A Simple Risk Score Based on Routine Clinical Parameters Can Predict Frailty in Hospitalized Heart Failure Patients (original) (raw)
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Frailty may be a risk marker for adverse outcome in patients with congestive heart failure
ESC Heart Failure
Aims To examine the availability of frailty concept with objective criteria for risk stratification in patients with congestive heart failure (CHF). Methods and results Study design was secondary analysis of our CHF cohort. We selected 181 patients who completed clinical assessments and were successfully followed 2-year post discharge. To set frailty criteria, grip strength <26 kg in men and <17 kg in women (weakness) and performance measure for activities of daily living-8 ≧21 points (exhaustion) were defined for predicting 6 min walking distance <300 m (slowness) by the receiver-operating characteristics. During 2 years of follow up, subjects who met all the criteria had a 4 times greater risk of cardiac event compared with those with no frailty criteria. Conclusion The findings of present study suggest that frailty criteria may serve as a new clinical marker for management of patients with CHF.
BMC Cardiovascular Disorders
Background: Heart failure (HF) and frailty often co-exist, and frailty in HF results in a poor prognosis. However, in Asian populations, prognostic criteria are needed to examine the effect of frailty on HF. Therefore, we conducted a nationwide cohort study to develop frailty-based prognostic criteria in HF patients (FLAGSHIP). FLAGSHIP mainly aims to 1) develop the frailty criteria based on HF-specific outcomes, 2) propose a hypothesis of the potential mechanisms of frailty manifestations in HF, and 3) examine the effects of outpatient cardiac rehabilitation on frailty. Methods: In this prospective study, we consecutively enroll ambulatory patients admitted because of acute HF or exacerbation of HF and elderly patients admitted for acute myocardial infarction (age ≥ 70 years). They will be followed up for 2 years to assess frailty and hard clinical events. The primary endpoints of FLAGSHIP are cardiac events including cardiac mortality and HF-related readmission after discharge. Secondary endpoints are readmissions because of fracture or pneumonia and all-cause mortality. We used clinical data, including the items related to the frailty phenotype to develop diagnostic criteria for frailty and known prognostic factors of HF. Cognitive function, depression, and anorexia are also considered as potential components of frailty. As of March 2018, 2650 patients (85% was patients admitted for HF) have been registered from 30 collaborating hospitals nationwide in Japan. Discussion: FLAGSHIP provides diagnostic criteria and fundamental information on frailty manifestations to develop the best practices for the long-term management of HF. Diagnostic criteria on frailty developed by FLAGSHIP is expected to become a novel indicator for the stratification of patients at risk to functional decline after medical or surgical treatment, and in turn to contribute to the best practices in the long-term management of HF.
Frailty assessment instruments in heart failure: A systematic review
European journal of cardiovascular nursing : journal of the Working Group on Cardiovascular Nursing of the European Society of Cardiology, 2017
Frailty is an independent predictor of mortality across many conditions. Reported rates of frailty in heart failure range from 15% to 74%. There are several instruments available to assess frailty; however, to date there has been no consensus on the most appropriate instrument for use in individuals with heart failure. To identify how frailty is assessed in individuals with heart failure and to elucidate which domains of frailty are most frequently assessed. Key electronic databases were searched (MEDLINE, COCHRANE Central and CINAHL) to identify studies that assessed frailty in individuals with heart failure using a formal frailty instrument. Twenty studies published in 24 articles were included, for which a total of seven unique frailty instruments were identified. The most commonly used instrument was Fried's Frailty Phenotype ( n= 11), with the majority of studies using a modified version of the Fried Phenotype ( n= 8). The second most commonly used instrument identified was...
European journal of heart failure, 2016
The aim of this study was to evaluate the prevalence, clinical features, and the independent impact of frailty-a geriatric syndrome characterized by the decline of physiological systems-and its components, on prognosis after heart failure (HF) hospitalization. FRAIL-HF is a prospective cohort study including 450 non-dependent patients ≥70 years old hospitalized for HF. Frailty was screened according to the biological phenotype criteria (low physical activity, weight loss, slow walking speed, weak grip strength, and exhaustion). The independent influence of frailty on mortality, functional decline, and readmission risks was calculated adjusted for HF characteristics and co-morbidities. Mean age was 80 ± 6 years; 76% fulfilled frailty criteria. Frail patients were older, more often female, but showed no differences in chronic co-morbidities, LVEF, and NT-proBNP levels. Slow walking speed was the most discriminative component between frail (89.2%) and non-frail patients (26%). Overall,...
