Cardiovascular autonomic profile in women with constitutional hypotension

Predicting therapeutic efficacy of oral rehydration salts in children with vasovagal syncope

Objective

This study was designed to develop an easy-to-perform and inexpensive measure to predict efficacy of the oral rehydration salts (ORS) in children with vasovagal syncope (VVS).

Materials and methods

Children diagnosed with VVS and treated with ORS for a median of 3 months at the Peking University First Hospital, China, were enrolled and followed up. Demographic data, clinical hemodynamic parameters, and variables related to red blood cells were collected at the baseline. On the basis of changes in symptom scores after treatment, participants were divided into effective or ineffective groups at the end of the follow-up. Logistic regression analysis was used to investigate parameters related to therapeutic efficacy of ORS and a predictive model of ORS effectiveness was created. The predictive efficiency was evaluated using the receiver operating characteristic curve. The accuracy/consistency was evaluated by the Hosmer-Lemeshow test and calibration curve. Internal validation was done using the bootstrap approach.

Results

Totally 97 pediatric participants were included in the study and 4 (4.1%) were lost during the follow-up. ORS therapy was effective in 46 children and ineffective in 47 children. Children in the effective group had higher baseline red blood cell count, hemoglobin, and hematocrit than those in the ineffective group (p < 0.01). Through logistic regression analysis, the baseline hematocrit and body mass index (BMI) were included in predictive model for the response to ORS treatment. The predictive efficacy of the model showed an area under the curve of 0.77 (p < 0.01). The predicted probability cut-off value of 0.5 was found to be optimal, with a resulting sensitivity of 67.4% and specificity of 80.9%. In the Hosmer-Lemeshow test, p-value was 0.75, and the calibration plot showed a good model fitness. Internal validation was performed using the bootstrap approach (n = 1,000), showing 95% confidence interval of 0.67-0.86.

Conclusion

Hemoglobin combined with BMI was useful for predicting the therapeutic efficacy of ORS in children with VVS.

Relationships Between Cardiovascular Autonomic Profile and Work Ability in Patients With Pure Autonomic Failure

Pure autonomic failure (PAF) is a rare disorder belonging to the group of synucleinopathies, characterized by autonomic nervous system degeneration. Severe orthostatic intolerance with recurrent syncope while standing are the two most disabling manifestations. Symptoms may start at middle age, thus affecting people at their working age. The aims of this study were to evaluate the autonomic and work ability impairment of a group of PAF patients and assess the relationships between cardiovascular autonomic control and work ability in these patients. Eleven PAF patients (age 57.3 ± 6.7 years), engaged in work activity, participated in the study. They completed the Composite Autonomic Symptom Score (COMPASS-31, range 0 no symptom-100 maximum symptom intensity) and Work Ability questionnaires (Work Ability Index, WAI, range 7-49; higher values indicate better work ability and lower values indicating unsatisfactory or jeopardized work ability). Electrocardiogram, blood pressure and respiratory activity were continuously recorded for 10 min while supine and during 75° head-up tilt (HUT). Autoregressive spectral analysis of cardiac cycle length approximated as the time distance between two consecutive R-wave peaks (RR) and systolic arterial pressure (SAP) variabilities provided the power in the high frequency (HF, 0.15-0.40 Hz) and low frequency (LF, 0.04-0.15 Hz) bands of RR and SAP variabilities. Cardiac sympatho-vagal interaction was assessed by LF to HF ratio (LF/HF), while the LF power of SAP (LFSAP) quantified the vascular sympathetic modulation. Changes in cardiovascular autonomic indexes induced by HUT were calculated as the delta (Δ) between HUT and supine resting positions. Spearman correlation analysis was applied. PAF patients were characterized by a moderate autonomic dysfunction (COMPASS-31 total score 47.08 ± 20.2) and by a reduction of work ability (WAI 26.88 ± 10.72). Direct significant correlations were found between WAI and ΔLFRR (r = 0.66, p = 0.03) and ΔLF/HFRR (r = 0.70, p = 0.02). Results indicate that patients who were better able to modulate heart rate, as revealed by a greater cardiac sympathetic increase and/or vagal withdrawal during the orthostatic stimulus, were those who reported higher values of WAI. This finding could be relevant to propose new strategies in the occupational environment to prevent early retirement or to extend the working life of these patients.

Association of Occupational Distress and Low Sleep Quality with Syncope, Presyncope, and Falls in Workers

Syncope and presyncope episodes that occur during work could affect one's safety and impair occupational performance. Few data are available regarding the prevalence of these events among workers. The possible role of sleep quality, mental stress, and metabolic disorders in promoting syncope, presyncope, and falls in workers is unknown. In the present study, 741 workers (male 35.4%; mean age 47 ± 11 years), employed at different companies, underwent clinical evaluation and blood tests, and completed questionnaires to assess sleep quality, occupational distress, and mental disorders. The occurrence of syncope, presyncope, and unexplained falls during working life was assessed via an ad hoc interview. The prevalence of syncope, presyncope, and falls of unknown origin was 13.9%, 27.0%, and 10.3%, respectively. The occurrence of syncope was associated with an increased risk of occupational distress (adjusted odds ratio aOR: 1.62, confidence intervals at 95%: 1.05-2.52), low sleep quality (aOR: 1.79 CI 95%: 1.16-2.77), and poor mental health (aOR: 2.43 CI 95%: 1.52-3.87). Presyncope was strongly associated with occupational distress (aOR: 1.77 CI 95%: 1.25-2.49), low sleep quality (aOR: 2.95 CI 95%: 2.08-4.18), and poor mental health (aOR: 2.61 CI 95%: 1.78-3.84), while no significant relationship was found between syncope or presyncope and metabolic syndrome. These results suggest that occupational health promotion interventions aimed at improving sleep quality, reducing stressors, and increasing worker resilience might reduce syncope and presyncope events in the working population.

