Comparison of clinical characteristics between malignant and non-malignant vasovagal syncope based on propensity score matching

Comparison of clinical characteristics between malignant and non-malignant vasovagal syncope based on propensity score matching | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparison of clinical characteristics between malignant and non-malignant vasovagal syncope based on propensity score matching Xinyi Wang, Aiyue Chen, Bin Tu, Pakezhati Maimaitijiang, Lihui Zheng, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8623153/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Vasovagal syncope (VVS) is a significant cause of syncope. However, a subset of VVS patients, defined as having malignant VVS, experience prolonged cardiac arrest during episodes (defined as > 3s), with a preference for the implantation of pacemakers. Research on malignant VVS remains limited, and its risk factors have not been fully clarified. This study aimed to identify the clinical characteristics and risk factors associated with malignant VVS. Methods Patients with ECG-confirmed cardiac arrest(> 3s) during syncope were assigned to the malignant VVS group during HUT. After Propensity Score Matching (PSM), given the small sample size of patients with malignant VVS, statistical analyses included univariate comparisons, multivariate logistic regression, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA). Results Patients comprised 26 in the malignant VVS group and 21 matched in the control group. The malignant VVS group had a significantly higher incidence of central triggers and a higher baseline diastolic blood pressure. Multivariate logistic regression identified central triggers and elevated DBP as independent risk factors for malignant VVS. The ROC curve showed that the combined model of DBP and central triggers had the best diagnostic efficacy. DCA confirmed this combined model maintained a stable, high net benefit across all threshold probability ranges. Conclusions Elevated baseline DBP and the presence of central triggers are core screening indicators for malignant VVS. The diagnostic model combining two factors exhibits excellent discriminatory ability and clinical utility, providing a reliable tool for the early identification and individualized management of patients with malignant VVS. Malignant vasovagal syncope risk factor blood pressure central triggers HUT. Figures Figure 1 Figure 2 Figure 3 Introduction Vasovagal syncope (VVS) is one of the main causes of syncope in patients. It may occur with or without obvious precipitating factors and is characterized by hemodynamic changes in heart rate and blood pressure, resulting in a transient loss of consciousness . Orthostatic stress is the most common trigger for VVS and is classified as a peripheral trigger. In addition, emotional stressors, including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia, can also mediate VVS onset and are defined as central triggers − . In most cases, patients with VVS show self-limiting progression or a favorable prognosis without leaving any sequelae. However, in patients with more severe clinical manifestations of VVS, a prolonged episode of cardiac arrest often occurs during the onset of syncope, which is closely associated with an increased risk of subsequent systemic organ damage . Clinically, VVS cases characterized by such prolonged cardiac arrest and high risk of organic damage are defined as malignant VVS, as well as a preference for the implantation of pacemakers . Some researchers define malignant VVS as a cardiac arrest lasting more than 3 seconds − . Clinically, malignant VVS requires active intervention to mitigate these risks, but its low prevalence and diagnostic challenges hinder effective identification. Currently, research focusing on patients with malignant VVS remains scarce, and the key risk factors specific to this distinct population have not yet been fully elucidated. In this study, we compared the demographics, clinical characteristics, and heart rate variability (HRV) of VVS patients with and without cardiac arrest and further provided some clinical clues for its early detection and screening. Study Design and Subjects Study population This observational study consecutively recruited patients who were diagnosed with VVS and visited Fuwai Hospital, Chinese Academy of Medical Sciences (Beijing, China) from March 2023 to March 2025. All subjects received 24-hour ambulatory electrocardiogram (ECG) monitoring as part of the routine syncope examination. Meanwhile, a head-up tilt test (HUT) was conducted to assist in the diagnosis of VVS and clarify the hemodynamic pattern. The diagnostic criteria for VVS are as follows: The clinical features are consistent with the mechanism of reflex syncope. After comprehensive examinations, other competing diagnoses are excluded, and the diagnosis is verified and confirmed by professional cardiologists in accordance with the European Society of Cardiology (ESC) Guidelines for the Diagnosis and Management of Syncope . If a record, confirmed by an electrocardiogram (ECG), shows the heart stopping for more than 3 seconds during a syncope episode, and there are no other diseases that can cause syncope, the patient is classified in the malignant group. The control group consisted of VVS patients who were admitted to the syncope ward during the same period. When they had a syncope episode, the cardiac arrest duration did not exceed 3 seconds. These patients were matched 1:1 with the malignant group according to age and gender. Exclusion criteria were as follows: (1) syncope due to orthostatic hypotension or arrhythmias (e.g., supraventricular or ventricular tachycardia, Mobitz II second- or third-degree atrioventricular block, sinus node dysfunction, Brugada syndrome, or long QT syndrome). (2) structural cardiac disease (e.g., congenital heart disease, cardiomyopathy, or valvular heart disease) or cardiopulmonary disease (e.g., pulmonary embolism, pulmonary hypertension). (3) a history of myocardial infarction, heart failure, or cerebrovascular disease. (4) other disease that affected the autonomic system (e.g., diabetes mellitus or hyperthyroidism). (5) a treatment history of catheter ablation, pacemaker implantation, cardiac surgery, or medication affecting autonomic function (e.g., beta-blockers or anticholinergics). Ethical approval was obtained from the Institutional Ethics Committee of Fuwai Hospital, ensuring that all research procedures adhered to the Declaration of Helsinki. Written informed consent was obtained from each participant before enrollment. Head-up tilt test HUT comprising a passive phase at a tilt angle of 60–70º and an additional provocative phase with sublingual administration of 0.35 mg nitroglycerine (if the passive phase is negative) was performed according to the conventional protocol delineated in the ESC syncope guidelines . The test was continued until either complete loss of consciousness occurred or the protocol was completed. The positive response to HUT was defined as the reproduction of spontaneous syncope with characteristic hemodynamic patterns of hypotension and bradycardia, which was further categorized into vasodepressor, mixed, or cardioinhibitory forms based on the VASIS classification 5 . Holter recording All participants underwent 24-hour ambulatory 12-lead Holter monitoring under hospital-supervised conditions. They were instructed to maintain habitual daily activities to reflect real-world autonomic responses, while adhering to regular sleep-wake patterns for relatively consistent circadian rhythm. Additionally, strenuous physical activities were prohibited during the monitoring period. The recordings digitized at 128 Hz were processed using dedicated analytical software (MIC-12H Analysis Platform; Jinke Instruments, Beijing, China), which employed adaptive thresholding and morphology-based algorithms for QRS complex identification and classification. To optimize accuracy while balancing automation efficiency with expert validation, automated outputs underwent two-stage manual verification: (1) pre-analytical signal quality control to eliminate artifact-contaminated segments; (2) post-processing review by board-certified physicians to rectify ectopic beat misclassification. To quantify parasympathetic activity, DC and AC are calculated based on the phase-rectified signal averaging (PRSA) algorithm . Clinical data collection Collect the clinical characteristics of patients, including gender, age, height, weight, body mass index (BMI), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), history of hypertension, medication history, drinking history, and smoking history. Record detailed medical history, including the age at which the patient experienced syncope, disease duration, number of episodes, number of prodromal episodes, symptom duration, Calgary Score, history of syncope-related trauma, and family history of typical VVS episodes. The precipitating factors can be categorized into two distinct groups based on the anatomical and functional origins of triggering stimuli, namely peripheral triggering factors and central triggers. . Peripheral triggering factors include prolonged standing, postural changes, and after exercise. Central triggers include intramuscular injections, venipuncture, emotional stress, and pain. Data Analysis Statistical analyses were performed using SPSS 26.0 (IBM, Armonk, NY, USA) and R software (version 4.3.3, R Foundation for Statistical Computing, Vienna, Austria). Given the small sample size of patients with malignant VVS, the purpose of using propensity score matching (PSM) in this study was not to adjust for existing baseline confounders. Instead, it aimed to select a subset of control samples that were more closely matched to the case group in terms of characteristics from an excessive number of control samples, under the premise that there were no significant differences in baseline data. This approach helps reduce the potential impact of uneven sample sizes on analysis results, thereby improving the stability and comparability between groups. After installing the PS Matching module in SPSS 26.0 statistical software, PSM was performed using a 0.2 SD calliper matching ratio of 1:1 . The propensity score values were calculated using a logistic regression model, with matching factors including patient age, Body Mass Index (BMI), and gender. The general clinical data of patients in the malignant VVS group and the control group were compared before and after PSM. The Shapiro-Wilk test was used to examine the normality of continuous data. For continuous variables that followed a normal distribution, the data were presented as (mean ± standard deviation), and the paired t-test was used for between-group comparisons, considering the matched nature of the data after PSM. For continuous variables that did not follow a normal distribution, the data were presented as median (interquartile range, IQR), and the Wilcoxon signed-rank test was used to compare differences between the matched groups.​Categorical data were presented as n (%) and analyzed using the McNemar test or Fisher’s exact test for McNemar’s design, replacing the conventional chi-square test to account for the paired structure of the PSM-matched samples. A P value < 0.05 was considered statistically significant.