Androgen excess polycystic ovary syndrome (AE-PCOS) is associated with elevated risk for hypertension and cardiovascular disease. Greater beat-to-beat blood pressure variability (BPV) has emerged as a novel marker of cardiovascular risk. Little is known about beat-to-beat BPV in AE-PCOS, but prior studies suggest blunted baroreflex sensitivity (BRS), a major contributor to beat-to-beat BP regulation. Both obesity and androgen excess are implicated as driving factors of cardiovascular risk in AE-PCOS. We hypothesized that 1) beat-to-beat BPV would be greater in AE-PCOS compared to both women with overweight/obesity (OW/OB) and lean controls; 2) beat-to-beat BPV would be augmented in OW/OB compared to lean controls. We measured beat-to-beat BP (finger photoplethysmography) during ~5-10 minutes of supine rest in 18 lean controls, 14 OW/OB controls, and 14 women with AE-PCOS. Serum testosterone was measured and spontaneous cardiovagal BRS was assessed via sequence technique. In AE-PCOS, resting BP was greater than lean controls (P<0.05) and serum testosterone greater than both control groups (P<0.001). Diastolic BP standard deviation was greater in AE-PCOS (3.9 ± 1.0 mmHg) compared to both control groups (lean: 3.0 ± 1.5; OW/OB: 2.9 ± 1.2 mmHg; P=0.007). Cardiovagal BRS was not different between groups (P=0.196). Neither cardiovagal BRS nor serum testosterone were related to beat-to-beat BPV in AE-PCOS. Collectively, these data suggest greater beat-to-beat BPV in AE-PCOS which cannot be accounted for by obesity alone and is not associated with cardiovagal BRS or circulating androgens.
Ventricular late potentials (VLPs) are markers of arrhythmogenic substrate, but conventional assessment using signal-averaged ECG (SAECG) requires prolonged acquisition and operator-dependent artifact handling, limiting scalability and ambulatory use. Single-beat detection of VLP-like activity from standard surface ECG remains insufficiently validated. To evaluate the technical feasibility of interpretable single-beat detection of VLP-like perturbations from standard ECG leads without signal averaging. Using the MIMIC-IV-ECG database, we analyzed 120,000 beats from leads II, V2, and V6. Because large public datasets with beat-level clinically adjudicated VLP labels are not currently available, physiologically constrained synthetic VLP-like signals were injected into a subset of beats to create a controlled feasibility benchmark. For each beat, more than 200 features were extracted, including time-domain statistics, frequency-domain measures, wavelet coefficients, autocorrelation features, and localized windowed summaries. Ten classifiers were optimized using nested patient-wise cross-validation and evaluated in five settings: single-lead detection, cross-lead generalization, mixed-lead training, reduced training size, and class-imbalance robustness. Gradient-boosted ensembles, particularly XGBoost and CatBoost, achieved strong discrimination on held-out single-beat data (AUC > 0.99; F1 > 0.93), while remaining stable with 10% of the training data and 5% positive-class prevalence. Performance was also robust in lead-transfer experiments. SHAP analysis identified localized entropy, dispersion, and related high-frequency descriptors in late post-R windows as the dominant predictors. These findings support the methodological feasibility of interpretable single-beat detection of VLP-like signatures from routine surface ECG under controlled synthetic conditions. Validation on clinically adjudicated cohorts and external datasets is required before clinical translation.
Developmental dyslexia involves deficits in phonological awareness and cortical connectivity, yet the effects of binaural beats on these domains remain underexplored. This study examined the effects of theta (5 Hz) and beta (15 Hz) binaural beats on phonological processing and EEG coherence in 45 dyslexic children aged 6.5-8.3 years. Participants were assigned to the theta, beta, or control condition and received 12 binaural beat sessions over a period of four weeks. Resting-state EEGs were recorded at baseline, after the binaural beats sessions, and at a 6-week follow-up. Results showed that theta binaural beats significantly enhanced intrahemispheric coherence in frontal and temporal regions, correlating with improved phonological awareness. Beta beats enhanced interhemispheric coherence, particularly between temporal lobes, potentially supporting phonological decoding. The control group showed no significant changes. Correlation analysis revealed that coherence in specific brain regions (e.g., T3-T4, r = 0.788, p = 0.0013) was significantly associated with performance on phoneme judgment tasks. These findings suggest that frequency-specific binaural beats can enhance neural connectivity and phonological processing. This non-invasive approach shows potential for further exploration of cognitive effects in dyslexic children, though limitations such as small sample size and restricted frequency range necessitate additional research.
