P4514Agreement and prognostic significance of 6 frailty tools in patients with chronic heart failure

Abstract

Abstract Background Frailty is common in patients with chronic heart failure (CHF) and is associated with adverse outcome. Many frailty tools are available, however, there is no standard way of evaluating frailty in patients with CHF. Purpose To report the prevalence of frailty, agreement and prognostic significance amongst 3 frailty assessment tools and 3 screening tools in CHF patients. Methods We comprehensively studied frailty using 6 frailty tools. Frailty screening tools include: Clinical frailty scale (CFS); Derby frailty index & Acute frailty network frailty criteria. Frailty assessment tools include: Fried criteria; Edmonton frailty score & Deficit index. Since there is no gold standard in evaluating frailty in CHF patients, for each of the frailty tools, we used the results of the other 5 tools to produce a combined frailty index which we used as a “standard” frailty tool. Subjects were defined as frail if so identified by at least 3 out of 5 tools. Results 467 consecutive ambulatory CHF patients (67% male, median age 76 (IQR: 69–82) years, median NTproBNP 1156 (IQR: 469–2463) ng/L) and 87 controls (79% male, median age 73 (IQR: 69–77 years) were studied. Prevalence of frailty was much higher in CHF patients than in controls (30–52% vs 2–15%, respectively). Amongst the frailty screening tools, DFI scored the greatest proportion of patients as frail (48%) while CFS scored the lowest proportion as frail (44%). Amongst the assessment tools, Fried criteria scored the greatest proportion of patients as frail (52%) while EFS scored the lowest proportion as frail (30%). Frail patients were older, have worse symptoms, higher NTproBNP and more co-morbidities compared to non-frail patients. Of the screening tools, CFS had the strongest agreement with assessment tools (kappa coefficient: 0.65–0.72, all p<0.001). CFS had the highest sensitivity (87%) and specificity (89%) amongst screening tools and the lowest misclassification rate (12%) amongst all 6 frailty tools in identifying frailty according to the combined frailty index. During a median follow-up of 559 days (IQR 512–629 days), 82 (18%) patients died. 55% (N=45) of frail patients died of non-cardiovascular causes. Worsening frailty as detected by all 6 frailty tools was associated with worse outcome. A base model for mortality prediction including sex, NYHA class (III/IV vs I/II), BMI, log NTproBNP and haemoglobin had a C-statistics of 0.78. Amongst frailty tools: CFS and Fried criteria increased model performance most compared with base model (c-statistics: 0.80 for both). Patients who were frail according to CFS had a 9 times greater mortality risk than non-frail patients (Figure). Conclusion Frailty is common in CHF patients and is associated with worse outcome. CFS is a simple screening tool which identifies a similar group as lengthy assessment tools and has similar prognostic significance. Frailty screening should be incorporated into routine care of patients with CHF. Acknowledgement/Funding None