Vungarala, Soumya

Abstract Introduction Detecting and estimating blood volume loss are important for the diagnosis and management of life-threatening hemorrhage. There is a direct relationship between percent blood volume loss (BVL%) and falling in stroke volume (SV); furthermore, there is a direct relationship between diminishing SV and the corrected flow time of the carotid artery (ccFT). Therefore, we hypothesized that change in ccFT (ccFTΔ) would directly relate with BVL% in a phlebotomy paradigm. Materials and Methods A prospective, convenience sample of healthy volunteers was studied. Volunteers underwent blood donation protocol in a physiology lab. A wireless, wearable Doppler ultrasound system monitored ccFT during blood donation. Traditional vital signs were also measured throughout. The relationship between traditional vital signs as well as ccFTΔ were compared to BVL% using 2 mixed linear regression models. Results Data from 20 subjects and blood donations comprising 46,123 cardiac cycles are included. On average 413.5 ± 39 mL of blood were drawn representing 8.6 ± 1.6% BVL%. There was a significant and strong linear relationship between BVL% and ccFTΔ during blood draw with the regression slope demonstrating that for every 1 ms reduction in ccFT there was a 0.4% reduction in blood volume. Conclusions In healthy subjects and when blood loss is the sole mechanism for falling SV, we estimate that for every 1 ms reduction in ccFT, there is an approximate 0.4 BVL%. Validation of these results in patients with traumatic hemorrhage is underway.

Abstract Aims Monitoring pulmonary congestion in chronic heart failure (HF) reduces decompensation and hospitalization, but conventional methods such as weight and symptom tracking are often unreliable. As fluid accumulation affects the lungs and vocal tract, subtle voice alterations may serve as a non-invasive signal for early detection of worsening HF. Methods and results The Voice Analysis for Monitoring Patients with HF trial (VAMP-HF, NCT06566911) prospectively enrolled 104 patients hospitalized with acute decompensated HF (ADHF) across two academic centres in the USA and Germany. Daily voice recordings were collected from admission to discharge, with breathing features extracted from speech and acoustic features from sustained vowels. A machine-learning model was trained to classify recordings as admission-phase vs. discharge-phase using leave-one-patient-out. Patients with clinical deterioration, insufficient audio quality, or short length of stay were excluded. Seventy-nine patients were included in the final dataset. The model classified admission and discharge with an F1-score of 0.83 (95% CI: 0.77–0.90; AUC = 0.90). In patients with higher audio volume (N = 54), performance reached 0.89 (95% CI: 0.82–0.94; AUC = 0.91). When applied to intermediate hospitalization days, model-predicted scores showed progressive increases from admission towards discharge. Performance remained robust irrespective of significant weight loss during hospitalization. Conclusion In this pilot study, structured voice and breathing analysis discriminated hospitalization phase from admission through discharge in patients with ADHF. This non-invasive approach captured progressive changes during the hospital course and warrants further investigation with concurrent objective congestion markers to establish physiological specificity.

Abstract Background Effective fluid status monitoring in chronic heart failure (HF) patients is critical for preventing decompensation and hospitalization. Conventional methods, such as daily weight tracking, often fail to detect early, pre-symptomatic fluid retention. As fluid accumulation affects the vocal tract, subtle voice alterations can serve as a biomarker for congestion. In this work, we present preliminary results from the first 55 patients enrolled at the German Heart Center at Charité (DHZC) within the multicenter VAMP-HF study, assessing the performance of AI-driven voice analysis for non-invasive fluid status monitoring. Methods The study design incorporated a run-in period for the first 20 patients to refine the recording setup and ensure sufficient audio quality for subsequent data collection. An additional three patients were excluded due to clinical deterioration or in-hospital mortality. Participants provided daily voice recordings (sustained vowels, standardized text, and varying sentences) alongside clinical measurements such as NT-proBNP, daily weight, and left-ventricular ejection fraction. A speaker-independent XGBoost classifier was trained on acoustic features to classify patient states (admission, discharge, and intermediate states). Performance was evaluated using a nested leave-one-patient-out approach, ensuring strict training and validation data separation. Results The final analysis included 32 patients (mean age 76.12 ± 12.65 years). At admission, patients had a mean NT-proBNP of 9575.55 ± 8202.87 pg/mL and a mean weight loss of 4.2 ± 4.29 kg until discharge. The trained machine learning model achieved an F1-score of 0.75 (Fig. 1b), demonstrating its ability to distinguish between admission and discharge states, based solely on voice samples. An exemplary prediction for a test patient is shown in Fig. 1a. Notably, the model was also able to detect subtle vocal changes even in patients with <2 kg weight loss. Conclusion Our findings suggest that AI-driven voice analysis is a feasible biomarker for detecting heart failure decompensation. While not directly compared with conventional early warning thresholds, these results support the hypothesis that voice-based biomarkers may serve as an early indicator of fluid congestion. Further validation in larger cohorts is needed to confirm these findings and enable integration into remote HF monitoring programs.

