Risk prediction in stable angina pectoris.

BACKGROUND: Although stable angina pectoris often carries a favourable prognosis, it remains important to identify patients with an increased risk of cardiovascular (CV) complications. Many new markers of disease activity and prognosis have been described. We evaluated whether common and easily accessible markers in everyday care provide sufficient prognostic information. MATERIALS AND METHODS: The Angina Pectoris Prognosis Study in Stockholm treated 809 patients (248 women) with stable angina pectoris with metoprolol or verapamil double blind during a median follow-up of 3·4 years, with a registry-based extended follow-up after 9·1 years. Clinical and mechanistic variables, including lipids and glucose, renal function, ambulatory and exercise-induced ischaemia, heart rate variability, cardiac and vascular ultrasonography, and psychosocial variables were included in an integrated analysis. Main outcome measures were nonfatal myocardial infarction (MI) and CV death combined. RESULTS: In all, 139 patients (18 women) suffered a main outcome. Independent predictive variables were (odds ratio [95% confidence intervals]), age (1·04 per year [1·00;1·08], P = 0·041), female sex (0·33 [0·16;0·69], P = 0·001), fasting blood glucose (1.29 per mM [1.14; 1.46], P < 0·001), serum creatinine (1·02 per µM [1·00;1·03], P < 0·001) and leucocyte counts (1·21 per 10(6)  cells/L [1·06;1·40], P = 0·008). Smoking habits, lipids and hypertension or a previous MI provided limited additional information. Impaired fasting glucose was as predictive as manifest diabetes and interacted adversely with serum creatinine. Sexual problems were predictive among men. CONCLUSIONS: Easily accessible clinical and demographic variables provide a good risk prediction in stable angina pectoris. Impaired glucose tolerance and an elevated serum creatinine are particularly important.

Long-term stability of heart rate variability in chronic stable angina pectoris, and the impact of an acute myocardial infarction.

BACKGROUND: Heart rate variability (HRV) reflects the balance between cardiac parasympathetic and sympathetic autonomic influences. Reduced HRV has adverse prognostic implications. The time course for changes in HRV over prolonged periods of time and the influence of an acute coronary event on HRV are not well established. METHODS: Heart rate variability was assessed in patients with chronic stable angina pectoris, who were followed for 3 years within the Angina Prognosis Study in Stockholm. Patients who suffered an acute myocardial infarction after the study were re-examined after this event. We assessed HRV by the simple geometric method differential index, and traditional time- and frequency-domain measurements of HRV. RESULTS: The differential index was essentially unchanged during the study (i.e. the ratio month 36/month 1 was 1.00 +/- 0.06, n = 261). Also most other time and frequency indices of HRV (SDNN, r-MSSD, SDNNIDX, total power, and VLF, LF, HF respectively; n = 63) remained largely unchanged; pNN50 and LF/HF were, however, less reproducible. In 21 patients with a subsequent acute myocardial infarction, SDNN, SDNNIDX, total power, LF and LF/HF were reduced following the event, whereas differential index, pNN50 and HF remained unchanged. CONCLUSIONS: Differential index and other indices of HRV are stable and reproducible in patients with chronic stable angina pectoris. High-frequency HRV (reflecting cardiac parasympathetic activity) and the differential index changed little following an acute coronary event, and may be suitable for predictions of the future risk of sudden death even in the presence of a recent acute coronary event.

Differential index: a simple time domain heart rate variability analysis with prognostic implications in stable angina pectoris.

OBJECTIVES: To examine the usefulness of time domain heart rate variability (HRV) measurements by a simple graphical method, the differential index (DI), in prognostic assessments of patients with chronic stable angina pectoris. METHODS: HRV measurements in the time domain by DI were compared to conventional measurements of standard deviation of all normal-to-normal intervals (SDNN), percent of differences between adjacent normal RR intervals >50 ms (PNN50) and square root of the mean of the sum of squares of differences between adjacent normal RR intervals (RMSSD) from 24-hour ambulatory electrocardiographic recordings in 678 patients in the Angina Prognosis Study in Stockholm. The patients received double-blind treatment with metoprolol or verapamil. Main outcome measures were cardiovascular death or non-fatal myocardial infarction during follow-up (median 40 months). RESULTS: Patients suffering cardiovascular death (n = 30) had lower DI, SDNN and PNN50 (all p < 0.001). In a multivariate Cox model, DI below median independently predicted cardiovascular death (p = 0.002), as did SDNN (p = 0.016) and PNN50 (p = 0.030), but not RMSSD (p = 0.10). The separation of survival curves was most pronounced and specificity was slightly better with DI. DI and PNN50 increased with metoprolol but not verapamil treatment. Short-term treatment effects were not related to prognosis. CONCLUSIONS: Low time domain HRV carries independent prognostic information regarding cardiovascular death in stable angina pectoris. The simple DI method provided equally good or better prognostic information than conventional, more laborious HRV methods.

Differential index, a novel graphical method for measurements of heart rate variability.

BACKGROUND: Commonly used methods to evaluate heart rate variability require extensive filtering of the registrations in order to exclude artefacts and ectopic beats. We developed and validated a novel graphical method for time-domain measurements of heart rate variability, the differential index, which does not require filtering and is simple to use. METHODS: The 24-h ambulatory long-term electrocardiogram recordings from 120 patients with angina pectoris and 49 control subjects were computerised without any filtering process. Sample density histograms of differences in the RR interval for successive beats were constructed and the widths of the histograms were used to obtain the differential index. For comparison, the same registrations were analysed by conventional methods. RESULTS: The differential index was most closely related (P<0.001) to conventional short-term time domain (e.g. percent of differences between adjacent normal RR intervals >50 ms, pNN50, r=0.81) and frequency-domain (e.g. high frequency power, r=0.84) components, but also to long-term time domain (e.g. standard deviation of all normal-to-normal RR intervals for all 5-min segments of the entire registration, SDNNIDX, r=0.72) and frequency-domain (e.g. low frequency power, r=0.64) components. CONCLUSION: The differential index method shows good agreement with established indices of heart rate variability. The insensitivity to recording artefacts and short-lasting disturbances of sinus rhythm make the differential index method particularly suited when data quality is imperfect. The simplicity of the method is valuable when large numbers of registrations are to be evaluated.