Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models.
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ABSTRACT:
SUBMITTER: Arevalo HJ
PROVIDER: S-EPMC4866040 | biostudies-literature | 2016 May
REPOSITORIES: biostudies-literature
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Arrhythmia risk stratification of patients after myocardial infarction using personalized heart models.
Arevalo Hermenegild J HJ Vadakkumpadan Fijoy F Guallar Eliseo E Jebb Alexander A Malamas Peter P Wu Katherine C KC Trayanova Natalia A NA
Nature communications 20160510
Sudden cardiac death (SCD) from arrhythmias is a leading cause of mortality. For patients at high SCD risk, prophylactic insertion of implantable cardioverter defibrillators (ICDs) reduces mortality. Current approaches to identify patients at risk for arrhythmia are, however, of low sensitivity and specificity, which results in a low rate of appropriate ICD therapy. Here, we develop a personalized approach to assess SCD risk in post-infarction patients based on cardiac imaging and computational ...[more]
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Project description:Biomechanical computational models have potential prognostic utility in patients after an acute ST-segment-elevation myocardial infarction (STEMI). In a proof-of-concept study, we defined two groups (1) an acute STEMI group (n = 6, 83% male, age 54 ± 12 years) complicated by left ventricular (LV) systolic dysfunction; (2) an age- and sex- matched hyper-control group (n = 6, 83% male, age 46 ± 14 years), no prior history of cardiovascular disease and normal systolic blood pressure (SBP < 130 mmHg). Cardiac MRI was performed in the patients (2 days & 6 months post-STEMI) and the volunteers, and biomechanical heart models were synthesized for each subject. The candidate parameters included normalized active tension (AT norm) and active tension at the resting sarcomere length (T req, reflecting required contractility). Myocardial contractility was inversely determined from personalized heart models by matching CMR-imaged LV dynamics. Compared with controls, patients with recent STEMI exhibited increased LV wall active tension when normalized by SBP. We observed a linear relationship between T req 2 days post-MI and global longitudinal strain 6 months later (r = 0.86; p = 0.03). T req may be associated with changes in LV function in the longer term in STEMI patients complicated by LV dysfunction. Further studies seem warranted.
| S-EPMC5648923 | biostudies-literature
Project description:BackgroundSeveral biomarkers have individually been shown to be useful for risk stratification in patients with acute myocardial infarction (MI). The optimal multimarker strategy remains undefined.Methods and resultsBiomarkers representing different pathobiological axes were studied, including myocardial stress/structural changes (NT-pro B-type natriuretic peptide [NT-proBNP], midregional proatrial natriuretic peptide [MR-proANP], suppression of tumorigenicity 2 [ST2], galectin-3, midregional proadrenomedullin [MR-proADM], and copeptin), myonecrosis (troponin T), and inflammation (myeloperoxidase [MPO], high sensitivity C-reactive protein [hsCRP], pregnancy-associated plasma protein A [PAPP-A], and growth-differentiation factor-15 [GDF-15]), in up to 1258 patients from Clopidogrel as Adjunctive Reperfusion Therapy-Thrombolysis in Myocardial Infarction 28 (CLARITY-TIMI 28), a randomized trial of clopidogrel in ST-elevation MI (STEMI). Patients were followed for 30 days. Biomarker analyses were adjusted for traditional clinical variables. Forward step-wise selection was used to assess a multimarker strategy. After adjustment for clinical variables and using a dichotomous cutpoint, 7 biomarkers were each significantly associated with a higher odds of cardiovascular death or heart failure (HF) through 30 days, including NT-proBNP (adjusted odds ratio [ORadj], 2.54; 95% CI, 1.47-4.37), MR-proANP (2.18; 1.27-3.76), ST2 (2.88; 1.72-4.81), troponin T (4.13; 1.85-9.20), MPO (2.75; 1.20-6.27), hsCRP (1.96, 1.17-3.30), and PAPP-A (3.04; 1.17-7.88). In a multimarker model, 3 biomarkers emerged as significant and complementary predictors of cardiovascular death or HF: ST2 (ORadj, 2.87; 1.61-5.12), troponin T (2.34; 1.09-5.01 and 4.13, 1.85-9.20, respectively for intermediate and high levels), and MPO (2.49; 1.04-5.96). When added to the TIMI STEMI Risk Score alone, the multimarker risk score significantly improved the C-statistic (area under the curve, 0.75 [95% CI, 0.69-0.81] to 0.82 [0.78-0.87]; P=0.001), net reclassification index (0.93; P<0.001), and integrated discrimination index (0.09; P<0.001).ConclusionsIn patients with STEMI, a multimarker strategy that combines biomarkers across pathobiological axes of myocardial stress, myocyte necrosis, and inflammation provides incremental prognostic information for prediction of cardiovascular death or HF.