Background: Exhaled volatile organic compounds (VOCs) can provide insight into various physiological and metabolic processes. Aim: The purpose of this study was to determine if exhaled VOCs would differ across disease severity in heart failure (HF) patients. Methods: We recruited 62 individuals who were classified as healthy control (CTL), admissions with fluid overload (DHF), NYHA class I-II or NYHA class II-III. Breath samples were collected using the ReCIVA Breath Sampler (Owlstone Medical Ltd) and analyzed using mass spectrometry and gas chromatography. Typical clinical characteristics were documented at the time of exhaled breath collection. Results: Data were obtained on 16 CTL, 21 DHF, 15 NYHA I-II and 10 NYHA II-III (characteristics shown in Table). For the HF groups, DHF, NYHA I-II and NYHA II-III, the %HPEFF were 32, 63 and 63% respectively. Regarding exhaled VOCs, we observed a stepwise increase in VOCs potentially linked to lipid peroxidation or fatty acid metabolism, such as pent-3-en-2-one, 2-pentanone, and 4-heptanone, as disease severity worsened. A similar trend was seen for sulphur containing compounds (methyl propyl sulfide, allyl methyl sulfide and 1(methyl thiol)-1 propene)), potentially providing insight into impaired hepatic or renal clearance in more advanced HF. The level of methyl pyruvate on breath also rose with increasing disease severity, which may reflect altered energy metabolism. Finally, gut microbiome-related VOCs (acetoin, 2,3-butanediol, and butyric anhydride) increased across severity groups, potentially reflecting dysbiosis in advanced disease. Conclusions: In a small pilot study aiming to identify potential exhaled breath biomarkers in HF, we observed significant differences in VOCs across disease severity. These compounds have been linked to lipid peroxidation, energy metabolism, liver and kidney function as well as microbial fermentation and short-chain fatty acid metabolism. Collectively, these data demonstrate the ability of breath omics to potentially stratify disease severity and provide additional biological insights into HF pathophysiology. Larger studies are needed to determine whether a breath biomarker panel could be established to quantify disease severity and predict decompensation risk in HF.

Abstract Background Obstructive sleep apnea (OSA) is a risk factor for hypertension and some evidence suggests this risk may not be mitigated with positive airway pressure. Low-intensity statin therapy can modestly reduce blood pressure (BP). In this exploratory analysis, we examined if six months of high-intensity statin therapy could lower resting or ambulatory BP in patients with OSA. Methods 39 patients with OSA (13F, age = 49 ± 9yrs, body mass index = 32.9 ± 4.2kg/m2, apnea-hypopnea index = 22.2 ± 12.4 events/hour) were randomized to high-intensity atorvastatin or placebo. BP was assessed using seated, “office” measurements and in 20-minute intervals over 24 consecutive hours at three timepoints (baseline, three- and six-months post-randomization). Participants maintained a diary denoting sleep and wake times for analysis. Changes (Δ) in BP from baseline were assessed and adjusted for adherence to participants’ intervention (atorvastatin or placebo) as well as to their treatment for OSA (yes or no). Results There were no between-group differences in baseline BP variables (P = .09-.96). At three months, the changes in resting (P = .74-.87), 24 hour mean (P = .54-.96), daytime (P = .70-.96), nor nighttime (P = .74-.96) BP did not differ between groups. Similarly, the changes in resting (P = .23-.92), 24 hour mean (P = .51-.82), daytime (P = .17-.78), and nighttime (P = .51-1.00) BP did not differ between groups following six months of their respective intervention. Conclusions Our data suggest that high-intensity atorvastatin does not lower resting or ambulatory BP in patients with OSA relative to a placebo. Thus, it does not appear that atorvastatin is a viable adjunct intervention for BP reduction in patients with OSA. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT03308578.

