Comorbid Conditions Heart Failure Research Articles

Prognostic value of reverse remodelling criteria in heart failure with reduced or mid-range ejection fraction.

AimsReverse remodelling (RR) is the recovery from left ventricular (LV) dilatation and dysfunction. Many arbitrary criteria for RR have been proposed. We searched the criteria with the strongest prognostic yield for the hard endpoint of cardiovascular death.Methods and resultsWe performed a systematic literature search of diagnostic criteria for RR. We evaluated their prognostic significance in a cohort of 927 patients with LV ejection fraction (LVEF) < 50% undergoing two echocardiograms within 12 ± 2 months. These patients were followed for a median of 2.8 years (interquartile interval 1.3–4.9) after the second echocardiogram, recording 123 cardiovascular deaths. Two prognostic models were defined. Model 1 included age, LVEF, N‐terminal pro‐B‐type natriuretic peptide, ischaemic aetiology, cardiac resynchronization therapy, estimated glomerular filtration rate, New York Heart Association, and LV end‐systolic volume (LVESV) index, and Model 2 the validated Cardiac and Comorbid Conditions Heart Failure score. We identified 25 criteria for RR, the most used being LVESV reduction ≥15% (12 studies out of 42). In the whole cohort, two criteria proved particularly effective in risk reclassification over Model 1 and Model 2. These criteria were (i) LVEF increase >10 U and (ii) LVEF increase ≥1 category [severe (LVEF ≤ 30%), moderate (LVEF 31–40%), mild LV dysfunction (LVEF 41–55%), and normal LV function (LVEF ≥ 56%)]. The same two criteria yielded independent prognostic significance and improved risk reclassification even in patients with more severe systolic dysfunction, namely, those with LVEF < 40% or LVEF ≤ 35%. Furthermore, LVEF increase >10 U and LVEF increase ≥1 category displayed a greater prognostic value than LVESV reduction ≥15%, both in the whole cohort and in the subgroups with LVEF < 40% or LVEF ≤ 35%. For example, LVEF increase >10 U independently predicted cardiovascular death over Model 1 and LVESV reduction ≥15% (hazard ratio 0.40, 95% confidence interval 0.18–0.90, P = 0.026), while LVESV reduction ≥15% did not independently predict cardiovascular death (P = 0.112).ConclusionsLeft ventricular ejection fraction increase >10 U and LVEF increase ≥1 category are stronger predictors of cardiovascular death than the most commonly used criterion for RR, namely, LVESV reduction ≥15%.

Effects of the Cardiac and Comorbid Conditions Heart Failure (3C-HF) Score at Admission on Life Space at Three Months after Hospital Discharge in Elderly Patients with Heart Failure: A Short Report.

We assessed 22 elderly patients with heart failure, 3 months after hospital discharge. We examined and compared factors that predict small life space after discharge with the same factors before discharge. Life-Space Assessment was used to classify the participants as either having “small living spaces” or “large living spaces”. We collected data regarding characteristics, Cardiac and Comorbid Conditions Heart Failure Score (3C-HF score), and evaluated motor function. We also collected data on the patients’ lifestyle habits. We investigated spreading life space at 3 months after discharge by mailing a questionnaire to the subjects. Using multiple logistic regression analysis, we were able to predict the patients having a small life space at 3 months after discharge by the Cardiac and Comorbid Conditions Heart Failure (3C-HF) score (odds ratio, 1.19; 95% confidence interval, 1.01–1.39; p = 0.038) at admission. Overall, the 3C-HF score at admission may be associated with the size of life space at 3 months after hospital discharge in elderly patients with heart failure. Future multicenter studies should be conducted to validate the results of this study by measuring post-discharge activity with a more objective index.

