A Novel Smartphone App for the Measurement of Ultra-Short-Term and Short-Term Heart Rate Variability: Validity and Reliability Study.

BACKGROUND: Smartphone apps for heart rate variability (HRV) measurement have been extensively developed in the last decade. However, ultra-short-term HRV recordings taken by wearable devices have not been examined. OBJECTIVE: The aims of this study were the following: (1) to compare the validity and reliability of ultra-short-term and short-term HRV time-domain and frequency-domain variables in a novel smartphone app, Pulse Express Pro (PEP), and (2) to determine the agreement of HRV assessments between an electrocardiogram (ECG) and PEP. METHODS: In total, 60 healthy adults were recruited to participate in this study (mean age 22.3 years [SD 3.0 years], mean height 168.4 cm [SD 8.0 cm], mean body weight 64.2 kg [SD 11.5 kg]). A 5-minute resting HRV measurement was recorded via ECG and PEP in a sitting position. Standard deviation of normal R-R interval (SDNN), root mean square of successive R-R interval (RMSSD), proportion of NN50 divided by the total number of RR intervals (pNN50), normalized very-low-frequency power (nVLF), normalized low-frequency power (nLF), and normalized high-frequency power (nHF) were analyzed within 9 time segments of HRV recordings: 0-1 minute, 1-2 minutes, 2-3 minutes, 3-4 minutes, 4-5 minutes, 0-2 minutes, 0-3 minutes, 0-4 minutes, and 0-5 minutes (standard). Standardized differences (ES), intraclass correlation coefficients (ICC), and the Spearman product-moment correlation were used to compare the validity and reliability of each time segment to the standard measurement (0-5 minutes). Limits of agreement were assessed by using Bland-Altman plot analysis. RESULTS: Compared to standard measures in both ECG and PEP, pNN50, SDNN, and RMSSD variables showed trivial ES (<0.2) and very large to nearly perfect ICC and Spearman correlation coefficient values in all time segments (>0.8). The nVLF, nLF, and nHF demonstrated a variation of ES (from trivial to small effects, 0.01-0.40), ICC (from moderate to nearly perfect, 0.39-0.96), and Spearman correlation coefficient values (from moderate to nearly perfect, 0.40-0.96). Furthermore, the Bland-Altman plots showed relatively narrow values of mean difference between the ECG and PEP after consecutive 1-minute recordings for SDNN, RMSSD, and pNN50. Acceptable limits of agreement were found after consecutive 3-minute recordings for nLF and nHF. CONCLUSIONS: Using the PEP app to facilitate a 1-minute ultra-short-term recording is suggested for time-domain HRV indices (SDNN, RMSSD, and pNN50) to interpret autonomic functions during stabilization. When using frequency-domain HRV indices (nLF and nHF) via the PEP app, a recording of at least 3 minutes is needed for accurate measurement.

Population-Based Screening for Atrial Fibrillation.

Atrial fibrillation (AF) is a common and morbid arrhythmia. Stroke is a major hazard of AF and may be preventable with oral anticoagulation. Yet since AF is often asymptomatic, many individuals with AF may be unaware and do not receive treatment that could prevent a stroke. Screening for AF has gained substantial attention in recent years as several studies have demonstrated that screening is feasible. Advances in technology have enabled a variety of approaches to facilitate screening for AF using both medical-prescribed devices as well as consumer electronic devices capable of detecting AF. Yet controversy about the utility of AF screening remains owing to concerns about potential harms resulting from screening in the absence of randomized data demonstrating effectiveness of screening on outcomes such as stroke and bleeding. In this review, we summarize current literature, present technology, population-based screening considerations, and consensus guidelines addressing the role of AF screening in practice.

Heart Rate Measures From Wrist-Worn Activity Trackers in a Laboratory and Free-Living Setting: Validation Study.

