Circadian Rhythm Of Heart Rate Research Articles

Accuracy and reliability of wristband smartwatch-based estimation of circadian rhythm of heart rate in stroke patients

Background & Objective: Stroke has a high incidence, disability, and mortality rate, which has a serious impact on the patients’ quality of life. Heart rate (HR) is valuable in the prognostic assessment of stroke patients. Continuous HR tracking helps to detect abnormal indicators and provide interventions timely to avoid disease progression. However, the cuff-based or electrode-based HR monitoring tools commonly used in clinic are not suitable for continuous monitoring in daily life. The aim of this study was to verify the accuracy and reliability of a wristband smartwatch in monitoring HR over 24-hour in stroke patients, including in terms of the circadian rhythm characteristics of HR. Methods: 25 stroke patients underwent 24-hour HR monitoring by wearing a smartwatch and a clinical monitor. We use ambulatory blood pressure monitors and bedside monitors as the gold standard for clinical HR monitoring. The degree of association between the two measurements was compared using Pearson’s correlation coefficient. Bland-Altman analysis showed the accuracy of the smartwatch in HR monitoring. Intraclass correlation coefficients (ICC) and coefficients of variation (CV) were used to verify the reliability of the wristband smartwatch for repeated measurements. Results: A total of 625 heart rate pairs were acquired. The smartwatches had an average error of 0.816 bpm in 24-hour, with no difference from standard monitors (P>0.05), indicating good accuracy. The intraday repeated measures ICC was 0.969 and the interday repeated measures ICC was 0.788, indicating good reliability. Conclusions: The smartwatch is acceptable in detecting 24-hour ambulatory HR in stroke patients, and in the future, long-term HR monitoring with diurnal variations can be performed in daily life.

Influence of night shift work on circadian heart-rate rhythm in nurses: using a Holter electrocardiogram that can be continuously measured for two weeks.

The influence of night shift work on circadian heart-rate rhythm was examined in nurses engaged in shift work using a Holter electrocardiogram, continuously measured for two weeks, and cosine periodic regression analysis. We enrolled 11 nurses who were engaged in a two-shift system. The R2 value in the cosine regression curve of heart-rate rhythm (concordance rate), indicating the concordance rate between the actual heart rate over 24 h and the cosine regression curve approximated by the least-squares procedure, was significantly lower in the night shift (0.40 ± 0.15) than in the day shift (0.66 ± 0.19; p<0.001). Moreover, the amplitude was significantly lower and the acrophase was significantly delayed in the night shift. Thus, the circadian heart-rate rhythm was disrupted by the night shift work. Although the heart-rate acrophase recovered during the day and two days after the night shift, the concordance rate and amplitude did not recover, indicating that the influence of night shift work on circadian heart-rate rhythm might persist even two days after the night shift. Based on these results, adequate clinical attention should be paid to how to spend the day and two days after the night shift to correct the circadian heart-rate rhythm disruption caused by night shift work.

Circadian rhythms in pump parameters of patients on contemporary left ventricular assist device support.

Algorithms to monitor pump parameters are needed to further improve outcomes after left ventricular assist device (LVAD) implantation. Previous research showed a restored circadian rhythm in pump parameters in patients on HeartWare (HVAD) support. Circadian patterns in HeartMate3 (HM3) were not studied before, but this is important for the development of LVAD monitoring algorithms. Hence, we aimed to describe circadian patterns in HM3 parameters and their relation to patterns in heart rate (HR). 18 HM3 patients were included in this study. HM3 data were retrieved at a high frequency (one sample per 1 or 2 h) for 1-2 weeks. HR was measured using a wearable biosensor. To study overall patterns in HM3 parameters and HR, a heatmap was created. A 24-h cosine was fitted on power and HR separately. The relationship between the amplitude of the fitted cosines of power and HR was calculated using Spearman correlation. A lower between patient variability was found in power compared with flow and PI. 83% of the patients showed a significant circadian rhythmicity in power (p < 0.001-0.04), with a clear morning increase. All patients showed significant circadian rhythmicity in HR (p < 0.001-0.02). The amplitudes of the circadian rhythm in power and HR were not correlated (Spearman correlation of 0.32, p = 0.19). A circadian rhythm of pump parameters is present in the majority of HM3 patients. Higher frequency pump parameter data should be collected, to enable early detection of complications in the future development of predictive algorithms.