Abstract Rationale: Heart failure (HF) is often characterized by elevated left ventricular filling pressures (LVFP) and pulmonary congestion. However, LVFP may not always predict congestion. Pulmonary congestion can be quantified by computed tomography (CT) imaging. We hypothesized that extravascular lung water quantified by CT may differ in HF groups such as HF with preserved ejection fraction (HFpEF) vs HF with reduced ejection fraction (HFrEF), inpatients with acute decompensated heart failure (ADHF) vs stable and this would be related to echocardiography (echo) derived estimates of LVFP. Methods: We enrolled and studied 83 patients with HF who were either admitted or had a clinic visit at Mayo Clinic, Rochester, MN from May 2018 through March 2019. All subjects underwent comprehensive echo and supine thoracic CT scans. CT lung fluid was quantified and reported as proportion (%) of total lung volume. CT attenuation in lung tissue was also measured. LVFP was evaluated according to standardized echo diagnostic algorithms. Patients were stratified based on clinical diagnosis of HF as inpatients with HFpEF (n=26, 75.6±8.5yrs, M=50%, BMI=36.2±8.9kg/m2) inpatients with HFrEF (n=33, 75.6±14yrs, M=79%, BMI=31.1±9.1kg/m2), inpatients with ADHF (n=14, 72.6±14.5yrs, m=64.2%, BMI= 32.2±7.6Kg/m2) and stable outpatient HF controls (n=10, 65±13 yrs, m=90%, BMI= 29.5±5.2Kg/m2). All four groups were compared using one-way ANOVA followed by a post-hoc analysis. A correlation between lung fluid % and LVFP was performed using Spearman's correlation test. Results: When HF groups were compared according to CT % lung fluid, significant differences were found between HF groups (p=0.004). Post-hoc analysis revealed a significant difference in % lung fluid as HFrEF group had higher mean value in % lung fluid compared to HF control group (p=0.004). Similarly, ADHF group had higher mean % lung fluid compared to HF control group (p= 0.007). However, we found no correlation between LVFP and % lung fluid. The rightward shift in CT attenuation for HFpEF, HFrEF, and ADHF subjects, as displayed in figure 1, suggests greater levels of % lung water in these subjects compared to controls. Conclusion: These data suggest that CT measures of lung water differ in subgroups of HF patients and may not correlate with LVFP.

