gms | German Medical Science

More than 50 % of patients with heart failure suffer from cardiac death within 5 years. The aim of this study was to develop an optimal multivariate parameter set for enhanced risk stratification in patients with heart failure (HF) using heart rate variability (HRV), blood pressure variability (BPV) and blood pressure morphology (BPM) analysis methods. ECG and continuously non-invasive blood pressure were recorded from 43 HF characterised by a NYHA value greater or equal 3, EF lower 45% and in 20 age and gender matched healthy subjects (REF). For the analysis of beat-to-beat variability in HRV and BPV time and frequency domain measures (according to the Task Force recommendations) were calculated. After a 6-month follow-up the HF group was divided into two subgroups: HF with no progression (HFlow, n=21, low risk group) and with significant progression of the disease including 7 patients suffered from cardiac death (HFhigh, n=22, high risk group). Mann-Whitney U-test (p<0.05) was assessed for statistical evaluation. A multivariate parameter set was developed for the risk stratification using Cox regression analysis and receiver operator curve (roc). Measures from BPV and BPM but not from HRV revealed high significances (p<0.0001) discriminating the groups REF and HF. For risk stratification in differentiating the groups HFhigh and HFlow an optimal set of three parameters was determined and achieved a sensitivity of 82.4%, specificity of 83,3% and accuracy (area under roc) of 85%. The parameter set consists of two linear parameters from BPM (maximum diastolic slope, blood pressure wave amplitude) and one non-linear parameter from BPV (non-linear interactions between blood pressure and interbeat intervals). In conclusion, the applied methods appear to be suitable for an enhanced diagnosis of HF including improved risk stratification. To validate these results further prospective studies with an increased number of patients have to be performed.