Toward Personalized Salbutamol Therapy: Validating Virtual Patient-Derived Population Pharmacokinetic Model with Real-World Data.

Interindividual variability, influenced by patient-specific factors including age, weight, gender, race, and genetics, among others, contributes to variations in therapeutic response. Population pharmacokinetic (popPK) modeling is an essential tool for pinpointing measurable factors affecting dose-concentration relationships and tailoring dosage regimens to individual patients. Herein, we developed a popPK model for salbutamol, a short-acting ß2-agonist (SABA) used in asthma treatment, to identify key patient characteristics that influence treatment response. To do so, synthetic data from physiologically-based pharmacokinetic (PBPK) models was employed, followed by an external validation using real patient data derived from an equivalent study. Thirty-two virtual patients were included in this study. A two-compartment model, with first-order absorption (no delay), and linear elimination best fitted our data, according to diagnostic plots and selection criteria. External validation demonstrated a strong agreement between individual predicted and observed values. The incorporation of covariates into the basic structural model identified a significant impact of age on clearance (Cl) and intercompartmental clearance (Q); gender on Cl and the constant rate of absorption (ka); race on Cl; and weight on Cl in the volume of distribution of the peripheral compartment (V2). This study addresses critical challenges in popPK modeling, particularly data scarcity, incompleteness, and homogeneity, in traditional clinical trials, by leveraging synthetic data from PBPK modeling. Significant associations between individual characteristics and salbutamol's PK parameters, here uncovered, highlight the importance of personalized therapeutic regimens for optimal treatment outcomes.

Advancing Virtual Bioequivalence for Orally Administered Drug Products: Methodology, Real-World Applications and Future Outlook.

Bioequivalence studies are pivotal in generic drug development wherein therapeutic equivalence is provided with an innovator product. However, bioequivalence studies represent significant complexities due to the interplay of multiple factors related to drug, formulation, physiology, and pharmacokinetics. Approaches such as physiologically based biopharmaceutics modeling (PBBM) can enable virtual bioequivalence (VBE) assessment through appropriately developed and validated models. Such models are now being extensively used for bioequivalence risk assessment, internal decision-making, and the evaluation of drug and formulation factors related to bioequivalence. Depiction of the above-mentioned factors through the incorporation of variability and development of a virtual population for bioequivalence assessment is of paramount importance in utilizing such models. In this manuscript, we have portrayed our current understanding of VBE. A detailed explanation was provided with respect to study designs, in vivo variability, and the impact of physiological, drug, and formulation factors on the development of the population for VBE. Furthermore, strategies are suggested to incorporate variability in GastroPlus with an emphasis on intra-subject and inter-occasion variability. Two industrial case studies pertaining to immediate and modified release formulation were portrayed wherein VBE was utilized for decision-making and regulatory justification. Finally, regulatory understanding in the area of VBE, along with future perspectives, was detailed.

Exploring the Real-Time Variability and Complexity of Sitting Patterns in Office Workers with Non-Specific Chronic Spinal Pain and Pain-Free Individuals.

Chronic spinal pain (CSP) is a prevalent condition, and prolonged sitting at work can contribute to it. Ergonomic factors like this can cause changes in motor variability. Variability analysis is a useful method to measure changes in motor performance over time. When performing the same task multiple times, different performance patterns can be observed. This variability is intrinsic to all biological systems and is noticeable in human movement. This study aims to examine whether changes in movement variability and complexity during real-time office work are influenced by CSP. The hypothesis is that individuals with and without pain will have different responses to office work tasks. Six office workers without pain and ten with CSP participated in this study. Participant's trunk movements were recorded during work for an entire week. Linear and nonlinear measures of trunk kinematic displacement were used to assess movement variability and complexity. A mixed ANOVA was utilized to compare changes in movement variability and complexity between the two groups. The effects indicate that pain-free participants showed more complex and less predictable trunk movements with a lower degree of structure and variability when compared to the participants suffering from CSP. The differences were particularly noticeable in fine movements.

