Background Hyper‐ and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood‐free method for tracking potassium would be an important clinical advance. Methods and Results Two groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high‐resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single‐channel ECG . In addition, by analyzing the entire development group's first‐visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). Conclusions The signal‐processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost‐effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.
A Randomized Trial of Cardiovascular Responses to Energy Drink Consumption in Healthy Adults
Background Epidemiologic evidence suggests a link between short sleep duration and cardiovascular risk, although the nature of any relationship and mechanisms remain unclear. Short sleep duration has also been linked to an increase in cardiovascular events. Endothelial dysfunction has itself been implicated as a mediator of heightened cardiovascular risk. We sought to determine the effect of 8 days/8 nights of partial sleep restriction on endothelial function in healthy humans. Methods and Results Sixteen healthy volunteers underwent a randomized study of usual sleep versus sleep restriction of two‐thirds normal sleep time for 8 days/8 nights in a hospital‐based clinical research unit. The main outcome was endothelial function measured by flow‐mediated brachial artery vasodilatation ( FMD ). Those randomized to sleep restriction slept 5.1 hours/night during the experimental period compared with 6.9 hours/night in the control group. Sleep restriction was associated with significant impairment in FMD (8.6±4.6% during the initial pre‐randomization acclimation phase versus 5.2±3.4% during the randomized experimental phase, P =0.01) whereas no change was seen in the control group (5.0±3.0 during the acclimation phase versus 6.73±2.9% during the experimental phase, P =0.10) for a between‐groups difference of −4.40% (95% CI −7.00 to −1.81%, P =0.003). No change was seen in non‐flow mediated vasodilatation ( NFMD ) in either group. Conclusion In healthy individuals, moderate sleep restriction causes endothelial dysfunction. Clinical Trial Registration URL : ClinicalTrials.gov. Unique identifier: NCT 01334788.
Interatrial pressure gradients during simulated obstructive sleep apnea: A catheter‐based study
Obesity has been associated with increased cardiac sympathetic activation during wakefulness, but the effect on sleep-related sympathetic modulation is not known. The aim of this study was to investigate the effect of fat gain on cardiac autonomic control during wakefulness and sleep in humans. We performed a randomized, controlled study to assess the effects of fat gain on heart rate variability. We recruited 36 healthy volunteers, who were randomized to either a standardized diet to gain ≈4 kg over 8 weeks followed by an 8-week weight loss period (n=20) or to serve as a weight-maintainer control (n=16). An overnight polysomnogram with power spectral analysis of heart rate variability was performed at baseline, after weight gain, and after weight loss to determine the ratio of low-frequency to high-frequency power and to examine the relationship between changes in heart rate variability and changes in insulin, leptin, and adiponectin levels. Mean weight gain was 3.9 kg in the fat gain group versus 0.1 kg in the maintainer group. Low frequency/high frequency increased both during wakefulness and sleep after fat gain and returned to baseline after fat loss in the fat gain group and did not change in the control group. Insulin, leptin, and adiponectin also increased after fat gain and fell after fat loss, but no clear pattern of changes was seen that correlated consistently with changes in heart rate variability. Short-term fat gain in healthy subjects is associated with increased cardiac sympathetic activation during wakefulness and sleep, but the mechanisms remain unclear.