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- Batra, Gorav, et al.
(author)
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Angiotensin-converting enzyme inhibitors and angiotensin II receptor blockers are associated with improved outcome but do not prevent new-onset atrial fibrillation after acute myocardial infarction
- 2017
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In: Journal of the American Heart Association. - 2047-9980 .- 2047-9980. ; 6:3
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Journal article (peer-reviewed)abstract
- Background Treatment with renin‐angiotensin system (RAS) inhibitors might restrain the structural/electrical remodeling associated with atrial fibrillation (AF). Limited evidence exists regarding the potential benefits of RAS inhibition post‐acute myocardial infarction (AMI) in patients with AF. This study sought to assess the association between RAS inhibition and all‐cause mortality and new‐onset AF in patients with/without congestive heart failure (CHF) post‐AMI.Methods and Results Patients hospitalized for AMI between 2006 and 2012 were identified in Swedish registries. Patients were stratified in 4 subgroups; patients with CHF and AF (n=11 489); patients with CHF without AF (n=31 676); patients with AF without CHF (n=10 066); and patients without both CHF and AF (n=59 417). Patients exposed to RAS inhibition were compared to nontreated. Three‐year risk of all‐cause mortality and new‐onset AF was assessed using adjusted Cox regression analyses. At discharge, 83 291 (73.9%) patients received RAS inhibition. RAS inhibition was associated with lower 3‐year risk of all‐cause mortality in CHF patients with AF, adjusted hazard ratio (HR) with 95% CI 0.75 (0.70–0.81), CHF patients without AF, HR 0.65 (0.60–0.69), AF patients without CHF, HR 0.82 (0.75–0.90), and in patients without CHF and AF, HR 0.76 (0.72–0.81), respectively. RAS inhibition was not associated with lower 3‐year risk of new‐onset AF in patients without AF but with/without CHF; HR 0.96 (0.84–1.10) and 1.12 (1.02–1.22), respectively.Conclusions RAS inhibition post‐AMI was associated with lower risk of all‐cause mortality. In patients with/without CHF, RAS inhibition was not associated with lower incidence of new‐onset AF.
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| 2. |
- Mohammad, Moman A., et al.
(author)
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Development and validation of an artificial neural network algorithm to predict mortality and admission to hospital for heart failure after myocardial infarction : a nationwide population-based study
- 2022
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In: The Lancet Digital Health. - : Elsevier. - 2589-7500. ; 4:1, s. 37-45
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Journal article (peer-reviewed)abstract
- Background: Patients have an estimated mortality of 15–20% within the first year following myocardial infarction and one in four patients who survive myocardial infarction will develop heart failure, severely reducing quality of life and increasing the risk of long-term mortality. We aimed to establish the accuracy of an artificial neural network (ANN) algorithm in predicting 1-year mortality and admission to hospital for heart failure after myocardial infarction. Methods: In this nationwide population-based study, we used data for all patients admitted to hospital for myocardial infarction and discharged alive from a coronary care unit in Sweden (n=139 288) between Jan 1, 2008, and April 1, 2017, from the Swedish Web system for Enhancement and Development of Evidence-based care in Heart disease Evaluated According to Recommended Therapies (SWEDEHEART) nationwide registry; these patients were randomly divided into training (80%) and testing (20%) datasets. We developed an ANN using 21 variables (including age, sex, medical history, previous medications, in-hospital characteristics, and discharge medications) associated with the outcomes of interest with a back-propagation algorithm in the training dataset and tested it in the testing dataset. The ANN algorithm was then validated in patients with incident myocardial infarction enrolled in the Western Denmark Heart Registry (external validation cohort) between Jan 1, 2008, and Dec 31, 2016. The predictive ability of the model was evaluated using area under the receiver operating characteristic curve (AUROC) and Youden's index was established as a means of identifying an empirical dichotomous cutoff, allowing further evaluation of model performance. Findings: 139 288 patients who were admitted to hospital for myocardial infarction in the SWEDEHEART registry were randomly divided into a training dataset of 111 558 (80%) patients and a testing dataset of 27 730 (20%) patients. 30 971 patients with myocardial infarction who were enrolled in the Western Denmark Heart Registry were included in the external validation cohort. A first event, either all-cause mortality or admission to hospital for heart failure 1 year after myocardial infarction, occurred in 32 308 (23·2%) patients in the testing and training cohorts only. For 1-year all-cause mortality, the ANN had an AUROC of 0·85 (95% CI 0·84–0·85) in the testing dataset and 0·84 (0·83–0·84) in the external validation cohort. The AUROC for admission to hospital for heart failure within 1 year was 0·82 (0·81–0·82) in the testing dataset and 0·78 (0·77–0·79) in the external validation dataset. With an empirical cutoff the ANN algorithm correctly classified 73·6% of patients with regard to all-cause mortality and 61·5% of patients with regard to admission to hospital for heart failure in the external validation cohort, ruling out adverse outcomes with 97·1–98·7% probability in the external validation cohort. Interpretation: Identifying patients at a high risk of developing heart failure or death after myocardial infarction could result in tailored therapies and monitoring by the allocation of resources to those at greatest risk. Funding: The Swedish Heart and Lung Foundation, Swedish Scientific Research Council, Swedish Foundation for Strategic Research, Knut and Alice Wallenberg Foundation, ALF Agreement on Medical Education and Research, Skane University Hospital, The Bundy Academy, the Märta Winkler Foundation, the Anna-Lisa and Sven-Eric Lundgren Foundation for Medical Research.
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| 3. |
- Mörtberg, Josefin, et al.
(author)
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Prognostic importance of biomarkers associated with haemostatic, vascular and endothelial disturbances in acute coronary syndrome patients in relation to kidney function
- 2023
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In: International Journal of Cardiology. - : Elsevier BV. - 0167-5273 .- 1874-1754. ; 373, s. 64-71
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Journal article (peer-reviewed)abstract
- BACKGROUND: Patients with kidney failure have a high risk for cardiovascular events. We aimed to evaluate the prognostic importance of selected biomarkers related to haemostasis, endothelial function, and vascular regulation in patients with acute coronary syndrome (ACS), and to study whether this association differed in patients with renal dysfunction.METHODS: Plasma was collected in 1370 ACS patients included between 2008 and 2015. Biomarkers were analysed using a Proximity Extension Assay and a Multiple Reaction Monitoring mass spectrometry assay. To reduce multiplicity, biomarkers correlating with eGFR were selected a priori among 36 plasma biomarkers reflecting endothelial and vascular function, and haemostasis. Adjusted Cox regression were used to study their association with the composite outcome of myocardial infarction, ischemic stroke, heart failure or death. Interaction with eGFR strata above or below 60 ml/min/1.73 m 2 was tested. RESULTS: Tissue factor, proteinase-activated receptor, soluble urokinase plasminogen activator surface receptor (suPAR), thrombomodulin, adrenomedullin, renin, and angiotensinogen correlated inversely with eGFR and were selected for the Cox regression. Mean follow-up was 5.2 years during which 428 events occurred. Adrenomedullin, suPAR, and renin were independently associated with the composite outcome. Adrenomedullin showed interaction with eGFR strata (p = 0.010) and was associated with increased risk (HR 1.88; CI 1.44-2.45) only in patients with eGFR ≥60 ml/min/ 1.73 m 2. CONCLUSIONS: Adrenomedullin, suPAR, and renin were associated with the composite outcome in all. Adrenomedullin, involved in endothelial protection, showed a significant interaction with renal function and outcome, and was associated with the composite outcome only in patients with preserved kidney function.
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