Preterm Infant's Heart Rate Variability Near Birth Predicts Autonomic Symptoms at Age 3 to 5 Years.

Aims To describe the autonomic function of premature infants born between 28 and 32 weeks of gestation, without medical risk factors, at the age of 3 to 5 years and to assess whether it's possible to predict the appearance of autonomic deficits in these children at this age range. Methods This follow-up study included 40 out of 55 premature infants born between weeks 28 and 32 during 2018 to 2020. During 2022 to 2023 parents were asked to report on medical and developmental follow-up and treatment, functional characteristics of the autonomic system, and the age at which walking was achieved. Results Approximately 27% of the participants (11 out of 40) presented autonomic symptoms at 3 to 5 years of age. A predictive relationship was noted between the function of the heart rate control system near birth and the presence of autonomic dysfunctions at ages 3 to 5. Fourteen of 40 children received neurodevelopmental treatments. However, children with autonomic symptoms were not treated for their symptoms. Conclusion These preliminary findings provide valuable insights into the autonomic function of children born premature and the potential predictive relationship between early autonomic measures and later autonomic dysfunctions. It also highlights the need for increased awareness and intervention strategies for addressing autonomic issues in premature infants to support their overall well-being.

Nonlinear Heart Rate Variability Analysis for Sleep Stage Classification Using Integration of Ballistocardiogram and Apple Watch.

Purpose: Wearable or non-contact, non-intrusive devices present a practical alternative to traditional polysomnography (PSG) for daily assessment of sleep quality. Physiological signals have been known to be nonlinear and nonstationary as the body adapts to states of rest or activity. By integrating more sophisticated nonlinear methodologies, the accuracy of sleep stage identification using such devices can be improved. This advancement enables individuals to monitor and adjust their sleep patterns more effectively without visiting sleep clinics. Patients and Methods: Six participants slept for three cycles of at least three hours each, wearing PSG as a reference, along with an Apple Watch, an actigraphy device, and a ballistocardiography (BCG) bed sensor. The physiological signals were processed with nonlinear methods and trained with a long short-term memory (LSTM) model to classify sleep stages. Nonlinear methods, such as return maps with advanced techniques to analyze the shape and asymmetry in physiological signals, were used to relate these signals to the autonomic nervous system (ANS). The changing dynamics of cardiac signals in restful or active states, regulated by the ANS, were associated with sleep stages and quality, which were measurable. Results: Approximately 73% agreement was obtained by comparing the combination of the BCG and Apple Watch signals against a PSG reference system to classify rapid eye movement (REM) and non-REM sleep stages. Conclusion: Utilizing nonlinear methods to evaluate cardiac dynamics showed an improved sleep quality detection with the non-intrusive devices in this study. A system of non-intrusive devices can provide a comprehensive outlook on health by regularly measuring sleeping patterns and quality over time, offering a relatively accessible method for participants. Additionally, a non-intrusive system can be integrated into a user's or clinic's bedroom environment to measure and evaluate sleep quality without negatively impacting sleep. Devices placed around the bedroom could measure user vitals over longer periods with minimal interaction from the user, representing their natural sleeping trends for more accurate health and sleep disorder diagnosis.

Angiotensin Receptor-Neprilysin Inhibitor Is Associated With Improved Cardiac Autonomic Function in Heart Failure.