BACKGROUND: Wrist-worn activity trackers are popular, and an increasing number of these devices are equipped with heart rate (HR) measurement capabilities. However, the validity of HR data obtained from such trackers has not been thoroughly assessed outside the laboratory setting. OBJECTIVE: This study aimed to investigate the validity of HR measures of a high-cost consumer-based tracker (Polar A370) and a low-cost tracker (Tempo HR) in the laboratory and free-living settings. METHODS: Participants underwent a laboratory-based cycling protocol while wearing the two trackers and the chest-strapped Polar H10, which acted as criterion. Participants also wore the devices throughout the waking hours of the following day during which they were required to conduct at least one 10-min bout of moderate-to-vigorous physical activity (MVPA) to ensure variability in the HR signal. We extracted 10-second values from all devices and time-matched HR data from the trackers with those from the Polar H10. We calculated intraclass correlation coefficients (ICCs), mean absolute errors, and mean absolute percentage errors (MAPEs) between the criterion and the trackers. We constructed decile plots that compared HR data from Tempo HR and Polar A370 with criterion measures across intensity deciles. We investigated how many HR data points within the MVPA zone (≥64% of maximum HR) were detected by the trackers. RESULTS: Of the 57 people screened, 55 joined the study (mean age 30.5 [SD 9.8] years). Tempo HR showed moderate agreement and large errors (laboratory: ICC 0.51 and MAPE 13.00%; free-living: ICC 0.71 and MAPE 10.20%). Polar A370 showed moderate-to-strong agreement and small errors (laboratory: ICC 0.73 and MAPE 6.40%; free-living: ICC 0.83 and MAPE 7.10%). Decile plots indicated increasing differences between Tempo HR and the criterion as HRs increased. Such trend was less pronounced when considering the Polar A370 HR data. Tempo HR identified 62.13% (1872/3013) and 54.27% (5717/10,535) of all MVPA time points in the laboratory phase and free-living phase, respectively. Polar A370 detected 81.09% (2273/2803) and 83.55% (9323/11,158) of all MVPA time points in the laboratory phase and free-living phase, respectively. CONCLUSIONS: HR data from the examined wrist-worn trackers were reasonably accurate in both the settings, with the Polar A370 showing stronger agreement with the Polar H10 and smaller errors. Inaccuracies increased with increasing HRs; this was pronounced for Tempo HR.

Validation of Polar OH1 optical heart rate sensor for moderate and high intensity physical activities.

BACKGROUND: Optical measurement techniques and recent advances in wearable technology have made heart rate (HR) sensing simpler and more affordable. OBJECTIVES: The Polar OH1 is an arm worn optical heart rate monitor. The objectives of this study are two-fold; 1) to validate the OH1 optical HR sensor with the gold standard of HR measurement, electrocardiography (ECG), over a range of moderate to high intensity physical activities, 2) to validate wearing the OH1 at the temple as an alternative location to its recommended wearing location around the forearm and upper arm. METHODS: Twenty-four individuals participated in a physical exercise protocol, by walking on a treadmill and riding a stationary spin bike at different speeds while the criterion measure, ECG and Polar OH1 HR were recorded simultaneously at three different body locations; forearm, upper arm and the temple. Time synchronised HR data points were compared using Bland-Altman analyses and intraclass correlation. RESULTS: The intraclass correlation between the ECG and Polar OH1, for the aggregated data, was 0.99 and the estimated mean bias ranged 0.27-0.33 bpm for the sensor locations. The three sensors exhibited a 95% limit of agreement (LoA: forearm 5.22, -4.68 bpm; upper arm 5.15, -4.49; temple 5.22, -4.66). The mean of the ECG HR for the aggregated data was 112.15 ± 24.52 bpm. The intraclass correlation of HR values below and above this mean were 0.98 and 0.99 respectively. The reported mean bias ranged 0.38-0.47 bpm (95% LoA: forearm 6.14, -5.38 bpm; upper arm 6.07, -5.13 bpm; temple 6.09, -5.31 bpm), and 0.15-0.16 bpm (95% LoA: forearm 3.99, -3.69 bpm; upper arm 3.90, -3.58 bpm; temple 4.06, -3.76 bpm) respectively. During different exercise intensities, the intraclass correlation ranged 0.95-0.99 for the three sensor locations. During the entire protocol, the estimated mean bias was in the range -0.15-0.55 bpm, 0.01-0.53 bpm and -0.37-0.48 bpm, for the forearm, upper arm and temple locations respectively. The corresponding upper limits of 95% LoA were 3.22-7.03 bpm, 3.25-6.82 bpm and 3.18-7.04 bpm while the lower limits of 95% LoA were -6.36-(-2.35) bpm, -6.46-(-2.30) bpm and -7.42-(-2.41) bpm. CONCLUSION: Polar OH1 demonstrates high level of agreement with the criterion measure ECG HR, thus can be used as a valid measure of HR in lab and field settings during moderate and high intensity physical activities.