Converging evidence suggests that musical training can elicit positive transfer effects across multiple domains of language processing, including grammar. In humans, exposure to musical rhythm induces beat and meter perception, which has been shown to enhance attentional allocation and temporal prediction. Theories hypothesize that the predictive gains intrinsic to music rhythmicity may exert cascading effects on syntactic processing by modulating sensitivity to speech prosody. From this perspective, learning should also be boosted insofar as prosody tends to align with grammatical structure. In the present study, we introduce a novel behavioural paradigm to investigate the link between rhythmicity and grammar learning by testing whether the rhythmic beat facilitates the detection of grammar-like structures in artificial languages (ALs), implemented as non-adjacent dependencies (NADs) between variable syllables forming a speech stream (e.g., PU reliably predicts KI in PUlaruKI). A total of 147 participants were exposed to four ALs that varied in rhythmic, grammatical structure, and the alignment between the two: (i) a beat-inducing rhythm with no NADs; (ii) a beat-hindering rhythm with NADs; (iii) a beat-inducing rhythm with embedded NADs temporally misaligned, and (iv) NADs aligned with beat time-points. Results of the implicit and, after exposure, explicit learning measures demonstrate enhanced learning when NADs are embedded within beat-inducing rhythmic structures. Together, these findings suggest that rhythm enhances predictive and attentional mechanisms implicated in grammar learning, underscoring their role in its acquisition.
Drug-induced QT prolongation is the leading cause of FDA nonapproval and a key safety concern for many medications, including cardiac drugs, antibiotics, psychotropic drugs, and oncology treatments. Conventional automated QT algorithms have shown variable reliability in recordings with abnormal or irregular morphology, with misclassification rates up to 75%. This article presents SafeBeat Rx, an AI-powered ECG platform that provides beat-by-beat ECG analysis, enabling full transparency and optional adjustment of measurements for each individual ECG heartbeat. Validated against expert cardiologist adjudication, SafeBeat addresses a critical gap in postdischarge cardiac surveillance and represents a novel approach to guideline-adherent pharmacological disease management.
Single-beat estimates of left-ventricular end-systolic elastance (Ees) and ventriculoarterial coupling are increasingly used in perioperative and critical care settings. However, their presumed load independence may not hold during ventilatory interventions. This study was designed to investigate the effect of graded positive end-expiratory pressure (PEEP) on these estimates. Prospective observational study. Single tertiary-care hospital. A total of 105 adults undergoing elective noncardiac surgery under general anesthesia. PEEP was increased stepwise (0, 5, 10, and 15 cmH2O) during controlled mechanical ventilation. Transthoracic echocardiography and invasive arterial pressure were recorded at each PEEP level. Single-beat Ees, Ea, and Ea/Ees were calculated using the Chen method and analyzed using linear mixed-effects models. For each 5 cmH2O increase in PEEP, Ees increased by 0.55 mmHg/mL (95% confidence interval [CI]: 0.49 to 0.61; p < 0.001), Ea increased by 0.24 mmHg/mL (95% CI: 0.20 to 0.27; p < 0.001), and Ea/Ees decreased by 0.04 (95% CI: -0.05 to -0.03; p < 0.001). Stroke volume decreased by 9.1 mL (95% CI: -9.9 to -8.4; p < 0.001), whereas heart rate remained unchanged. In sensitivity analyses, the apparent increase in Ees disappeared when assuming a stroke volume at PEEP of 0 cmH2O but persisted when assuming baseline-estimated normalized ventricular elastance at arterial end-diastole or applying transmural pressure correction. Apparent increases in single-beat left-ventricular Ees during PEEP titration were consistent with substantial stroke volume-related mathematical sensitivity of the single-beat formulation. These findings suggest that such increases should not be interpreted as direct evidence of improved left-ventricular systolic function.