Incremental Value of Gait Speed in Predicting Prognosis of Older Adults With Heart Failure: Insights From the IMAGE-HF Study

ObjectivesThe aim of this study was to assess the relationship between gait speed and the risk for death and/or hospital admission in older patients with heart failure (HF). BackgroundGait speed is a reliable single marker of frailty in older people and can predict falls, disability, hospital admissions, and mortality. MethodsIn total, 331 community-living patients ≥70 years of age (mean age 78 ± 6 years, 43% women, mean ejection fraction 35 ± 11%, mean New York Heart Association functional class 2.7 ± 0.6) in stable condition and receiving optimized therapy for chronic HF were prospectively enrolled and followed for 1 year. Gait speed was measured at the usual pace over 4 m, and cutoffs were defined by tertiles: ≤0.65, 0.66 to 0.99, and ≥1.0 m/s. ResultsThere was a significant association between gait speed tertiles and 1-year mortality: 38.3%, 21.9%, and 9.1% (p < 0.001), respectively. On multivariate analysis, gait speed was associated with a lower risk for all-cause death (hazard ratio: 0.62; 95% confidence interval: 0.43 to 0.88) independently of age, ejection fraction <20%, systolic blood pressure, anemia, and absence of beta-blocker therapy. Gait speed was also associated with a lower risk for hospitalization for HF and all-cause hospitalization. When gait speed was added to the multiparametric Cardiac and Comorbid Conditions Heart Failure risk score, it improved the accuracy of risk stratification for all-cause death (net reclassification improvement 0.49; 95% confidence interval: 0.26 to 0.73, p < 0.001) and HF admissions (net reclassification improvement 0.37; 95% confidence interval: 0.15 to 0.58; p < 0.001). ConclusionsGait speed is independently associated with death, hospitalization for HF, and all-cause hospitalization and improves risk stratification in older patients with HF evaluated using the Cardiac and Comorbid Conditions Heart Failure score. Assessment of frailty using gait speed is simple and should be part of the clinical evaluation process.

Reasons why patients suffering from chronic heart failure at very high risk for death survive

BackgroundAn accurate prognostic stratification is essential for optimizing the clinical management and treatment decision-making of patients with chronic heart failure (HF). Among the best available models, we used the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause mortality in patients with CHF. Methods: we selected and characterized the subgroup of patients at very high risk with the worst mid-term prognosis belonging to the highest decile of 3C-HF score with the aim to assess predictors of survival in subjects with an expected probability of 1-year mortality near to 45%. Methods and resultsWe recruited 1777 consecutive chronic HF patients at 3 Italian Cardiology Units. Median age was 76±10years, 43% were female, and 32% had preserved ejection fraction. Subjects belonging to the highest decile of 3C-HF score were 246 (13.8% of total population). During a median follow-up of 21 [12–40] months, 110 of these patients (45%) survived and 136 (55%) died. The variables that contributed to survival prediction emerged by Cox regression multivariate analysis were the lower degree of renal dysfunction and higher body mass index. ConclusionsThe prognostic stratification of chronic HF patients allows in daily practice to select patients at different risk for death and identify prognosticators of survival in outliers at very high risk of death. The reasons why these patients outlive the matching part of subjects who expectedly die are related to the maintenance of a satisfactory renal function and body mass index.

Predicting heart failure outcome from cardiac and comorbid conditions: The 3C-HF score

BackgroundPrognostic stratification in heart failure (HF) is crucial to guide clinical management and treatment decision-making. Currently available models to predict HF outcome have multiple limitations. We developed a simple risk stratification model, based on routinely available clinical information including comorbidities, the Cardiac and Comorbid Conditions HF (3C-HF) Score, to predict all-cause 1-year mortality in HF patients. MethodsWe recruited in a cohort study 6274 consecutive HF patients at 24 Cardiology and Internal Medicine Units in Europe. 2016 subjects formed the derivation cohort and 4258 the validation cohort. We entered information on cardiac and comorbid candidate prognostic predictors in a multivariable model to predict 1-year outcome. ResultsMedian age was 69years, 35.8% were female, 20.6% had a normal ejection fraction, and 65% had at least one comorbidity. During 5861 person-years follow-up, 12.1% of the patients met the study end-point of all-cause death (n=750) or urgent transplantation (n=9). The variables that contributed to outcome prediction, listed in decreasing discriminating ability, were: New York Heart Association class III–IV, left ventricular ejection fraction <20%, no beta-blocker, no renin–angiotensin system inhibitor, severe valve heart disease, atrial fibrillation, diabetes with micro or macroangiopathy, renal dysfunction, anemia, hypertension and older age. The C statistic for 1-year all-cause mortality was 0.87 for the derivation and 0.82 for the validation cohort. ConclusionsThe 3C-HF score, based on easy-to-obtain cardiac and comorbid conditions and applicable to the 1-year time span, represents a simple and valuable tool to improve the prognostic stratification of HF patients in daily practice.