Accuracy of Apple Watch Measurements for Heart Rate and Energy Expenditure in Patients With Cardiovascular Disease: Cross-Sectional Study.

BACKGROUND: Wrist-worn tracking devices such as the Apple Watch are becoming more integrated in health care. However, validation studies of these consumer devices remain scarce. OBJECTIVES: This study aimed to assess if mobile health technology can be used for monitoring home-based exercise in future cardiac rehabilitation programs. The purpose was to determine the accuracy of the Apple Watch in measuring heart rate (HR) and estimating energy expenditure (EE) during a cardiopulmonary exercise test (CPET) in patients with cardiovascular disease. METHODS: Forty patients (mean age 61.9 [SD 15.2] yrs, 80% male) with cardiovascular disease (70% ischemic, 22.5% valvular, 7.5% other) completed a graded maximal CPET on a cycle ergometer while wearing an Apple Watch. A 12-lead electrocardiogram (ECG) was used to measure HR; indirect calorimetry was used for EE. HR was analyzed at three levels of intensity (seated rest, HR1; moderate intensity, HR2; maximal performance, HR3) for 30 seconds. The EE of the entire test was used. Bias or mean difference (MD), standard deviation of difference (SDD), limits of agreement (LoA), mean absolute error (MAE), mean absolute percentage error (MAPE), and intraclass correlation coefficients (ICCs) were calculated. Bland-Altman plots and scatterplots were constructed. RESULTS: SDD for HR1, HR2, and HR3 was 12.4, 16.2, and 12.0 bpm, respectively. Bias and LoA (lower, upper LoA) were 3.61 (-20.74, 27.96) for HR1, 0.91 (-30.82, 32.63) for HR2, and -1.82 (-25.27, 21.63) for HR3. MAE was 6.34 for HR1, 7.55 for HR2, and 6.90 for HR3. MAPE was 10.69% for HR1, 9.20% for HR2, and 6.33% for HR3. ICC was 0.729 (P<.001) for HR1, 0.828 (P<.001) for HR2, and 0.958 (P<.001) for HR3. Bland-Altman plots and scatterplots showed good correlation without systematic error when comparing Apple Watch with ECG measurements. SDD for EE was 17.5 kcal. Bias and LoA were 30.47 (-3.80, 64.74). MAE was 30.77; MAPE was 114.72%. ICC for EE was 0.797 (P<.001). The Bland-Altman plot and a scatterplot directly comparing Apple Watch and indirect calorimetry showed systematic bias with an overestimation of EE by the Apple Watch. CONCLUSIONS: In patients with cardiovascular disease, the Apple Watch measures HR with clinically acceptable accuracy during exercise. If confirmed, it might be considered safe to incorporate the Apple Watch in HR-guided training programs in the setting of cardiac rehabilitation. At this moment, however, it is too early to recommend the Apple Watch for cardiac rehabilitation. Also, the Apple Watch systematically overestimates EE in this group of patients. Caution might therefore be warranted when using the Apple Watch for measuring EE.

Physical Activity Trend eXtraction: A Framework for Extracting Moderate-Vigorous Physical Activity Trends From Wearable Fitness Tracker Data.

