Cardiac autonomic modulation in individuals with controlled and uncomplicated hypertension during exercise-heat stress.

TAKE-HOME MESSAGE: During short bouts of light-to-vigorous exercise in the heat, controlled and uncomplicated hypertension did not significantly modulate HRV in physically active individuals. These findings can be used to refine guidance on use of exercise for hypertension management in the heat.

Economic feasibility of a novel tool to assist extubation decision-making: an early health economic modeling.

OBJECTIVES: To estimate the minimum percent change in failed extubation to make a tool designed to reduce extubation failure (Extubation Advisor [EA]) economically viable. METHODS: We conducted an early return on investment (ROI) analysis using data from intubated intensive care unit (ICU) patients at a large Canadian tertiary care hospital. We obtained input parameters from the hospital database and published literature. We ran generalized linear models to estimate the attributable length of stay, total hospital cost, and time to subsequent extubation attempt following failure. We developed a Markov model to estimate the expected ROI and performed probabilistic sensitivity analyses to assess the robustness of findings. Costs were presented in 2020 Canadian dollars (C$). RESULTS: The model estimated a 1 percent reduction in failed extubation could save the hospital C$289 per intubated patient (95 percent CI: 197, 459). A large center seeing 2,500 intubated ICU patients per year could save C$723,124/year/percent reduction in failed extubation. At the current annual price of C$164,221, the EA tool must reduce extubation failure by at least 0.24 percent (95 percent CI: .14, .41) to make the tool cost-effective at our site. CONCLUSIONS: Clinical decision-support tools like the EA may play an important role in reducing healthcare costs by reducing the rate of extubation failure, a costly event in the ICU.

Predicting Time to Death After Withdrawal of Life-Sustaining Measures Using Vital Sign Variability: Derivation and Validation.

To develop a predictive model using vital sign (heart rate and arterial blood pressure) variability to predict time to death after withdrawal of life-supporting measures. DESIGN: Retrospective analysis of observational data prospectively collected as part of the Death Prediction and Physiology after Removal of Therapy study between May 1, 2014, and May 1, 2018. SETTING: Adult ICU. PATIENTS: Adult patients in the ICU with a planned withdrawal of life-supporting measures and an expectation of imminent death. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Vital sign waveforms and clinical data were prospectively collected from 429 patients enrolled from 20 ICUs across Canada, the Czech Republic, and the Netherlands. Vital sign variability metrics were calculated during the hour prior to withdrawal. Patients were randomly assigned to the derivation cohort (288 patients) or the validation cohort (141 patients), of which 103 and 54, respectively, were eligible for organ donation after circulatory death. Random survival forest models were developed to predict the probability of death within 30, 60, and 120 minutes following withdrawal using variability metrics, features from existing clinical models, and/or the physician's prediction of rapid death. A model employing variability metrics alone performed similarly to a model employing clinical features, whereas the combination of variability, clinical features, and physician's prediction achieved the highest area under the receiver operating characteristics curve of all models at 0.78 (0.7-0.86), 0.79 (0.71-0.87), and 0.8 (0.72-0.88) for 30-, 60- and 120-minute predictions, respectively. CONCLUSIONS: Machine learning models of vital sign variability data before withdrawal of life-sustaining measures, combined with clinical features and the physician's prediction, are useful to predict time to death. The impact of providing this information for decision support for organ donation merits further investigation.

Exploring the Effects of Yoga Therapy on Heart Rate Variability and Patient-Reported Outcomes After Cancer Treatment: A Study Protocol.