​To identify the risk factors for malignant VVS, conditional binary logistic regression analysis was applied, as this method is specifically designed for matched data and can effectively control for the confounding effects introduced by the matching process. For the multivariable conditional logistic regression model, variables with a P value < 0.10 in the univariate conditional logistic regression analysis, as well as gender (a clinically important covariate), were initially included. Forward variable selection was used to remove non-significant variables until all remaining variables were significant at the 0.05 level. All tests were two-tailed, and effect sizes were expressed as the odds ratio (OR) and its 95% confidence interval (95% CI). The receiver operating characteristic (ROC) curve was used to evaluate the discriminatory ability of malignant VVS, and the area under the curve (AUC) was calculated; the optimal cut-off value was determined by maximizing Youden's index to balance sensitivity and specificity. To clarify the clinical utility of the predictive model for malignant VVS constructed based on multifactorial logistic regression in this study, decision curve analysis (DCA) was used to quantify the difference in net benefit between the model and traditional strategies at different clinical decision thresholds, to compensate for the limitation of relying solely on the ROC curve to evaluate the model's discriminatory ability while ignoring clinical benefits. The rmda package in R software version 4.3.3 was used to plot the DCA curve, and the net benefit rates of these three strategies were calculated within the threshold probability range of 0–100%. Results Basic Information of the Studied Patients Before PSM, there were 26 patients in the malignant VVS group and 95 patients in the control group,with an 80.8% matching success rate. Comparisons of general clinical data, including age, gender, and BMI, between the two groups showed no statistically significant differences (P > 0.05), as shown in Table 1 . After successful PSM, 21 patients in the control group were matched with those in the study group. A total of 47 patients (17 males and 30 females) were finally enrolled in this study. The mean age of the study population was 37.71 ± 15.93 years, with young patients being the majority (a ratio of 46:3; note: young and elderly patients were defined in accordance with the WHO criteria for age stratification). All enrolled cases reported no history of trauma prior to syncopal episodes, nor did they have a history of systemic diseases, heart diseases, or neurological diseases. Additionally, no positive findings were identified during physical examination for any of the participants. Comparisons of demographic characteristics and clinical features between the malignant VVS group and the control group are presented in Table 2 . At the time of admission, there were no statistically significant differences between the two groups in terms of age, gender distribution, height, weight, or BMI. Notably, the incidence of central triggers, including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia, was significantly higher in the malignant VVS group than in the control group (53.8% vs. 26.3%, P < 0.05). In contrast, no significant between-group differences were observed in terms of age of onset, number of syncopal episodes, number of premonitory syncopal episodes, symptom duration, Calgary score, medical history, family history, and trauma history between the two groups. Regarding the past medical history, there were no significant differences in the history of hypertension, medication history, alcohol history, and smoking history between the two populations. Heart Rate Variability (HRV) After 24-hour Holter monitoring was performed in patients of both groups, statistical analysis revealed no significant differences in multiple HRV parameters including standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (rMSSD), low-frequency power (LF), high-frequency power (HF), LF/HF ratio, acceleration capacity(AC) component, and deceleration capacity (DC) component between the malignant VVS group and the control group (Table 3). Hemodynamic Indicators When comparing the hemodynamic parameters between the two populations, no statistically significant differences were observed in HR or SBP (Table 4). In contrast, a statistically significant difference in DBP was detected between the two groups (75.88 ± 1.85 mmHg vs. 66.83 ± 1.50 mmHg, P < 0.001).​Furthermore, a ROC curve was constructed to evaluate the discriminatory performance of DBP for identifying malignant VVS, and the results demonstrated good diagnostic efficacy (AUC = 0.781; 95% CI = 0.652–0.910). Using the Youden index to determine the optimal cut-off value of DBP (75.5 mmHg), the diagnostic model achieved a sensitivity of 87.0% and a specificity of 57.7% (Fig. 1).​ Risk Factors for Malignant Vasovagal Syncope In the univariate analysis, six variables, namely age, weight, symptom duration, central triggers (including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia), SBP, and DBP, exhibited statistically significant differences between the malignant VVS group and the control group (P < 0.1). These variables were further included as candidate predictors in a subsequent multivariate logistic regression analysis, whose purpose was to identify independent risk factors for malignant VVS.​ The results of the multivariate logistic regression analysis showed that both central triggers and DBP were independent predictors of malignant VVS. The odds ratios (95% confidence intervals) for central triggers and DBP were 6.65 (1.42–31.19) (p < 0.05) and 1.17 (1.07–1.29) (p < 0.05), respectively (Table 5). Comparison of the Efficacy of Different Diagnostic Models To evaluate the diagnostic efficacy of three strategies for malignant VVS, namely DBP alone, central triggers alone, and the combination of these two, ROC curves were constructed to assess the discriminatory ability of each strategy.​As presented in Fig. 2, the combined use of DBP and central triggers exhibited the highest diagnostic efficacy, with an AUC of 0.846 (95% confidence interval [95% CI]: 0.737–0.955). In comparison, the AUC value for DBP alone was 0.781 (95% CI: 0.652–0.910), and that for central triggers alone was 0.661 (95% CI: 0.530–0.791).​Using the Youden index to determine the optimal cut-off value for DBP (75.5 mmHg) and taking the presence of central triggers as a positive indicator, the combined diagnostic strategy achieved a sensitivity of 78.3% and a specificity of 80.8%. Evaluation of the Clinical Practicality of the Prediction Model To further clarify the clinical practicality of the prediction model for malignant VVS constructed based on DBP and central triggers, DCA was conducted. As shown in Fig. 3, all three models generated a net benefit and were significantly superior to the ineffective strategy. Discussion Major Findings In this study, we identified correlations between DBP levels, central triggers, and the specific patient group with malignant VVS. Compared with patients with non-malignant VVS, those with malignant VVS had higher DBP levels and more frequent central triggers.Notably, when DBP exceeded 75.5 mmHg, it showed strong discriminatory power for malignant VVS. Additionally, combining DBP with central triggers further improved diagnostic performance. These correlational findings provided a preliminary reference for clinical practice. The Relationship between Diastolic Blood Pressure and Malignant Vasovagal Syncope This study is the first to demonstrate that elevated DBP is an independent risk factor for malignant VVS. When 75.5 mmHg is used as the cut-off value, it exhibits the optimal diagnostic efficacy, providing a quantitative indicator for clinical screening of malignant VVS. This finding may be associated with the classic pathophysiological mechanism of vasovagal syncope. Under normal physiological conditions, when the human body is in an upright position, baroreceptors maintain blood pressure stability by activating the sympathetic nervous system. In patients with vasovagal syncope, however, the autonomic compensatory reflex is impaired, which is manifested as an abnormal response characterized by vasodilation and bradycardia . Multiple possibilities exist regarding the causal relationship between elevated DBP and malignant VVS. Elevated baseline DBP may exacerbate the intensity of the vagal reflex through two potential pathways. First, long-term elevation of DBP may reset the threshold of baroreceptors, increasing the sensitivity of the vasomotor center to changes in volume load. When a triggering factor induces reduced ventricular filling, it is more likely to trigger excessive vagal activation, ultimately leading to prolonged cardiac arrest. Second, elevated DBP is often accompanied by increased peripheral vascular resistance; this hemodynamic state may be associated with upregulated sensitivity of mechanoreceptors in the left ventricular posterior wall, and excessive activation of these receptors constitutes a key link in vagally mediated cardiac inhibition − . On the other hand, the possibility of reverse causality cannot be excluded. Episodes of malignant VVS may induce alterations in the compensatory blood pressure regulation mechanism, thereby resulting in elevated baseline DBP − . Additionally, a shared underlying pathophysiological mechanism may contribute to both conditions, such as neurohumoral regulatory disorders and autonomic nervous system imbalance. These factors may simultaneously drive the elevation of baseline DBP and the occurrence of malignant VVS . It is noteworthy that no intergroup differences in SBP were observed in this study, indicating that the hemodynamic characteristics of malignant VVS depend more on the state of peripheral vascular tone than on the absolute value of blood pressure alone. Most existing studies mainly focus on the pattern of blood pressure decline during syncope episodes, while paying insufficient attention to the association between baseline blood pressure and the severity of the disease. The results of this study help to fill this gap, but the mechanism still requires further verification. However, the causal direction of this association still requires further validation through prospective cohort studies or interventional studies to clarify whether an elevated baseline DBP is an independent risk factor for malignant vasovagal syncope or just an accompanying phenomenon. The Relationship between Central Triggers and Malignant Vasovagal Syncope This study found that central triggers were significantly associated with malignant VVS. The incidence of central triggers in the malignant group was significantly higher than that in the control group, which was consistent with the results of Furukaka T . In their research, they observed that the cardioinhibitory form was more prevalent among patients with a central trigger compared to those with vasodepressive or mixed forms. Expanding on this finding, we further clarified that a specific subtype of the cardioinhibitory form, malignant VVS, is linked to a higher incidence of central triggers. This tendency, characterized by an elevated proportion of central triggers in pediatric patients with malignant VVS, was also noted by Du . Mechanistically, central triggers regulate autonomic nervous system balance directly via the cortex-hypothalamus-vagus nerve pathway, whereas peripheral triggers primarily initiate reflex responses through changes in intravascular volume load. This fundamental difference in triggering pathways may result in substantial variations in the intensity of the autonomic reflex, thereby contributing to the malignant phenotype of VVS . From the perspective of neural regulation, emotional stress or nociceptive stimulation can activate the amygdala-insular cortex network, which then inhibits the sympathetic center and enhances vagal nerve output via descending nerve fibers. This central-driven autonomic nervous system imbalance is more likely to exceed the compensatory threshold, thereby leading to severe bradycardia or even cardiac arrest − . In contrast, peripheral triggers require multi-level regulation via the baroreceptor-medulla pathway, and the intensity of the resulting reflex is constrained by the intensity of the peripheral signal input − . This may explain why patients with central triggers are more likely to develop a malignant phenotype. In clinical practice, high