BACKGROUND: Moderate-vigorous physical activity (MVPA) offers extensive health benefits but is neglected by many. As a result, a wide body of research investigating physical activity behavior change has been conducted. As many of these studies transition from paper-based methods of MVPA data collection to fitness trackers, a series of challenges arise in extracting insights from these new data. OBJECTIVE: The objective of this research was to develop a framework for preprocessing and extracting MVPA trends from wearable fitness tracker data to support MVPA behavior change studies. METHODS: Using heart rate data collected from fitness trackers, we propose Physical Activity Trend eXtraction (PATX), a framework that imputes missing data, recalculates personalized target heart zones, and extracts MVPA trends. We tested our framework on a dataset of 123 college study participants observed across 2 academic years (18 months) using Fitbit Charge HRs. To demonstrate the value of our frameworks' output in supporting MVPA behavior change studies, we applied it to 2 case studies. RESULTS: Among the 123 participants analyzed, PATX labeled 41 participants as experiencing a significant increase in MVPA and 44 participants who experienced a significant decrease in MVPA, with significance defined as P<.05. Our first case study was consistent with previous works investigating the associations between MVPA and mental health. Whereas the second, exploring how individuals perceive their own levels of MVPA relative to their friends, led to a novel observation that individuals were less likely to notice changes in their own MVPA when close ties in their social network mimicked their changes. CONCLUSIONS: By providing meaningful and flexible outputs, PATX alleviates data concerns common with fitness trackers to support MVPA behavior change studies as they shift to more objective assessments of MVPA.

Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study.

BACKGROUND: Wrist-worn smart watches and fitness monitors (ie, wearables) have become widely adopted by consumers and are gaining increased attention from researchers for their potential contribution to naturalistic digital measurement of health in a scalable, mobile, and unobtrusive way. Various studies have examined the accuracy of these devices in controlled laboratory settings (eg, treadmill and stationary bike); however, no studies have investigated the heart rate accuracy of wearables during a continuous and ecologically valid 24-hour period of actual consumer device use conditions. OBJECTIVE: The aim of this study was to determine the heart rate accuracy of 2 popular wearable devices, the Apple Watch 3 and Fitbit Charge 2, as compared with the gold standard reference method, an ambulatory electrocardiogram (ECG), during consumer device use conditions in an individual. Data were collected across 5 daily conditions, including sitting, walking, running, activities of daily living (ADL; eg, chores, brushing teeth), and sleeping. METHODS: One participant, (first author; 29-year-old Caucasian male) completed a 24-hour ecologically valid protocol by wearing 2 popular wrist wearable devices (Apple Watch 3 and Fitbit Charge 2). In addition, an ambulatory ECG (Vrije Universiteit Ambulatory Monitoring System) was used as the gold standard reference method, which resulted in the collection of 102,740 individual heartbeats. A single-subject design was used to keep all variables constant except for wearable devices while providing a rapid response design to provide initial assessment of wearable accuracy for allowing the research cycle to keep pace with technological advancements. Accuracy of these devices compared with the gold standard ECG was assessed using mean error, mean absolute error, and mean absolute percent error. These data were supplemented with Bland-Altman analyses and concordance class correlation to assess agreement between devices. RESULTS: The Apple Watch 3 and Fitbit Charge 2 were generally highly accurate across the 24-hour condition. Specifically, the Apple Watch 3 had a mean difference of -1.80 beats per minute (bpm), a mean absolute error percent of 5.86%, and a mean agreement of 95% when compared with the ECG across 24 hours. The Fitbit Charge 2 had a mean difference of -3.47 bpm, a mean absolute error of 5.96%, and a mean agreement of 91% when compared with the ECG across 24 hours. These findings varied by condition. CONCLUSIONS: The Apple Watch 3 and the Fitbit Charge 2 provided acceptable heart rate accuracy (<±10%) across the 24 hour and during each activity, except for the Apple Watch 3 during the daily activities condition. Overall, these findings provide preliminary support that these devices appear to be useful for implementing ambulatory measurement of cardiac activity in research studies, especially those where the specific advantages of these methods (eg, scalability, low participant burden) are particularly suited to the population or research question.

The Current State of Mobile Phone Apps for Monitoring Heart Rate, Heart Rate Variability, and Atrial Fibrillation: Narrative Review.