BACKGROUND: Heart failure with reduced ejection fraction is associated with potentially deleterious imbalance of the cardiac autonomic nervous system. Sacubitril/valsartan (angiotensin receptor-neprilysin inhibitor [ARNI]) reduces cardiovascular mortality and hospitalization for heart failure with reduced ejection fraction. Whether ARNI affects the cardiac autonomic nervous system has not been studied. METHODS AND RESULTS: This investigator-initiated, prospective, single-center cohort study compared heart rate (HR) variability, HR, deceleration capacity, and periodic repolarization dynamics as noninvasive measures of the cardiac autonomic nervous system before and after initiation of ARNI therapy. Patients underwent standardized 12-lead Holter-ECG, echocardiography and laboratory testing before and 3 months after start of therapy. End points were changes in HR variability (SD of normal-to-normal intervals, mean square of differences between consecutive R-R intervals), HR, deceleration capacity, and periodic repolarization dynamics as well as ventricular function and NT-proBNP (N-terminal pro-B-type natriuretic peptide). Of 63 patients with heart failure with reduced ejection fraction enrolled, 48 (76.2%) patients were still on ARNI at follow-up. SD of normal-to-normal intervals increased from 25 to 36 milliseconds (P<0.001), mean square of differences between consecutive R-R intervals increased from 12 to 19 milliseconds (P<0.001), HR decreased from 73±9 bpm to 67±4 bpm, (P<0.001), and deceleration capacity increased from 2.1 to 4.4 milliseconds (P<0.001). A trend for periodic repolarization dynamics reduction was observed (5.6 deg2 versus 4.7 deg2, P=0.09). Autonomic changes were accompanied by increased left ventricular ejection fraction (29±6% versus 40±8%, P<0.001) and reduced NT-proBNP (3548 versus 685 ng/L, P<0.001). Correlation analysis showed a significant relationship between volume-unloading (as evidenced by NT-proBNP reduction) and autonomic improvement. CONCLUSIONS: Three months of ARNI therapy resulted in a significant increase in cardiac parasympathetic tone. The improvement in autonomic properties may be mediated by "volume unloading" and likely contributes to the beneficial effects of ARNI in heart failure with reduced ejection fraction. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique Identifier: NCT04587947.

Variant patterns of electrical activation and recovery in normal human hearts revealed by noninvasive electrocardiographic imaging.

AIMS: Although electrical activity of the normal human heart is well characterized by the electrocardiogram, detailed insights into within-subject and between-subject variations of ventricular activation and recovery by noninvasive electroanatomic mapping are lacking. We characterized human epicardial activation and recovery within and between normal subjects using non-invasive electrocardiographic imaging (ECGI) as a basis to better understand pathology. METHODS AND RESULTS: Epicardial activation and recovery were assessed by ECGI in 22 normal subjects, 4 subjects with bundle branch block (BBB) and 4 with long-QT syndrome (LQTS). We compared characteristics between the ventricles [left ventricle (LV) and right ventricle (RV)], sexes, and age groups (<50/≥50years). Pearson's correlation coefficient (CC) was used for within-subject and between-subject comparisons. Age of normal subjects averaged 49 ± 14 years, 6/22 were male, and no structural/electrical heart disease was present. The average activation time was longer in LV than in RV, but not different by sex or age. Electrical recovery was similar for the ventricles, but started earlier and was on average shorter in males. Median CCs of between-subject comparisons of the ECG signals, activation, and recovery patterns were 0.61, 0.32, and 0.19, respectively. Within-subject beat-to-beat comparisons yielded higher CCs (0.98, 0.89, and 0.82, respectively). Activation and/or recovery patterns of patients with BBB or LQTS contrasted significantly with those found in the normal population. CONCLUSION: Activation and recovery patterns vary profoundly between normal subjects, but are stable individually beat to beat, with a male preponderance to shorter recovery. Individual characterization by ECGI at baseline serves as reference to better understand the emergence, progression, and treatment of electrical heart disease.

Integrating dynamic psychophysiological indices across time and contexts: Elucidating mechanisms, risk markers, and intervention targets.