vigilance should be maintained for VVS patients with definite central triggers. For instance, in patients who experience recurrent syncope induced by pain or emotional fluctuations, close follow-up via cohort studies is recommended even in the absence of a history of prolonged cardiac arrest, and potential risks should be evaluated using ambulatory electrocardiography. The results of this study provide an evidence-based foundation for trigger-based stratification in VVS patients, further optimizing the existing risk assessment system. Discriminatory Efficacy and Clinical Practicality of Different Diagnostic Models Among the three diagnostic models constructed in this study, the model combining DBP and central triggering factors exhibited the optimal discriminatory efficacy. The balance between its sensitivity and specificity was significantly superior to that of the single-index models, confirming the diagnostic value of integrating multidimensional indicators. However, this finding only reflects a correlational relationship between the integrated indicators and malignant VVS, rather than confirming a causal link. From the perspective of clinical practicality, DCA showed that all three models generated a net benefit and were significantly superior to the ineffective strategy. This net benefit enables the potential identification of patients at high risk of malignant VVS and provides a preliminary reference for intervention decisions, including cardiac neuroablation. It is crucial to underscore that the practical significance of these indicators lies solely in their correlational properties, rather than implying that modifying these parameters would directly impact disease progression or prognosis. Compared with the assessment tools recommended in existing guidelines, the models developed in this study exhibit significant advantages in clinical application. However, these advantages are predominantly manifested in their function as early screening indicators for malignant VVS, rather than serving as replacements for conclusive diagnostic tools. Currently, the head-up tilt test (HUT) is recognized as the gold standard for diagnosing VVS. However, HUT requires specific equipment and the collaboration of professional personnel for its implementation. Furthermore, it carries the risk of complications such as severe hypotension and arrhythmias. These limitations restrict its promotion and application in primary healthcare institutions and emergency scenarios . In contrast, the assessment models constructed in this study can facilitate rapid early identification and precise intervention for malignant VVS, relying on basic blood pressure measurement and inquiry about triggering factors. However, it should be clearly noted that the model offers significant pre-HUT value. Not only can it provide early screening clues for potential malignant VVS by analyzing correlational signals, but it also enables proactive identification of patients at risk of cardiac arrest during HUT. This enables the timely implementation of preventive therapeutic interventions prior to the procedure. Limitations This study has several limitations. First, the sample size was relatively small (n = 47), and a single-center retrospective design was adopted, which may have introduced selection bias. Specifically, the proportion of elderly patients was extremely low (only 3 cases), making it difficult to extrapolate the results to the elderly population. The age-related characteristics of malignant VVS still need to be clarified through multi-center large-sample studies. Second, long-term prognosis data were lacking. This study only evaluated diagnostic efficacy and did not conduct follow-ups on patients’ long-term outcome indicators; thus, the model’s predictive value for prognosis could not be verified. Additionally, the interaction between DBP and central triggering factors has not been explored, and whether a synergistic enhancement effect exists between the two remains unclear. Conclusion By comparing and analyzing the clinical and physiological indicators of patients with malignant and non-malignant vasovagal syncope (VVS), this study preliminarily elucidated potential screening indicators for malignant VVS and constructed a corresponding diagnostic model. Elevated baseline diastolic blood pressure and the presence of central triggers were associated with the occurrence of malignant VVS and could serve as potential core screening indicators for such patients. This finding provides an important reference for the individualized management of patients with VVS. Abbreviations DCA: decision curve analysis HUT: head-up tilt test HRV: heart rate variability PSM: propensity score matching ROC: receiver operating characteristic VVS: vasovagal syncope Declarations Funding This study was supported by the National Natural Science Foundation of China (82371595); Beijing Municipal Health Commission Scientific and Technological Achievements and Appropriate Technology Promotion Project (BHTPP2024101); Chinese Academy of Medical Sciences (CAMS) Clinical and Translational Medicine Research Program (2025-I2M-C&T-A-006); and CAMS Innovation Fund for Medical Sciences (2021-I2M-1-063). Conflict of interest statement: All authors have no conflicts to disclose. Funding This study was supported by the National Natural Science Foundation of China (82371595); Beijing Municipal Health Commission Scientific and Technological Achievements and Appropriate Technology Promotion Project (BHTPP2024101); Chinese Academy of Medical Sciences (CAMS) Clinical and Translational Medicine Research Program (2025-I2M-C&T-A-006); and CAMS Innovation Fund for Medical Sciences (2021-I2M-1-063). Data availability Data is available on a reasonable request to the corresponding authors. References Longo S, Legramante JM, Rizza S, Federici M. Vasovagal syncope: An overview of pathophysiological mechanisms. Eur J Intern Med. 2023; 112:6-14. Shimoda, H.; Yamauchi, K.; Takahashi, T. Transient asystole associated with vasovagal reflex in an oral surgery patient: A case report. SAGE Open Med. Case Rep. 2023, 11, 2050313X221146019. Hockin, B.C.D.; Lucci, V.M.; Wu, R.E.Y.; Nicholas, M.; Parsons, I.T.; Claydon, V.E. Pain associated with intravascular instrumentation reduces orthostatic tolerance and predisposes to vasovagal reactions in healthy young adults without needle phobia: A randomised controlled study. Clin. Auton. Res. 2023, 33, 673–689. Xu WR, Jin HF, Du JB, Liao Y. Malignant vasovagal syncope in children. World J Pediatr. 2025;21(1):41-47. doi:10.1007/s12519-024-00867-2 Shen WK, Sheldon RS, Benditt DG, Cohen MI, Forman DE, Goldberger ZD, Grubb BP, Hamdan MH, Krahn AD, Link MS, Olshansky B, Raj SR, Sandhu RK, Sorajja D, Sun BC, Yancy CW. 2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Circulation. 2017;136(5): e60-e122. Wang, C.; Liao, Y.; Wang, S.; Tian, H.; Huang, M.; Dong, X.Y.; Shi, L.; Li, Y.Q.; Sun, J.H.; Du, J.B.; et al. Guidelines for the diagnosis and treatment of neurally mediated syncope in children and adolescents (revised 2024). World J. Pediatr. 2024, 20, 983–1002. Ayabe K, Komiyama T, Hasegawa M, Sakai T, Morise M, Sakama S, Yagishita A, Amino M, Ikari Y, Yoshioka K. Clinical Significance of the Head-Up Tilt Test in Improving Prognosis in Patients with Possible Neurally Mediated Syncope. Biology (Basel). 2021;10(9):919. Zhao T, Wang S, Wang M, Cai H, Wang Y, Xu Y, Zou R, Wang C. Research progress on the predictive value of electrocardiographic indicators in the diagnosis and prognosis of children with vasovagal syncope. Front Cardiovasc Med. 2022; 9:916770. Brignole M, Moya A, de Lange FJ, et al. 2018 ESC Guidelines for the diagnosis and management of syncope. Eur Heart J. Jun 1, 2018;39(21):1883-1948. Brignole M, Moya A, de Lange FJ, et al. Practical Instructions for the 2018 ESC Guidelines for the diagnosis and management of syncope. Eur Heart J. Jun 1, 2018;39(21): e43-e80. Bauer A, Kantelhardt JW, Bunde A, Malik M, Schneider R, Schmidt G. Phase-rectified signal averaging detects quasi-periodicities in non-stationary data. Physica A: Statistical Mechanics and its Applications. 2006; 364:423-434. van Dijk, J.G.; van Rossum, I.A.; Thijs, R.D. The pathophysiology of vasovagal syncope: Novel insights. Auton. Neurosci. 2021,236, 102899 Chen JW, Maldonado DR, Kowalski BL, Miecznikowski KB, Kyin C, Gornbein JA, Domb BG. Best Practice Guidelines for Propensity Score Methods in Medical Research: Consideration on Theory, Implementation, and Reporting. A Review. Arthroscopy. 2022;38(2):632-642. Larson RA, Chapleau MW. Increased cardiac sympathetic activity: Cause or compensation in vasovagal syncope? Clin Auton Res. 2018;28(3):265-266. Zhang DY, Anderson AS. The sympathetic nervous system and heart failure. Cardiol Clin. 2014;32(1):33-45, vii. Liu P, Zeng X, Mei W, Wang Y, Zou R, Wang C. The predictive value of urine specific gravity in the diagnosis of vasovagal syncope in children and adolescents. Ital J Pediatr. 2021;47(1):93. Coiado O, Buiochi E, O'Brien W Jr. Ultrasound-induced heart rate decrease: role of the vagus nerve. IEEE Trans Ultrason Ferroelectr Freq Control. 2015;62(2):329-36. Fongemie J, Felix-Getzik E. A Review of Nebivolol Pharmacology and Clinical Evidence. Drugs. 2015;75(12):1349-71. Borovac JA, D'Amario D, Bozic J, Glavas D. Sympathetic nervous system activation and heart failure: Current state of evidence and the pathophysiology in the light of novel biomarkers. World J Cardiol. 2020;12(8):373-408. Furukawa, T.; Maggi, R.; Solano, A.; Croci, F.; Brignole, M. Effect of clinical triggers on positive responses to tilt-table testing potentiated with nitroglycerin or clomipramine. Am. J. Cardiol. 2011, 107, 1693–1697. Xu W, Zhang C, Du J, Jin H, Liao Y. Features of Clinical Manifestations and Heart Rate Variability in Children with Malignant Vasovagal Syncope. Children (Basel). 2025;12(5):636. Dias RM, Hoshi RA, Vanderlei LCM, Monteiro CBM, Alvarez MPB, Crocetta TB, Grossklauss LF, Fernani DCGL, Dantas MTAP, Martins FPA, Garner DM, Abreu LC, Ferreira C, da Silva TD. Influence of Different Types of Corticosteroids on Heart Rate Variability of Individuals with Duchenne Muscular Dystrophy-A Pilot Cross Sectional Study. Life (Basel). 2021;11(8):752. Omole JG, Okon IA, Udom GJ, Aziakpono OM, Agbana RD, Aturamu A, Niwamanya N, Oritsemuelebi B, Etukudo EM, Yemitan OK. Neurophysiological mechanisms underlying cardiovascular adaptations to exercise: A narrative review. Physiol Rep. 2025;13(13): e70439. Steenbergen L, Maraver MJ, Actis-Grosso R, Ricciardelli P, Colzato LS. Recognizing emotions in bodies: Vagus nerve stimulation enhances recognition of anger while impairing sadness. Cogn Affect Behav Neurosci. 2021;21(6):1246-1261. Furukawa T, Maggi R, Solano A, Croci F, Brignole M. Effect of clinical triggers on positive responses to tilt-table testing potentiated with nitroglycerin or clomipramine. Am J Cardiol. 2011;107(11):1693-7. Previgliano IJ, Aboumarie HS, Tamagnone FM, Merlo PM, Sosa FA, Feijoo J, Carruega MC. Point of care ultrasound evaluation of cardio-cerebral coupling. World J Crit Care Med. 2025;14(3):101462. Zhang Z, Jiang X, Han L, Chen S, Tao L, Tao C, Tian H, Du J. Differential Diagnostic Models Between Vasovagal Syncope and Psychogenic Pseudosyncope in Children. Front Neurol. 