Efficient assessment of real-world dynamics of circadian rhythms in heart rate and body temperature from wearable data.

Laboratory studies have made unprecedented progress in understanding circadian physiology. Quantifying circadian rhythms outside of laboratory settings is necessary to translate these findings into real-world clinical practice. Wearables have been considered promising way to measure these rhythms. However, their limited validation remains an open problem. One major barrier to implementing large-scale validation studies is the lack of reliable and efficient methods for circadian assessment from wearable data. Here, we propose an approximation-based least-squares method to extract underlying circadian rhythms from wearable measurements. Its computational cost is ∼ 300-fold lower than that of previous work, enabling its implementation in smartphones with low computing power. We test it on two large-scale real-world wearable datasets: [Formula: see text] of body temperature data from cancer patients and ∼ 184 000 days of heart rate and activity data collected from the 'Social Rhythms' mobile application. This shows successful extraction of real-world dynamics of circadian rhythms. We also identify a reasonable harmonic model to analyse wearable data. Lastly, we show our method has broad applicability in circadian studies by embedding it into a Kalman filter that infers the state space of the molecular clocks in tissues. Our approach facilitates the translation of scientific advances in circadian fields into actual improvements in health.

Measure by measure: Resting heart rate across the 24-hour cycle.

Photoplethysmography (PPG) sensors, typically found in wrist-worn devices, can continuously monitor heart rate (HR) in large populations in real-world settings. Resting heart rate (RHR) is an important biomarker of morbidities and mortality, but no universally accepted definition nor measurement criteria exist. In this study, we provide a working definition of RHR and describe a method for accurate measurement of this biomarker, recorded using PPG derived from wristband measurement across the 24-hour cycle. 433 healthy subjects wore a wrist device that measured activity and HR for up to 3 months. HR during inactivity was recorded and the duration of inactivity needed for HR to stabilise was ascertained. We identified the lowest HR during each 24-hour cycle (true RHR) and examined the time of day or night this occurred. The variation of HR during inactivity through the 24-hour cycle was also assessed. The sample was also subdivided according to daily activity levels for subset analysis. Adequate data was obtained for 19,242 days and 18,520 nights. HR stabilised in most subjects after 4 minutes of inactivity. Mean (SD) RHR for the sample was 54.5 (8.0) bpm (day) and 50.5 (7.6) bpm (night). RHR values were highest in the least active group (lowest MET quartile). A circadian variation of HR during inactivity was confirmed, with the lowest values being between 0300 and 0700 hours for most subjects. RHR measured using a PPG-based wrist-worn device is significantly lower at night than in the day, and a circadian rhythm of HR during inactivity was confirmed. Since RHR is such an important health metric, clarity on the definition and measurement methodology used is important. For most subjects, a minimum rest time of 4 minutes provides a reliable measurement of HR during inactivity and true RHR in a 24-hour cycle is best measured between 0300 and 0700 hours. Funding: This study was funded by Google.

Providing baseline data for conservation-Heart rate monitoring in captive scimitar-horned oryx.

Heart rate biologging has been successfully used to study wildlife responses to natural and human-caused stressors (e.g., hunting, landscape of fear). Although rarely deployed to inform conservation, heart rate biologging may be particularly valuable for assessing success in wildlife reintroductions. We conducted a case study for testing and validating the use of subcutaneous heart rate monitors in eight captive scimitar-horned oryx (Oryx dammah), a once-extinct species that is currently being restored to the wild. We evaluated biologger safety and accuracy while collecting long-term baseline data and assessing factors explaining variation in heart rate. None of the biologgers were rejected after implantation, with successful data capture for 16-21months. Heart rate detection accuracy was high (83%-99%) for six of the individuals with left lateral placement of the biologgers. We excluded data from two individuals with a right lateral placement because accuracies were below 60%. Average heart rate for the six scimitar-horned oryx was 60.3 ± 12.7bpm, and varied by about 12bpm between individuals, with a minimum of 31bpm and a maximum of 188bpm across individuals. Scimitar-horned oryx displayed distinct circadian rhythms in heart rate and activity. Heart rate and activity were low early in the morning and peaked near dusk. Circadian rhythm in heart rate and activity were relatively unchanged across season, but hourly averages for heart rate and activity were higher in spring and summer, respectively. Variation in hourly heart rate averages was best explained by a combination of activity, hour, astronomical season, ambient temperature, and an interaction term for hour and season. Increases in activity appeared to result in the largest changes in heart rate. We concluded that biologgers are safe and accurate and can be deployed in free-ranging and reintroduced scimitar-horned oryx. In addition to current monitoring practices of reintroduced scimitar-horned oryx, the resulting biologging data could significantly aid in 1) evaluating care and management action prior to release, 2) characterizing different animal personalities and how these might affect reintroduction outcomes for individual animals, and 3) identifying stressors after release to determine their timing, duration, and impact on released animals. Heart rate monitoring in released scimitar-horned oryx may also aid in advancing our knowledge about how desert ungulates adapt to extreme environmental variation in their habitats (e.g., heat, drought).