Frailty predicts long-term mortality in elderly subjects with chronic heart failure
European Journal of Clinical Investigation, 2005
Background The elderly are characterized by a high prevalence of chronic heart failure (CHF) and frailty, which is a complex interaction of physical, psychological and social impairment. This study aimed to examine the predictive role of frailty on long-term mortality in elderly subjects with CHF.
Frailty significantly impairs the short term prognosis in elderly patients with heart failure
Journal of Geriatric Cardiology : JGC, 2018
Background Frailty is a condition of elderly characterized by increased vulnerability to stressful events with high risk of adverse outcomes. The purpose of this study was to evaluate the association between frailty and adverse outcomes including death and hospitalization due to heart failure in elderly patients. Methods We included patients aged ≥ 65 years with the diagnosis of heart failure. The clinical and laboratory data, echocardiography and ECGs were recorded. Additionally, the frailty scores of the patients were evaluated according to Canadian Study of Health and Aging. All the patients were divided as frail or non-frail. The groups were compared for their characteristics and the occurrence of clinical outcomes. Results We included 86 eligible patients. The median follow-up time was four months. The mean age was 75 ± 6.5 years. Of these 86 patients, 17 (19.7%) patients encountered an event (death and/or hospitalization). Nine patients (10.4%) died during follow-up. Thirty pa...
Congestive Heart Failure, 2012
The prevalence of heart failure (HF) in the population is increasing, concomitant with high incidence of rehospitalizations and mortality. The aim of this study was to characterize a prognostic risk score model for patients with chronic HF. A total of 500 patients followed at the HF clinic were evaluated by clinical, functional, laboratory, imaging, and therapeutic variables that were correlated to mortality during a follow-up period of 25 months. Risk stratification was carried out by applying a risk score model based on multivariate analysis. Predictors correlated with mortality during follow-up were systolic blood pressure <110 mm Hg, male sex, age older than 70 years, 6-minute walk distance <300 m, lack of b-blocker therapy, hyperuri-cemia (>7.5 mg ⁄ dL), hyponatremia, and prolonged QTc interval (>450 ms). Based on these variables, a risk score model (score 0-55) was established and included low risk, score <21 (9% mortality during 2-year follow-up); moderate risk, 21 to 29 (22%); high risk, 30 to 35 (35%), and very high risk: !36 points (62% 2-year mortality). The risk model had good discrimination ability (concordance index 0.75), which was better than the performance of the Seattle Heart Failure Model on our cohort (0.69). Simple noninvasive characteristics examined during the initial admission to the HF clinic can serve as prognostic markers for mortality and may help in the process of therapeutic decisionmaking in patients with HF. Ó2012 Wiley Periodicals, Inc.
Impact of Frailty and Disability on 30-Day Mortality in Older Patients With Acute Heart Failure
The American journal of cardiology, 2017
The objectives were to determine the impact of frailty and disability on 30-day mortality and whether the addition of these variables to HFRSS EFFECT risk score (FBI-EFFECT model) improves the short-term mortality predictive capacity of both HFRSS EFFECT and BI-EFFECT models in older patients with acute decompensated heart failure (ADHF) atended in the emergency department. We performed a retrospective analysis of OAK Registry including all consecutive patients ≥65 years old with ADHF attended in 3 Spanish emergency departments over 4 months. FBI-EFFECT model was developed by adjusting probabilities of HFRSS EFFECT risk categories according to the 6 groups (G1: non frail, no or mildly dependent; G2: frail, no or mildly dependent; G3: non frail, moderately dependent; G4: frail, moderately dependent; G5: severely dependent; G6: very severely dependent).We included 596 patients (mean age: 83 [SD7]; 61.2% females). The 30-day mortality was 11.6% with statistically significant difference...
Predicting mortality in patients with acute heart failure: Role of risk scores
World Journal of Cardiology, 2015
and death, and it is an increasing burden on health care systems. The correct risk stratification of patients could improve clinical outcome and resources allocation, avoiding the overtreatment of low-risk subjects or the early, inappropriate discharge of high-risk patients. Many clinical scores have been derived and validated for in-hospital and post-discharge survival; predictive models include demographic, clinical, hemodynamic and laboratory variables. Data sets are derived from public registries, clinical trials, and retrospective data. Most models show a good capacity to discriminate patients who reach major clinical end-points, with C-indices generally higher than 0.70, but their applicability in realworld populations has been seldom evaluated. No study has evaluated if the use of risk score-based stratification might improve patient outcome. Some variables (age, blood pressure, sodium concentration, renal function) recur in most scores and should always be considered when evaluating the risk of an individual patient hospitalized for acute heart failure. Future studies will evaluate the emerging role of plasma biomarkers.