2020; 10:1392. Tables Table 1 Demographic characteristics of malignant VVS patients and controls before PSM Malignant VVS (n = 26) Controls (n = 95) P value Age, yrs 39.00(22.75) 45.00(31.75) 0.631 Male, n (%) 9(42.3) 34 (75.6) 0.542 Height, m 168.62±8.58 166.98±7.63 0.352 Weight, kg 69.50(15.50) 64.00(19.25) 0.076 BMI, kg/m² 23.17(3.13) 23.10(5.00) 0.398 Values are presented as mean±standard deviation, median (interquartile range), or number (percentage). Abbreviations: BMI, body mass index; VVS, vasovagal syncope. Table 2 Demographic and clinical characteristics of malignant VVS patients and controls after PSM Malignant VVS (n = 26) Controls (n = 21) P value Age, yrs 39.00(22.75) 28.00(27.00) 0.067 Male, n (%) 9(42.3) 8 (26.1) 0.234 Height, m 168.62±8.58 167.04±6.57 0.480 Weight, kg 69.50(15.50) 62.00(15.00) 0.076 BMI, kg/m² 23.17(3.13) 22.06(7.45) 0.136 Characteristics of syncope Age of onset, yrs 29.00(25.50) 16.00(17.00) 0.311 Number of syncope episodes, n 3.50(6.25) 4.00(8.00) 0.732 Number of pre-syncope episodes, n 3.00 (10.50) 8.00 (37.00) 0.123 Symptom duration, mins 0.54(3.67) 2.00(3.25) 0.074 Calgary score -0.38±4.05 0.13±4.17 0.663 History, yrs 10.00(23,50) 7.00(18.00) 0.346 Family history, n (%) 6(23.10) 7(30.40) 0.560 Trauma history, n (%) 13 (50.00) 8(34.80) 0.283 Central triggers, n (%) 14(53.80) 5(21.70) 0.021 Past medical history Hypertension, n (%) 3(11.50) 1(4.30) 0.359 Medication, n (%) 3(11.50) 3(13.00) 0.873 Alcohol, n (%) 2(7.70) 2(8.70) 0.898 Cigarette, n (%) 4(15.40) 0(0.00) 0.150 Values are presented as mean±standard deviation, median (interquartile range), or number (percentage). Abbreviations: BMI, body mass index; VVS, vasovagal syncope. Central tiggers include fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia. Table 3 HRV metrics of malignant VVS patients and controls Malignant VVS (n = 26) Controls (n = 21) P value SDNN 143.50(79.24) 137.00(71.97) 0.992 rMSSD 37.00(32.84) 37.00(15.00) 0.515 pNN50(%) 13.17(24.63) 13.03(6.10) 0.920 TI 26.00(17.18) 27.00(19.17) 0.674 LF 563.80(671.65) 535.20(596.56) 0.810 HF 375.85(812.63) 378.80(541.50) 0.764 LF/HF 1.34(1.15) 1.58(0.70) 0.440 DC, ms 7.31(2.33) 6.80(2.60) 0.912 AC, ms -7.97±2.25 -7.32±2.94 0.387 Values are presented as mean (standard deviation) or median (interquartile range). Abbreviations: AC, acceleration capacity; DC, deceleration capacity; HF, high frequency; HRV, heart rate variability; LF, low frequency; LF/HF, the ratio of LF to HF; pNN50,percent of differences between adjacent normal to normal intervals greater than 50 milliseconds; rMSSD, root mean square of successive normal-to-normal differences; SDNN, standard deviation of normal-to-normal intervals; TI, triangular index; VVS, vasovagal syncope. Table 4 Hemodynamic indicators of malignant VVS patients and controls Malignant VVS (n = 26) Controls (n = 21) P value Mean HR, bpm 70.31±11.77 69.35±13.22 0.789 Systolic BP, mmHg 120.04±13.86 114.0 ±9.57 0.086 Diastolic BP, mmHg 75.88±9.42 66.83±7.19 ＜ 0.001 Values are presented as mean (standard deviation), median [interquartile range], or number (percentage). Abbreviations: BP, blood pressure; bpm, beats per minute; HR, heart rate; VVS, vasovagal syncope. Table 5 Univariate and multivariate logistic regression analysis for indicators of malignant VVS patients and controls Univariate Multivariate OR (95% CI) P value OR (95% CI) P value Age 1.03 (0.99-1.07) 0.093 Weight 1.05 (0.99-1.10) 0.065 Symptom duration 0.72 (0.52-1.00) 0.056 Central triggers 4.20(1.20,14.74) 0.025 5.82(1.13,30.02) 0.035 Systolic BP 1.05 (0.99-1.10) 0.095 Diastolic BP 1.14 (1.05-1.25) 0.002 1.27 (1.06-1.51) 0.010 Abbreviations: CI, confidence interval; OR, odds ratio; BP, blood pressure. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8623153","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":586638850,"identity":"8fac07ed-4381-4634-9298-2778fe6e0d61","order_by":0,"name":"Xinyi Wang","email":"","orcid":"","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Wang","suffix":""},{"id":586638851,"identity":"ca45eaad-bdb3-4d1d-9e75-c985d6470119","order_by":1,"name":"Aiyue Chen","email":"","orcid":"","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":false,"prefix":"","firstName":"Aiyue","middleName":"","lastName":"Chen","suffix":""},{"id":586638852,"identity":"7ca8890c-bcab-4531-9cb6-2d76f4973bfe","order_by":2,"name":"Bin Tu","email":"","orcid":"","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":false,"prefix":"","firstName":"Bin","middleName":"","lastName":"Tu","suffix":""},{"id":586638853,"identity":"07813dd8-dc34-4e5c-8729-c19c09952d18","order_by":3,"name":"Pakezhati Maimaitijiang","email":"","orcid":"","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":false,"prefix":"","firstName":"Pakezhati","middleName":"","lastName":"Maimaitijiang","suffix":""},{"id":586638854,"identity":"2e6ffafb-a4f4-47f4-9cf2-062b2b304525","order_by":4,"name":"Lihui Zheng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYDACCRBRIJHAwMx88MGHH0RrMQBpYUs2nNkD5LARp4UhgYGBx0yag40ILfKzm489/GJgkWdwnOeDNAMPQx6/fAN+LYxzjqUbyxhIFBsc5t1gXGDBUCzZRsAWZokcM2kJA4nEDUAtyTN4GBI3HCOghU0i/xtUC8+DwzxsDIn7CWnhkchhk/wA0cLYDNKygZD3JSTSzKSBgZw48zCbMePMHonEGccS8GuRn5H8TPJHRV1i3/nDz398+GGT2N98gIA1QMDMg2QrYeUgwEhUMhkFo2AUjIKRCwD+cT56pYPQHQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0000-2867-411X","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":true,"prefix":"","firstName":"Lihui","middleName":"","lastName":"Zheng","suffix":""},{"id":586638855,"identity":"007d915c-5798-46e6-a8d6-e776a0f4de6d","order_by":5,"name":"Yan Yao","email":"","orcid":"","institution":"Fuwai Hospital State Key Laboratory of Cardiovascular Disease","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Yao","suffix":""}],"badges":[],"createdAt":"2026-01-17 03:25:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8623153/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8623153/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102376444,"identity":"c4705784-cbd9-467e-8579-388dee3adb3e","added_by":"auto","created_at":"2026-02-11 05:31:26","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62988,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curve for differentiating malignant VVS using DBP.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8623153/v1/ce0f5b016770ee0575fe3103.png"},{"id":102398247,"identity":"ce862e07-e1db-43bc-ae85-e103c7478660","added_by":"auto","created_at":"2026-02-11 10:21:54","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":405380,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC curves for differentiating malignant VVS using different diagnostic models.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8623153/v1/4841843df9bb60cccf9ac057.png"},{"id":102376445,"identity":"86908072-bf88-4ffe-b40b-e3ab3d47d386","added_by":"auto","created_at":"2026-02-11 05:31:26","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":86846,"visible":true,"origin":"","legend":"\u003cp\u003eThe DCA curves of different prediction models.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8623153/v1/6a20d46b7eb8b18e303daf69.png"},{"id":102970964,"identity":"8b870395-b6bc-46ab-8ca1-2cce87d7dda6","added_by":"auto","created_at":"2026-02-19 06:08:17","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1309084,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8623153/v1/1cab2f79-fa18-48b3-b426-d725c694e454.pdf"}],"financialInterests":"","formattedTitle":"Comparison of clinical characteristics between malignant and non-malignant vasovagal syncope based on propensity score matching","fulltext":[{"header":"Introduction","content":"\u003cp\u003eVasovagal syncope (VVS) is one of the main causes of syncope in patients. It may occur with or without obvious precipitating factors and is characterized by hemodynamic changes in heart rate and blood pressure, resulting in a transient loss of consciousness\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e. Orthostatic stress is the most common trigger for VVS and is classified as a peripheral trigger. In addition, emotional stressors, including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia, can also mediate VVS onset and are defined as central triggers\u003ca class=\"FNLink\" href=\"#Fn2\" id=\"#FNLinkFn2\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn3\" id=\"#FNLinkFn3\"\u003e\u003c/a\u003e. In most cases, patients with VVS show self-limiting progression or a favorable prognosis without leaving any sequelae. However, in patients with more severe clinical manifestations of VVS, a prolonged episode of cardiac arrest often occurs during the onset of syncope, which is closely associated with an increased risk of subsequent systemic organ damage\u003ca class=\"FNLink\" href=\"#Fn4\" id=\"#FNLinkFn4\"\u003e\u003c/a\u003e. Clinically, VVS cases characterized by such prolonged cardiac arrest and high risk of organic damage are defined as malignant VVS, as well as a preference for the implantation of pacemakers\u003ca class=\"FNLink\" href=\"#Fn5\" id=\"#FNLinkFn5\"\u003e\u003c/a\u003e. Some researchers define malignant VVS as a cardiac arrest lasting more than 3 seconds\u003ca class=\"FNLink\" href=\"#Fn6\" id=\"#FNLinkFn6\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn7\" id=\"#FNLinkFn7\"\u003e\u003c/a\u003e. Clinically, malignant VVS requires active intervention to mitigate these risks, but its low prevalence and diagnostic challenges hinder effective identification. Currently, research focusing on patients with malignant VVS remains scarce, and the key risk factors specific to this distinct population have not yet been fully elucidated. In this study, we compared the demographics, clinical characteristics, and heart rate variability (HRV) of VVS patients with and without cardiac arrest and further provided some clinical clues for its early detection and screening.\u003c/p\u003e\n\u003ch3\u003eStudy Design and Subjects\u003c/h3\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy population\u003c/h2\u003e \u003cp\u003eThis observational study consecutively recruited patients who were diagnosed with VVS and visited Fuwai Hospital, Chinese Academy of Medical Sciences (Beijing, China) from March 2023 to March 2025. All subjects received 24-hour ambulatory electrocardiogram (ECG) monitoring as part of the routine syncope examination. Meanwhile, a head-up tilt test (HUT) was conducted to assist in the diagnosis of VVS and clarify the hemodynamic pattern.\u003c/p\u003e \u003cp\u003eThe diagnostic criteria for VVS are as follows: The clinical features are consistent with the mechanism of reflex syncope. After comprehensive examinations, other competing diagnoses are excluded, and the diagnosis is verified and confirmed by professional cardiologists in accordance with the European Society of Cardiology (ESC) Guidelines for the Diagnosis and Management of Syncope\u003ca class=\"FNLink\" href=\"#Fn8\" id=\"#FNLinkFn8\"\u003e\u003c/a\u003e. If a record, confirmed by an electrocardiogram (ECG), shows the heart stopping for more than 3 seconds during a syncope episode, and there are no other diseases that can cause syncope, the patient is classified in the malignant group. The control group consisted of VVS patients who were admitted to the syncope ward during the same period. When they had a syncope episode, the cardiac arrest duration did not exceed 3 seconds. These patients were matched 1:1 with the malignant group according to age and gender. Exclusion criteria were as follows:\u003c/p\u003e \u003cp\u003e(1) syncope due to orthostatic hypotension or arrhythmias (e.g., supraventricular or ventricular tachycardia, Mobitz II second- or third-degree atrioventricular block, sinus node dysfunction, Brugada syndrome, or long QT syndrome).\u003c/p\u003e \u003cp\u003e(2) structural cardiac disease (e.g., congenital heart disease, cardiomyopathy, or valvular heart disease) or cardiopulmonary disease (e.g., pulmonary embolism, pulmonary hypertension).\u003c/p\u003e \u003cp\u003e(3) a history of myocardial infarction, heart failure, or cerebrovascular disease.\u003c/p\u003e \u003cp\u003e(4) other disease that affected the autonomic system (e.g., diabetes mellitus or hyperthyroidism).\u003c/p\u003e \u003cp\u003e(5) a treatment history of catheter ablation, pacemaker implantation, cardiac surgery, or medication affecting autonomic function (e.g., beta-blockers or anticholinergics).\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical approval\u003c/strong\u003e \u003cp\u003e was obtained from the Institutional Ethics Committee of Fuwai Hospital, ensuring that all research procedures adhered to the Declaration of Helsinki. Written informed consent was obtained from each participant before enrollment.