Patients with obstructive sleep apnea (OSA) have increased risk for cardiovascular diseases. Data from the Atherosclerosis Risk in the Communities and Sleep Heart Health Study suggest that OSA is more deleterious to females versus males, although mechanistic data are lacking. Estimates of central (aortic) blood pressure (BP) are superior in predicting future cardiovascular events than traditional brachial BP measurements. While patients with OSA have altered central hemodynamics (e.g., higher aortic pulse wave velocity; PWV), potential sex differences are unexplored. We tested the hypothesis that females with OSA (n=7, 50±3yrs, 35.1±1.9kg/m2, 22.2±7.6 events/hr) have worse central hemodynamics than males with OSA (n=9, 47±3yrs, 35.0±1.4kg/m2, 31.7±6.2 events/hr). Data collection consisted of an overnight sleep study (polysomnography) to identify the presence, and characterize the severity, of OSA via the apnea-hypopnea index (AHI). Then, duplicate measures of central (aortic) and peripheral (brachial) BP, as well as central artery stiffness (PWV) and wave reflection (AIx), were made in the morning after ≥15min of quiet, supine rest. Additional hemodynamic measurements were made if data differed by ≥2% (AIx) or ≥0.5m/s (PWV). Data that met these criteria were averaged and used for analysis. Comparisons were made using two-tailed, independent samples t-tests or nonparametric Mann-Whitney Rank Sum tests, as indicated. No differences were observed in age (p=0.44), body mass index (p=0.96), nor AHI (p=1.00) between sexes. Similarly, no sex differences were observed in brachial systolic (female vs. male: 129±7 vs. 134±8mmHg, p=0.83), diastolic (77±5 vs. 85±4mmHg, p=0.26), or mean BP (96±6 vs. 101±5mmHg, p=0.45). Similarly, central systolic (122±6 vs. 125±7mmHg, p=0.96), diastolic (78±5 vs. 86±4mmHg, p=0.25), and augmentation (21±2 vs. 15±2mmHg, p=0.07) BP did not differ between sexes. Resting heart rate was also comparable between groups (67±3 vs. 65±2bpm, p=0.64). However, AIx (AIx; 42±3 vs. 35±4%) and AIx normalized to a heart rate of 75bpm (42±3 vs. 30±3%) were higher in females with OSA relative to males with OSA (p<0.05 for both). Interestingly, the forward (30±3 vs. 28±2mmHg, p=0.63) and reflected (20±2 vs. 18±2mmHg, p=0.44) pulse heights, as well as PWV (7.3±0.6 vs. 7.4±0.6m/s, p=0.85), were similar between groups. Our data indicate that despite a trend towards higher BP in males with OSA (~5mmHg) that may be clinically, though not statistically different, females with OSA have a higher AIx. As AIx is positively associated with left ventricular hypertrophy, these data also suggest that altered central (aortic) hemodynamics may contribute to the sex differences in cardiovascular risk with OSA. This work was supported by the National Institutes of Health T32-HL007111 and U54AG044170 (JMB), HL065176 (PS and VKS), and HL134885 (VKS). This is the full abstract presented at the American Physiology Summit 2024 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Hypertension is commonly observed with obstructive sleep apnea (OSA), partly due to dysregulation of sympathetic activity. As OSA is considered male-dominant, potential sex differences in the sympathetic regulation of BP have yet to be explored. Hemodynamic responses to an orthostatic challenge have implications for cardiovascular risk and are sympathetically-modulated. Therefore, we tested the hypothesis that females with OSA have differential BP and HR responses to orthostasis relative to males with OSA. 160 individuals not taking antihypertensive medications completed an overnight polysomnography to identify OSA (apnea-hypopnea index ≥5 events/hr). Orthostatic responses were quantified as the changes (Δ) in BP and HR (assessed via brachial cuff) from rest (10min supine) to 60sec post-standing. Females with (n=17, 42±14yrs, 30.7±6.0kg/m2) and without (n=43, 39±12yrs, 27.6±5.7kg/m2) OSA were compared to males with (n=60, 45±11yrs, 31.4±3.8kg/m2) and without (n=40, 39±13yrs, 27.4±3.1kg/m2) OSA using a one-way ANOVA. There were no between-group differences in age (p>0.05 for post-hoc comparisons) and BMI was lower in both females, and males, without OSA relative to males with OSA (p<0.05 for both). ΔSBP did not differ between females with (1±8mmHg) and without (2±8mmHg) OSA nor between males with (4±8mmHg) and without OSA (5±12mmHg, ANOVA p=0.37). Females with OSA had a blunted ΔDBP relative to females without OSA (5±7 vs. 10±6mmHg, p<0.05), whereas males with and without OSA demonstrated similar responses (9±8 vs. 10±6mmHg, p=0.95). ΔHR did not differ between females with (8±8beats/min) and without OSA (9±11beats/min) nor between males with (13±10beats/min) and without OSA (12±10beats/min, ANOVA p=0.06). ΔDBP was not associated with the apnea-hypopnea index (Spearman's r=-0.19, p=0.47; Spearman’s r=0.23, p=0.08) nor nadir SpO2 (Spearman's r=0.27, p=0.29; Spearman’s r=0.06, p=0.64) in females or males with OSA. These data suggest that OSA influences the DBP response to orthostasis in females to a greater extent than males. As DBP is associated with sympathetic activation, this finding could indicate greater sympathetic dysregulation in females, relative to males, with OSA. This work was supported by the National Institutes of Health T32-HL007111 (JMB), HL134808 (NC), HL065176 (PS and VKS), and HL134885 (VKS). This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.