Robust cardiac gating is critical for cardiac magnetic resonance (CMR) imaging; however, electrocardiography (ECG) and other contact sensors are often limited by electromagnetic interference and practical setup constraints. Hence, this paper presents Laser HeartBeat (Laser HB), a contactless gating method using defocused laser speckle imaging to track chest-wall micro vibrations. Specifically, Laser HB comprises (i) an MRI compatible optical acquisition module that projects and records defocused speckle patterns without contacting the subject, (ii) an integrated real-time processing and triggering pipeline, which incorporates our proposed Laser HB trigger algorithm to extract a robust cardiac-motion surrogate signal from speckle imaging and generate gating trigger signals in real time. To evaluate its feasibility in realistic occlusion scenarios with electromagnetic interference, we conducted two out-of-bore studies and one in-bore feasibility study. Comparative experiments show that Laser HB achieves 97.6% availability, with beat-wise precision/recall/F1 = 0.946/0.946/0.943. The extracted triggers exhibit an average 22.6 ms delay relative to the ECG R-peak. Moreover, integration of the Laser HB system decreased the phantom MRI signal-to-noise ratio (SNR) by 2.8 compared with the baseline condition. These results indicate that Laser HB is an MRI-compatible, low-latency, fully contactless gating method that can reduce setup burden, improve workflow efficiency, and enhance patient comfort.
Antitachycardia pacing (ATP) delivered by implantable cardioverter-defibrillators (ICD) is a well-established therapy for monomorphic ventricular tachycardia (VT). Recently, extravascular ICD has emerged as a novel technique that provides ATP with an entirely extravenous system, at the epicardial level. ECG documentation of a succesful ATP delivery by this innovative ICD is a rare but stimulating report. We present a case of sustained monomorphic VT successfully terminated by the first ATP stimulus delivered by an extravascular ICD, with surface ECG documentation of the termination beat. Beyond documenting successful ATP therapy, the recording also provides insight into the electrophysiological interaction between the paced impulse and the VT circuit, suggesting potential mechanistic information about the underlying reentrant substrate.
This case illustrates a rare presentation of premature junctional contractions arising from the atrioventricular nodal region, particularly the slow pathway, mediated by non-sustained reentrant activity. This mechanism does not result in sustained tachycardia but instead produces isolated echo beats.
To develop an online pediatric electrocardiogram (ECG) educational intervention, d to examine pediatricians' diagnostic skill development as they progressed to achieve a performance-based standard, and to determine the frequency of pediatric ECG findings at highest risk for diagnostic error. This multicenter, prospective cohort study included a convenience sample of pediatricians. There were 400 cases in the intervention, and for each case, participants first determined whether an actionable abnormality was present or absent. If present, participants categorized abnormalities as rate/rhythm, anatomical/technical, or Q-wave/repolarization, and selected the most appropriate specific diagnosis from a drop-down list of options. Immediate feedback was provided after each case, and practice continued until a minimal passing standard was achieved. A total of 345 pediatricians performed 46,649 pediatric ECG case interpretations. Initial accuracy was 82.1% in identifying ECG with actionable findings, 70.9% for correct categorization of actionable findings, and 45.2% for selecting most actionable specific diagnosis. There were learning gains for each of these diagnostic tasks: +14.6% (95% CI 13.1, 15.8), +15.0% (95% CI 13.2, 16.8), and +19.8% (95% CI 17.5, 22.1), respectively. Furthermore, 65% achieved the minimal passing standard in a median of 325 cases (IQR 198, 496) or 6.5 hours (IQR 3.4, 10.0) of practice. Among the 46,649 case interpretations, 7,675 (16.5%) were incorrect interpretations. ECG findings consistent with ventricular hypertrophy, Brugada sign, prolonged QTc, and ischemia/pericarditis were among the most challenging diagnoses. Structured practice with feedback can feasibly improve pediatrician ECG interpretation skills and derive data to identify ECG findings prone to diagnostic error.
