Author/Editor     Szabo, Tibor; von Haehling, Stephan; Habedank, Dirk; Rauchhaus, Mathias; Lainščak, Mitja; Sandek, Anja; Schefold, Joerg; Anker, Stefan D; Doehner, Wolfram
Title     Usefulness of minimal modelling to assess impaired insulin sensitivity in patients with chronic heart failure
Type     članek
Source     Int J Cardiol
Publication year     2009
Language     eng
Abstract     Background: In chronic heart failure (CHF), impaired insulin sensitivity (Si) is frequently observed. It is associated with symptomatic status and poor prognosis suggesting an intrinsic role of Si within CHF pathophysiology. HOmeostasis Model Assessment (HOMA), Fasting Insulin Resistance Index (FIRI), and QUick Insulin CheCK Index (QUICKI) are based on single-time fasting glucose and insulin assessment. Their value and discriminatory power in comparison to dynamic range assessment of Si by minimal modelling are not well established. Methods and results: In 105 patients with stable CHF (mean age 62+/-1years, peak VO(2) 18.2+/-0.7mL/kg/min, LVEF 28+/-2%, mean+/-SEM) Si was assessed by minimal modelling. HOMA, FIRI, and QUICKI were calculated from single-time point fasting glucose and insulin measurements. Detailed body composition was analyzed using dual-energy X-ray absorptiometry. All assessment methods showed impaired Si in CHF patients compared to healthy controls (n=25). Yet, only minimal model-derived Si differentiated between NYHA classes (p=0.0007). Further, minimal modelling was the only method to be directly associated with peak oxygen uptake and skeletal muscle strength. Model-derived Si predicted survival independently of established prognostic markers in CHF (RR 0.30 [95%CI 0.14-0.63]; p=0.0016). In contrast, HOMA, FIRI and QUICKI did not show any of these qualities. Conclusion: HOMA, FIRI and QUICKI are surrogate estimates of Si with reduced discriminatory power in patients with CHF. While they are suitable to semi-quantitatively categorize impaired Si compared to normal values, the dynamic range assessment of Si by minimal modelling is superior for quantitative assessment of Si in pathophysiological studies.
Descriptors     HEART FAILURE, CONGESTIVE
INSULIN RESISTANCE
EXERCISE TEST
BODY COMPOSITION
DENSITOMETRY, X-RAY
PROGNOSIS