Why should researchers measure psychophysiological processes repeatedly over time? The study of psychophysiology inherently involves sampling biological processes as they manifest over time. The most common approach is to use a brief sample to make conclusions about how individuals or groups differ. Although these types of between-subject comparisons have utility for understanding individual and group differences, many of the important conceptual questions in the field involve processes that are dynamic, varying within individuals over time. Using examples from the literature on affect regulation, this conceptual review contrasts three types of study designs: the classic single-observation design and the aggregated and temporally linked repeated observation designs, which have great promise for measuring variables that fluctuate dynamically over time. Importantly, these designs can be integrated to elucidate research questions about risk (when and for whom will the likelihood of an unwanted outcome occurring increase?), mechanisms (how and why does a change in psychophysiology contribute to a change in another process of interest?), and interventions (how and when should interventions take place to modify an outcome?). Researchers are encouraged to implement intensive sampling in their research, which can be conducted in traditional laboratory settings (e.g., fMRI, event-related brain potentials, and heart rate variability) and in ecologically valid contexts in everyday life using ambulatory assessment.

Measuring and correcting staff variability in large-scale OSCEs.

CONTEXT: Objective Structured Clinical Examinations (OSCEs) are an increasingly popular evaluation modality for medical students. While the face-to-face interaction allows for more in-depth assessment, it may cause standardization problems. Methods to quantify, limit or adjust for examiner effects are needed. METHODS: Data originated from 3 OSCEs undergone by 900-student classes of 5th- and 6th-year medical students at Université Paris Cité in the 2022-2023 academic year. Sessions had five stations each, and one of the three sessions was scored by consensus by two raters (rather than one). We report OSCEs' longitudinal consistency for one of the classes and staff-related and student variability by session. We also propose a statistical method to adjust for inter-rater variability by deriving a statistical random student effect that accounts for staff-related and station random effects. RESULTS: From the four sessions, a total of 16,910 station scores were collected from 2615 student sessions, with two of the sessions undergone by the same students, and 36, 36, 35 and 20 distinct staff teams in each station for each session. Scores had staff-related heterogeneity (p<10-15), with staff-level standard errors approximately doubled compared to chance. With mixed models, staff-related heterogeneity explained respectively 11.4%, 11.6%, and 4.7% of station score variance (95% confidence intervals, 9.5-13.8, 9.7-14.1, and 3.9-5.8, respectively) with 1, 1 and 2 raters, suggesting a moderating effect of consensus grading. Student random effects explained a small proportion of variance, respectively 8.8%, 11.3%, and 9.6% (8.0-9.7, 10.3-12.4, and 8.7-10.5), and this low amount of signal resulted in student rankings being no more consistent over time with this metric, rather than with average scores (p=0.45). CONCLUSION: Staff variability impacts OSCE scores as much as student variability, and the former can be reduced with dual assessment or adjusted for with mixed models. Both are small compared to unmeasured sources of variability, making them difficult to capture consistently.

Current landscape and comprehensive management of glycemic variability in diabetic retinopathy.

Diabetic retinopathy (DR), a well-known microvascular complication of diabetes mellitus, remains the main cause of vision loss in working-age adults worldwide. Up to now, there is a shortage of information in the study regarding the contributing factors of DR in diabetes. Accumulating evidence has identified glycemic variability (GV), referred to fluctuations of blood glucose levels, as a risk factor for diabetes-related complications. Recent reports demonstrate that GV plays an important role in accounting for the susceptibility to DR development. However, its exact role in the pathogenesis of DR is still not fully understood. In this review, we highlight the current landscape and relevant mechanisms of GV in DR, as well as address the mechanism-based therapeutic strategies, aiming at better improving the quality of DR management in clinical practice.

The Clinical Significance and Application of Heart Rate Variability in Dialysis Patients: A Narrative Review.