Low-blood pressure phenotype underpins the tendency to reflex syncope

BACKGROUND

We hypothesized that cardiovascular physiology differs in reflex syncope patients compared with the general population, predisposing such individuals to vasovagal reflex.

METHODS

In this multicohort cross-sectional study, we compared aggregate data of resting SBP, DBP, pulse pressure (PP) and heart rate (HR), collected from six community-based cohort studies (64 968 observations) with those from six databases of reflex syncope patients (6516 observations), subdivided by age decades and sex.

RESULTS

Overall, in male individuals with reflex syncope, SBP (-3.4 mmHg) and PP (-9.2 mmHg) were lower and DBP (+2.8 mmHg) and HR (+5.1 bpm) were higher than in the general population; the difference in SBP was higher at ages above 60 years. In female individuals, PP (-6.0 mmHg) was lower and DBP (+4.7 mmHg) and HR (+4.5 bpm) were higher than in the general population; differences in SBP were less pronounced, becoming evident only above 60 years. Compared with male individuals, SBP in female individuals exhibited slower increase until age 40 years, and then demonstrated steeper increase that continued throughout remaining life.

CONCLUSION

The patients prone to reflex syncope demonstrate a different resting cardiovascular haemodynamic profile as compared with a general population, characterized by lower SBP and PP, reflecting reduced venous return and lower stroke volume, and a higher HR and DBP, suggesting the activation of compensatory mechanisms. Our data contribute to a better understanding why some individuals with similar demographic characteristics develop reflex syncope and others do not.

VIDEO ABSTRACT

http://links.lww.com/HJH/B580.

Classification of orthostatic intolerance through data analytics

Imbalance in the autonomic nervous system can lead to orthostatic intolerance manifested by dizziness, lightheadedness, and a sudden loss of consciousness (syncope); these are common conditions, but they are challenging to diagnose correctly. Uncertainties about the triggering mechanisms and the underlying pathophysiology have led to variations in their classification. This study uses machine learning to categorize patients with orthostatic intolerance. We use random forest classification trees to identify a small number of markers in blood pressure, and heart rate time-series data measured during head-up tilt to (a) distinguish patients with a single pathology and (b) examine data from patients with a mixed pathophysiology. Next, we use Kmeans to cluster the markers representing the time-series data. We apply the proposed method analyzing clinical data from 186 subjects identified as control or suffering from one of four conditions: postural orthostatic tachycardia (POTS), cardioinhibition, vasodepression, and mixed cardioinhibition and vasodepression. Classification results confirm the use of supervised machine learning. We were able to categorize more than 95% of patients with a single condition and were able to subgroup all patients with mixed cardioinhibitory and vasodepressor syncope. Clustering results confirm the disease groups and identify two distinct subgroups within the control and mixed groups. The proposed study demonstrates how to use machine learning to discover structure in blood pressure and heart rate time-series data. The methodology is used in classification of patients with orthostatic intolerance. Diagnosing orthostatic intolerance is challenging, and full characterization of the pathophysiological mechanisms remains a topic of ongoing research. This study provides a step toward leveraging machine learning to assist clinicians and researchers in addressing these challenges. Graphical abstract Machine learning tools utilized to analyze heart rate (HR) and blood pressure (BP) time-series data from syncope and control patients. Results show that machine learning can provide accurate classification of disease groups for 98% of patients and we identified two subgroups within the control patients differentiated by their BP response.

New insights in diagnostics and therapies in syncope: a novel approach to non-cardiac syncope

This article aims to give advice on how to identify and manage patients with syncope who are at risk of severe outcomes, that is, at risk of trauma, potentially life-threatening episodes or frequent recurrences reducing quality of life. The first step of syncope diagnostic assessment is to identify patients with cardiac syncope, and once established, these patients must receive the adequate mechanism-specific treatment. If cardiac syncope is unlikely, reflex (neurally mediated) syncope and orthostatic hypotension are the most frequent causes of transient loss of consciousness. For these presentations, efficacy of therapy is largely determined by the mechanism of syncope rather than its aetiology or clinical features. The identified mechanism of syncope should be carefully assessed and assigned either to hypotensive or bradycardic phenotype, which will determine the choice of therapy (counteracting hypotension or counteracting bradycardia). The results of recent trials indicate that 'mechanism-specific therapy' is highly effective in preventing recurrences. Established mechanism-specific treatment strategies include withdrawal of hypotensive drugs, applying fludrocortisone and midodrine for the hypotensive phenotype and cardiac pacing in the bradycardic phenotype.