scholarly journals Characteristic of Metabolic Status in Heart Failure and Its Impact in Outcome Perspective

Metabolites ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 437
Author(s):  
Hsiang-Yu Tang ◽  
Chao-Hung Wang ◽  
Hung-Yao Ho ◽  
Jui-Fen Lin ◽  
Chi-Jen Lo ◽  
...  
Keyword(s):  
Heart Failure ◽  
Metabolic Profiling ◽  
High Performance ◽  
Prediction Models ◽  
Operating Characteristics ◽  
Prognostic Information ◽  
Peripheral Tissues ◽  
Flight Mass Spectrometry ◽  
Characteristics Analysis ◽  
Outcome Perspective

Metabolic alterations have been documented in peripheral tissues in heart failure (HF). Outcomes might be improved by early identification of risk. However, the prognostic information offered is still far from enough. We hypothesized that plasma metabolic profiling potentially provides risk stratification for HF patients. Of 61 patients hospitalized due to acute decompensated HF, 31 developed HF-related events in one year after discharge (Event group), and the other 30 patients did not (Non-event group). The plasma collected during hospital admission was analyzed by an ultra-high performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOFMS)-based metabolomic approach. The orthogonal projection to latent structure discriminant analysis (OPLS-DA) reveals that the metabolomics profile is able to distinguish between events in HF. Levels of 19 metabolites including acylcarnitines, lysophospholipids, dimethylxanthine, dimethyluric acid, tryptophan, phenylacetylglutamine, and hypoxanthine are significantly different between patients with and without event (p < 0.05). Established risk prediction models of event patients by using receiver operating characteristics analysis reveal that the combination of tetradecenoylcarnitine, dimethylxanthine, phenylacetylglutamine, and hypoxanthine has better discrimination than B-type natriuretic peptide (BNP) (AUC 0.871 and 0.602, respectively). These findings suggest that metabolomics-derived metabolic profiling have the potential of identifying patients with high risk of HF-related events and provide insights related to HF outcome.

P3528Circulating microRNA-210 concentrations are increased in patients with acute heart failure and provide prognostic information

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
A Rutkovskiy ◽  
M N Lyngbakken ◽  
M B Dahl ◽  
A Bye ◽  
M H Pedersen ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Troponin T ◽  
Quantitative Polymerase Chain Reaction ◽  
Fold Increase ◽  
Acute Dyspnea ◽  
Operating Characteristics ◽  
Prognostic Information ◽  
Control Subjects

Abstract Background MicroRNA (miR)-210 is induced by cellular hypoxia and circulating miR-210 concentrations are associated with clinical outcome in patients with myocardial infarction and aortic stenosis. Whether circulating miR-210 concentrations provide diagnostic and prognostic information in unselected patients with dyspnea is not known. Purpose To assess the diagnostic and prognostic value of circulating miR-210 concentrations in patients hospitalised due to acute dyspnea. Methods We extracted microRNA from plasma samples obtained on admission from 314 patients hospitalised for acute dyspnea and 10 healthy control subjects. miR-210 concentrations were measured by quantitative polymerase chain reaction and we used miR-425 for normalisation. The merit of circulating miR-210 concentrations to diagnose and provide prognostic information in patients with acute heart failure (HF) was compared to the merit of N-terminal pro-B-type natriuretic peptide (NT-proBNP). Results In total, 143 patients (46%) were adjudicated as hospitalised due to acute heart failure (HF) and 84 patients (27%) due to acute exacerbation of chronic obstructive lung disease (AECOPD). All patients and control subjects had miR-210 concentrations within the range of detection (Cq 26–32) and analytical variation was low. miR-210 concentrations correlated with age, NT-proBNP and cardiac troponin T concentrations in the total cohort. Circulating miR-210 concentrations were increased in patients with HF (4.7±3.3 fold increase, p<0.0001) and AECOPD (3.4±1.7 fold increase, p<0.0001) compared to control subjects. Circulating miR-210 concentrations were not different between patient groups and receiver operating characteristics area under the curve (AUC) for miR-210 to diagnose acute HF was 0.50 (95% CI 0.43–0.57) compared to AUC 0.85 (0.81–0.89) for NT-proBNP. During a median 817 days of follow-up, 66 patients (46%) with acute HF died and 35 patients (42%) with AECOPD died. Circulating miR-210 concentrations separated acute HF patients with a poor and favourable outcome (Figure 1; p by the log rank test =0.017). Circulating miR-210 concentrations were also associated with mortality during follow-up in Cox regression model: hazard ratio (HR) for lnRQ of miR-210 was 2.11 (95% CI 1.27–2.50), p=0.004. The association between circulating miR-210 concentrations and outcome was attenuated and no longer significant after adjusting for NT-proBNP concentrations. Circulating miR-210 concentrations did not predict outcome in patients with AECOPD: HR 1.38 (0.65–2.93); p=0.4. Figure 1 Conclusions Circulating miR-210 concentrations are increased in patients with acute HF, and provide prognostic information during follow-up. Still, circulating miR-210 concentrations did not diagnose acute HF among unselected patients with dyspnea and the association with outcome was attenuated by NT-proBNP. Acknowledgement/Funding Nasjonalforeningen for Folkehelsen

scholarly journals Using the OHDSI network to develop and externally validate a patient-level prediction model for Heart Failure in Type II Diabetes Mellitus

2021 ◽  
Author(s):  
Ross D. Williams ◽  
Jenna M. Reps ◽  
Jan A Kors ◽  
Patrick B Ryan ◽  
Ewout Steyerberg ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Heart Failure ◽  
High Performance ◽  
Prediction Models ◽  
External Validation ◽  
The United States ◽  
The Other ◽  
Patient Treatment ◽  
Administrative Claims ◽  
Second Line

AbstractIntroductionHeart Failure (HF) and Type 2 Diabetes Mellitus (T2DM) frequently coexist and exacerbate symptoms of each other. Treatments are available for T2DM that also provide beneficial treatment effects for HF. Guidelines recommend that patients with HF should be given Sodium-glucose co-transporter-2 inhibitors in preference to other second-line treatments for T2DM. Increasing personalization of treatment means that patients who have or are at risk of HF receive a customised treatment. We aimed to develop and externally validate prediction models to predict the 1-year risk of incident HF in T2DM patients starting second-line treatment.MethodsWe analysed a federated network of electronic medical records and administrative claims data from five databases (CCAE, MDCD, MDCR, Optum Clinformatics and Optum EHR) in the United States. We used each database to develop a model to predict 1-year risk of incident HF in patients initialising a second pharmaceutical intervention, following initial treatment with metformin for T2DM. We then performed internal validation for each model as well as external validation using the other databases.ResultsA total of 403,187 patients were included in the study. We developed 5 models with discrimination ranging from 0.72 to 0.80 at external validation in the other databases. Consistent high performance was noted for models developed in CCAE, Optum Clinformatics and Optum EHR with AUCs ranging from 0.74 to 0.81. For these models, calibration was acceptable.ConclusionThree high-performing prediction models were developed for this problem. The CCAE developed model was selected for recommendation as it achieved the same discrimination and better calibration performance than the Optum Clinformatics and Optum EHR models, whilst selecting fewer covariates and as such was selected as the best developed model. The models could be useful in stratifying patient treatment, planning healthcare utilization and reducing cost by aiding in increasing preparedness of healthcare providers.

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