Autonomic nervous system (ANS) dysfunction is prevalent in end-stage kidney disease (ESKD) patients, carrying significant risks for morbidity and mortality. Heart rate variability (HRV) is a simple and non-invasive method to evaluate ANS functions and predict prognoses in specific patient populations. Since there is a lack of a clear understanding of the clinical significance of HRV in predicting prognoses in ESKD patients, an updated review on this topic is urgently warranted. The clinical significance of HRV in dialysis patients includes its associations with metabolic syndrome, nutritional status, intradialytic hypotension, vascular access failure, major adverse cardiovascular events, and mortality. These findings underscore the essential role of the autonomic reserve, which might denote the elevation of ANS activity as a response to external stimulus. Patients with a higher level of sympathetic activity at the resting stage, but who are unable to adequately elevate their sympathetic activity under stress might be susceptible to a worse outcome in critical circumstances. Further applications of HRV include HRV biofeedback, risk classification, and real-time HRV monitoring. Overall, HRV is an optimal tool for predicting prognoses in dialysis patients. Further study is encouraged in order to gain a clearer understanding of the clinical significance and application of HRV, and thereby enhance the care of ESKD patients.

Reliability of an "At-Home" Method for Monitoring Resting and Reactive Autonomic Nervous System Activity in Children: A Pilot Study.

BACKGROUND: Heart rate variability (HRV), an index of the functional status of the autonomic nervous system (ANS), provides an opportunity for early detection of ANS dysfunction. Lower resting, vagally related HRV parameters are associated with increased risk of physical and mental illness. External factors influencing the ANS, such as the testing environment, may impact the interpretation of HRV. This study's main aim was to determine the reliability of HRV resting and reactivity tests performed at home with children aged 4-9 years. METHODS: Fourteen healthy children (female n = 8) aged 6.8 ± 1.5 years participated. Two HRV tests were performed at home via online supervision 7 days apart using a Polar H10 heart rate monitor. The absolute and relative reliability of the pre-exercise resting (5 min) and sub-maximal exercise step test recovery (4 × 30 s segments) HRV time and frequency domains were calculated. RESULTS: The Pearson correlation coefficients for day 1 versus day 7 for the vagal activity HRV domains (RMSSD log) at rest and in the first 30 s and 30-60 s of recovery indicated good-to-excellent relative reliability (r > 0.8, p < 0.01). Absolute reliability was moderate for the resting RMSSD log, with a coefficient of variation (CV) of 5.2% (90% CI: 3.9, 7.8%), high for the first 30 s of standing recovery, with a CV of 10.7% (90% CI: 8.2, 15.7%), and moderate for 30-60 s of recovery, with a CV of 8.7% (90% CI: 6.6, 12.9%). CONCLUSIONS: The findings of this pilot study indicate that the resting and exercise recovery HRV measures of vagal activity can be measured reliably at home in children. This represents a novel "at-home" protocol for monitoring ANS health and development in children.

Protocol and preregistration for the CODEC project: measuring, modelling and mechanistically understanding the nature of cognitive variability in early childhood.

BACKGROUND: Children's cognitive performance fluctuates across multiple timescales. However, fluctuations have often been neglected in favour of research into average cognitive performance, limiting the unique insights into cognitive abilities and development that cognitive variability may afford. Preliminary evidence suggests that greater variability is associated with increased symptoms of neurodevelopmental disorders, and differences in behavioural and neural functioning. The relative dearth of empirical work on variability, historically limited due to a lack of suitable data and quantitative methodology, has left crucial questions unanswered, which the CODEC (COgnitive Dynamics in Early Childhood) study aims to address. METHOD: The CODEC cohort is an accelerated 3-year longitudinal study which encompasses 600 7-to-10-year-old children. Each year includes a 'burst' week (3 times per day, 5 days per week) of cognitive measurements on five cognitive domains (reasoning, working memory, processing speed, vocabulary, exploration), conducted both in classrooms and at home through experience sampling assessments. We also measure academic outcomes and external factors hypothesised to predict cognitive variability, including sleep, mood, motivation and background noise. A subset of 200 children (CODEC-MRI) are invited for two deep phenotyping sessions (in year 1 and year 3 of the study), including structural and functional magnetic resonance imaging, eye-tracking, parental measurements and questionnaire-based demographic and psychosocial measures. We will quantify developmental differences and changes in variability using Dynamic Structural Equation Modelling, allowing us to simultaneously capture variability and the multilevel structure of trials nested in sessions, days, children and classrooms. DISCUSSION: CODEC's unique design allows us to measure variability across a range of different cognitive domains, ages, and temporal resolutions. The deep-phenotyping arm allows us to test hypotheses concerning variability, including the role of mind wandering, strategy exploration, mood, sleep, and brain structure. Due to CODEC's longitudinal nature, we are able to quantify which measures of variability at baseline predict long-term outcomes. In summary, the CODEC study is a unique longitudinal study combining experience sampling, an accelerated longitudinal 'burst' design, deep phenotyping, and cutting-edge statistical methodologies to better understand the nature, causes, and consequences of cognitive variability in children. TRIAL REGISTRATION: ClinicalTrials.gov - NCT06330090.