The cumulative effect of chronic stress and depressive symptoms affects heart rate in a working population.

BackgroundChronic stress and depressive symptoms have both been linked to increased heart rate (HR) and reduced HR variability. However, up to date, it is not clear whether chronic stress, the mechanisms intrinsic to depression or a combination of both cause these alterations. Subclinical cases may help to answer these questions. In a healthy working population, we aimed to investigate whether the effect of chronic stress on HR circadian rhythm depends on the presence of depressive symptoms and whether chronic stress and depressive symptoms have differential effects on HR reactivity to an acute stressor.Methods1,002 individuals of the SWEET study completed baseline questionnaires, including psychological information, and 5 days of electrocardiogram (ECG) measurements. Complete datasets were available for 516 individuals. In addition, a subset (n = 194) of these participants completed a stress task on a mobile device. Participants were grouped according to their scores for the Depression Anxiety Stress Scale (DASS) and Perceived Stress Scale (PSS). We explored the resulting groups for differences in HR circadian rhythm and stress reactivity using linear mixed effect models. Additionally, we explored the effect of stress and depressive symptoms on night-time HR variability [root mean square of successive differences (RMSSD)].ResultsHigh and extreme stress alone did not alter HR circadian rhythm, apart from a limited increase in basal HR. Yet, if depressive symptoms were present, extreme chronic stress levels did lead to a blunted circadian rhythm and a lower basal HR. Furthermore, blunted stress reactivity was associated with depressive symptoms, but not chronic stress. Night-time RMSSD data was not influenced by chronic stress, depressive symptoms or their interaction.ConclusionThe combination of stress and depressive symptoms, but not chronic stress by itself leads to a blunted HR circadian rhythm. Furthermore, blunted HR reactivity is associated with depressive symptoms and not chronic stress.

The impact of heart rate circadian rhythm on in-hospital mortality in patients with stroke and critically ill: Insights from the eICU Collaborative Research Database

Data showing the impact of dysregulated heart rate circadian rhythm in patients with stroke and critically ill are scarce. The purpose of this study was to investigate whether the circadian rhythm of heart rate was an independent risk factor for in-hospital mortality in patients with stroke and critically ill. Study patients from the recorded eICU Collaborative Research Database were included in the present analyses. Three variables-mesor, amplitude, and peak time-were used to evaluate the heart rate circadian rhythm. The incremental value of circadian rhythm variables in addition to Acute Physiology and Chronic Health Evaluation (APACHE) IV score to predict in-hospital mortality was explored. A total of 6201 patients whose heart rate have cosinor rhythmicity. After adjustments, mesor per 10 beats/min increase was associated with a 1.18-fold (95% confidence interval [CI] 1.12- to 1.25-fold; P < .001) and amplitude per 5 beats/min was associated with a 1.17-fold (95% CI 1.07- to 1.27-fold; P < .001) increase in the risk of in-hospital mortality. The risk of in-hospital mortality was highest in patients who had peak time reached between 12:00 and 18:00 (odds ratio 1.35; 95% CI 1.06-1.72; P=.015). Compared with APACHE IV score only (c-index 0.757), a combination of APACHE IV score and circadian rhythm variables of heart rate (c-index 0.766) was associated with increased discriminative ability (P = .003). Circadian rhythm of heart rate is an independent risk factor for in-hospital mortality in patients with stroke and critically ill. Including circadian rhythm variables of heart rate might increase the discriminative ability of the risk score to predict the prognosis of patients.

Unstable Circadian Rhythm of Heart Rate of Alzheimer Dementia Based on Biological Data of Mattress Sensor.