BACKGROUND: Following cancer treatment, adults commonly report worsened patient-reported outcomes (PROs) such as anxiety, stress, depression, persistent and upsetting cognitive complaints, unrelenting fatigue, and reduced quality of life. Poorer PROs are associated with disrupted autonomic nervous system functioning as measured by heart rate variability (HRV), both of which have been associated with greater morbidity and mortality. Interventions to improve HRV and PROs among adults following cancer treatment are needed. Yoga therapy holds promise as an intervention to improve HRV and PROs. Therefore, we conducted a single-subject exploratory experimental study to investigate the effects of yoga therapy on HRV and specific PROs (ie, cancer-related fatigue, anxiety, cognitive function, depression, stress, quality of life) in adults treated for cancer. To reduce publication bias, improve reproducibility, and serve as a reference for forthcoming reporting of study results, we present the study protocol for this study herein. METHODS: Participants were adults who completed cancer treatment that were recruited from the Ottawa Integrative Cancer Centre. Consenting and eligible participants received one 1:1 yoga therapy session (ie, 1 participant, 1 Yoga Therapist) and 6 weekly group-based yoga therapy sessions (ie, 2-3 participants, 1 Yoga Therapist). Participants completed assessments 7 times: 3 times prior to the program (ie, -6 weeks, -3 weeks, immediately prior to the 1:1 yoga therapy session), immediately following the 1:1 yoga therapy session, prior to the first group-based yoga therapy session, after the last group-based yoga therapy session, and at a 6-week follow-up. Hierarchical linear modeling will be used to test the average effects of the yoga therapy program across participants. DISCUSSION: This study will explore several novel hypotheses, including whether yoga therapy can improve HRV and/or specific PROs among adults treated for cancer acutely (ie, during a 1:1 yoga therapy session) and/or through repeated exposure (ie, after completing 6 weeks of group-based yoga therapy). Although the findings will require confirmation or refutation in future trials, they may provide initial evidence that YT may benefit adults treated for cancer. TRIAL REGISTRATION: ISRCTN registry, ISRCTN64763228. Registered on December 12, 2021. This trial was registered retrospectively. URL of trial registry record: https://www.isrctn.com/ISRCTN64763228.

The impact of age, type 2 diabetes and hypertension on heart rate variability during rest and exercise at increasing levels of heat stress.

PURPOSE: In older adults with type 2 diabetes (T2D) and hypertension (HTN), cardiac autonomic modulation is markedly attenuated during exercise-heat stress. However, the extent to which this impairment is evident under increasing levels of heat stress remains unknown. METHODS: We examined heart rate variability (HRV), a surrogate of cardiac autonomic modulation, during incremental exercise-heat stress exposures in young (20-30 years) and middle-aged-to-older individuals (50-70 years) without and with T2D and HTN. Thirteen young and healthy (Young, n = 13) and 37 older men without (Older, n = 14) and with HTN (n = 13) or T2D (n = 10) performed 180-min treadmill walking at a fixed metabolic rate (~ 200 W/m2; ~ 3.5 METs) in a differing wet-bulb globe temperature (WBGT; 16 °C, 24 °C, 28 °C, and 32 °C). Electrocardiogram (ECG) and core temperature measurements were recorded throughout. Data were analysed using 5-min averaged epochs following 60-min exercise, which represented the last common timepoint across groups and conditions. RESULTS: Ageing did not significantly reduce HRV during increasing exercise-heat stress (all p > 0.050). However, T2D and HTN modified HRV during exercise-heat stress such that Detrended Fluctuation Analysis (DFA) α1 (p = 0.012) and the cardiac sympathetic index (p = 0.037) were decreased compared to Older in all except the warmest WBGT condition (32 °C). CONCLUSION: Our unique observations indicate that, relative to their younger counterparts, HRV in healthy older individuals is not perturbed during exercise heat-stress. However, relative to their age-matched healthy counterparts, HRV is reduced during exercise-heat stress in individuals with age-associated chronic conditions, indicative of cardiac autonomic dysfunction.

Effects of sex and wet-bulb globe temperature on heart rate variability during prolonged moderate-intensity exercise: a secondary analysis.