Agreement between Ultra-Short-Term and Standard Heart Rate Variability Analysis in Resting and Post-Exercise Conditions.

BACKGROUND: Short-term (5 min) heart rate variability (HRV) analysis is widely used in assessing autonomic nervous system activity during exercise. While shortening the HRV measurement duration can help improve its application efficiency, its accuracy needs to be verified. This study investigated the agreement between ultra-short-term (UST) HRV (3 or 4 min) and standard 5 min HRV and explored the optimal recording duration under resting and post-exercise conditions. METHODS: Fourteen participants exercised on a cycle ergometer at 60% of their maximum peak power. Data were collected during the rest condition (Pre-E) and three post-exercise conditions (Post-E1, Post-E2, and Post-E3), with indicators of the standard deviation (SDNN) of the ultra-short and short-term RR intervals and the root mean square (RMSSD) of the continuous difference between RR intervals. Repeated measures ANOVA, Cohen's d statistic, Bland-Altman analysis, and interclass correlation coefficients (ICC) assessed the agreement between UST-HRV and ST-HRV. RESULTS: The consistency results of SDNN and RMSSD in resting and post-exercise were different. At the Pre-E, Post-E2, and Post-E3 phases, no statistical differences for SDNN and RMSSD were observed, with ICCs surpassing 0.9, indicating a high level of agreement. However, at Post-E2, there was a significant difference between 3 min RMSSD and 5 min RMSSD (p < 0.05), as well as between 3 min SDNN, 4 min SDNN, and 5 min SDNN (p < 0.05). Furthermore, the limits of agreement were observed to decrease as the time duration increased in Bland-Altman plots. CONCLUSIONS: UST-HRV analysis is a reliable substitute for standard 5 min HRV assessment, particularly during resting conditions. For post-exercise measurements, assessing the appropriateness of a 3- or 4 min duration based on the exercise's length is recommended to ensure accuracy and reliability.

Inter- and Intra-Observer Variability of the AMADEUS Tool for Osteochondral Lesions of the Talus.

BACKGROUND: Managing osteochondral cartilage defects (OCDs) of the talus is a common daily challenge in orthopaedics as they predispose patients to further cartilage damage and progression to osteoarthritis. Therefore, the implementation of a reliable tool to quantify the amount of cartilage damage that is present is of the essence. METHODS: We retrospectively identified 15 adult patients diagnosed with uncontained OCDs of the talus measuring <150 mm2, which were treated arthroscopically with bone marrow stimulation. Five independent assessors evaluated the pre-operative MRI scans with the AMADEUS scoring system (i.e., MR-based pre-operative assessment system) and the intra-/inter-observer variability was then calculated by means of the intraclass correlation coefficients (ICC) and Kappa (κ) statistics, respectively. In addition, the correlation between the mean AMADEUS scores and pre-operative self-reported outcomes as measured by the Manchester-Oxford foot questionnaire (MOxFQ) was assessed. RESULTS: The mean ICC and the κ statistic were 0.82 (95% CI [0.71, 0.94]) and 0.42 (95% CI [0.25, 0.59]). The Pearson correlation coefficient was found to be r = -0.618 (p = 0.014). CONCLUSIONS: The AMADEUS tool, which was originally designed to quantify knee osteochondral defect severity prior to cartilage repair surgery, demonstrated good reliability and moderate inter-observer variability for small OCDs of the talar shoulder. Given the strong negative correlation between the AMADEUS tool and pre-operative clinical scores, this tool could be implemented in clinical practise to reliably quantify the extent of the osteochondral defects of the talus.