It is important to detect daily Alzheimer dementia (AD) possibility using unconstrained mattress sensors because dementia takes time before subjective symptoms appear and the main treatment is to slow the rate of progression. Forcusing on circadian rhythm disorder which tend to occur with AD, this paper analyzes the features of unstable circadian rhythms of heart rate associated with its weakening and misalignment in AD. It is found that the external feature of heart rate of AD that of up and down changes seen frequently compared to that of healthy subjects makes the multiple types of effects on the estimation process of the AD detection method based on the circadian instability represented by the trigonometric regression equation estimated from the heart rate. So, we designed two feature values from the effects and analyzed them in an analysis experiment. An analysis experiment was conducted on the heart rate of total 72 days data of one AD patient and total 30 days data of 21 healthy people, and the result confirmed significant differences between the AD and the healthy people at from 0.01% to 0.1 % level for the first feature and at from 0.1% to 5% level for the second feature. And the result shows the possibility that differences in the heart rate features is found between AD and healthy people.

Nomogram Model Based on Clinical Risk Factors and Heart Rate Variability for Predicting All-Cause Mortality in Stage 5 CKD Patients.

Background: Heart rate variability (HRV), reflecting circadian rhythm of heart rate, is reported to be associated with clinical outcomes in stage 5 chronic kidney disease (CKD5) patients. Whether CKD related factors combined with HRV can improve the predictive ability for their death remains uncertain. Here we evaluated the prognosis value of nomogram model based on HRV and clinical risk factors for all-cause mortality in CKD5 patients. Methods: CKD5 patients were enrolled from multicenter between 2011 and 2019 in China. HRV parameters based on 24-h Holter and clinical risk factors associated with all-cause mortality were analyzed by multivariate Cox regression. The relationships between HRV and all-cause mortality were displayed by restricted cubic spline graphs. The predictive ability of nomogram model based on clinical risk factors and HRV were evaluated for survival rate. Results: CKD5 patients included survival subgroup (n = 155) and all-cause mortality subgroup (n = 45), with the median follow-up time of 48 months. Logarithm of standard deviation of all sinus R-R intervals (lnSDNN) (4.40 ± 0.39 vs. 4.32 ± 0.42; p = 0.007) and logarithm of standard deviation of average NN intervals for each 5 min (lnSDANN) (4.27 ± 0.41 vs. 4.17 ± 0.41; p = 0.008) were significantly higher in survival subgroup than all-cause mortality subgroup. On the basis of multivariate Cox regression analysis, the lnSDNN (HR = 0.35, 95%CI: 0.17–0.73, p = 0.01) and lnSDANN (HR = 0.36, 95% CI: 0.17–0.77, p = 0.01) were associated with all-cause mortality, their relationships were negative linear. Spearman’s correlation analysis showed that lnSDNN and lnSDANN were highly correlated, so we chose lnSDNN, sex, age, BMI, diabetic mellitus (DM), β-receptor blocker, blood glucose, phosphorus and ln intact parathyroid hormone (iPTH) levels to build the nomogram model. The area under the curve (AUC) values based on lnSDNN nomogram model for predicting 3-year and 5-year survival rates were 79.44% and 81.27%, respectively. Conclusion: In CKD5 patients decreased SDNN and SDANN measured by HRV were related with their all-cause mortality, meanwhile, SDNN and SDANN were highly correlated. Nomogram model integrated SDNN and clinical risk factors are promising for evaluating their prognosis.

MO501: A Nomogram Based on Heart Rate Variability Parameters for Predicting All-Cause Mortality in Stage 5 CKD Patients

Abstract BACKGROUND AND AIMS Heart rate variability (HRV), reflecting the circadian rhythm of heart rate, is associated with clinical outcomes in stage 5 chronic kidney disease 5 (CKD5) patients. Whether CKD-related factors combined with HRV can improve the predictive ability for their death remains uncertain. Here we evaluated the prognosis value of nomogram models based on HRV for all-cause mortality in CKD5 patients. METHOD Multicenter CKD5 patients were enrolled from 2011 to 2019 in China. The multivariate Cox regression analysis screened HRV parameters, which associated with all-cause mortality. Their relationships were displayed by restricted cubic spline graphs. The predictive abilities of nomogram models were evaluated for survival rate. RESULTS CKD5 patients included survival group (n = 155) and the all-cause mortality group (n = 45), with a median follow-up time of 48 months. Logarithm of standard deviation of all sinus R–R intervals (lnSDNN) {HR: 0.35, [95% confidence interval (95% CI): 0.17–0.73]; P = .01} and logarithm of standard deviation of average NN intervals for each 5 min (lnSDANN) (HR: 0.36, 95% CI: 0.17–0.77; P = .01) were associated with all-cause mortality, their relationships were negative linear. The area under the curve (AUC) values based on lnSDNN nomogram model for predicting 3-year and 5-year survival rates were 79.44% and 81.27%, respectively. The AUC values based on lnSDANN nomogram model for predicting 3-year and 5-year survival rates were 78.73% and 80.61%, respectively. CONCLUSION As clinical indicators of heart rate circadian rhythm, SDNN and SDANN are highly correlated with the prognosis of CKD5 patients. Nomogram models that integrate HRV and multiple CKD-related risk factors are promising for evaluating their all-cause mortality.