Sex differences in heart rate (HR) and heart rate variability (HRV), a surrogate of cardiac autonomic modulation, are evident during rest and exercise in young healthy individuals. However, it remains unclear whether sex impacts HRV during prolonged exercise at differing levels of environmental heat stress. Therefore, we completed a secondary analysis upon the effects of sex and wet-bulb globe temperature (WBGT) on HR and HRV during prolonged exercise. To achieve this, HR and HRV were assessed in non-endurance-trained and non-heat-acclimatised healthy men (n = 19) and women (n = 15) aged 18-45 years during 180 min of treadmill walking at a moderate metabolic rate (200 W/m2: equivalent to ∼35% peak aerobic power) in 16, 24, 28, and 32 °C WBGT. In the final 5 min prior to exercise termination, HR was observed to be higher in women relative to men in all but the 32 °C WBGT. Although no sex differences were observed for the HRV metric of root-mean-square of successive differences, high-frequency power was higher in women relative to men across WBGT conditions. These findings indicate that, in healthy non-heat-acclimatised individuals, women respond to prolonged exercise-heat stress with a greater increase in HR despite cardiac vagal autonomic modulation remaining equal or increasing compared to men. Novelty: Prior to exercise termination, females respond with a greater increase in HR under all WBGTs except the hottest (32 °C). Sex influenced  HRV metrics during all WBGTs, but results were mixed. Further characterisation of HRV sex differences remains an important area of research.

Early Warning of Infection in Patients Undergoing Hematopoietic Stem Cell Transplantation Using Heart Rate Variability and Serum Biomarkers.

Early warning of infection is critical to reduce the risk of deterioration and mortality, especially in neutropenic patients following hematopoietic stem cell transplantation (HCT). Given that heart rate variability (HRV) is a sensitive and early marker for infection, and that serum inflammatory biomarkers can have high specificity for infection, we hypothesized their combination may be useful for accurate early warning of infection. In this study, we developed and evaluated a composite predictive model using continuous HRV with daily serum biomarker measurements to provide risk stratification of future deterioration in HCT recipients. A total of 116 ambulatory outpatients about to undergo HCT consented to collection of prospective demographic, clinical (daily vital signs), HRV (continuous electrocardiography [ECG] monitoring, laboratory [daily serum samples frozen at -80 °C]), and infection outcome variables (defined as the time of escalation of antibiotics), all from 24 hours pre-HCT to the onset of infection or 14 days post-HCT. Indications for antibiotic escalation were adjudicated as "true infection" or not by 2 blinded HCT clinicians. A composite time series of 8 HRV metrics was created for each patient, and the probability of deterioration within the next 72 hours was estimated using logistic regression modeling of composite HRV and serum biomarkers using a rule-based naïve Bayes model if the HRV-based probability exceeded a median threshold. Thirty-five patients (30%) withdrew within <24 hours owing to intolerability of ECG monitoring, leaving 81 patients, of whom 48 (59%) had antibiotic escalation adjudicated as true infection. The combined HRV and biomarker (TNF-α, IL-6, and IL-7) predictive model began increasing at ~48 hours on average before the diagnosis of infection, could distinguish between high risk of impending infection (>90% incidence of subsequent infection within 72 hours), average risk (~50%), and low risk (<10%), with an area under the receiver operating characteristic curve of 0.87. However, given that prophylactic predictive ECG monitoring and daily serum collection proved challenging for many patients, further refinement in measurement is necessary for further study.

Feasibility of implementing Extubation Advisor, a clinical decision support tool to improve extubation decision-making in the ICU: a mixed-methods observational study.

