Cuomo S

Diagnostic value of the ratio of recovery systolic blood pressure to peak exercise systolic blood pressure for the detection of coronary artery disease.

It has been previously reported that at treadmill exercise testing an abnormal ratio of recovery systolic blood pressure (SBP) to peak exercise SBP is more sensitive than exercise-induced angina or ST segment depression for diagnosing coronary artery disease (CAD). To investigate whether the SBP ratio keeps its diagnostic value during upright bicycle exercise, we evaluated the ratio of postexercise SBP to peak SBP in 73 patients with angiographically documented CAD and in 48 patients with normal coronary arteries (OV group) undergoing maximal stress testing on a bicycle ergometer. Three minutes after exercise ended, SBP ratio was significantly higher in the CAD than in the OV group (0.79 +/- 0.1 vs 0.71 +/- 0.08; p less than .001). Setting the upper normal limits of the recovery SBP ratio at 2 SDs from the mean for the OV group (SBP ratio = 0.98 and 0.88 at 1 and 3 min after exercise, respectively), with an increase or no change in SBP ratio at between 1 and 3 min of recovery considered an abnormal response, the sensitivity of SBP ratio was 30%, the specificity was 83%, and the accuracy was 51%. The respective values for ST depression were 81% (p less than .0001 vs SBP ratio), 48% (p less than .001 vs SBP ratio), and 67% (p less than .01 vs SBP ratio). Thus, for bicycle ergometer exercise testing, ST segment depression seems to be more accurate than SBP ratio in diagnosing CAD.

R wave amplitude changes during stress testing. Comparison with ST segment depression and angiographic correlation

Abstract One-hundred and seven exercise stress tests and coronary angiograms were reviewed retrospectively, in order to evaluate the usefulness of R wave amplitude changes (ΔR) during exercise compared with ST segment depression in the screening of patients with coronary artery disease (CAD). We also attempted to correlate ΔR with the severity of CAD as expressed by coronary arteriography and left ventriculography. Thirty-six patients showed no coronary artery narrowing (0-V); the remaining 71 patients with stenosis of 70% of at least one of the major coronary arteries were divided into three groups. Sixteen patients had single vessel disease (1-V); five (31%) in this group showed abnormal left ventricular wall motion. Thirty-one patients had two-vessel disease (2-V); 22 (71%) of the 31 demonstrated abnormal left ventricular wall motion. Twenty-four patients had three-vessel disease (3-V); 20 (83%) of the 24 showed abnormal left ventricular wall motion. We considered ΔR values ≥ 0 and ST segment depression ≥ 1 mm. significant for diagnosis of CAD. The sensitivity of the ΔR method in predicting CAD was superior to the method based upon ST segment depression; however, the latter was significantly (P We found ΔR values ≥ 0 more frequently in the 2-V and 3-V groups as compared with the 1-V group. Patients of the 2-V and 3-V groups had a significantly higher incidence of abnormal left ventricular wall motion (P Even though the accuracy of the ΔR method was greater in more severe CAD, it seems to be offset by a concomitant decrease in specificity.

Assessment of dynamic relationship between QT dispersion and RR interval in normal subjects

Little is known to what extent heart rate and its circadian variations can influence QT dispersion (QTd). Thus we studied the relationship between RR and QTd in 10 healthy subjects (6 M, 4 F mean age 32/spl plusmn/11 years). Beat-to-beat automated measurement of RR and QT was performed on a home-made analyzer. QTd was automatically measured for each beat on X, Y and Z leads. Mean hourly RR and QTd values were calculated for each 60 min period of 24-hour Holter recordings. A significant linear relationship was found between mean hourly RR and QTd values (r=.47; p=0.02). Hourly median RR values showed the expected circadian variation, with a nocturnal peak between 3 and 6 A.M. Similarly, there was a circadian rhythm in hourly median QTd values, with a prominent peak between the hours 2 and 3 A.M. In conclusion, in healthy subjects QTd is weakly correlated to RR and shows a circadian variation.

Dynamic correlation between QT and RR intervals: how long is QT adaptation to heart rate?

Abnormalities in the adaptation of QT to variations of heart rate may be associated with a predisposition to ventricular arrhythmics, more than the prolongation of the QT interval at rest. A new automatic method is presented to assess the dynamic correlation between the QT and RR intervals over the entire duration of 24 h Holter monitoring. In order to separate short from long term adaptation and to investigate on selected portions of the circadian sequences (sleep, awake, waking up and falling asleep) both frequency and time windows are used. Sequences of RR and QT values were measured over 24 h recordings and interpolated to provide a continuous time scale. By wavelet transform four RR and QT band filtered sequences were originated. From them the correlation coefficient and their fiducial limits were calculated within the chosen frequency and time windows for time lags from 1 to 300, thus evaluating the lag corresponding to the maximum correlation.

Classification of patients with and without syncope by means of QT analysis in hypertrophic cardiomyopathy: preliminary results

In patients with hypertrophic cardiomyopathy (HCM), a history of syncope is associated with increased risk of sudden death, an important role in its pathophysiology being presumably played by an arrhythmic mechanism. The aim of this study was to find out whether several ventricular repolarization parameters are useful to discriminate between patients with and without syncope. The Holter recordings of three groups of subjects (HCM with syncope, HCM without syncope and normals) were analysed, and three sets of variables were measured: six spectral variables, six QT/RR slope variables and 12 QT time parameters. All three sets were submitted to tests (e.g. discriminant analysis) in order to verify the differences among the groups. Finally, classification of single subjects was carried out.

Increased QT variability in patients with hypertrophic cardiomyopathy

The purpose of this study was to examine QT interval variability in hypertrophic cardiomyopathy (HCM) by using frequency domain indices. Twenty-six subjects participated to the study: 16 had HCM (5 females, 9 males; mean age 39/spl plusmn/13 years), 10 were healthy volunteers (5 females, 5 males, mean age 35/spl plusmn/13 years), who served as controls. Twenty-four-hour Holter recordings of each subject were analysed on a homemade Holter analyser. The following spectral domain measures of QT interval variability were computed: ultra low (ULF), very low (VLF), low (LF) high frequency (HF) and total power. Spectral domain measures of QT interval variability were significantly higher in subjects with HCM than in controls. Further studies are required to evaluate whether analysis of QT variability on Holter recordings might have prognostic implications.

Spontaneous variability of the QTc interval in healthy subjects

Little is known to what extent spontaneous beat-to-beat changes in QT duration can contribute to its variations. Thus, the authors defined the amount of rate-independent changes in QT duration on continuous 24-hour electrocardiograms in 11 healthy subjects (6 M, 5 F, aged between 19 and 80 years). Mean daily QTc was 419 msec, with a mean daily standard deviation of 24 msec. Mean daily QTc variability was 29/spl plusmn/10 msec; the mean coefficient of variation for QTc was 5.6/spl plusmn/.8% Marked hour-to-hour variations in QT value at the same RR cycle length were evident specially at higher heart rates. These results indicate that there is a considerable beat to beat variability of the QTc interval. The casual importance of interventions inducing QT variations cannot be accurately assessed, unless the amount of the heart rate-independent QT variability is considered QT variations /spl les/39 msec (mean+1 SD) should be considered physiologic.