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Objectives This study was undertaken to determine whether the short-lived sinus tachycardia that occurs during standing will expose changes in the QT interval that are of diagnostic value. Background The QT interval shortens during heart rate acceleration, but this response is not instantaneous. We tested whether the transient, sudden sinus tachycardia that occurs during standing would expose abnormal QT interval prolongation in patients with long QT syndrome (LQTS). Methods Patients (68 with LQTS [LQT1 46%, LQT2 41%, LQT3 4%, not genotyped 9%] and 82 control subjects) underwent a baseline electrocardiogram (ECG) while resting in the supine position and were then asked to get up quickly and stand still during continuous ECG recording. The QT interval was studied at baseline and during maximal sinus tachycardia, maximal QT interval prolongation, and maximal QT interval stretching. Results In response to brisk standing, patients and control subjects responded with similar heart rate acceleration of 28 ± 10 beats/min (p = 0.261). However, the response of the QT interval to this tachycardia differed: on average, the QT interval of controls shortened by 21 ± 19 ms whereas the QT interval of LQTS patients increased by 4 ± 34 ms (p < 0.001). Since the RR interval shortened more than the QT interval, during maximal tachycardia the corrected QT interval increased by 50 ± 30 ms in the control group and by 89 ± 47 ms in the LQTS group (p < 0.001). Receiver-operating characteristic curves showed that the test adds diagnostic value. The response of the QT interval to brisk standing was particularly impaired in patients with LQT2. Conclusions Evaluation of the response of the QT interval to the brisk tachycardia induced by standing provides important information that aids in the diagnosis of LQTS.

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BACKGROUND Patients with long QT syndrome (LQTS) have inadequate shortening of the QT interval in response to the sudden heart rate accelerations provoked by standing—a phenomenon of diagnostic value. We now validate our original observations in a cohort twice as large. We also describe that this abnormal QT-interval response persists as the heart rate acceleration returns to baseline. OBJECTIVES To describe a novel observation, termed “QT stunning” and to validate previous observations regarding the “QT-stretching” phenomenon in patients with LQTS by using our recently described “standing test.” METHODS The electrocardiograms of 108 patients with LQTS and 112 healthy subjects were recorded in the supine position. Subjects were then instructed to stand up quickly and remain standing for 5 minutes during continuous electrocardiographic recording. The corrected QT interval was measured at baseline (QTcbase), when heart rate acceleration without appropriate QT-interval shortening leads to maximal QT stretching (QTcstretch) and upon return of heart rate to baseline (QTcreturn). RESULTS QTcstretch lengthened significantly more in patients with LQTS (103 ± 80 ms vs 66 ± 40 ms in controls; P <.001) and so did QTcreturn (28 ± 48 ms for patients with LQTS vs −3 ± 32 ms for controls; P <.001). Using a sensitivity cutoff of 90%, the specificity for diagnosing LQTS was 74% for QTcbase, 84% for QTcreturn, and 87% for QTcstretch. CONCLUSIONS The present study extends our previous findings on the abnormal response of the QT interval in response to standing in patients with LQTS. Our study also shows that this abnormal response persists even after the heart rate slows back to baseline.

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Heart rate variability (HRV) in women has been related independently to endogenous sex hormones, hormone replacement therapy, menopause, menstrual cycle, body mass index (BMI), and physical conditioning. However, the joint influence of all these factors has not been reported. The present study describes the relation between circadian variation HRV and assesses its association with BMI, age, and menstrual cycle in healthy young women. A multivariable analysis was performed to estimate the predictive variables involved in SDNN, pNN50, and rMSSD profile, using the classification and regression tree (CART) and the logistic regression models. It was found that the first predictive variable was age, which divided women in two groups: >29.5 years old and <29.5 years old. In the case of the SDNN, the second predictive variable was BMI; the highest values were observed in women younger than 23 years old, with a BMI less than 19.82 kg/m2 and during the follicular phase of her menstrual cycle. For pNN50 and rMSSD the second predictive variable was menstrual cycle for women younger than 29.5 years old. Thus, in this group of women, age was a major determinant of cardiac autonomic nervous modulation followed by the BMI. HRV may be better understood using a multivariable analysis that could mimic physiological conditions.