OBJECTIVES: Although spontaneous breathing trials (SBTs) are standard of care to extubation readiness, no tool exists that optimises prediction and standardises assessment. In this study, we evaluated the feasibility and clinical impressions of Extubation Advisor (EA), a comprehensive clinical extubation decision support (CDS) tool. DESIGN: Phase I mixed-methods observational study. SETTING: Two Canadian intensive care units (ICUs). PARTICIPANTS: We included patients on mechanical ventilation for ≥24 hours and clinicians (respiratory therapists and intensivists) responsible for extubation decisions. INTERVENTIONS: Components included a predictive model assessment, feasibility evaluation, questionnaires and interviews with clinicians. RESULTS: We enrolled 117 patients, totalling 151 SBTs and 80 extubations. The incidence of extubation failure was 11% in low-risk patients and 21% in high-risk patients stratified by the predictive model; 38% failed extubation when both the model and clinical impression were at high risk. The tool was well rated: 94% and 75% rated the data entry and EA report as average or better, respectively. Interviews (n=15) revealed favourable impressions regarding its user interface and functionality, but unexpectedly, also concerns regarding EA's potential impact on respiratory therapists' job security. CONCLUSIONS: EA implementation was feasible, and users perceived it to have potential to support extubation decision-making. This study helps to understand bedside implementation of CDS tools in a multidisciplinary ICU. TRIAL REGISTRATION NUMBER: NCT02988167.

Fetal Cardiovascular Decompensation During Labor Predicted From the Individual Heart Rate Tracing: A Machine Learning Approach in Near-Term Fetal Sheep Model.

Background: When exposed to repetitive umbilical cord occlusions (UCO) with worsening acidemia, fetuses eventually develop cardiovascular decompensation manifesting as pathological hypotensive arterial blood pressure (ABP) responses to fetal heart rate (FHR) decelerations. Failure to maintain cardiac output during labor is a key event leading up to brain injury. We reported that the timing of the event when a fetus begins to exhibit this cardiovascular phenotype is highly individual and was impossible to predict. Objective: We hypothesized that this phenotype would be reflected in the individual behavior of heart rate variability (HRV) as measured by root mean square of successive differences of R-R intervals (RMSSD), a measure of vagal modulation of HRV, which is known to increase with worsening acidemia. This is clinically relevant because HRV can be computed in real-time intrapartum. Consequently, we aimed to predict the individual timing of the event when a hypotensive ABP pattern would emerge in a fetus from a series of continuous RMSSD data. Study Design: Fourteen near-term fetal sheep were chronically instrumented with vascular catheters to record fetal arterial blood pressure, umbilical cord occluder to mimic uterine contractions occurring during human labor and ECG electrodes to compute the ECG-derived HRV measure RMSSD. All animals were studied over a ~6 h period. After a 1-2 h baseline control period, the animals underwent mild, moderate, and severe series of repetitive UCO. We applied the recently developed machine learning algorithm to detect physiologically meaningful changes in RMSSD dynamics with worsening acidemia and hypotensive responses to FHR decelerations. To mimic clinical scenarios using an ultrasound-based 4 Hz FHR sampling rate, we recomputed RMSSD from FHR sampled at 4 Hz and compared the performance of our algorithm under both conditions (1,000 Hz vs. 4 Hz). Results: The RMSSD values were highly non-stationary, with four different regimes and three regime changes, corresponding to a baseline period followed by mild, moderate, and severe UCO series. Each time series was characterized by seemingly randomly occurring (in terms of timing of the individual onset) increase in RMSSD values at different time points during the moderate UCO series and at the start of the severe UCO series. This event manifested as an increasing trend in RMSSD values, which counter-intuitively emerged as a period of relative stationarity for the time series. Our algorithm identified these change points as the individual time points of cardiovascular decompensation with 92% sensitivity, 86% accuracy and 92% precision which corresponded to 14 ± 21 min before the visual identification. In the 4 Hz RMSSD time series, the algorithm detected the event with 3 times earlier detection times than at 1,000 Hz, i.e., producing false positive alarms with 50% sensitivity, 21% accuracy, and 27% precision. We identified the overestimation of baseline FHR variability by RMSSD at a 4 Hz sampling rate to be the cause of this phenomenon. Conclusions: The key finding is demonstration of FHR monitoring to detect fetal cardiovascular decompensation during labor. This validates the hypothesis that our HRV-based algorithm identifies individual time points of ABP responses to UCO with worsening acidemia by extracting change point information from the physiologically related fluctuations in the RMSSD signal. This performance depends on the acquisition accuracy of beat to beat fluctuations achieved in trans-abdominal ECG devices and fails at the sampling rate used clinically in ultrasound-based systems. This has implications for implementing such an approach in clinical practice.