Heart Rate Variability Biofeedback Efficacy on Fatigue and Energy Levels in Fibromyalgia: A Secondary Analysis of RCT NCT0412183.

Background: Fibromyalgia syndrome (FMs) is a chronic condition characterized by widespread musculoskeletal pain and a range of complex symptoms, with chronic fatigue being a central feature significantly impacting daily life. The aim of this study was to analyze the secondary outcomes, specifically those related to perceived energy and fatigue symptoms in a randomized controlled trial (RCT) assessing the efficacy of heart rate variability biofeedback (HRV-BF) as an adjunctive treatment for FMs. Methods: Sixty-four FMs patients were randomly assigned to either receive 10 HRV-BF training sessions alongside standard pharmacological therapy (experimental group) or standard therapy alone for 10 weeks (control group). For this secondary analysis, potential improvements in specific items were evaluated regarding perceived energy (Item 10 of the Short-Form Health Survey), the ability to walk and climb stairs (Item 7 and Item 11 of the Fibromyalgia Impact Questionnaire, respectively), and the impact of pain on movement ability (Item 17 of the Bodily and Emotional Perception of Pain). Results: The experimental group demonstrated an improvement in the perception of energy, the ability to walk, and the impact of pain on movement ability. However, the same improvement was not observed in the ability to climb stairs. Conclusions: Fatigue assessment has emerged as a crucial factor for evaluating treatment efficacy in FMs and related conditions linked to altered energy levels, such as bipolar depression, and can offer valuable insights for precisely guiding HRV-BF treatments. ClinicalTrials.gov with code: NCT04121832.

COVID-19-Associated Multisystem Inflammatory Syndrome in Children and Cardiovascular Autonomic Control: A Prospective Cohort Study Nine Months after SARS-CoV-2 Infection.

Background: Multisystem Inflammatory Syndrome in Children (MIS-C) has emerged as a severe pediatric complication during the SARS-CoV-2 pandemic, with potential long-term cardiovascular repercussions. We hypothesized that heart rate and blood pressure control at rest and during postural maneuvers in MIS-C patients, months after the remission of the inflammatory syndrome, may reveal long-term autonomic dysfunctions. Methods: We assessed 17 MIS-C patients (13 males; 11.9 ± 2.6 years, m ± SD) 9 months after acute infection and 18 age- (12.5 ± 2.1 years) and sex- (13 males) matched controls. Heart rate and blood pressure variability, baroreflex function, and hemodynamic parameters were analyzed in supine and standing postures. Results: MIS-C patients exhibited reduced heart rate variability, particularly in parasympathetic parameters during standing (pNN50+: 6.1 ± 6.4% in controls, 2.5 ± 3.9% in MIS-C; RMSSD: 34 ± 19 ms in controls, 21 ± 14 ms in MIS-C, p < 0.05), with no interaction between case and posture. Blood pressure variability and baroreflex sensitivity did not differ between groups except for the high-frequency power in systolic blood pressure (3.3 ± 1.2 mmHg2 in controls, 1.8 ± 1.2 mmHg2 in MIS-C, p < 0.05). The MIS-C group also showed lower diastolic pressure-time indices (DPTI) and systolic pressure-time indices (SPTI), particularly in standing (DPTI: 36.2 ± 9.4 mmHg·s in controls, 29.4 ± 6.2 mmHg·s in MIS-C; SPTI: 26.5 ± 4.3 mmHg·s in controls, 23.9 ± 2.4 mmHg·s in MIS-C, p < 0.05). Conclusions: Altered cardiovascular autonomic control may persist in MIS-C patients with, however, compensatory mechanisms that may help maintain cardiovascular homeostasis during light autonomic challenges, such as postural maneuvers. These results highlight the importance of assessing long-term cardiovascular autonomic control in children with MIS-C to possibly identify residual cardiovascular risks and inform targeted interventions and rehabilitation protocols.

