OUES provides an effective, independent measure of pathological exercise physiology. Its numerical value is relatively insensitive to the duration of exercise data from which it is calculated. Its prognostic value seems to be stronger than the best available existing measures of exercise physiology.

Ischemia modified albumin (IMA), as measured using the albumin cobalt binding test, is currently the most promising biomarker for early detection of ischemia before the onset of irreversible cardiac injury. This paper reviews the information available on IMA, including its pathophysiology, analysis, clinical applications and future perspectives. The data provided was identified by a search of MEDLINE using the terms IMA, biomarkers and ischemia. IMA may be useful to cover the complete diagnostic window of patients presenting with acute coronary syndromes (ACS) in the Emergency Department, along with the electrocardiogram and cardiac troponins. Preliminary data regarding the significance of IMA in the prognosis of either ACS or following revascularization need further study.

The diagnostic and prognostic power of the fractal complexity measure ‘α’ of detrended fluctuation analysis (DFA) has remained mysterious because there has been no explanation of its meaning, particularly in relation to spectral analysis. First, we present a mathematical analysis of the meaning of α, in weighted power‐spectral terms. Second, we test this hypothesis and observe correlations between DFA‐based and weighted spectral methods of 0.97 (P < 0.0001) for α1 and 0.98 (P < 0.0001) for α2. Third, we predict mathematically that even in conventional (unweighted) spectral analysis there should be approximate counterparts to DFA, namely that α1 and α2 behave broadly in proportion to the conventional (unweighted) ratios LF/(HF + LF) and VLF/(LF + VLF), respectively, where HF is high frequency, LF is low frequency and VLF is very low frequency. Fourth, we test this hypothesis by physiologically manipulating spectral ratios in healthy volunteers in two ways. The effect of 0.1 Hz controlled breathing on LF/(HF + LF) correlates markedly with the effect on α1 (r= 0.73, P= 0.01); the effect on VLF/(LF + VLF) correlates markedly with that on α2 (r= 0.76, P < 0.01). Likewise, with voluntary periodic breathing the reduction in α2 correlates strongly with that in VLF/(LF + VLF) (r= 0.88, P < 0.001); effects on α1 and LF/(HF + LF) again clearly correlate (r= 0.73, P= 0.01). Finally, we examine published literature to identify previously undiscussed evidence of the relationship between α1 and LF/(HF + LF). We conclude that the α1 and α2 indices are simply frequency‐weighted versions of the spectral ratios LF/(HF + LF) and VLF/(LF + VLF), respectively, multiplied by two (giving a range of 0‐2). We can now understand fractal manifestations of physiological abnormalities: depressed baroreflex sensitivity → low LF/HF → low LF/(HF + LF) → low α1, while periodic breathing → high VLF/LF → high VLF/(LF + VLF) → high α2. Prognostic associations of α are no longer mysterious.

SUMMAR Y The aim of this study was to determine the prevalence of sleep-related breathing disorders (SDB) in a UK general heart failure (HF) population, and assess its impact on neurohumoral markers and symptoms of sleepiness and quality of life. Eighty-four ambulatory patients (72 male, mean (SD) age 68.6 (10) yrs) attending UK HF clinics underwent an overnight recording of respiratory impedance, SaO 2 and heart rate using a portable monitor (Nexan). Brain natriuretic peptide (BNP) and urinary catecholamines were measured. Subjective sleepiness and the impairment in quality of life were assessed (Epworth Sleepiness Scale (ESS), SF-36 Health Performance Score). SDB was classified using the Apnoea/Hypopnoea Index (AHI). The prevalence of SDB (AHI > 15 events h )1 ) was 24%, increasing from 15% in mild-to-moderate HF to 39% in severe HF. Patients with SDB had significantly higher levels of BNP and noradrenaline than those without SDB (mean (SD) BNP: 187 (119) versus 73 (98) pg mL )1 , P ¼ 0.02; noradrenaline: 309 (183) versus 225 (148) nmol/24 h, P ¼ 0.05).There was no significant difference in reported sleepiness or in any domain of SF-36, between groups with and without SDB (ESS: 7.8 (4.7) versus 7.5 (3.6), P ¼ 0.87). In summary, in a general HF clinic population, the prevalence of SDB increased with the severity of HF. Patients with SDB had higher activation of a neurohumoral marker and more severe HF. Unlike obstructive sleep apnoea, SDB in HF had little discernible effect on sleepiness or quality of life as measured by standard subjective scales.