Machine learning model on heart rate variability metrics identifies asymptomatic toddlers exposed to zika virus during pregnancy.

Objective. Although the Zika virus (ZIKV) seems to be prominently neurotropic, there are some reports of involvement of other organs, particularly the heart. Of special concern are those children exposed prenatally to ZIKV and born without microcephaly or other congenital anomalies. Electrocardiogram (ECG)-derived heart rate variability (HRV) metrics represent an attractive, low-cost, widely deployable tool for early identification of developmental functional alterations in exposed children born without such overt clinical symptoms. We hypothesized that HRV in such children would yield a biomarker of fetal ZIKV exposure. Our objective was to test this hypothesis in young children exposed to ZIKV during pregnancy.Approach. We investigated the HRV properties of 21 children aged 4-25 months from Brazil. The infants were divided into two groups, the ZIKV-exposed (n = 13) and controls (n = 8). Single-channel ECG was recorded in each child at ∼15 months of age and HRV was analyzed in 5 min segments to provide a comprehensive characterization of the degree of variability and complexity of the heart rate.Main results.Using a cubic support vector machine classifier we identified babies as Zika cases or controls with a negative predictive value of 92% and a positive predictive value of 86%. Our results show that a machine learning model derived from HRV metrics can help differentiate between ZIKV-affected, yet asymptomatic, and non-ZIKV-exposed babies. We identified the box count as the best HRV metric in this study allowing such differentiation, regardless of the presence of microcephaly.Significance.We show that it is feasible to measure HRV in infants and toddlers using a small non-invasive portable ECG device and that such an approach may uncover the memory ofin uteroexposure to ZIKV. We discuss putative mechanisms. This approach may be useful for future studies and low-cost screening tools involving this challenging to examine population.

Multimodal pathophysiological dataset of gradual cerebral ischemia in a cohort of juvenile pigs.

Ischemic brain injuries are frequent and difficult to detect reliably or early. We present the multi-modal data set containing cardiovascular (blood pressure, blood flow, electrocardiogram) and brain electrical activities to derive electroencephalogram (EEG) biomarkers of corticothalamic communication under normal, sedation, and hypoxic/ischemic conditions with ensuing recovery. We provide technical validation using EEGLAB. We also delineate the corresponding changes in the electrocardiogram (ECG)-derived heart rate variability (HRV) with the potential for future in-depth analyses of joint EEG-ECG dynamics. We review an open-source methodology to derive signatures of coupling between the ECoG and electrothalamogram (EThG) signals contained in the presented data set to better characterize the dynamics of thalamocortical communication during these clinically relevant states. The data set is presented in full band sampled at 2000 Hz, so the additional potential exists for insights from the full-band EEG and high-frequency oscillations under the bespoke experimental conditions. Future studies on the dataset may contribute to the development of new brain monitoring technologies, which will facilitate the prevention of neurological injuries.

Variability Predictors of Vasospasm in Subarachnoid Hemorrhage: A Feasibility Study.

