Dataset Information

Red blood cell fatty acid levels improve GRACE score prediction of 2-yr mortality in patients with myocardial infarction.

ABSTRACT:

Background

Blood omega-3 and omega-6 fatty acid levels have been associated with reduced risk for total mortality in patients with stable coronary heart disease (CHD), but their relationships with mortality in the setting of myocardial infarction (MI) are unknown.

Objective

To determine the association between red blood cell (RBC) fatty acid levels measured at admission and 2-year mortality in MI patients, independent of the GRACE risk score, a traditional mode of risk stratification.

Design

Admission RBC fatty acid levels were measured in patients enrolled in a prospective, 24-center MI registry (TRIUMPH). Two-year mortality was modeled with Cox proportional hazards regression to assess the extent to which the inclusion of fatty acid levels would improve, over and above the GRACE score, risk stratification for 2-year mortality.

Results

RBC fatty acid data were available from 1144 patients who did not report taking fish oil supplements after discharge. Two RBC fatty acids [eicosapentaenoic acid (EPA) and docosapentaenoic n-6 (DPA)] were univariate predictors of total mortality. The combined fatty acid c-statistic (0.60, p<0.001) improved the c-statistic of the GRACE score alone from 0.747 (p<0.001) to 0.768 (p<0.05 vs. GRACE alone). The net reclassification index improved by 31% (95% CI, 15% to 48%) and the relative incremental discrimination index improved by 19.8% (7.5% to 35.7%).

Conclusion

RBC EPA and DPA n-6 levels improved the prediction of 2-yr mortality over and above the GRACE score in MI patients.

SUBMITTER: Harris WS

PROVIDER: S-EPMC3574624 | biostudies-literature | 2013 Sep

REPOSITORIES: biostudies-literature

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Publications

Red blood cell fatty acid levels improve GRACE score prediction of 2-yr mortality in patients with myocardial infarction.

Harris William S WS Kennedy Kevin F KF O'Keefe James H JH Spertus John A JA

International journal of cardiology 20121006 1

<h4>Background</h4>Blood omega-3 and omega-6 fatty acid levels have been associated with reduced risk for total mortality in patients with stable coronary heart disease (CHD), but their relationships with mortality in the setting of myocardial infarction (MI) are unknown.<h4>Objective</h4>To determine the association between red blood cell (RBC) fatty acid levels measured at admission and 2-year mortality in MI patients, independent of the GRACE risk score, a traditional mode of risk stratificat ...[more]

PMID: 23044429

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Project description:BACKGROUND:Risk prediction after myocardial infarction is often complex in older patients. The Global Registry of Acute Coronary Events (GRACE) model includes clinical parameters and age, but not frailty. We hypothesised that frailty would enhance the prognostic properties of GRACE. METHODS:We performed a prospective observational cohort study in two independent cardiology units: the Royal Infirmary of Edinburgh, UK (primary cohort) and the South Yorkshire Cardiothoracic Centre, Sheffield, UK (external validation). The study sample included 198 patients ?65?years old hospitalised with type 1 myocardial infarction (primary cohort) and 96 patients ?65?years old undergoing cardiac catheterisation for myocardial infarction (external validation). Frailty was assessed using the Clinical Frailty Scale (CFS). The GRACE 2.0 estimated risk of 12-month mortality, Charlson comorbidity index and Karnofsky disability scale were also determined for each patient. RESULTS:Forty (20%) patients were frail (CFS ?5). These individuals had greater comorbidity, functional impairment and a higher risk of death at 12?months (49% vs. 9% in non-frail patients, p?<?0.001). The hazard of 12-month all-cause mortality nearly doubled per point increase in CFS after adjustment for age, sex and comorbidity (Hazard Ratio [HR] 1.90, 95% CI 1.47-2.44, p?<?0.001). The CFS had good discrimination for mortality by Receiver Operating Characteristic (ROC) curve analysis (Area Under the Curve [AUC] 0.81, 95% CI 0.72-0.89) and enhanced the GRACE estimate (AUC 0.86 vs. 0.80 without CFS, p?=?0.04). At existing GRACE thresholds, the CFS resulted in a Net Reclassification Improvement (NRI) of 0.44 (95% CI 0.28-0.60, p?<?0.001), largely through reductions in risk estimates amongst non-frail patients. Similar findings were observed in the external validation cohort (NRI 0.46, 95% CI 0.23-0.69, p?<?0.001). CONCLUSIONS:The GRACE score overestimated mortality risk after myocardial infarction in these cohorts of older patients. The CFS is a simple guided frailty tool that may enhance prediction in this setting. These findings merit evaluation in larger cohorts of unselected patients. TRIAL REGISTRATION:Clinicaltrials.gov; NCT02302014 (November 26th 2014, retrospectively registered).