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHead-up tilt test\u003c/h3\u003e\n\u003cp\u003eHUT comprising a passive phase at a tilt angle of 60\u0026ndash;70\u0026ordm; and an additional provocative phase with sublingual administration of 0.35 mg nitroglycerine (if the passive phase is negative) was performed according to the conventional protocol delineated in the ESC syncope guidelines\u003ca class=\"FNLink\" href=\"#Fn9\" id=\"#FNLinkFn9\"\u003e\u003c/a\u003e. The test was continued until either complete loss of consciousness occurred or the protocol was completed. The positive response to HUT was defined as the reproduction of spontaneous syncope with characteristic hemodynamic patterns of hypotension and bradycardia, which was further categorized into vasodepressor, mixed, or cardioinhibitory forms based on the VASIS classification\u003csup\u003e5\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eHolter recording\u003c/h3\u003e\n\u003cp\u003eAll participants underwent 24-hour ambulatory 12-lead Holter monitoring under hospital-supervised conditions. They were instructed to maintain habitual daily activities to reflect real-world autonomic responses, while adhering to regular sleep-wake patterns for relatively consistent circadian rhythm. Additionally, strenuous physical activities were prohibited during the monitoring period. The recordings digitized at 128 Hz were processed using dedicated analytical software (MIC-12H Analysis Platform; Jinke Instruments, Beijing, China), which employed adaptive thresholding and morphology-based algorithms for QRS complex identification and classification. To optimize accuracy while balancing automation efficiency with expert validation, automated outputs underwent two-stage manual verification: (1) pre-analytical signal quality control to eliminate artifact-contaminated segments; (2) post-processing review by board-certified physicians to rectify ectopic beat misclassification. To quantify parasympathetic activity, DC and AC are calculated based on the phase-rectified signal averaging (PRSA) algorithm\u003ca class=\"FNLink\" href=\"#Fn10\" id=\"#FNLinkFn10\"\u003e\u003c/a\u003e.\u003c/p\u003e\n\u003ch3\u003eClinical data collection\u003c/h3\u003e\n\u003cp\u003eCollect the clinical characteristics of patients, including gender, age, height, weight, body mass index (BMI), heart rate (HR), systolic blood pressure (SBP), diastolic blood pressure (DBP), history of hypertension, medication history, drinking history, and smoking history. Record detailed medical history, including the age at which the patient experienced syncope, disease duration, number of episodes, number of prodromal episodes, symptom duration, Calgary Score, history of syncope-related trauma, and family history of typical VVS episodes.\u003c/p\u003e \u003cp\u003eThe precipitating factors can be categorized into two distinct groups based on the anatomical and functional origins of triggering stimuli, namely peripheral triggering factors and central triggers.\u003ca class=\"FNLink\" href=\"#Fn11\" id=\"#FNLinkFn11\"\u003e\u003c/a\u003e. Peripheral triggering factors include prolonged standing, postural changes, and after exercise. Central triggers include intramuscular injections, venipuncture, emotional stress, and pain.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using SPSS 26.0 (IBM, Armonk, NY, USA) and R software (version 4.3.3, R Foundation for Statistical Computing, Vienna, Austria). Given the small sample size of patients with malignant VVS, the purpose of using propensity score matching (PSM) in this study was not to adjust for existing baseline confounders. Instead, it aimed to select a subset of control samples that were more closely matched to the case group in terms of characteristics from an excessive number of control samples, under the premise that there were no significant differences in baseline data. This approach helps reduce the potential impact of uneven sample sizes on analysis results, thereby improving the stability and comparability between groups. After installing the PS Matching module in SPSS 26.0 statistical software, PSM was performed using a 0.2 SD calliper matching ratio of 1:1\u003ca class=\"FNLink\" href=\"#Fn12\" id=\"#FNLinkFn12\"\u003e\u003c/a\u003e. The propensity score values were calculated using a logistic regression model, with matching factors including patient age, Body Mass Index (BMI), and gender. The general clinical data of patients in the malignant VVS group and the control group were compared before and after PSM. The Shapiro-Wilk test was used to examine the normality of continuous data. For continuous variables that followed a normal distribution, the data were presented as (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation), and the paired t-test was used for between-group comparisons, considering the matched nature of the data after PSM. For continuous variables that did not follow a normal distribution, the data were presented as median (interquartile range, IQR), and the Wilcoxon signed-rank test was used to compare differences between the matched groups.​Categorical data were presented as n (%) and analyzed using the McNemar test or Fisher\u0026rsquo;s exact test for McNemar\u0026rsquo;s design, replacing the conventional chi-square test to account for the paired structure of the PSM-matched samples. A P value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.​To identify the risk factors for malignant VVS, conditional binary logistic regression analysis was applied, as this method is specifically designed for matched data and can effectively control for the confounding effects introduced by the matching process. For the multivariable conditional logistic regression model, variables with a P value\u0026thinsp;\u0026lt;\u0026thinsp;0.10 in the univariate conditional logistic regression analysis, as well as gender (a clinically important covariate), were initially included. Forward variable selection was used to remove non-significant variables until all remaining variables were significant at the 0.05 level. All tests were two-tailed, and effect sizes were expressed as the odds ratio (OR) and its 95% confidence interval (95% CI).\u003c/p\u003e \u003cp\u003eThe receiver operating characteristic (ROC) curve was used to evaluate the discriminatory ability of malignant VVS, and the area under the curve (AUC) was calculated; the optimal cut-off value was determined by maximizing Youden's index to balance sensitivity and specificity. To clarify the clinical utility of the predictive model for malignant VVS constructed based on multifactorial logistic regression in this study, decision curve analysis (DCA) was used to quantify the difference in net benefit between the model and traditional strategies at different clinical decision thresholds, to compensate for the limitation of relying solely on the ROC curve to evaluate the model's discriminatory ability while ignoring clinical benefits. The rmda package in R software version 4.3.3 was used to plot the DCA curve, and the net benefit rates of these three strategies were calculated within the threshold probability range of 0\u0026ndash;100%.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBasic Information of the Studied Patients\u003c/h2\u003e \u003cp\u003eBefore PSM, there were 26 patients in the malignant VVS group and 95 patients in the control group,with an 80.8% matching success rate. Comparisons of general clinical data, including age, gender, and BMI, between the two groups showed no statistically significant differences (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), as shown in \u003cb\u003eTable\u0026nbsp;1\u003c/b\u003e. After successful PSM, 21 patients in the control group were matched with those in the study group. A total of 47 patients (17 males and 30 females) were finally enrolled in this study. The mean age of the study population was 37.71\u0026thinsp;\u0026plusmn;\u0026thinsp;15.93 years, with young patients being the majority (a ratio of 46:3; note: young and elderly patients were defined in accordance with the WHO criteria for age stratification). All enrolled cases reported no history of trauma prior to syncopal episodes, nor did they have a history of systemic diseases, heart diseases, or neurological diseases. Additionally, no positive findings were identified during physical examination for any of the participants.\u003c/p\u003e \u003cp\u003eComparisons of demographic characteristics and clinical features between the malignant VVS group and the control group are presented in \u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e. At the time of admission, there were no statistically significant differences between the two groups in terms of age, gender distribution, height, weight, or BMI. Notably, the incidence of central triggers, including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia, was significantly higher in the malignant VVS group than in the control group (53.8% vs. 26.3%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In contrast, no significant between-group differences were observed in terms of age of onset, number of syncopal episodes, number of premonitory syncopal episodes, symptom duration, Calgary score, medical history, family history, and trauma history between the two groups. Regarding the past medical history, there were no significant differences in the history of hypertension, medication history, alcohol history, and smoking history between the two populations.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eHeart Rate Variability (HRV)\u003c/h3\u003e\n\u003cp\u003eAfter 24-hour Holter monitoring was performed in patients of both groups, statistical analysis revealed no significant differences in multiple HRV parameters including standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (rMSSD), low-frequency power (LF), high-frequency power (HF), LF/HF ratio, acceleration capacity(AC) component, and deceleration capacity (DC) component between the malignant VVS group and the control group (Table\u0026nbsp;3).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eHemodynamic Indicators\u003c/h2\u003e \u003cp\u003eWhen comparing the hemodynamic parameters between the two populations, no statistically significant differences were observed in HR or SBP (Table\u0026nbsp;4). In contrast, a statistically significant difference in DBP was detected between the two groups (75.88\u0026thinsp;\u0026plusmn;\u0026thinsp;1.85 mmHg vs. 66.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.50 mmHg, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).​Furthermore, a ROC curve was constructed to evaluate the discriminatory performance of DBP for identifying malignant VVS, and the results demonstrated good diagnostic efficacy (AUC\u0026thinsp;=\u0026thinsp;0.781; 95% CI\u0026thinsp;=\u0026thinsp;0.652\u0026ndash;0.910). Using the Youden index to determine the optimal cut-off value of DBP (75.5 mmHg), the diagnostic model achieved a sensitivity of 87.0% and a specificity of 57.7% (Fig.\u0026nbsp;1).​\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eRisk Factors for Malignant Vasovagal Syncope\u003c/h2\u003e \u003cp\u003eIn the univariate analysis, six variables, namely age, weight, symptom duration, central triggers (including fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia), SBP, and DBP, exhibited statistically significant differences between the malignant VVS group and the control group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.1). These variables were further included as candidate predictors in a subsequent multivariate logistic regression analysis, whose purpose was to identify independent risk factors for malignant VVS.