Takotsubo cardiomyopathy (TTC) is a transient and reversible form of left ventricular systolic dysfunction that often mimics acute coronary syndrome and is usually precipitated by emotional or physical stress. We describe an unusual presentation of mid-ventricular TTC in which ventricular arrhythmia was the dominant clinical feature and a probable precipitating factor. A 71-year-old woman presented with left shoulder pain and palpitations in the absence of chest pain or an identifiable emotional stressor. Initial electrocardiography demonstrated frequent runs of rapid non-sustained ventricular tachycardia, with a markedly elevated troponin I level of 2188 ng/L. Coronary angiography showed unobstructed epicardial coronary arteries with delayed contrast clearance. Cardiac magnetic resonance imaging revealed severe left ventricular systolic dysfunction (left ventricular ejection fraction (LVEF) 20%-25%) with isolated mid-ventricular akinesia and preserved basal and apical contractility, consistent with a mid-ventricular variant of TTC. Management focused on arrhythmia control and supportive heart failure therapy, with acute stabilisation using intravenous amiodarone followed by beta-blockade with bisoprolol and guideline-directed medical therapy. The ventricular arrhythmia resolved, and left ventricular systolic function improved significantly, with follow-up cardiac magnetic resonance imaging demonstrating recovery of LVEF to 50%. Device therapy was not pursued, given the reversible nature of TTC. This case highlights ventricular arrhythmia as both a presenting manifestation and a possible trigger of TTC and emphasises the importance of considering atypical variants in patients presenting with unexplained cardiomyopathy and ventricular arrhythmias. Multimodality imaging remains essential for accurate diagnosis and for guiding appropriate management in such cases.
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Variability in 24-hour and visit-to-visit blood pressure has been reported to be predictive of adverse cardiovascular outcomes. While recent studies have employed beat-to-beat blood pressure variability (BPV) as a predictor of cardiovascular risk, the reliability of beat-to-beat BPV remains equivocal. The purpose of this study was to examine intraindividual reliability of BPV, and to compare that reliability to more widely-documented heart rate variability (HRV) in young healthy adults. Continuous heart rate (HR, electrocardiogram), beat-to-beat blood pressure (BP, finger plethysmography), and respiratory rate (pneumobelt) were recorded during 10 minutes of rest in 77 participants (38 males, 39 females; age: 23±5 yr; BMI: 25±4 kg/m2) on two occasions separated by ≥2 days (25±19 days; 2-98 days). Reliability of beat-to-beat BPV, HRV (time- and frequency-domain), and additional cardiovascular (heart rate, blood pressure) assessments were quantified as relative and absolute reliability using the intraclass correlation coefficient (ICC) and the coefficient of variation (CoV), respectively. Beat-to-beat BPV demonstrated moderate relative and good absolute reliability (10-min duration: ICC=0.601-0.684, CoV=14-16%). In contrast, relative reliability of time-domain HRV was good-to-excellent, while absolute reliability was poor-to-good (10-min duration: ICC=0.844-0.904, CoV=13-34%). Frequency-domain HRV demonstrated moderate to excellent relative reliability and poor absolute reliability (10-min duration: ICC=0.626-0.903, CoV=34-37%). In summary, the rigor and reliability of continuous BPV and HRV are different when parsed out by relative vs. absolute reliability, with relative reliability being stronger with HRV and absolute reliability being stronger with BPV. These findings suggest both caution and specificity when employing continuous BPV or HRV for CVD risk stratification purposes.
Cardiovascular diseases are the leading cause of death in the world, requiring the accurate and timely detection of arrhythmias to prevent sudden cardiac death. In this work, ScaHybNet, a deep learning ensemble model is proposed for multi-class arrhythmia classification using the widely adopted ECG Heartbeat Categorization Dataset. The dataset comprises 109,446 samples across five heartbeat classes (N, S, V, F, Q), enabling comprehensive arrhythmia analysis. The proposed method first transforms the ECG signals to 224 × 224 RGB-scalogram images using CWT with the Morlet wavelet. Then, a hybrid model is developed, which is composed of (1) a residual block-based CNN with skip connections to learn spatial features, (2) a BiLSTM layer for learning temporal features from the CNN feature maps and (3) a Transformer encoder layer with a custom-built multi-head self-attention mechanism to capture long-term dependencies. Thus, to address the extreme class imbalance within the data, stratified balancing of the data among normal beat, supraventricular ectopic beat, ventricular ectopic beat, fusion beat, and unknown beat, and inverse-frequency class weighting were performed. They assessed model robustness using fivefold cross-validation. Hyperparameters set to final values included a batch size of 2, 150 epochs, and an Adam optimizer. Ensemble train accuracy 99.81% and the mean accuracy on the fivefold cross validation set was 90.42% ± 1.26 (std) for ScaHybNet. On the test set (unseen data), it showed a total ensemble test accuracy of 94.73%, precision of 76.51%, recall of 82.93%, and F1-score of 77.40%. The ablation test proved the joint efficacy of each part of the model, and state-of-the-art analysis revealed better or equal results on current standards regarding ECG data with noise and imbalance. ScaHybNet appears to offer the potential to act as a more patient-centric tool that could offer considerable benefits to the medical field.