Mice Exposed to Maternal Separation are Resilient to the Loss of Circadian Heart Rate Rhythm in Response to Chronic High Salt Diet

Early life stress (ELS) is associated with increases in body mass index and systolic blood pressure in adult life, leading to obesity and obesity‐induced hypertension, major risk factors for cardiovascular disease (CVD). Previously, we have shown that Maternal Separation and Early Weaning (MSEW), a model that mimics the effects of ELS in humans, increases blood pressure and sympathetic activation in obese male mice. We have also shown that MSEW males fed a low‐fat diet (LF) displayed increased water intake, urine excretion, potassium excretion, glomerular filtration rate (GFR), and renal cortex NHE3 expression compared to controls. The aim of this study was to further investigate the status of the water and electrolyte homeostasis (WEH) when we challenge mice exposed to MSEW with a chronic high‐salt diet (HS). C57BL/6J mice pups were separated from the dams from postnatal day (PD) 2 to PD 16 and weaned early on PD 17. Control (C) litters remained undisturbed with the dams and were weaned on PD 21. At weaning, mice were placed on a LF (10% Kcal from fat, Research Diets). After 18 weeks, mice were implanted with radiotelemeters to measure systolic blood pressure (SBP) and heart rate (HR). At 20 weeks, a baseline was recorded and then mice were placed on a LF+HS (10% Kcal from fat, 4% NaCl, Research Diets) for 6 weeks. Single mouse metabolic cages were used to measure water intake and urine excretion before and after LF+HS. GFR was measured using a transcutaneous technique. After 6 weeks, control and MSEW mice showed a similar response to LF+HS in water intake (3.84 ± 0.54 vs. 4.56 ± 1.01 ml), urine excretion (1.90 ± 0.93 vs. 2.63 ± 1.18 ml), and GFR (930.98 ± 41.30 vs. 975.97 ± 86.12 ml/min/100g BW). In addition, 6 weeks of LF+HS did not change 24‐hr SBP from baseline in control (125.5 ± 5.85 vs. 129.33 ± 6.0 mmHg) and MSEW mice (117.33 ± 9.55 vs. 126.67 ± 11.98 mmHg). Similarly, HR did not change in control (612.88 ± 19.51 vs. 651.67 ± 17.84 bpm) and MSEW mice (602.25 ± 15.27 vs. 575.83 ± 11.24 bpm). At baseline, both groups show normal circadian rhythm of blood pressure. However, LF+HS control males lack day‐night HR amplitude (day: 655 ± 14.50 vs. night: 647.67 ± 11.17 bpm, p=NS) while MSEW mice preserve this function (day: 557.67 ± 6.97 mmHg vs. night: 594 ± 5.51 bpm, p&lt;0.05). These data indicate that MSEW male mice are resilient to loss of circadian HR rhythm in response to a chronic HS. Ongoing studies of renal sodium transporters expression may provide insights into the potential mechanisms by which MSEW male mice display this resilience.

Physiological recovery among workers in long-distance sleddog races: A case study on female veterinarians in Finnmarksløpet

BACKGROUND: During Finnmarksløpet (FL, one of the longest distance sleddog races in the world), veterinarians are exposed to extreme environmental conditions and tight working schedules, with little and fragmented sleep. OBJECTIVE: The aim of this case study was to examine cardiovascular parameters and sleep-wake patterns among veterinarians working within FL, during and after (for a month) the end of the race. METHODS: Six female veterinarians volunteered for the study. The participants wore a wrist device for a total of eight weeks in order to passively and semi-continuously record physiological responses throughout the day (i.e., heart rate, heart rate variability, number of steps, and sleep quality). Moreover, perceived sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI) at three time-points. RESULTS: During and for one month after completion of the FL, most veterinarians presented an alteration of cardiovascular parameters and sleep quality. The heart rate circadian rhythm returned to pre-race values within about two weeks. CONCLUSIONS: The long-lasting alteration of the veterinarians’ cardiovascular parameters and sleep-wake patterns might have negative consequences for their health in the long-term, especially if similar experiences are repeated more times though the course of a year or season. More research is needed in order to understand the health risks, as well as how to prevent them, among veterinarians in long-distance sleddog races or other similar events.