BACKGROUND: Mean cerebral blood flow velocity (mean-CBFV) obtained from Transcranial Doppler (TCD) poorly predicts cerebral vasospasm in patients with aneurysmal subarachnoid hemorrhage (aSAH). Variability descriptors of mean-CBFV obtained during extended TCD recordings may improve this prediction. We assessed the feasibility of generating reliable linear and non-linear descriptors of mean-CBFV variability using extended recordings in aSAH patients and in healthy controls. We also explored which of those metrics might have the ability to discriminate between aSAH patients and healthy controls, and among patients who would go on to develop vasospasm and those who would not. METHODS: Bilateral mean-CBFV, blood pressure, and heart rate were continuously recorded for 40 minutes in aSAH patients (n = 8) within the first 5 days after ictus, in age-matched healthy controls (n = 8) and in additional young controls (n = 8). We obtained linear [standard deviation, coefficient of variations, and the very-low (0.003-0.040 Hz), low (0.040-0.150 Hz), and high-frequency (0.15-0.4 Hz) power spectra] and non-linear (Fractality, deterministic Chaos analyses) variability metrics. RESULTS: We successfully obtained TCD recordings from patients and healthy controls and calculated the desired metrics of mean-CBFV variability. Differences were appreciable between aSAH patients and healthy controls, as well as between aSAH patients who later developed vasospasm and those who did not. CONCLUSIONS: A 40-minute TCD recording provides reliable variability metrics in aSAH patients and healthy controls. Future studies are required to determine if mean-CBFV variability metrics remain stable over time, and whether they may serve to identify patients who are at greatest risk of developing cerebral vasospasm after aSAH.

Effect of exercise-heat acclimation on cardiac autonomic modulation in type 2 diabetes: a pilot study.

The effects of exercise-heat acclimation on heart rate variability (HRV) in individuals with type 2 diabetes (T2D) remains unclear. We assessed electrocardiogram recordings during exercise-heat stress in middle-aged-to-older individuals (50-70 years) with (n = 6) and without (control; n = 8;) T2D, before and after 7 days of exercise-heat acclimation. Exercising heart rate was reduced (control, -9 ± 5 bpm; T2D, -14 ± 9 bpm) yet HRV was not significantly different. Given the negative correlations between diminished HRV and cardiac risk observed in the scientific literature, further research is warranted. Novelty: Our observations indicate that 7 days exercise-heat acclimation may not effectively attenuate the deviation toward reduced overall HRV and unfavourable cardiac autonomic modulation in individuals with T2D.

Heart rate variability in older men on the day following prolonged work in the heat.

Susceptibility to heat illness during physically demanding work in hot environments is greater on the second of two consecutive workdays. While it has been demonstrated that heat storage is exacerbated on the second compared to first workday in older workers (50-65 yr), the effects on heart rate variability (HRV), an established surrogate of cardiac autonomic modulation, remain unclear. This study evaluated HRV in older workers on the day following prolonged work in the heat. Electrocardiogram was recorded in nine older (53-64 yr) males at rest, during three 30-min bouts of semi-recumbent cycling at fixed rates of metabolic heat production (150, 200, 250 W/m2), each separated by 15-min recovery. Experiments were conducted in hot-dry conditions (40 °C, 20% relative humidity), immediately prior to (Day 1), and on the day following (Day 2), a prolonged work simulation (∼7.5 hr) involving moderate intensity intermittent exercise in hot-dry conditions (38 °C, 34% relative humidity). Core temperature, as well as time, frequency, and nonlinear HRV indices were derived for analysis during rest, the final 5-min of exercise at the highest heat production and recovery. The change in core temperature at the end of work (mean ±SD) was significantly greater on Day 2 (1.0 °C ±0.3) relative to Day 1 (0.8 °C ±0.2; p < 0.01). Heart rate, however, did not significantly differ between days 1 and 2 at rest (Day 1, 59 ±11 bpm; Day 2, 62 ±13 bpm), during exercise (Day 1, 113 ±21 bpm; Day 2, 114 ±18 bpm ) and at the end of recovery (Day 1, 75 ±16 bpm; Day 2, 76 ±12 bpm). Likewise, there were no significant differences in any HRV indices derived from time, frequency, and nonlinear domains (all p > 0.05). Prolonged work in the heat did not modulate next-day heart rhythms, as reflected by HRV, despite augmented core temperature. While HRV can reflect physiological aspects of cardiac autonomic stressors, these findings indicate it does not provide a means to identify exacerbated heat strain in older workers over consecutive work shifts in the heat.

