scholarly journals APPLICATION OF THE TIMI HEART FAILURE RISK SCORE TO THE EMPA-REG OUTCOME POPULATION

2020 ◽  
Vol 75 (11) ◽  
pp. 1851
Author(s):  
Subodh Verma ◽  
Abhinav Sharma ◽  
Bernard Zinman ◽  
Anne Pernille Ofstad ◽  
David Fitchett ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Failure Risk

scholarly journals External assessment of the EUROMACS right-sided heart failure risk score

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hirak Shah ◽  
Thomas Murray ◽  
Jessica Schultz ◽  
Ranjit John ◽  
Cindy M. Martin ◽  
...  
Keyword(s):  
Heart Failure ◽  
Right Ventricular ◽  
Risk Score ◽  
Pressure Ratio ◽  
Area Under The Curve ◽  
Left Ventricular ◽  
Right Atrial ◽  
Risk Scores ◽  
External Assessment ◽  
Failure Risk

AbstractThe EUROMACS Right-Sided Heart Failure Risk Score was developed to predict right ventricular failure (RVF) after left ventricular assist device (LVAD) placement. The predictive ability of the EUROMACS score has not been tested in other cohorts. We performed a single center analysis of a continuous-flow (CF) LVAD cohort (n = 254) where we calculated EUROMACS risk scores and assessed for right ventricular heart failure after LVAD implantation. Thirty-nine percent of patients (100/254) had post-operative RVF, of which 9% (23/254) required prolonged inotropic support and 5% (12/254) required RVAD placement. For patients who developed RVF after LVAD implantation, there was a 45% increase in the hazards of death on LVAD support (HR 1.45, 95% CI 0.98–2.2, p = 0.066). Two variables in the EUROMACS score (Hemoglobin and Right Atrial Pressure to Pulmonary Capillary Wedge Pressure ratio) were not predictive of RVF in our cohort. Overall, the EUROMACS score had poor external discrimination in our cohort with area under the curve of 58% (95% CI 52–66%). Further work is necessary to enhance our ability to predict RVF after LVAD implantation.

scholarly journals The MESA heart failure risk score: can't we do more?: Table 1

Heart ◽  
2014 ◽  
Vol 101 (1) ◽  
pp. 7-9
Author(s):  
Jennifer E Ho ◽  
Jared W Magnani
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Failure Risk

scholarly journals “Get with the Guidelines Heart Failure Risk Score” for mortality prediction in patients undergoing MitraClip

2021 ◽  
Author(s):  
Christos Iliadis ◽  
Maximilian Spieker ◽  
Refik Kavsur ◽  
Clemens Metze ◽  
Martin Hellmich ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Goodness Of Fit ◽  
Left Ventricular ◽  
Risk Scores ◽  
Left Ventricular Ejection ◽  
Goodness Of Fit Test ◽  
Ventricular Ejection Fraction ◽  
Failure Risk ◽  
Get With The Guidelines

Abstract Background Reliable risk scores in patients undergoing transcatheter edge-to-edge mitral valve repair (TMVR) are lacking. Heart failure is common in these patients, and risk scores derived from heart failure populations might help stratify TMVR patients. Methods Consecutive patients from three Heart Centers undergoing TMVR were enrolled to investigate the association of the “Get with the Guidelines Heart Failure Risk Score” (comprising the variables systolic blood pressure, urea nitrogen, blood sodium, age, heart rate, race, history of chronic obstructive lung disease) with all-cause mortality. Results Among 815 patients with available data 177 patients died during a median follow-up time of 365 days. Estimated 1-year mortality by quartiles of the score (0–37; 38–42, 43–46 and more than 46 points) was 6%, 10%, 23% and 30%, respectively (p < 0.001), with good concordance between observed and predicted mortality rates (goodness of fit test p = 0.46). Every increase of one score point was associated with a 9% increase in the hazard of mortality (95% CI 1.06–1.11%, p < 0.001). The score was associated with long-term mortality independently of left ventricular ejection fraction, NYHA class and NTproBNP, and was equally predictive in primary and secondary mitral regurgitation. Conclusion The “Get with the Guidelines Heart Failure Risk Score” showed a strong association with mortality in patients undergoing TMVR with additive information beyond traditional risk factors. Given the routinely available variables included in this score, application is easy and broadly possible. Graphic abstract

scholarly journals External Assessment of EUROMACS Right-Sided Heart Failure Risk Score

2019 ◽  
Vol 38 (4) ◽  
pp. S354
Author(s):  
H. Shah ◽  
T. Murray ◽  
A. El Rafei ◽  
J. Schultz ◽  
T. Thenappan ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
External Assessment ◽  
Failure Risk

Creation and validation of the acute heart failure risk score: AHFRS

2016 ◽  
Vol 12 (8) ◽  
pp. 1197-1206 ◽  
Author(s):  
Susana Garcia-Gutierrez ◽  
◽  
José Maria Quintana ◽  
Ane Antón-Ladislao ◽  
Maria Soledad Gallardo ◽  
...  
Keyword(s):  
Heart Failure ◽  
Acute Heart Failure ◽  
Risk Score ◽  
Failure Risk

Abstract 15659: Dynamic Device Derived Heart Failure Risk Score as a Predictor of Heart Failure Hospitalisation

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Maciej Debski ◽  
Lesley Howard ◽  
Paula Black ◽  
Angelic Goode ◽  
Christopher Cassidy ◽  
...  
Keyword(s):  
Heart Failure ◽  
Risk Score ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Tertiary Centre ◽  
Cardiac Devices ◽  
Failure Risk ◽  
Heart Failure Hospitalisation

Introduction: The number of people being admitted to hospital in England due to heart failure (HF) has risen by a third in the last five years. Implantable cardiac devices with integrated heart failure diagnostics are capable of combining daily measurements of multiple device-derived parameters and provide a heart failure risk score (HFRS) which might help predict HF worsening. Methods: Between 2015 and 2019 231 consecutive HF device patients were co-managed (CM) by specialist HF nurses in a tertiary centre. Follow-up was truncated at last device transmission in 2019. HF nurses’ interventions to alerts were recorded prospectively. HF-related hospitalisations were collected from hospital records. We analysed the predictive value of baseline variables on the count of days in high HFRS in a negative binomial regression model. The device settings: Optivol CareAlert switched ON vs OFF were compared. Results: 200 patients with CRT-D were followed up for 2.6 [1.0-2.8] years (Figure). Baseline characteristics and their effect on the incidence rate ratio (IRR) of days in high HFRS are presented in Table. A total of 3,486 transmissions were assessed, median 7.3 [5.9-10.0] per patient-year; 591 high HFRS episodes occurred in 115 (58%) pts. Optivol OFF increased the rate of high HFRS being transmitted >30 days after its end (45% vs 35%, P=0.018) and increased the time from episode start to transmission (36 [16-68] vs 24 [8-53] days, P<0.001). Of 21 hospitalisations for decompensated HF, 15 were predicted by high HFRS within 30 days whereas 6 were predated by medium HFRS. Conclusion: Patients who have not had a single high HFRS during follow-up did not need admission for decompensated HF.

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