Distinct Circadian Assessments From Wearable Data Reveal Social Distancing Promoted Internal Desynchrony Between Circadian Markers.

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body.

Influence of smoking and other cardiovascular risk factors on heart rate circadian rhythm in normotensive and hypertensive subjects.

Circadian heart rate (HR) is influenced by hypertension and other cardiovascular risk factors particularly smoking, obesity and dyslipidemia. Until now, to evaluate the HR changes due to presence of these risk factors, a single HR office measure or a mean evaluated on day time or night time or 24h was used. However, since HR shows a circadian behavior, a single value represents only a rough approximation of this behavior. In this study, we analyzed the influence of smoking, obesity and dyslipidemia on the circadian rhythm in normotensive and hypertensive subject groups presenting only one of these risk factors. The 24h HR recordings of 170 normotensive (83 without risk factors, 20 smokers, 44 with dyslipidemia, 23 obese) and 353 hypertensive (169 without risk factors, 32 smokers, 99 with dyslipidemia, 53 obese) subjects were acquired using a Holter Blood Pressure Monitor. Results highlighted a specific circadian behavior with three characteristic periods presenting different HR means and rates of HR change in the eight subject groups. The slopes could be used both to estimate the morning HR surge associated with acute cardiovascular effects in the awakening and to evaluate the decline during the night. Moreover, we suggest to use three HR mean values (one for each identified period of the day) rather than two HR values to better describe the circadian HR behavior. Furthermore, smoking increased and dyslipidemia decreased mean HR values from 10:00 to 04:00, both in normotensive and hypertensive subjects in comparison with subjects without risk factors. In this time interval, hypertensive obese subjects showed higher values while normotensive ones presented quite similar values than subjects without risk factors. During the awakening (05:00–10:00) the slopes were similar among all groups with no significant difference among the mean HR values.

A method for characterizing daily physiology from widely used wearables

SummaryMillions of wearable-device users record their heart rate (HR) and activity. We introduce a statistical method to extract and track six key physiological parameters from these data, including an underlying circadian rhythm in HR (CRHR), the direct effects of activity, and the effects of meals, posture, and stress through hormones like cortisol. We test our method on over 130,000 days of real-world data from medical interns on rotating shifts, showing that CRHR dynamics are distinct from those of sleep-wake or physical activity patterns and vary greatly among individuals. Our method also estimates a personalized phase-response curve of CRHR to activity for each individual, representing a passive and personalized determination of how human circadian timekeeping continually changes due to real-world stimuli. We implement our method in the “Social Rhythms” iPhone and Android app, which anonymously collects data from wearable-device users and provides analysis based on our method.

A SAS macro for modelling periodic data using cosinor analysis

Background and objectiveCosinor analysis, developed by Franz Hallberg and colleagues in the 1960s, allows for the fitting of a cosine curve to data of a known period. Cosinor analysis is frequently used in the analysis of biological rhythm data. While software exists to perform these analyses, we are not aware of any published SAS procedures or macros which would facilitate them. MethodsTo meet this gap, we herein describe SAS macros which perform cosinor analyses that assume either normally or gamma distributed outcomes and fixed period. The macros can 1) produce datasets with cosinor parameters including acrophase, mesor, amplitude, nadir and test for rhythmicity 2) output datasets with fitted and observed values from the model, and 3) plot the resulting curve and underlying data. ResultsWe demonstrate the use of these macros with data from our research on circadian rhythms of heart rate and sleep in critically ill patients. ConclusionsCosinor analysis provides a parsimonious and intuitive set of estimates to summarize periodic data. We are hopeful that the publication of our macro will allow a wider spectrum of users to avail themselves of this technique.