​ The results of the multivariate logistic regression analysis showed that both central triggers and DBP were independent predictors of malignant VVS. The odds ratios (95% confidence intervals) for central triggers and DBP were 6.65 (1.42\u0026ndash;31.19) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and 1.17 (1.07\u0026ndash;1.29) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), respectively (Table\u0026nbsp;5).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eComparison of the Efficacy of Different Diagnostic Models\u003c/h2\u003e \u003cp\u003eTo evaluate the diagnostic efficacy of three strategies for malignant VVS, namely DBP alone, central triggers alone, and the combination of these two, ROC curves were constructed to assess the discriminatory ability of each strategy.​As presented in Fig.\u0026nbsp;2, the combined use of DBP and central triggers exhibited the highest diagnostic efficacy, with an AUC of 0.846 (95% confidence interval [95% CI]: 0.737\u0026ndash;0.955). In comparison, the AUC value for DBP alone was 0.781 (95% CI: 0.652\u0026ndash;0.910), and that for central triggers alone was 0.661 (95% CI: 0.530\u0026ndash;0.791).​Using the Youden index to determine the optimal cut-off value for DBP (75.5 mmHg) and taking the presence of central triggers as a positive indicator, the combined diagnostic strategy achieved a sensitivity of 78.3% and a specificity of 80.8%.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEvaluation of the Clinical Practicality of the Prediction Model\u003c/h2\u003e \u003cp\u003eTo further clarify the clinical practicality of the prediction model for malignant VVS constructed based on DBP and central triggers, DCA was conducted. As shown in Fig.\u0026nbsp;3, all three models generated a net benefit and were significantly superior to the ineffective strategy.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eMajor Findings\u003c/h2\u003e \u003cp\u003eIn this study, we identified correlations between DBP levels, central triggers, and the specific patient group with malignant VVS. Compared with patients with non-malignant VVS, those with malignant VVS had higher DBP levels and more frequent central triggers.Notably, when DBP exceeded 75.5 mmHg, it showed strong discriminatory power for malignant VVS. Additionally, combining DBP with central triggers further improved diagnostic performance. These correlational findings provided a preliminary reference for clinical practice.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eThe Relationship between Diastolic Blood Pressure and Malignant Vasovagal Syncope\u003c/h2\u003e \u003cp\u003eThis study is the first to demonstrate that elevated DBP is an independent risk factor for malignant VVS. When 75.5 mmHg is used as the cut-off value, it exhibits the optimal diagnostic efficacy, providing a quantitative indicator for clinical screening of malignant VVS. This finding may be associated with the classic pathophysiological mechanism of vasovagal syncope. Under normal physiological conditions, when the human body is in an upright position, baroreceptors maintain blood pressure stability by activating the sympathetic nervous system. In patients with vasovagal syncope, however, the autonomic compensatory reflex is impaired, which is manifested as an abnormal response characterized by vasodilation and bradycardia\u003ca class=\"FNLink\" href=\"#Fn13\" id=\"#FNLinkFn13\"\u003e\u003c/a\u003e.\u003c/p\u003e \u003cp\u003eMultiple possibilities exist regarding the causal relationship between elevated DBP and malignant VVS. Elevated baseline DBP may exacerbate the intensity of the vagal reflex through two potential pathways. First, long-term elevation of DBP may reset the threshold of baroreceptors, increasing the sensitivity of the vasomotor center to changes in volume load. When a triggering factor induces reduced ventricular filling, it is more likely to trigger excessive vagal activation, ultimately leading to prolonged cardiac arrest. Second, elevated DBP is often accompanied by increased peripheral vascular resistance; this hemodynamic state may be associated with upregulated sensitivity of mechanoreceptors in the left ventricular posterior wall, and excessive activation of these receptors constitutes a key link in vagally mediated cardiac inhibition\u003ca class=\"FNLink\" href=\"#Fn14\" id=\"#FNLinkFn14\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn15\" id=\"#FNLinkFn15\"\u003e\u003c/a\u003e.\u003c/p\u003e \u003cp\u003eOn the other hand, the possibility of reverse causality cannot be excluded. Episodes of malignant VVS may induce alterations in the compensatory blood pressure regulation mechanism, thereby resulting in elevated baseline DBP\u003ca class=\"FNLink\" href=\"#Fn16\" id=\"#FNLinkFn16\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn17\" id=\"#FNLinkFn17\"\u003e\u003c/a\u003e. Additionally, a shared underlying pathophysiological mechanism may contribute to both conditions, such as neurohumoral regulatory disorders and autonomic nervous system imbalance. These factors may simultaneously drive the elevation of baseline DBP and the occurrence of malignant VVS\u003ca class=\"FNLink\" href=\"#Fn18\" id=\"#FNLinkFn18\"\u003e\u003c/a\u003e. It is noteworthy that no intergroup differences in SBP were observed in this study, indicating that the hemodynamic characteristics of malignant VVS depend more on the state of peripheral vascular tone than on the absolute value of blood pressure alone.\u003c/p\u003e \u003cp\u003eMost existing studies mainly focus on the pattern of blood pressure decline during syncope episodes, while paying insufficient attention to the association between baseline blood pressure and the severity of the disease. The results of this study help to fill this gap, but the mechanism still requires further verification. However, the causal direction of this association still requires further validation through prospective cohort studies or interventional studies to clarify whether an elevated baseline DBP is an independent risk factor for malignant vasovagal syncope or just an accompanying phenomenon.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eThe Relationship between Central Triggers and Malignant Vasovagal Syncope\u003c/h2\u003e \u003cp\u003eThis study found that central triggers were significantly associated with malignant VVS. The incidence of central triggers in the malignant group was significantly higher than that in the control group, which was consistent with the results of Furukaka T\u003ca class=\"FNLink\" href=\"#Fn19\" id=\"#FNLinkFn19\"\u003e\u003c/a\u003e. In their research, they observed that the cardioinhibitory form was more prevalent among patients with a central trigger compared to those with vasodepressive or mixed forms. Expanding on this finding, we further clarified that a specific subtype of the cardioinhibitory form, malignant VVS, is linked to a higher incidence of central triggers. This tendency, characterized by an elevated proportion of central triggers in pediatric patients with malignant VVS, was also noted by Du\u003ca class=\"FNLink\" href=\"#Fn20\" id=\"#FNLinkFn20\"\u003e\u003c/a\u003e. Mechanistically, central triggers regulate autonomic nervous system balance directly via the cortex-hypothalamus-vagus nerve pathway, whereas peripheral triggers primarily initiate reflex responses through changes in intravascular volume load. This fundamental difference in triggering pathways may result in substantial variations in the intensity of the autonomic reflex, thereby contributing to the malignant phenotype of VVS\u003ca class=\"FNLink\" href=\"#Fn21\" id=\"#FNLinkFn21\"\u003e\u003c/a\u003e.\u003c/p\u003e \u003cp\u003eFrom the perspective of neural regulation, emotional stress or nociceptive stimulation can activate the amygdala-insular cortex network, which then inhibits the sympathetic center and enhances vagal nerve output via descending nerve fibers. This central-driven autonomic nervous system imbalance is more likely to exceed the compensatory threshold, thereby leading to severe bradycardia or even cardiac arrest\u003ca class=\"FNLink\" href=\"#Fn22\" id=\"#FNLinkFn22\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn23\" id=\"#FNLinkFn23\"\u003e\u003c/a\u003e. In contrast, peripheral triggers require multi-level regulation via the baroreceptor-medulla pathway, and the intensity of the resulting reflex is constrained by the intensity of the peripheral signal input\u003ca class=\"FNLink\" href=\"#Fn24\" id=\"#FNLinkFn24\"\u003e\u003c/a\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e\u003ca class=\"FNLink\" href=\"#Fn25\" id=\"#FNLinkFn25\"\u003e\u003c/a\u003e. This may explain why patients with central triggers are more likely to develop a malignant phenotype.\u003c/p\u003e \u003cp\u003eIn clinical practice, high vigilance should be maintained for VVS patients with definite central triggers. For instance, in patients who experience recurrent syncope induced by pain or emotional fluctuations, close follow-up via cohort studies is recommended even in the absence of a history of prolonged cardiac arrest, and potential risks should be evaluated using ambulatory electrocardiography. The results of this study provide an evidence-based foundation for trigger-based stratification in VVS patients, further optimizing the existing risk assessment system.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eDiscriminatory Efficacy and Clinical Practicality of Different Diagnostic Models\u003c/h2\u003e \u003cp\u003eAmong the three diagnostic models constructed in this study, the model combining DBP and central triggering factors exhibited the optimal discriminatory efficacy. The balance between its sensitivity and specificity was significantly superior to that of the single-index models, confirming the diagnostic value of integrating multidimensional indicators. However, this finding only reflects a correlational relationship between the integrated indicators and malignant VVS, rather than confirming a causal link.\u003c/p\u003e \u003cp\u003eFrom the perspective of clinical practicality, DCA showed that all three models generated a net benefit and were significantly superior to the ineffective strategy. This net benefit enables the potential identification of patients at high risk of malignant VVS and provides a preliminary reference for intervention decisions, including cardiac neuroablation. It is crucial to underscore that the practical significance of these indicators lies solely in their correlational properties, rather than implying that modifying these parameters would directly impact disease progression or prognosis.\u003c/p\u003e \u003cp\u003e Compared with the assessment tools recommended in existing guidelines, the models developed in this study exhibit significant advantages in clinical application. However, these advantages are predominantly manifested in their function as early screening indicators for malignant VVS, rather than serving as replacements for conclusive diagnostic tools. Currently, the head-up tilt test (HUT) is recognized as the gold standard for diagnosing VVS. However, HUT requires specific equipment and the collaboration of professional personnel for its implementation. Furthermore, it carries the risk of complications such as severe hypotension and arrhythmias. These limitations restrict its promotion and application in primary healthcare institutions and emergency scenarios\u003ca class=\"FNLink\" href=\"#Fn26\" id=\"#FNLinkFn26\"\u003e\u003c/a\u003e. In contrast, the assessment models constructed in this study can facilitate rapid early identification and precise intervention for malignant VVS, relying on basic blood pressure measurement and inquiry about triggering factors. However, it should be clearly noted that the model offers significant pre-HUT value. Not only can it provide early screening clues for potential malignant VVS by analyzing correlational signals, but it also enables proactive identification of patients at risk of cardiac arrest during HUT. This enables the timely implementation of preventive therapeutic interventions prior to the procedure.