Dataset Information

Biomarker prognostication across Universal Definition of Heart Failure stages.

ABSTRACT:

Aim

The Universal Definition of Heart Failure (UDHF) provides a framework for staging risk for HF events. It is not clear whether prognostic biomarkers have different meaning across UDHF stages. We sought to evaluate performance of biomarkers to predict HF events among high-risk patients undergoing coronary and/or peripheral angiography categorized into UDHF stages.

Methods

One thousand two hundred thirty-five individuals underwent coronary and/or peripheral angiography were enrolled. Study participants were categorized into UDHF Stage A (at risk), Stage B (pre-HF), and Stage C or D (HF, including end stage) and grouped into Stage A/B and C/D. Biomarkers and clinical variables were used to develop prognostic models. Other measures examined included total HF hospitalizations.

Results

Over a median of 3.67 years of follow-up, 155 cardiovascular (CV) deaths occurred, and 299 patients were hospitalized with acute HF. In patients with Stage A/B, galectin-3 (HR = 1.52, P = 0.03), endothelin-1 (HR = 2.16, P = 0.001), and N-terminal pro-B-type natriuretic peptide (NT-proBNP; HR = 1.43, P < 0.001) were associated with incident CV death/HF hospitalization. In Stage C/D, NT-proBNP (HR = 1.26, P = 0.006), soluble urokinase-type plasminogen activator receptor (suPAR; HR = 1.57, P = 0.007) and high-sensitivity C-reactive protein (hs-CRP; HR = 1.15, P = 0.01) were associated with these outcomes. Higher biomarker concentrations were associated with greater total burden of HF events in Stages A/B and C/D.

Conclusions

Among higher risk individuals undergoing angiographic procedures, different biomarkers improve risk stratification in different UDHF stages of HF. More precise prognostication may offer a window of opportunity to initiate targeted preventive measures.

SUBMITTER: Mohebi R

PROVIDER: S-EPMC9773759 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

Biomarker prognostication across Universal Definition of Heart Failure stages.

Mohebi Reza R Murphy Sean S Jackson Laurel L McCarthy Cian C Abboud Andrew A Murtagh Gillian G Gawel Susan S Miksenas Hannah H Gaggin Hanna H Januzzi James L JL

ESC heart failure 20220808 6

<h4>Aim</h4>The Universal Definition of Heart Failure (UDHF) provides a framework for staging risk for HF events. It is not clear whether prognostic biomarkers have different meaning across UDHF stages. We sought to evaluate performance of biomarkers to predict HF events among high-risk patients undergoing coronary and/or peripheral angiography categorized into UDHF stages.<h4>Methods</h4>One thousand two hundred thirty-five individuals underwent coronary and/or peripheral angiography were enrol ...[more]

PMID: 35942508

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Project description:BackgroundObjective tools to define the optimal time for referral for advanced therapies and to help guide escalation and de-escalation of support can improve management decisions and outcomes for patients with advanced heart failure. The current parameters have variable prognostic potential depending on the patient population being studied and often have arbitrary thresholds.MethodsHere, a mathematical and physiological framework to define the patient-specific tipping point of myocardial energetics is defined. A novel hemodynamic parameter known as the myocardial performance score (MPS), a marker of power and efficiency, is introduced that allows for the objective assessment of the physiological tipping point. The performance of the MPS and other advanced hemodynamic parameters including aortic pulsatility index (API) and cardiac power output (CPO) in predicting myocardial energetics and the overall myocardial performance was evaluated using a validated computer simulation model of heart failure (Harvi) as well as a proof-of-concept clinical validation using a cohort of the Society for Cardiovascular Angiography and Interventions (SCAI) Stage C cardiogenic shock patients.ResultsApproximately 1010 discrete heart failure scenarios were modeled. API strongly correlated with the left ventricular coupling ratio (R2 = 0.81) and the strength of association became even stronger under loaded conditions where pulmonary capillary wedge pressure (PCWP) was >20 mmHg (R2 = 0.94). Under loaded conditions, there is a strong logarithmic relationship between MPS and mechanical efficiency (R2 = 0.93) with a precipitous rise in potential energy (PE) and drop in mechanical efficiency with an MPS <0.5. An MPS <0.5 was able to predict a CPO <0.6 W and coupling ratio of <0.7 with sensitivity (Sn) of 87%, specificity (Sp) of 91%, positive predictive value of 81%, and negative predictive value of 94%. In a cohort of 224 patients with SCAI Stage C shock requiring milrinone initiation, a baseline MPS score of <0.5 was associated with a 35% event rate of the composite endpoint of death, left ventricular assist device, or transplant at 30 days compared with 3% for those with an MPS >1 (p < 0.001). Patients who were able to augment their MPS to >1 after milrinone infusion had a lower event rate than those with insufficient reserve (40% vs. 16%, p = 0.01).ConclusionsThe MPS, which defines the patient-specific power-to-efficiency ratio and is inversely proportional to PE, represents an objective assessment of the myocardial energetic state of a patient and can be used to define the physiological tipping point for patients with advanced heart failure.

Project description:BackgroundDespite advances in pharmacologic therapy and devices, patients with heart failure (HF) continue to have significant rehospitalization rates and risk prediction remains challenging. We sought to explore the value of a multi-biomarker panel [including NT-proBNP, high-sensitivity cardiac troponin T (hs-TnT), and ST2] on top of clinical assessment for long-term prediction of recurrent hospitalizations in HF.Methods and resultsNT-proBNP, hs-TnT, and ST2 (suppression of tumorigenicity-2) levels were measured in 891 consecutive ambulatory HF patients. The independent association between the multi-biomarker panel and recurrent hospitalizations was assessed through a multivariable negative binomial regression and expressed as incidence rates ratios. McFadden pseudo-R2 and goodness-of-fit measures were also used. The total number of unplanned hospitalizations [all-cause, cardiovascular (CV)-, and HF-related] were selected as the primary endpoints. At a mean follow-up of 4.2 ± 2.1 years, 1623 all-cause hospitalizations in 498 patients (55.9%), 710 CV-related hospitalizations in 331 patients (37.2%), and 444 HF-related hospitalizations in 214 patients (24.1%) were registered. The crude incidence of all-cause, CV-, and HF-related recurrent hospitalizations was significantly higher for patients with the multi-biomarker panel above the cut-point (hs-TnT > 14 ng/L, NT-proBNP > 1000 ng/L, and ST2 > 35 ng/mL) (all P < 0.001). For all-cause, CV-, and HF-related recurrent hospitalizations, the McFadden R2, Akaike information criterion, and Bayesian information criterion supported the superiority of incorporating the multi-biomarker panel into a clinical predictive model.ConclusionA multi-biomarker approach based on NT-proBNP, hs-TnT, and ST2 better identifies HF patients at risk for recurrent hospitalizations as compared to approaches entailing just one or two of these biomarkers. Elucidation of new biophysiological predictors for recurrent hospitalizations may identify patient profiles for focused intervention.

Dataset Information

Biomarker prognostication across Universal Definition of Heart Failure stages.

Aim

Methods

Results

Conclusions

Publications

Biomarker prognostication across Universal Definition of Heart Failure stages.

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