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Project description:BackgroundAdults with repaired tetralogy of Fallot (rTOF) are at increased risk for ventricular tachycardia (VT) due to fibrotic remodeling of the myocardium. However, the current clinical guidelines for VT risk stratification and subsequent implantable cardioverter-defibrillator deployment for primary prevention of sudden cardiac death in rTOF remain inadequate.ObjectiveThe purpose of this study was to determine the feasibility of using an rTOF-specific virtual-heart approach to identify patients stratified incorrectly as being at low VT risk by current clinical criteria.MethodsThis multicenter retrospective pilot study included 7 adult rTOF patients who were considered low risk for VT based on clinical criteria. Patient-specific computational heart models were generated from late gadolinium enhanced magnetic resonance imaging (LGE-MRI), incorporating the individual distribution of rTOF fibrotic remodeling in both ventricles. Simulations of rapid pacing determined VT inducibility. Model creation and simulations were performed by operators blinded to clinical outcome.ResultsTwo patients in the study experienced clinical VT. The virtual hearts constructed from LGE-MRI scans of 7 rTOF patients correctly predicted reentrant VT in the models from VT-positive patients and no arrhythmia in those from VT-negative patients. There were no statistically significant differences in clinical criteria commonly used to assess VT risk, including QRS duration and age, between patients who did and those who did not experience clinical VT.ConclusionThis study demonstrates the feasibility of image-based virtual-heart modeling in patients with congenital heart disease and structurally abnormal hearts. It highlights the potential of the methodology to improve VT risk stratification in patients with rTOF.
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Project description:BackgroundNumerous studies have revealed the relationship between lipid expression and increased cardiovascular risk in ST-segment elevation myocardial infarction (STEMI) patients. Nevertheless, few investigations have focused on the risk stratification of STEMI patients using machine learning algorithms.MethodsA total of 1355 STEMI patients who underwent percutaneous coronary intervention were enrolled in this study during 2015-2018. Unsupervised machine learning (consensus clustering) was applied to the present cohort to classify patients into different lipid expression phenogroups, without the guidance of clinical outcomes. Kaplan-Meier curves were implemented to show prognosis during a 904-day median follow-up (interquartile range: 587-1316). In the adjusted Cox model, the association of cluster membership with all adverse events including all-cause mortality, all-cause rehospitalization, and cardiac rehospitalization was evaluated.ResultsAll patients were classified into three phenogroups, 1, 2, and 3. Patients in phenogroup 1 with the highest Lp(a) and the lowest HDL-C and apoA1 were recognized as the statin-modified cardiovascular risk group. Patients in phenogroup 2 had the highest HDL-C and apoA1 and the lowest TG, TC, LDL-C and apoB. Conversely, patients in phenogroup 3 had the highest TG, TC, LDL-C and apoB and the lowest Lp(a). Additionally, phenogroup 1 had the worst prognosis. Furthermore, a multivariate Cox analysis revealed that patients in phenogroup 1 were at significantly higher risk for all adverse outcomes.ConclusionMachine learning-based cluster analysis indicated that STEMI patients with increased concentrations of Lp(a) and decreased concentrations of HDL-C and apoA1 are likely to have adverse clinical outcomes due to statin-modified cardiovascular risks.Trial registrationChiCTR1900028516 ( http://www.chictr.org.cn/index.aspx ).
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Project description:AimsMyocardial infarction (MI) alters cardiac fibre organization with unknown consequences on ventricular arrhythmia. We used diffusion tensor imaging (DTI) of three-dimensional (3D) cardiac fibres and scar reconstructions to identify the main parameters associated with ventricular arrhythmia inducibility and ventricular tachycardia (VT) features after MI.Methods and resultsTwelve pigs with established MI and three controls underwent invasive electrophysiological characterization of ventricular arrhythmia inducibility and VT features. Animal-specific 3D scar and myocardial fibre distribution were obtained from ex vivo high-resolution contrast-enhanced T1 mapping and DTI sequences. Diffusion tensor imaging-derived parameters significantly different between healthy and scarring myocardium, scar volumes, and left ventricular ejection fraction (LVEF) were included for arrhythmia risk stratification and correlation analyses with VT features. Ventricular fibrillation (VF) was the only inducible arrhythmia in 4 out of 12 infarcted pigs and all controls. Ventricular tachycardia was also inducible in the remaining eight pigs during programmed ventricular stimulation. A DTI-based 3D fibre disorganization index (FDI) showed higher disorganization within dense scar regions of VF-only inducible pigs compared with VT inducible animals (FDI: 0.36; 0.36-0.37 vs. 0.32; 0.26-0.33, respectively, P = 0.0485). Ventricular fibrillation induction required lower programmed stimulation aggressiveness in VF-only inducible pigs than VT inducible and control animals. Neither LVEF nor scar volumes differentiated between VF and VT inducible animals. Re-entrant VT circuits were localized within areas of highly disorganized fibres. Moreover, the FDI within heterogeneous scar regions was associated with the median VT cycle length per animal (R2 = 0.5320).ConclusionThe amount of scar-related cardiac fibre disorganization in DTI sequences is a promising approach for ventricular arrhythmia stratification after MI.