BACKGROUND: Mobile phone apps capable of monitoring arrhythmias and heart rate (HR) are increasingly used for screening, diagnosis, and monitoring of HR and rhythm disorders such as atrial fibrillation (AF). These apps involve either the use of (1) photoplethysmographic recording or (2) a handheld external electrocardiographic recording device attached to the mobile phone or wristband. OBJECTIVE: This review seeks to explore the current state of mobile phone apps in cardiac rhythmology while highlighting shortcomings for further research. METHODS: We conducted a narrative review of the use of mobile phone devices by searching PubMed and EMBASE from their inception to October 2018. Potentially relevant papers were then compared against a checklist for relevance and reviewed independently for inclusion, with focus on 4 allocated topics of (1) mobile phone monitoring, (2) AF, (3) HR, and (4) HR variability (HRV). RESULTS: The findings of this narrative review suggest that there is a role for mobile phone apps in the diagnosis, monitoring, and screening for arrhythmias and HR. Photoplethysmography and handheld electrocardiograph recorders are the 2 main techniques adopted in monitoring HR, HRV, and AF. CONCLUSIONS: A number of studies have demonstrated high accuracy of a number of different mobile devices for the detection of AF. However, further studies are warranted to validate their use for large scale AF screening.

Use of the low-frequency/high-frequency ratio of heart rate variability to predict short-term deterioration in emergency department patients with sepsis.

OBJECTIVE: To examine the ability of the low-frequency/high-frequency (LF/HF) ratio of heart rate variability (HRV) analysis to identify patients with sepsis at risk of early deterioration. METHODS: This is a prospective observational cohort study of patients with sepsis presenting to the Montefiore Medical Center ED from December 2014 through September 2015. On presentation, a single ECG Holter recording was obtained and analysed to obtain the LF/HF ratio of HRV. Initial Sequential Organ Failure Assessment (SOFA) scores were computed. Patients were followed for 72 hours to identify those with early deterioration. RESULTS: 466 patients presenting to the ED with sepsis were analysed. Thirty-two (7%) reached at least one endpoint within 72 hours. An LF/HF ratio <1 had a sensitivity and specificity of 34% (95% CI (19% to 53%)) and 82% (95% CI (78% to 85%)), respectively, with positive and negative likelihood ratios of 1.9 (95% CI (1.1 to 3.2)) and 0.8 (95% CI (0.6 to 1.0)). An initial SOFA score ≥3 had a sensitivity and specificity of 38% (95% CI (22% to 56%)) and 92% (95% CI (89% to 95%)), with positive and negative likelihood ratios of 4.9 (95% CI (2.8 to 8.6)) and 0.7 (95% CI (0.5 to 0.9)). The composite measure of HRV+SOFA had improved sensitivity (56%, 95% CI (38% to 73%)) but at the expense of specificity (77%, 95% CI (72% to 80%)), with positive and negative likelihood ratios of 2.4 (95% CI (1.7 to 3.4)) and 0.6 (95% CI (0.4 to 0.9)). Receiver operating characteristic analysis did not identify a superior alternate threshold for the LF/HF ratio. Kaplan-Meier survival functions differed significantly (p=0.02) between low (<1) and high (≥1) LF/HF groups. CONCLUSIONS: While we found a statistically significant relationship between HRV, SOFA and HRV+SOFA, and early deterioration, none reliably functioned as a clinical predictive tool. More complex multivariable models will likely be required to construct models with clinical utility.

Validation of radial artery-based uncalibrated pulse contour method (PulsioFlex) in critically ill patients: A observational study.

BACKGROUND: Because of their simplicity, uncalibrated pulse contour (UPC) methods have been introduced into clinical practice in critical care but are often validated with a femoral arterial waveform. OBJECTIVE: We aimed to test the accuracy of cardiac index (CI) measurements and trending ability from a radial artery with one UPC. DESIGN: An observational study. SETTING: Tertiary care mixed-surgical ICU. Data were obtained from April 2015 to July 2016. PATIENTS: We studied 20 critically ill mechanically ventilated patients monitored by UPC (PulsioFlex; Pulsion Medical Systems SE, Feldkirchen, Germany). We used transpulmonary thermodilution (PiCCO2) as a reference. MAIN OUTCOME MEASURES: Bland-Altman-analyses with percentage errors were calculated to assess the accuracy of CI values from radial pulse contour analysis (CIRAD), autocalibration (CIAC) and femoral pulse contour analysis (CIFEM). All were compared with a reference (CITD) at 4-h intervals for 24 h. Trending ability was assessed by polar-plots and four-quadrant-plots. CI is given in l min m. RESULTS: Bland-Altman-analyses: for CIRAD, the mean bias was -0.1 with limits of agreement (LOA) of -2.9 to 2.7 and a percentage error of 70%; for CIAC, the mean bias was 0 with LOA -2.8 to 2.7 and a percentage error of 70%; for CIFEM, the mean bias was 0 with LOA -1.2 to 1.2 and a percentage error of 30%, respectively. Polar plots for trending: for CIRAD, the angular bias was 12° with radial LOA of 39°, a polar concordance rate of 73% and a concordance rate of 67% in the four-quadrant-plot; for CIAC, the angular bias was 4° with radial LOA of 41°, polar concordance rate of 79% and a concordance rate of 74% in the four quadrant plot; for CIFEM, the angular bias was -2° with radial LOA of 50°, polar concordance rate of 74% and a concordance rate of 81%. CONCLUSION: In critically ill patients, the PulsioFlex system connected to a radial arterial catheter is inaccurate for CI measurements and does not track changes in CI adequately. We therefore recommend using validated thermodilution techniques for monitoring in the critical care setting.