The use of wearable sensors to measure and monitor heart rate has exponentially grown in recent years, representing an inexpensive, time-efficient, and non-invasive method to assess the status of cardiovascular fitness and the autonomic nervous system. Validating new devices against a criterion standard, such as electrocardiography (ECG), is essential to ensure their accuracy and reliability. This study examined the accuracy and validity of the Prevayl heart rate monitor against 3-lead ECG. Twenty-six healthy adults (15 female, mean age 32.0 ± 10.4 years) completed a 16-min, incremental running test on a treadmill. Heart rate data were recorded simultaneously throughout the test via ECG and the Prevayl wearable and compared retrospectively. Beat count error (%), mean heart rate absolute error (beats per minute (bpm)), and percentage error (bpm) were calculated. In addition, a Bland-Altman analysis and Pearson's correlation coefficient were conducted to assess agreement and correlation, respectively. The Prevayl device demonstrated a median beat count agreement of 100.5% with ECG (range: 98.6-104.4%; Npart = 26). Strong correlations were observed between ECG and Prevayl for both raw beat count (r = 0.94, p < 0.01) and heart rate (beats per minute (bpm)) from ECG and the Prevayl algorithm (r = 0.96, p < 0.01). Across running speeds (0-12 kph), a strong correlation was found between raw beat count from ECG and Prevayl (r = 0.82-0.89, p < 0.01) and between bpm from ECG and Prevayl (r = 0.86-0.93, p < 0.01). Bland-Altman plots demonstrated negligible systematic bias. The Prevayl system provides valid measurements when compared to ECG during incremental running. This is demonstrated through strong correlations to ECG heart rate data at different speeds and with different analysis methods, supporting its use for monitoring cardiovascular responses during exercise.
We introduce a free-space optical sensing architecture in which spatial refractive-index gradients are mapped directly into heterodyne modulation sidebands using a frequency-diverse beamlet array. Mutually coherent beamlets with distinct frequency offsets sample the medium at different transverse positions, producing a time-dependent interference signal on a single detector whose Fourier transform yields a comb of heterodyne beat frequencies. Spatially varying refractive index gradients induce differential phase shifts between beamlets, yielding symmetric sidebands around each beat frequency that encode the local gradient. This approach enables multiple parallel sensing channels on a single detector without a reference arm or embedded sensing elements, with spatial sampling and detection defined entirely by the optical field. An analytic framework describing beat formation and sideband scaling is developed and validated experimentally. Using an eight-beamlet array at 532 nm with 5 MHz spacing, the system achieves > 80 dB beat-to-sidelobe ratios and near-pascal acoustic sensitivity. Because the detection bandwidth is set by the optical beat frequencies, this approach supports extension to substantially higher acoustic bandwidths, establishing a compact, reconfigurable platform for remote, non-contact acoustic sensing. This approach establishes a general framework for non-contact sensing of refractive index gradients using structured light, with potential applications beyond acoustics including turbulence and thermal sensing.