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Project description:BackgroundThis study was to probe into the relationship between the neutrophil-to-lymphocyte ratio (NLR) and both in-hospital and long-term heart failure risk in patients with acute myocardial infarction (AMI).Methods990 patients with AMI, including 386 with non-ST-segment elevation myocardial infarction (NSTEMI) and 604 with segment elevation myocardial infarction (STEMI) were recruited between January 2019 and March 2022. The in-hospital acute heart failure (AHF) and arrhythmia events were recorded.ResultsThe NLR was significantly greater in the AHF group in STEMI and NSTEMI patients, with a higher frequency of arrhythmia in comparison to the non-AHF group. A high NLR was related to a high level of myocardial injury markers, accompanied with more AHF and arrhythmia events. Multivariate logistic regression analyses revealed that high NLR is independently linked with increased in-hospital AHF and arrhythmia risk. Receiver operating characteristic curve analyses revealed that the prognostic value of NLR for in-hospital AHF was 0.704 in STEMI patients and 0.766 in NSTEMI patients. However, during a median follow-up of 28 months with 32 heart failure patients, there was no significant difference between the low NLR group (n = 18) and the high NLR group (n = 14). Further analysis showed that the two groups did not significantly differ in the occurrence of heart failure within 12 months of discharge.ConclusionOur results indicate that NLR is an independent risk factor of in-hospital AHF in AMI patients. However, NLR has no value in predicting long-term heart failure.
| S-EPMC10623153 | biostudies-literature
Project description:Ischemic cardiomyopathy is associated with an increased risk of sudden death, activation of the unfolded protein response (UPR), and reductions in multiple cardiac ion channels. When activated, the protein kinase-like ER kinase (PERK) branch of the UPR reduces protein translation and abundance. We hypothesized that PERK inhibition could prevent ion channel downregulation and reduce arrhythmia risk after myocardial infarct (MI). MI induced in mice by coronary artery ligation resulted in reduced ion channel levels, ventricular tachycardia (VT), and prolonged corrected intervals between the Q and T waves on the ECGs (QTc). Protein levels of major cardiac ion channels were decreased. MI cardiomyocytes showed significantly prolonged action potential duration and decreased maximum upstroke velocity. Cardiac-specific PERK KO reduced electrical remodeling in response to MI, with shortened QTc intervals, fewer VT episodes, and higher survival rates. Pharmacological PERK inhibition had similar effects. In conclusion, we found that activated PERK during MI contributed to arrhythmia risk by the downregulation of select cardiac ion channels. PERK inhibition prevented these changes and reduced arrhythmia risk. These results suggest that ion channel downregulation during MI is a fundamental arrhythmia mechanism and that maintenance of ion channel levels is antiarrhythmic.
| S-EPMC8439592 | biostudies-literature
Project description:ObjectiveCardiogenic shock (CS) is the leading cause of death in patients with acute myocardial infarction (AMI) despite advances in care. This study aims to derive and validate a risk score for in-hospital development of CS in patients with AMI.MethodsIn this study, we used the Improving Care for Cardiovascular Disease in China-Acute Coronary Syndrome (CCC-ACS) registry of 76,807 patients for model development and internal validation. These patients came from 158 tertiary hospitals and 82 secondary hospitals between 2014 and 2019, presenting AMI without CS upon admission. The eligible patients with AMI were randomly assigned to derivation (n = 53,790) and internal validation (n = 23,017) cohorts. Another cohort of 2,205 patients with AMI between 2014 and 2016 was used for external validation. Based on the identified predictors for in-hospital CS, a new point-based CS risk scheme, referred to as the CCC-ACS CS score, was developed and validated.ResultsA total of 866 (1.1%) and 39 (1.8%) patients subsequently developed in-hospital CS in the CCC-ACS project and external validation cohort, respectively. The CCC-ACS CS score consists of seven variables, including age, acute heart failure upon admission, systolic blood pressure upon admission, heart rate, initial serum creatine kinase-MB level, estimated glomerular filtration rate, and mechanical complications. The area under the curve for in-hospital development of CS was 0.73, 0.71, and 0.85 in the derivation, internal validation and external validation cohorts, respectively.ConclusionThis newly developed CCC-ACS CS score can quantify the risk of in-hospital CS for patients with AMI, which may help in clinical decision making.Clinical trial registrationwww.ClinicalTrials.gov, identifier: NCT02306616.
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