Project description:Background: The Global Registry of Acute Coronary Events (GRACE) risk score (GRS) is an established powerful model in predicting prognosis of patients with acute coronary syndrome. However, it does not contain pathophysiological biomarkers. Myeloperoxidase (MPO) and trimethylamine N-oxide (TMAO) are novel biomarkers of different pathophysiological processes of acute myocardial infarction, and each of them predicts risk of adverse clinical outcomes. We aimed to investigate whether the addition of MPO and TMAO could improve a GRS-based prediction model in patients with ST-segment elevation myocardial infarction (STEMI). Methods: A prospective cohort of 444 consecutive patients with STEMI who underwent primary percutaneous coronary intervention were enrolled in this study. Plasma levels of MPO and TMAO were measured using samples collected before the interventional procedure. GRS at admission was calculated. Death and nonfatal myocardial infarction were recorded as major adverse cardiac events (MACEs). Kaplan-Meier survival analysis with Cox proportional-hazards regression was used to identify predictive values of MPO and TMAO. Area under the receiver-operator characteristic curve (AUC) and net reclassification improvement (NRI) were calculated to evaluate the increment of predictive value for the combination of MPO and TMAO with GRS in predicting adverse clinical outcomes. Results: During 6 months follow-up, 27 patients suffered MACEs. Both MPO (hazard ratio [HR]: 2.55, 95% confidence interval [CI]: 1.11-5.87; p < 0.05) and TMAO (HR: 4.50, 95% CI: 1.78-11.40, p < 0.01) predicted MACEs at 6 months. The AUC for MPO, TMAO, GRS, and their combination in predicting risk of MACEs at 6 months is 0.642, 0.692, 0.736, and 0.760, respectively. The addition of MPO and TMAO significantly improved the net reclassification of GRS for predicting MACEs at 6 months (NRI: 0.42, p = 0.032). Conclusion: Plasma MPO and TMAO each predict near-term risk of adverse outcomes in patients with STEMI. Furthermore, the combination of MPO and TMAO with GRS enables more accurate prediction of cardiovascular events compared with GRS alone.

Project description:ObjectiveTo develop a clinical risk prediction tool for estimating the cumulative six month risk of death and death or myocardial infarction to facilitate triage and management of patients with acute coronary syndrome.DesignProspective multinational observational study in which we used multivariable regression to develop a final predictive model, with prospective and external validation.SettingNinety four hospitals in 14 countries in Europe, North and South America, Australia, and New Zealand.Population43,810 patients (21,688 in derivation set; 22,122 in validation set) presenting with acute coronary syndrome with or without ST segment elevation enrolled in the global registry of acute coronary events (GRACE) study between April 1999 and September 2005.Main outcome measuresDeath and myocardial infarction.Results1989 patients died in hospital, 1466 died between discharge and six month follow-up, and 2793 sustained a new non-fatal myocardial infarction. Nine factors independently predicted death and the combined end point of death or myocardial infarction in the period from admission to six months after discharge: age, development (or history) of heart failure, peripheral vascular disease, systolic blood pressure, Killip class, initial serum creatinine concentration, elevated initial cardiac markers, cardiac arrest on admission, and ST segment deviation. The simplified model was robust, with prospectively validated C-statistics of 0.81 for predicting death and 0.73 for death or myocardial infarction from admission to six months after discharge. The external applicability of the model was validated in the dataset from GUSTO IIb (global use of strategies to open occluded coronary arteries).ConclusionsThis risk prediction tool uses readily identifiable variables to provide robust prediction of the cumulative six month risk of death or myocardial infarction. It is a rapid and widely applicable method for assessing cardiovascular risk to complement clinical assessment and can guide patient triage and management across the spectrum of patients with acute coronary syndrome.

Project description:The polygenic risk score (PRS) can help to identify individuals' genetic susceptibility for various diseases by combining patient genetic profiles and identified single-nucleotide polymorphisms (SNPs) from genome-wide association studies. Although multiple diseases will usually afflict patients at once or in succession, conventional PRSs fail to consider genetic relationships across multiple diseases. Even multi-trait PRSs, which take into account genetic effects for more than one disease at a time, fail to consider a sufficient number of phenotypes to accurately reflect the state of disease comorbidity in a patient, or are biased in terms of the traits that are selected. Thus, we developed novel network-based comorbidity risk scores to quantify associations among multiple phenotypes from phenome-wide association studies (PheWAS). We first constructed a disease-SNP heterogeneous multi-layered network (DS-Net), which consists of a disease network (disease-layer) and SNP network (SNP-layer). The disease-layer describes the population-level interactome from PheWAS data. The SNP-layer was constructed according to linkage disequilibrium. Both layers were attached to transform the information from a population-level interactome to individual-level inferences. Then, graph-based semi-supervised learning was applied to predict possible comorbidity scores on disease-layer for each subject. The SNP-layer serves as receiving individual genotyping data in the scoring process, and the disease-layer serves as the propagated output for an individual's multiple disease comorbidity scores. The possible comorbidity scores were combined by logistic regression, and it is denoted as netCRS. The DS-Net was constructed from UK Biobank PheWAS data, and the individual genetic profiles were collected from the Penn Medicine Biobank. As a proof-of-concept study, myocardial infarction (MI) was selected to compare netCRS with the PRS with pruning and thresholding (PRS-PT). The combined model (netCRS + PRS-PT + covariates) achieved an AUC improvement of 6.26% compared to the (PRS-PT + covariates) model. In terms of risk stratification, the combined model was able to capture the risk of MI up to approximately eight-fold higher than that of the low-risk group. The netCRS and PRS-PT complement each other in predicting high-risk groups of patients with MI. We expect that using these risk prediction models will allow for the development of prevention strategies and reduction of MI morbidity and mortality.

Dataset Information

Red blood cell fatty acid levels improve GRACE score prediction of 2-yr mortality in patients with myocardial infarction.

Background

Objective

Design

Results

Conclusion

Publications

Red blood cell fatty acid levels improve GRACE score prediction of 2-yr mortality in patients with myocardial infarction.

Similar Datasets

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