BackgroundOrthostatic hypotension (OH) and supine hypertension (SH) are common in patients with Parkinson's disease (PD), contributing to disease-related morbidity and mortality. However, initial OH, a transient blood pressure that decreases immediately after standing, is often unrecognized, and the interactions among OH, SH, and anti-hypertensive therapy remain unclear.MethodsThis single-centre retrospective observational study included 183 patients with PD who underwent an active supine-to-stand test with beat-to-beat blood pressure monitoring. Logistic regression was used to identify factors associated with OH and SH, and linear regression was performed to examine the determinants of postural blood pressure decline and changes in cerebral haemodynamics.ResultsOH occurred in 72.1% of patients, including 27.9% with symptomatic OH; SH was present in 21.9%. Female sex (P = 0.013) and anti-hypertensive therapy (P = 0.026) were associated with lower odds of OH. Older age (P = 0.017), arterial hypertension (P = 0.002), and a high Hoehn and Yahr stage (P = 0.006) were associated with higher odds of SH (AUC 0.80). Increased supine systolic and diastolic blood pressure were associated with increased postural decline (β = 0.40, P < 0.001; β = 0.31, P = 0.001), whereas anti-hypertensive therapy was associated with decreased postural decline. Among patients with complete middle cerebral artery monitoring data, changes in the pulsatility index were correlated with reductions in cerebral blood flow velocity (β = -11.24; P = 0.002).ConclusionsThis study comprehensively characterized the prevalence and determinants of OH and SH in patients with PD. SH was associated with greater decreases in postural blood pressure, whereas anti-hypertensive therapy was associated with smaller decreases. Pulsatility index variation may serve as a physiological marker of cerebral haemodynamic adaptation during an orthostatic challenge. Understanding Blood Pressure Changes in People with Parkinson's DiseasePlain language summaryPurpose and Aim:This study looked at blood pressure regulation problems in people with Parkinson's disease (PD), especially blood pressure dropping when standing up, called orthostatic hypotension (OH), and blood pressure being high when lying down, called supine hypertension (SH). The aim was to find out how common these problems are and which clinical factors are associated with them.Background:Blood pressure changes are common in PD but are often overlooked. They may cause dizziness, fainting, falls, and other health problems. In some patients, blood pressure may also become high while lying down. Better understanding of these patterns may help clinicians assess cardiovascular risk and manage symptoms more effectively.>Methods:We reviewed medical records from 183 patients with PD who completed an active supine-to-stand test with continuous beat-to-beat blood pressure monitoring. Statistical analyses were used to examine factors associated with OH, SH, and the degree of blood pressure change after standing. In a subgroup with complete middle cerebral artery monitoring data, we also assessed changes in cerebral haemodynamics.Results and Significance:OH was found in 72.1% of patients, including 27.9% with symptoms, and SH was present in 21.9%. Female sex and anti-hypertensive therapy were associated with lower odds of OH, whereas older age, arterial hypertension, and more advanced PD were associated with higher odds of SH. Higher supine blood pressure was associated with larger blood pressure drops after standing. These findings show that abnormal blood pressure regulation is common in PD and may support more individualized clinical assessment.
Despite the growing popularity of electronic cigarettes, evidence is mounting that vaping induces autonomic nervous system imbalance, cardiac arrhythmia, and potentially even cardiac arrest. The ingredients menthol, WS-3, and WS-23 are cooling agents that enhance the appeal of electronic cigarettes (e-cigs) but bear unknown risks when inhaled. We systematically evaluated how these coolants influence the impacts of e-cigs on cardiac and cellular electrophysiology in mice and human induced pluripotent stem cell-derived cardiomyocytes, respectively. Mice were exposed by inhalation to e-cig aerosols generated from standard e-liquid solvents and 2.5% nicotine benzoate (vehicle), or from vehicle plus menthol, WS-3, or WS-23, at increasing concentrations throughout exposure. Telemetry-derived electrocardiograms were analyzed for changes in heart rate, heart rate variability, morphology, and ventricular premature beat arrhythmias. Human induced pluripotent stem cell-derived cardiomyocytes were evaluated for the effects of serially increasing coolant concentrations on beat rate, electric field potential duration, and rate-corrected field potential duration from a newly validated formula, in the absence and presence of norepinephrine to simulate basal physiology and nicotine-evoked sympathoexcitation. Upon e-cig aerosol inhalation, all coolants acutely enhanced vehicle-induced autonomic imbalance, but only the synthetic coolants, WS-3 and WS-23, potentiated ventricular arrhythmogenesis. Ventricular premature beats during e-cig exposures correlated with sympathetic dominance and transient delays in ventricular repolarization measured by heart rate variability and rate-corrected QT interval, respectively; however, correlations were strongest for WS-23 despite no significant impact of coolants on nicotine intake. Conversely, in human induced pluripotent stem cell-derived cardiomyocytes, coolants did not affect basal physiology but slowed beat rate and shortened rate-corrected field potential duration during norepinephrine stimulation. Together, these data indicate that coolants dose-dependently enhance the arrhythmogenicity of e-cigs, likely through acute alterations in autonomic modulation and repolarization. Pending confirmation by human studies, these common non-nicotine additives may exacerbate e-cig cardiotoxicity and pose unique cardiovascular risks, particularly in those with arrhythmogenic susceptibility to sympathetic stimulation or slowed ventricular repolarization.