Introduction: Growing evidence suggests that aberrant sleep architecture is linked to heightened risk of cardiovascular disease independently of sleep apnea. Rapid Eye Movement (REM) sleep is characterized by increased sympathetic activity and blood pressure (BP) compared to non-REM sleep stages. However, whether REM sleep is associated with BP across the 24 hours has not been investigated. Hypothesis: We hypothesized that increased REM sleep would be associated with higher ambulatory BP. Methods: We recruited 137 individuals (58% men, aged 39±14 years, office systolic/diastolic BP [SBP/DBP] 125±14/77±11 mmHg) who completed overnight polysomnography followed by 24-h ambulatory BP monitoring. Sleep was scored according to standard criteria. 24-h, daytime, and nighttime averages were calculated for SBP, DBP and heart rate. REM sleep duration was computed as percentage of total sleep time and used to group participants into tertiles as follows: T1 (REM% ≤18.8), T2 (REM% 18.9-24), and T3 (REM% ≥24.1). Results: Sex ratio, body mass index, and apnea-hypopnea index were similar across REM tertiles, but age increased with increasing tertiles (p=0.029). 24-h SBP (T1 vs T2 vs T3: 121±12 vs 117±7 vs 124±12 mmHg, p=0.015) and DBP (72±7 vs 70±6 vs 76±8 mmHg, p<0.001) differed across REM sleep tertiles, with significantly higher values in those in the highest tertile. Results were consistent when considering daytime SBP (T1 vs T2 vs T3: 126±12 vs 122±8 vs 132±14 mmHg, p<0.001) and DBP (77±7 vs 76±6 vs 83±9 mmHg, p<0.001), and nighttime DBP (65±9 vs 61±7 vs 65±8 mmHg, p=0.047). No differences were noted on nighttime SBP or any heart rate measures. A significant interaction was found between hypertension status and REM sleep in multiple regression analysis, with the observed associations being significant only among hypertensives (n=69). In those with hypertension, REM sleep duration was associated with 24-h mean BP independently of age, sex, body mass index, apnea-hypopnea index and antihypertensive medications (standardized beta 0.22, p=0.041). Conclusions: Longer REM sleep duration is independently associated with elevated ambulatory BP in individuals with hypertension. REM sleep may be a novel cardiovascular risk indicator in this population.

Abstract While the contribution of several physiological systems to arterial blood pressure regulation has been studied extensively, the role of normal and disrupted sleep as a modifiable determinant of blood pressure control, and in the pathophysiology of hypertension, has only recently emerged. Several sleep disorders, including sleep apnea and insomnia, are thought to contribute to the development of hypertension, although less attention is paid to the relationship between sleep duration and blood pressure independent of sleep disorders per se. Accordingly, this review focuses principally on the physiology of sleep and the consequences of abnormal sleep duration both experimentally and at the population level. Clinical implications for patients with insomnia who may or may not have abbreviated sleep duration are explored. As a corollary, we further review studies of the effects of sleep extension on blood pressure regulation. We also discuss epidemiological evidence suggesting that long sleep may also be associated with hypertension and describe the parabolic relationship between total sleep time and blood pressure. We conclude by highlighting gaps in the literature regarding the potential role of gut microbial health in the cross-communication of lifestyle patterns (exercise, diet, and sleep) with blood pressure regulation. Additionally, we discuss populations at increased risk of short sleep, and specifically the need to understand mechanisms and therapeutic opportunities in women, pregnancy, the elderly, and in African Americans.