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, the sample size was relatively small (n\u0026thinsp;=\u0026thinsp;47), and a single-center retrospective design was adopted, which may have introduced selection bias. Specifically, the proportion of elderly patients was extremely low (only 3 cases), making it difficult to extrapolate the results to the elderly population. The age-related characteristics of malignant VVS still need to be clarified through multi-center large-sample studies. Second, long-term prognosis data were lacking. This study only evaluated diagnostic efficacy and did not conduct follow-ups on patients\u0026rsquo; long-term outcome indicators; thus, the model\u0026rsquo;s predictive value for prognosis could not be verified. Additionally, the interaction between DBP and central triggering factors has not been explored, and whether a synergistic enhancement effect exists between the two remains unclear.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBy comparing and analyzing the clinical and physiological indicators of patients with malignant and non-malignant vasovagal syncope (VVS), this study preliminarily elucidated potential screening indicators for malignant VVS and constructed a corresponding diagnostic model. Elevated baseline diastolic blood pressure and the presence of central triggers were associated with the occurrence of malignant VVS and could serve as potential core screening indicators for such patients. This finding provides an important reference for the individualized management of patients with VVS.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eDCA: decision curve analysis\u003c/p\u003e\n\u003cp\u003eHUT: head-up tilt test\u003c/p\u003e\n\u003cp\u003eHRV: heart rate variability\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ePSM: propensity score matching\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eROC: receiver operating characteristic\u003c/p\u003e\n\u003cp\u003eVVS: vasovagal syncope\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (82371595); Beijing Municipal Health Commission Scientific and Technological Achievements and Appropriate Technology Promotion Project (BHTPP2024101); Chinese Academy of Medical Sciences (CAMS) Clinical and Translational Medicine Research Program (2025-I2M-C\u0026amp;T-A-006); and CAMS Innovation Fund for Medical Sciences (2021-I2M-1-063).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest statement:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have no conflicts to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (82371595); Beijing Municipal Health Commission Scientific and Technological Achievements and Appropriate Technology Promotion Project (BHTPP2024101); Chinese Academy of Medical Sciences (CAMS) Clinical and Translational Medicine Research Program (2025-I2M-C\u0026amp;T-A-006); and CAMS Innovation Fund for Medical Sciences (2021-I2M-1-063).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData is available on a reasonable request to the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLongo S, Legramante JM, Rizza S, Federici M. Vasovagal syncope: An overview of pathophysiological mechanisms. Eur J Intern Med. 2023; 112:6-14. \u003c/li\u003e\n\u003cli\u003eShimoda, H.; Yamauchi, K.; Takahashi, T. Transient asystole associated with vasovagal reflex in an oral surgery patient: A case report. SAGE Open Med. Case Rep. 2023, 11, 2050313X221146019.\u003c/li\u003e\n\u003cli\u003eHockin, B.C.D.; Lucci, V.M.; Wu, R.E.Y.; Nicholas, M.; Parsons, I.T.; Claydon, V.E. Pain associated with intravascular instrumentation reduces orthostatic tolerance and predisposes to vasovagal reactions in healthy young adults without needle phobia: A randomised controlled study. Clin. Auton. Res. 2023, 33, 673\u0026ndash;689.\u003c/li\u003e\n\u003cli\u003eXu WR, Jin HF, Du JB, Liao Y. Malignant vasovagal syncope in children. World J Pediatr. 2025;21(1):41-47. doi:10.1007/s12519-024-00867-2\u003c/li\u003e\n\u003cli\u003eShen WK, Sheldon RS, Benditt DG, Cohen MI, Forman DE, Goldberger ZD, Grubb BP, Hamdan MH, Krahn AD, Link MS, Olshansky B, Raj SR, Sandhu RK, Sorajja D, Sun BC, Yancy CW. 2017 ACC/AHA/HRS Guideline for the Evaluation and Management of Patients With Syncope: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Circulation. 2017;136(5): e60-e122. \u003c/li\u003e\n\u003cli\u003eWang, C.; Liao, Y.; Wang, S.; Tian, H.; Huang, M.; Dong, X.Y.; Shi, L.; Li, Y.Q.; Sun, J.H.; Du, J.B.; et al. Guidelines for the diagnosis and treatment of neurally mediated syncope in children and adolescents (revised 2024). World J. Pediatr. 2024, 20, 983\u0026ndash;1002.\u003c/li\u003e\n\u003cli\u003eAyabe K, Komiyama T, Hasegawa M, Sakai T, Morise M, Sakama S, Yagishita A, Amino M, Ikari Y, Yoshioka K. Clinical Significance of the Head-Up Tilt Test in Improving Prognosis in Patients with Possible Neurally Mediated Syncope. Biology (Basel). 2021;10(9):919. \u003c/li\u003e\n\u003cli\u003eZhao T, Wang S, Wang M, Cai H, Wang Y, Xu Y, Zou R, Wang C. Research progress on the predictive value of electrocardiographic indicators in the diagnosis and prognosis of children with vasovagal syncope. Front Cardiovasc Med. 2022; 9:916770. \u003c/li\u003e\n\u003cli\u003eBrignole M, Moya A, de Lange FJ, et al. 2018 ESC Guidelines for the diagnosis and management of syncope. Eur Heart J. Jun 1, 2018;39(21):1883-1948. \u003c/li\u003e\n\u003cli\u003eBrignole M, Moya A, de Lange FJ, et al. Practical Instructions for the 2018 ESC Guidelines for the diagnosis and management of syncope. Eur Heart J. Jun 1, 2018;39(21): e43-e80. \u003c/li\u003e\n\u003cli\u003eBauer A, Kantelhardt JW, Bunde A, Malik M, Schneider R, Schmidt G. Phase-rectified signal averaging detects quasi-periodicities in non-stationary data. Physica A: Statistical Mechanics and its Applications. 2006; 364:423-434.\u003c/li\u003e\n\u003cli\u003evan Dijk, J.G.; van Rossum, I.A.; Thijs, R.D. The pathophysiology of vasovagal syncope: Novel insights. Auton. Neurosci. 2021,236, 102899\u003c/li\u003e\n\u003cli\u003eChen JW, Maldonado DR, Kowalski BL, Miecznikowski KB, Kyin C, Gornbein JA, Domb BG. Best Practice Guidelines for Propensity Score Methods in Medical Research: Consideration on Theory, Implementation, and Reporting. A Review. Arthroscopy. 2022;38(2):632-642.\u003c/li\u003e\n\u003cli\u003eLarson RA, Chapleau MW. Increased cardiac sympathetic activity: Cause or compensation in vasovagal syncope? Clin Auton Res. 2018;28(3):265-266.\u003c/li\u003e\n\u003cli\u003eZhang DY, Anderson AS. The sympathetic nervous system and heart failure. Cardiol Clin. 2014;32(1):33-45, vii.\u003c/li\u003e\n\u003cli\u003eLiu P, Zeng X, Mei W, Wang Y, Zou R, Wang C. The predictive value of urine specific gravity in the diagnosis of vasovagal syncope in children and adolescents. Ital J Pediatr. 2021;47(1):93.\u003c/li\u003e\n\u003cli\u003eCoiado O, Buiochi E, O\u0026apos;Brien W Jr. Ultrasound-induced heart rate decrease: role of the vagus nerve. IEEE Trans Ultrason Ferroelectr Freq Control. 2015;62(2):329-36.\u003c/li\u003e\n\u003cli\u003eFongemie J, Felix-Getzik E. A Review of Nebivolol Pharmacology and Clinical Evidence. Drugs. 2015;75(12):1349-71. \u003c/li\u003e\n\u003cli\u003eBorovac JA, D\u0026apos;Amario D, Bozic J, Glavas D. Sympathetic nervous system activation and heart failure: Current state of evidence and the pathophysiology in the light of novel biomarkers. World J Cardiol. 2020;12(8):373-408.\u003c/li\u003e\n\u003cli\u003eFurukawa, T.; Maggi, R.; Solano, A.; Croci, F.; Brignole, M. Effect of clinical triggers on positive responses to tilt-table testing potentiated with nitroglycerin or clomipramine. Am. J. Cardiol. 2011, 107, 1693\u0026ndash;1697.\u003c/li\u003e\n\u003cli\u003eXu W, Zhang C, Du J, Jin H, Liao Y. Features of Clinical Manifestations and Heart Rate Variability in Children with Malignant Vasovagal Syncope. Children (Basel). 2025;12(5):636.\u003c/li\u003e\n\u003cli\u003eDias RM, Hoshi RA, Vanderlei LCM, Monteiro CBM, Alvarez MPB, Crocetta TB, Grossklauss LF, Fernani DCGL, Dantas MTAP, Martins FPA, Garner DM, Abreu LC, Ferreira C, da Silva TD. Influence of Different Types of Corticosteroids on Heart Rate Variability of Individuals with Duchenne Muscular Dystrophy-A Pilot Cross Sectional Study. Life (Basel). 2021;11(8):752. \u003c/li\u003e\n\u003cli\u003eOmole JG, Okon IA, Udom GJ, Aziakpono OM, Agbana RD, Aturamu A, Niwamanya N, Oritsemuelebi B, Etukudo EM, Yemitan OK. Neurophysiological mechanisms underlying cardiovascular adaptations to exercise: A narrative review. Physiol Rep. 2025;13(13): e70439.\u003c/li\u003e\n\u003cli\u003eSteenbergen L, Maraver MJ, Actis-Grosso R, Ricciardelli P, Colzato LS. Recognizing emotions in bodies: Vagus nerve stimulation enhances recognition of anger while impairing sadness. Cogn Affect Behav Neurosci. 2021;21(6):1246-1261. \u003c/li\u003e\n\u003cli\u003eFurukawa T, Maggi R, Solano A, Croci F, Brignole M. Effect of clinical triggers on positive responses to tilt-table testing potentiated with nitroglycerin or clomipramine. Am J Cardiol. 2011;107(11):1693-7. \u003c/li\u003e\n\u003cli\u003ePrevigliano IJ, Aboumarie HS, Tamagnone FM, Merlo PM, Sosa FA, Feijoo J, Carruega MC. Point of care ultrasound evaluation of cardio-cerebral coupling. World J Crit Care Med. 2025;14(3):101462.\u003c/li\u003e\n\u003cli\u003eZhang Z, Jiang X, Han L, Chen S, Tao L, Tao C, Tian H, Du J. Differential Diagnostic Models Between Vasovagal Syncope and Psychogenic Pseudosyncope in Children. Front Neurol. 2020; 10:1392. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Demographic characteristics of malignant VVS patients and controls before PSM\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant VVS (n = 26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n = 95)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge, yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.00(22.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e45.00(31.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34 (75.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHeight, m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168.62\u0026plusmn;8.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e166.98\u0026plusmn;7.63\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.352\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWeight, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.50(15.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e64.00(19.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.17(3.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.10(5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.398\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean\u0026plusmn;standard deviation, median (interquartile range), or number (percentage). Abbreviations: BMI, body mass index; VVS, vasovagal syncope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Demographic and clinical characteristics of malignant VVS patients and controls after PSM\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant VVS (n = 26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n = 21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge, yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.00(22.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.00(27.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9(42.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8 (26.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.234\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHeight, m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e168.62\u0026plusmn;8.58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e167.04\u0026plusmn;6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.480\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWeight, kg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.50(15.