Astronauts well-being and possibly anti-aging improved during long-duration spaceflight

This study assesses how circadian rhythms of heart rate (HR), HR variability (HRV) and activity change during long-term missions in space and how they relate to sleep quality. Ambulatory 48-h ECG and 96-h actigraphy were performed four times on ten healthy astronauts (44.7 ± 6.9 years; 9 men): 120.4 ± 43.7 days (Before) launch; 21.1 ± 2.5 days (ISS01) and 143.0 ± 27.1 days (ISS02) after launch; and 86.6 ± 40.6 days (After) return to Earth. Sleep quality was determined by sleep-related changes in activity, RR-intervals, HRV HF- and VLF-components and LF-band. The circadian amplitude of HR (HR-A) was larger in space (ISS01: 12.54, P = 0.0099; ISS02: 12.77, P = 0.0364) than on Earth (Before: 10.90; After: 10.55 bpm). Sleep duration in space (ISS01/ISS02) increased in 3 (Group A, from 370.7 to 388.0/413.0 min) and decreased in 7 (Group B, from 454.0 to 408.9/381.6 min) astronauts. Sleep quality improved in Group B from 7.07 to 8.36 (ISS01) and 9.36 (ISS02, P = 0.0001). Sleep-related parasympathetic activity increased from 55.2% to 74.8% (pNN50, P = 0.0010) (ISS02). HR-A correlated with the 24-h (r = 0.8110, P = 0.0044), 12-h (r = 0.6963, P = 0.0253), and 48-h (r = 0.6921, P = 0.0266) amplitudes of the magnetic declination index. These findings suggest associations of mission duration with increased well-being and anti-aging benefitting from magnetic fluctuations.

Effects of blood pressure and heart rate circadian rhythms on left atrial function.

We examined the associations among the circadian rhythms of blood pressure (BP), heart rate (HR) and left atrial function in essential hypertensive patients. The study included 237 essential hypertensive patients who completed 24-h ambulatory BP, HR monitoring and two-dimensional speckle tracking echocardiography (2DSTE). The strain and strain rate images were studied, and the following parameters were measured: left atrial reservoir strain and strain rate (LAS-S and LASR-S), left atrial conduit strain and strain rate (LAS-E and LASR-E), and left atrial booster strain and strain rate (LAS-A and LASR-A). The left atrial stiffness index (LASI) was identified as the ratio of E/e' to LAS-S. All participants were divided into three groups according to the percentage of nocturnal BP dipping (dippers, nondippers and reverse dippers). The LASI was significantly higher in BP reverse dippers than in dippers and nondippers. LAS-S, LAS-E and LASR-E were significantly lower in BP reverse dippers than dippers and nondippers. Multivariate logistic regression analysis demonstrated that age, night-time mean SBP and the percentage of nocturnal HR decline were independently related to an increased LASI. Impairment of the left atrial reservoir and conduit functions was correlated with abnormal BP and HR circadian rhythms in hypertension. Increased left atrial stiffness was associated with night-time SBP and the percentage of nocturnal HR decline.

Can offsetting the energetic cost of hibernation restore an active season phenotype in grizzly bears (Ursus arctos horribilis)?

Hibernation is characterized by depression of many physiological processes. To determine if this state is reversible in a non-food caching species, we fed hibernating grizzly bears (Ursus arctos horribilis) dextrose for 10 days to replace 53% or 100% of the estimated minimum daily energetic cost of hibernation. Feeding caused serum concentrations of glycerol and ketones (β-hydroxybutyrate) to return to active season levels irrespective of the amount of glucose fed. By contrast, free fatty acids (FFAs) and indices of metabolic rate, such as general activity, heart rate, strength of heart rate circadian rhythm, and insulin sensitivity were restored to approximately 50% of active season levels. Body temperature was unaffected by feeding. To determine the contribution of adipose to the metabolic effects observed after glucose feeding, we cultured bear adipocytes collected at the beginning and end of the feeding and performed metabolic flux analysis. We found a ∼33% increase in energy metabolism after feeding. Moreover, basal metabolism before feeding was 40% lower in hibernation cells compared with fed cells or active cells cultured at 37°C, thereby confirming the temperature independence of metabolic rate. The partial depression of circulating FFAs with feeding likely explains the incomplete restoration of insulin sensitivity and other metabolic parameters in hibernating bears. Further depression of metabolic function is likely to be an active process. Together, the results provide a highly controlled model to examine the relationship between nutrient availability and metabolism on the hibernation phenotype in bears.