Age as an Effect Modifier of the Effects of Transcutaneous Auricular Vagus Nerve Stimulation (taVNS) on Heart Rate Variability in Healthy Subjects.

Background: Evidence suggests that vagus nerve stimulation can modulate heart rate variability (HRV). However, there is a lack of mechanistic studies in healthy subjects assessing the effects of bilateral transcutaneous auricular vagus nerve stimulation (taVNS) on HRV. Our study aims to investigate how taVNS can influence the HRV response, including the influence of demographic variables in this response. Methods: Therefore, we conducted a randomized controlled study with 44 subjects, 22 allocated to active and 22 to sham taVNS. Results: Our results showed a significant difference between groups in the high-frequency (HF) metric. Active taVNS increased the HF metric significantly as compared to sham taVNS. Also, we found that age was a significant effect modifier of the relationship between taVNS and HF-HRV, as a larger increase in HF-HRV was seen in the older subjects. Importantly, there was a decrease in HF-HRV in the sham group. Conclusions: These findings suggest that younger subjects can adapt and maintain a constant level of HF-HRV regardless of the type of stimulation, but in the older subjects, only the active taVNS recipients were able to maintain and increase their HF-HRV. These results are important because they indicate that taVNS can enhance physiological regulation processes in response to external events.

Alleviating premenstrual symptoms with smartphone-based heart rate variability biofeedback training: a pilot study.

Introduction: Heart rate variability biofeedback (HRVB) is a well-studied intervention known for its positive effects on emotional, cognitive, and physiological well-being, including relief from depressive symptoms. However, its practical use is hampered by high costs and a lack of trained professionals. Smartphone-based HRVB, which eliminates the need for external devices, offers a promising alternative, albeit with limited research. Additionally, premenstrual symptoms are highly prevalent among menstruating individuals, and there is a need for low-cost, accessible interventions with minimal side effects. With this pilot study, we aim to test, for the first time, the influence of smartphone-based HRVB on depressive and premenstrual symptoms, as well as anxiety/stress symptoms and attentional control. Methods: Twenty-seven participants with above-average premenstrual or depressive symptoms underwent a 4-week photoplethysmography smartphone-based HRVB intervention using a waitlist-control design. Laboratory sessions were conducted before and after the intervention, spaced exactly 4 weeks apart. Assessments included resting vagally mediated heart rate variability (vmHRV), attentional control via the revised attention network test (ANT-R), depressive symptoms assessed with the BDI-II questionnaire, and stress/anxiety symptoms measured using the DASS questionnaire. Premenstrual symptomatology was recorded through the PAF questionnaire if applicable. Data analysis employed linear mixed models. Results: We observed improvements in premenstrual, depressive, and anxiety/stress symptoms, as well as the Executive Functioning Score of the ANT-R during the intervention period but not during the waitlist phase. However, we did not find significant changes in vmHRV or the Orienting Score of the ANT-R. Discussion: These findings are promising, both in terms of the effectiveness of smartphone-based HRVB and its potential to alleviate premenstrual symptoms. Nevertheless, to provide a solid recommendation regarding the use of HRVB for improving premenstrual symptoms, further research with a larger sample size is needed to replicate these effects.