Gyrocardiography: A New Non-invasive Monitoring Method for the Assessment of Cardiac Mechanics and the Estimation of Hemodynamic Variables.

Gyrocardiography (GCG) is a new non-invasive technique for assessing heart motions by using a sensor of angular motion - gyroscope - attached to the skin of the chest. In this study, we conducted simultaneous recordings of electrocardiography (ECG), GCG, and echocardiography in a group of subjects consisting of nine healthy volunteer men. Annotation of underlying fiducial points in GCG is presented and compared to opening and closing points of heart valves measured by a pulse wave Doppler. Comparison between GCG and synchronized tissue Doppler imaging (TDI) data shows that the GCG signal is also capable of providing temporal information on the systolic and early diastolic peak velocities of the myocardium. Furthermore, time intervals from the ECG Q-wave to the maximum of the integrated GCG (angular displacement) signal and maximal myocardial strain curves obtained by 3D speckle tracking are correlated. We see GCG as a promising mechanical cardiac monitoring tool that enables quantification of beat-by-beat dynamics of systolic time intervals (STI) related to hemodynamic variables and myocardial contractility.

Assessment of blind source separation techniques for video-based cardiac pulse extraction.

Blind source separation (BSS) aims at separating useful signal content from distortions. In the contactless acquisition of vital signs by means of the camera-based photoplethysmogram (cbPPG), BSS has evolved the most widely used approach to extract the cardiac pulse. Despite its frequent application, there is no consensus about the optimal usage of BSS and its general benefit. This contribution investigates the performance of BSS to enhance the cardiac pulse from cbPPGs in dependency to varying input data characteristics. The BSS input conditions are controlled by an automated spatial preselection routine of regions of interest. Input data of different characteristics (wavelength, dominant frequency, and signal quality) from 18 postoperative cardiovascular patients are processed with standard BSS techniques, namely principal component analysis (PCA) and independent component analysis (ICA). The effect of BSS is assessed by the spectral signal-to-noise ratio (SNR) of the cardiac pulse. The preselection of cbPPGs, appears beneficial providing higher SNR compared to standard cbPPGs. Both, PCA and ICA yielded better outcomes by using monochrome inputs (green wavelength) instead of inputs of different wavelengths. PCA outperforms ICA for more homogeneous input signals. Moreover, for high input SNR, the application of ICA using standard contrast is likely to decrease the SNR.

Intersubject variability and intrasubject reproducibility of 12-lead ECG metrics: Implications for human verification.

BACKGROUND: Electrocardiogram (ECG) biometrics is an advanced technology, not yet covered by guidelines on criteria, features and leads for maximal authentication accuracy. OBJECTIVE: This study aims to define the minimal set of morphological metrics in 12-lead ECG by optimization towards high reliability and security, and validation in a person verification model across a large population. METHODS: A standard 12-lead resting ECG database from 574 non-cardiac patients with two remote recordings (>1year apart) was used. A commercial ECG analysis module (Schiller AG) measured 202 morphological features, including lead-specific amplitudes, durations, ST-metrics, and axes. Coefficient of variation (CV, intersubject variability) and percent-mean-absolute-difference (PMAD, intrasubject reproducibility) defined the optimization (PMAD/CV→min) and restriction (CV<30%) criteria for selection of the most stable and distinctive features. Linear discriminant analysis (LDA) validated the non-redundant feature set for person verification. RESULTS AND CONCLUSIONS: Maximal LDA verification sensitivity (85.3%) and specificity (86.4%) were validated for 11 optimal features: R-amplitude (I,II,V1,V2,V3,V5), S-amplitude (V1,V2), Tnegative-amplitude (aVR), and R-duration (aVF,V1).