Heart rate variability in older workers during work under the Threshold Limit Values for heat exposure.

BACKGROUND: The Threshold Limit Values (TLV) of the American Conference of Governmental and Industrial Hygienists indicate the levels of heat stress that all workers may be repeatedly exposed to without adverse health effects. In this study, we evaluated heart rate variability (HRV) during moderate-to-heavy work performed continuously or according to different TLV work-rest (WR) allocations in healthy physically active older workers. METHODS: Nine healthy older (58 ± 5 years) males performed three different 120-minute conditions in accordance with TLV guidelines for moderate-to-heavy intensity work (360 W fixed rate of heat production) in different wet-bulb globe temperatures (WBGT): continuous cycling at 28°C WBGT (CON), as well as intermitted work performed at WR of 3:1 in 29°C WBGT (WR3:1), and at WR of 1:1 at 30°C (WR1:1). Rectal temperature and HRV (3-lead electrocardiogram [ECG]) were assessed throughout. RESULTS: Coefficient of Variation, Poincaré SD2, and Shannon Entropy were decreased during the CON compared with the WR3:1 when core temperature exceeded 38°C and after 1 hour of continuous work (P < .05). Also, 4 of the 12 HRV indices studied were reduced at CON compared with WR1:1 after 2 hours of accumulated work time (P < .05). Participants worked longer before core temperature reached 38°C during the WR1:1 and the WR3:1, compared with CON (P < .05). CONCLUSIONS: Incorporating breaks during moderate-to-heavy work in the heat for older adults can reduce autonomic stress and prolong the work performed at safe core temperature levels. The TLV WR1:1 provides increased cardiac protection for older workers, as compared with the CON and the WR3:1.

Cardiac autonomic modulation in type 1 diabetes during exercise-heat stress.

AIMS: Cardiac autonomic modulation, as assessed by heart rate variability (HRV), is independently attenuated by both type 1 diabetes (T1D) and exercise-heat stress, although their combined effects remain unclear. We therefore assessed HRV during exercise-heat stress in young individuals (18-37 years) with (n = 14) and without type 1 diabetes (n = 14). METHODS: Participants completed 30-min seated rest and three, 30-min bouts of semi-recumbent cycling at light, moderate, and vigorous metabolic heat productions (200, 250, 300 W/m2, respectively), each followed by 30-min recovery. Body core temperature (Tcore) and electrocardiogram were recorded throughout and analyzed during the final 5-min of rest and each exercise period. RESULTS: Relative to baseline, Tcore was increased in both groups, albeit to a greater extent in type 1 diabetes during vigorous exercise (T1D, 1.1 ± 0.3 °C; control, 0.8 ± 0.3 °C; P < 0.05). Overall HRV (as reflected by entropy) was attenuated throughout exercise relative to baseline in both groups, with the magnitude of the reduction greater in type 1 diabetes during vigorous exercise (T1D, - 108%; control, - 70%; P < 0.05). CONCLUSIONS: Given the negative correlations between decreased HRV and cardiac risk, our novel observations indicate that vigorous exercise in hot environments may pose a health concern for individuals with type 1 diabetes.

Age differences in cardiac autonomic regulation during intermittent exercise in the heat.