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e62.00(15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.076\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eBMI, kg/m\u0026sup2;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.17(3.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.06(7.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics of syncope\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge of onset, yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29.00(25.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.00(17.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.311\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNumber of syncope episodes, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.50(6.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.00(8.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNumber of pre-syncope episodes, n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.00 (10.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.00 (37.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSymptom duration, mins\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.54(3.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.00(3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCalgary score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.38\u0026plusmn;4.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.13\u0026plusmn;4.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.663\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHistory, yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.00(23,50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.00(18.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.346\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFamily history, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6(23.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7(30.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.560\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTrauma history, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13 (50.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8(34.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCentral triggers, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14(53.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5(21.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003ePast medical history\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3(11.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1(4.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.359\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedication, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3(11.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3(13.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.873\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAlcohol, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2(7.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2(8.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.898\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCigarette, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4(15.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0(0.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.150\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean\u0026plusmn;standard deviation, median (interquartile range), or number (percentage). Abbreviations: BMI, body mass index; VVS, vasovagal syncope. Central tiggers include fear, pain, exposure to loud noise, instrumentation, venipuncture and blood phobia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e HRV metrics of malignant VVS patients and controls\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant VVS (n = 26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n = 21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSDNN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e143.50(79.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e137.00(71.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003erMSSD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.00(32.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e37.00(15.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003epNN50(%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.17(24.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e13.03(6.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.920\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e26.00(17.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.00(19.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.674\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e563.80(671.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e535.20(596.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e375.85(812.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e378.80(541.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.764\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLF/HF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.34(1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.58(0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.440\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDC, ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.31(2.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.80(2.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.912\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAC, ms\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-7.97\u0026plusmn;2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-7.32\u0026plusmn;2.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.387\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean (standard deviation) or median (interquartile range). Abbreviations: AC, acceleration capacity; DC, deceleration capacity; HF, high frequency; HRV, heart rate variability; LF, low frequency; LF/HF, the ratio of LF to HF; pNN50,percent of differences between adjacent normal to normal intervals greater than 50 milliseconds; rMSSD, root mean square of successive normal-to-normal differences; SDNN, standard deviation of normal-to-normal intervals; TI, triangular index; VVS, vasovagal syncope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4\u003c/strong\u003e Hemodynamic indicators of malignant VVS patients and controls\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMalignant VVS (n = 26)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eControls (n = 21)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean HR, bpm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e70.31\u0026plusmn;11.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e69.35\u0026plusmn;13.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.789\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSystolic BP, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e120.04\u0026plusmn;13.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e114.0 \u0026plusmn;9.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiastolic BP, mmHg\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.88\u0026plusmn;9.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e66.83\u0026plusmn;7.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e＜\u003c/strong\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are presented as mean (standard deviation), median [interquartile range], or number (percentage). Abbreviations: BP, blood pressure; bpm, beats per minute; HR, heart rate; VVS, vasovagal syncope.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5\u003c/strong\u003e Univariate and multivariate logistic regression analysis for indicators of malignant VVS patients and controls\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eUnivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMultivariate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e \u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03 (0.99-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.05 (0.99-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSymptom duration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72 (0.52-1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eCentral triggers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.20(1.20,14.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.025\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.82(1.13,30.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSystolic BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.05 (0.99-1.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.095\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDiastolic BP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.14 (1.05-1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.002\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.27 (1.06-1.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e0.010\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: CI, confidence interval; OR, odds ratio; BP, blood pressure.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Malignant vasovagal syncope, risk factor, blood pressure, central triggers, HUT.","lastPublishedDoi":"10.21203/rs.3.rs-8623153/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8623153/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eVasovagal syncope (VVS) is a significant cause of syncope. However, a subset of VVS patients, defined as having malignant VVS, experience prolonged cardiac arrest during episodes (defined as \u0026gt;\u0026thinsp;3s), with a preference for the implantation of pacemakers. Research on malignant VVS remains limited, and its risk factors have not been fully clarified. This study aimed to identify the clinical characteristics and risk factors associated with malignant VVS.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003ePatients with ECG-confirmed cardiac arrest(\u0026gt;\u0026thinsp;3s) during syncope were assigned to the malignant VVS group during HUT. After Propensity Score Matching (PSM), given the small sample size of patients with malignant VVS, statistical analyses included univariate comparisons, multivariate logistic regression, receiver operating characteristic (ROC) curve analysis, and decision curve analysis (DCA).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePatients comprised 26 in the malignant VVS group and 21 matched in the control group. The malignant VVS group had a significantly higher incidence of central triggers and a higher baseline diastolic blood pressure. Multivariate logistic regression identified central triggers and elevated DBP as independent risk factors for malignant VVS. The ROC curve showed that the combined model of DBP and central triggers had the best diagnostic efficacy. DCA confirmed this combined model maintained a stable, high net benefit across all threshold probability ranges.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eElevated baseline DBP and the presence of central triggers are core screening indicators for malignant VVS. The diagnostic model combining two factors exhibits excellent discriminatory ability and clinical utility, providing a reliable tool for the early identification and individualized management of patients with malignant VVS.\u003c/p\u003e","manuscriptTitle":"Comparison of clinical characteristics between malignant and non-malignant vasovagal syncope based on propensity score matching","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-11 05:31:22","doi":"10.21203/rs.3.rs-8623153/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"547cf4ff-fbaf-4b23-bc6f-e8e2d4e1e1ce","owner":[],"postedDate":"February 11th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-19T06:08:01+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-11 05:31:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8623153","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8623153","identity":"rs-8623153","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}