by Cox proportional hazard models in a 1:1 propensity score-matched cohort. To assess consistency, the same analyses were performed in a positive control cohort with age amp;lt;80 years. A negative control outcome analysis was run using hospitalization for cancer as endpoint. Of 6562 patients aged amp;gt;= 80 years, 5640 (86%) received beta-blockers. In the matched cohort including 1732 patients, beta-blocker use was associated with a significant reduction in the risk of all-cause mortality [hazard ratio (HR) 0.89, 95% confidence interval (CI) 0.79-0.99]. Reduction in CV mortality/HF hospitalization was not significant (HR 0.94, 95% CI 0.85-1.05) due to the lack of association with HF hospitalization, whereas CV death was significantly reduced. After adjustment rather than matching for the propensity score in the overall cohort, beta-blocker use was associated with reduced risk of all outcomes. In patients aged amp;lt;80 years, use of beta-blockers was associated with reduced risk of all-cause death (HR 0.79, 95% CI 0.68-0.92) and of the composite outcome (HR 0.88, 95% CI 0.77-0.99). Conclusions In HFrEF patients amp;gt;= 80 years of age, use of beta-blockers was high and was associated with improved all-cause and CV survival.
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