How to estimate heart rate from pulse rate reported by oscillometric method in atrial fibrillation: The value of pulse rate variation.

OBJECTIVES: To evaluate whether the mean pulse rate (PR) from three oscillometric blood pressure (BP) measurements provides an accurate estimation of electrocardiogram ventricular rate (HR) in patients with permanent atrial fibrillation (AF). METHODS: BP and PR were measured with an oscillometric BP device for three times with one-minute interval. Simultaneously, one-minute electrocardiogram was also recorded for three times. The first PR and HR values were recorded as PR1 and HR1, and the averages of three PR and HR values as mean PR (mPR) and mean HR (mHR). Meanwhile, the differences between the highest and lowest values among the three PR and HR were calculated as ΔPR and ΔHR. Furthermore, the patients were stratified on ΔPR into the 0-15 and >15 subgroups. RESULTS: A moderate positive correlation existed between PR1 and HR1 or mPR and mHR, and Bland-Altman plot also showed quite wide 95% limits between them. Meanwhile, ΔPR was significantly higher than ΔHR (12.1±8.6 vs 3.6±2.5bpm, P<0.001). However, in the 0-15 subgroup, the correlation between mPR and mHR was high (R2=0.800), and the 95% limits were only from -11.3 to 14.2bpm with a difference of 1.4bpm. The coincidence (mPR-mHR<10bpm) rate was 93.9% when PR≤80bpm, 96.3% when PR 81-100bpm, and 88.9% when PR over 100bpm. CONCLUSION: The average of three PR values reported by an oscillometric BP device could provide a clinically accepted estimation of mean HR of 3min in AF patients with ΔPR 0-15bpm and mean PR ≤100bpm.

Influence of food intake on the QT and QT/RR relation.

BACKGROUND: There are conflicting data on the influence of meal intake on the QT interval. METHODS: Ten healthy subjects were studied before and after a standardized breakfast and lunch with a sequence of supine resting, standing and exercise. Data collection was performed using a 12-lead Holter with semi-automated analysis. QT correction was performed using Fridericia (QTcF) correction formula and a subject-specific method based on individual QT/RR-regression (QTcI). RESULTS: Meal intake induced significant changes in HR (p<0.001), but not in QTcF (p=0.512) or QTcI (p=0.739). Postural analysis showed only significant differences in supine position for HR (p=0.010), not when standing or during exercise. CONCLUSION: Food intake induced an increase in heart rate limited to supine position. Using QTcF and QTcI no QTc changes were found.

Reference ranges for short-term heart rate variability measures in individuals free of cardiovascular disease: The Multi-Ethnic Study of Atherosclerosis (MESA).

BACKGROUND: Normative values for heart rate variability (HRV) measures from 10-s electrocardiograms (ECG) have not been defined. METHODS: We reported borderline abnormal (<5th percentile) and abnormal (<2nd percentile) values of standard deviation of all normal-to-normal R-R intervals (SDNN) and root mean square of successive differences between normal-to-normal R-R intervals (rMSSD) from 10-s ECGs in 1175 participants (mean age=59±10; 59% female; 47% white) ≥45years of age from the Multi-Ethnic Study of Atherosclerosis (MESA) who were free of cardiovascular disease (CVD) and CVD risk factors. We validated the prognostic significance of these measures in a subset of the MESA cohort with complete data. RESULTS: Borderline abnormal and abnormal SDNN and rMSSD varied by sex and race. Borderline abnormal and abnormal SDNN and rMSSD were associated with an increased risk of CVD and all-cause mortality. CONCLUSIONS: The references ranges provided in this report will guide future research using these common HRV parameters.