PURPOSE: This study aimed to detect potential differences in heart-rate variability (HRV) during a moderate-intensity intermittent exercise in the heat among physically active young (25.8 ± 1.9 years), middle-aged (43.5 ± 2.8 years), and older (62.9 ± 3.7 years) men. METHODS: Thirty-three participants (11/group) performed four successive bouts of 15-min cycling at a moderate fixed rate of metabolic heat production of ~ 400 W; each separated by a 15-min recovery with 1 h of final recovery in a hot and dry environment (35 °C, 20% relative humidity). Twelve HRV indices were computed that have been commonly described in the literature, and characterized various domains of the variability and complexity of heart rate. RESULTS: Cardiac autonomic regulation during intermittent exercise in the heat, as well as during pre-exercise rest and recovery was significantly affected by age, as changes were observed among the three different aged groups in five indices (p ≤ 0.05). Similarly, time influenced cardiac autonomic regulation as three indices showed changes across time (p ≤ 0.05) during intermittent exercise, whilst five indices displayed significant changes (p ≤ 0.05) during rest and recovery in the heat. CONCLUSIONS: This study supports that moderate-intensity intermittent exercise in the heat is associated with significant cardiac autonomic dysregulation in older men, as compared to young and middle-aged men, yet it highlights the importance of developing preventative health strategies for heat-related illness in aged individuals.

Fluid Loss during Exercise-Heat Stress Reduces Cardiac Vagal Autonomic Modulation.

PURPOSE: Sweat-induced fluid loss during prolonged exercise-heat stress can compromise cardiovascular and thermoregulatory function, although its effects on cardiac autonomic modulation remain unclear. We therefore examined heart rate variability (HRV) and recovery (HRRec), as surrogates of cardiac autonomic modulation, during and after prolonged exercise in the heat with and without fluid replacement. METHODS: Eleven young and healthy men performed 90 min of semi-recumbent cycling in dry heat (40°C; 20% relative humidity) at a fixed rate of metabolic heat production (600 W; ~46% V˙O2peak) followed by 40-min resting recovery without fluid replacement (No-FR; ~3.4% reduction in body mass). On a separate day, participants completed the same protocol with fluid replacement (FR; 500-700 mL timed boluses) to offset sweat losses. Esophageal temperature and ECG were recorded throughout, with measurements analyzed over 10-min averaged epochs during baseline, each 30-min interval during exercise and 20-min interval during recovery. RESULTS: Esophageal temperature and heart rate were elevated in No-FR relative to FR throughout exercise (all P ≤ 0.02). The HRV indices reflecting vagal influence of heart rate including the cardiac vagal index (CVI = log10[16 × SD1 × SD2]) and root-mean-square of successive differences were attenuated throughout exercise relative to baseline in both conditions (all P < 0.05), with the magnitude of the reduction greater in the No-FR condition (all P < 0.05). Further, sample entropy was reduced throughout all time points measured during exercise in the No-FR relative to FR condition (all P ≤ 0.03). CONCLUSIONS: Our unique observations indicate that while prolonged exercise heat stress attenuates the vagal influence and complexity of cardiac rhythms, that reduction is further exacerbated by fluid loss, highlighting the importance of fluid replacement in such conditions.

Non-invasive biomarkers of fetal brain development reflecting prenatal stress: An integrative multi-scale multi-species perspective on data collection and analysis.

Prenatal stress (PS) impacts early postnatal behavioural and cognitive development. This process of 'fetal programming' is mediated by the effects of the prenatal experience on the developing hypothalamic-pituitary-adrenal (HPA) axis and autonomic nervous system (ANS). We derive a multi-scale multi-species approach to devising preclinical and clinical studies to identify early non-invasively available pre- and postnatal biomarkers of PS. The multiple scales include brain epigenome, metabolome, microbiome and the ANS activity gauged via an array of advanced non-invasively obtainable properties of fetal heart rate fluctuations. The proposed framework has the potential to reveal mechanistic links between maternal stress during pregnancy and changes across these physiological scales. Such biomarkers may hence be useful as early and non-invasive predictors of neurodevelopmental trajectories influenced by the PS as well as follow-up indicators of success of therapeutic interventions to correct such altered neurodevelopmental trajectories. PS studies must be conducted on multiple scales derived from concerted observations in multiple animal models and human cohorts performed in an interactive and iterative manner and deploying machine learning for data synthesis, identification and validation of the best non-invasive detection and follow-up biomarkers, a prerequisite for designing effective therapeutic interventions.