In Norway, NORRISK2 is the government-recommended risk model for predicting an individual's 10-year probability of getting cardiovascular disease (CVD). This study aims to investigate the potential for improvement of CVD prediction by using hemodynamic measurements from a non-invasive beat-to-beat blood pressure monitor, taken as part of pain sensitivity assessment with the cold-pressor test (CPT) during the Tromsø6 Study (2007-2008). Using 6694 recordings, ultra-short-term pulse rate variability (PRV) and baroreflex sensitivity (BRS) obtained during the CPT were added as additional variables into the existing NORRISK2 survival model (extended model). In addition, the time-series data was used in a machine learning (ML) model without the NORRISK2 background variables. Both models were compared to a recalibration of the original NORRISK2 model. The predictions from the recalibrated NORRISK2 model and the ML model were then combined with logistic regression. The statistical models performed similarly on the test set, with an area under the receiver operating characteristic (AUROC) of 0.8 (95% CI: 0.71-0.86), 0.79 (0.71-0.85) and 0.77 (0.69-0.84) (original, recalibrated and extended NORRISK2, respectively). The ML model using only hemodynamic measurements obtained a test set AUROC of 0.73 (0.67-0.80). Combining the NORRISK2 and ML model did not increase the AUROC. Adding ultra-short-term PRV and BRS derived from Tromsø6 did not improve the prediction of the NORRISK2 model either. Although with lower accuracy, the beat-to-beat time series of hemodynamic variables from a CPT had a significant (p < 0.01) ability to predict future CVD without any other person-specific data.
Chronic kidney disease (CKD) impairs cardiac baroreflex sensitivity (cBRS), contributing to poor blood pressure (BP) control and heightened cardiovascular risk. Emerging evidence indicates that isometric handgrip (IHG) exercise may enhance cBRS in healthy individuals; however, its effects in CKD remain unclear. Therefore, this study tested the hypothesis that a single IHG session increases cBRS and reduces beat-to-beat BP variability (BPV) in CKD patients. In 21 patients (61 ± 12 yr; stages III-IV), beat-to-beat BP (finger photoplethysmography), heart rate (HR, electrocardiography), and respiration were continuously measured before and 10-, 20-, and 30-min post IHG vs. sham exercise in a crossover design. cBRS was assessed via the sequence technique and cardiac autonomic modulation via time- and frequency-domain HR variability (HRV). BPV was quantified using time domain indexes. cBRS increased following IHG exercise (10-min: Δ20 ± 4%; 20-min: Δ23 ± 5%; 30-min: Δ17 ± 5%; all P < 0.004 vs rest). This increase was significantly different from sham at 10-min and 20-min (all P < 0.006 vs sham), but not at 30-min post-IHG (P = 0.074). HR decreased throughout recovery (all P = 0.001 vs rest). Systolic BP decreased 30-min following IHG exercise (Δ-5 ± 2 mmHg; P = 0.047 vs. rest). Time-domain HRV increased during recovery (P = 0.005) whereas BPV remained unchanged following IHG exercise. After sham, all variables remained similar to rest, except systolic BP was significantly higher 20-min after sham. A single IHG session increased cBRS and vagal modulation, with a modest reduction in systolic BP and no change in BPV, in CKD patients. Overall, these findings suggest that IHG may serve as a non-pharmacological intervention for cardiovascular regulation in CKD.