Syncope, a form of transient loss of consciousness, remains a complex medical condition for which adverse cardiovascular outcomes, including death, are of major concern but rarely occur. Current risk stratification algorithms have not completely delineated which patients benefit from hospitalization and specific interventions. Patients are often admitted unnecessarily and at high cost. Artificial intelligence (AI) and machine learning may help define the transient loss of consciousness event, diagnose the cause, assess short- and long-term risks, predict recurrence, and determine need for hospitalization and therapeutic intervention; however, several challenges remain, including medicolegal and ethical concerns. This collaborative statement, from a multidisciplinary group of clinicians, investigators, and scientists, focuses on the potential role of AI in syncope management with a goal to inspire creation of AI-derived clinical decision support tools that may improve patient outcomes, streamline diagnostics, and reduce health-care costs.

It is controversial whether people with vasovagal syncope (VVS) have abnormal autonomic responses at baseline and whether specific diagnostic manoeuvres have a diagnostic value. We investigated whether the pupillary light reflex and cardiac autonomic tests can be used to identify autonomic dysfunction in volunteers with a medical history of VVS. The study groups included 128 healthy volunteers, of whom 31 reported a history of typical VVS. The right pupil was evaluated using an automated, commercial infra-red pupillometer under strict conditions. In addition to miosis and mydriasis kinetics, pupil diameters were measured. Heart rate variability at rest and heart rate changes to standing were quantified with high-resolution electrocardiography and designated software. The demographic and clinical characteristics of both groups were statistically similar. Average constriction velocity (ACV) was significantly higher in VVS patients following a univariate analysis (3.83 ± 0.59 vs. 3.56 ± 0.73 mm/s, p = 0.042) and after correcting for potential confounders (p = 0.049). All other pupillometric and heart rate indices were comparable between groups. Patients with a history of VVS depict pupillary parasympathetic overactivity in response to light stimuli, manifested as increased ACV. The prognostic implications of this finding and the significance of using this simple clinical tool to identify patients who are at risk for developing frequent episodes of VVS or physical injuries following a syncope merits further study.

Syncope is a highly prevalent clinical condition characterized by a rapid, complete, and brief loss of consciousness, followed by full recovery caused by cerebral hypoperfusion. This symptom carries significance, as its potential underlying causes may involve the heart, blood pressure, or brain, leading to a spectrum of consequences, from sudden death to compromised quality of life. Various factors contribute to syncope, and adhering to a precise diagnostic pathway can enhance diagnostic accuracy and treatment effectiveness. A standardized initial assessment, risk stratification, and appropriate test identification facilitate determining the underlying cause in the majority of cases. New technologies, including artificial intelligence and smart devices, may have the potential to reshape syncope management into a proactive, personalized, and data-centric model, ultimately enhancing patient outcomes and quality of life. This review addresses key aspects of syncope management, including pathogenesis, current diagnostic testing options, treatments, and considerations in the geriatric population.

OBJECTIVE: A clinical decision tool for Transient Loss of Consciousness (TLOC) could reduce currently high misdiagnosis rates and waiting times for specialist assessments. Most clinical decision tools based on patient-reported symptom inventories only distinguish between two of the three most common causes of TLOC (epilepsy, functional /dissociative seizures, and syncope) or struggle with the particularly challenging differentiation between epilepsy and FDS. Based on previous research describing differences in spoken accounts of epileptic seizures and FDS seizures, this study explored the feasibility of predicting the cause of TLOC by combining the automated analysis of patient-reported symptoms and spoken TLOC descriptions.
METHODS: Participants completed an online web application that consisted of a 34-item medical history and symptom questionnaire (iPEP) and spoken interaction with a virtual agent (VA) that asked eight questions about the most recent experience of TLOC. Support Vector Machines (SVM) were trained using different combinations of features and nested leave-one-out cross validation. The iPEP provided a baseline performance. Inspired by previous qualitative research three spoken language based feature sets were designed to assess: (1) formulation effort, (2) the proportion of words from different semantic categories, and (3) verb, adverb, and adjective usage.
RESULTS: 76 participants completed the application (Epilepsy = 24, FDS = 36, syncope = 16). Only 61 participants also completed the VA interaction (Epilepsy = 20, FDS = 29, syncope = 12). The iPEP model accurately predicted 65.8 % of all diagnoses, but the inclusion of the language features increased the accuracy to 85.5 % by improving the differential diagnosis between epilepsy and FDS.
CONCLUSIONS: These findings suggest that an automated analysis of TLOC descriptions collected using an online web application and VA could improve the accuracy of current clinical decisions tools for TLOC and facilitate clinical stratification processes (such as ensuring appropriate referral to cardiological versus neurological investigation and management pathways).

BACKGROUND: This study aimed to assess the efficacy of a screening questionnaire, based on historical criteria, in distinguishing between seizures and syncope in patients experiencing their first episode of transient loss of consciousness (TLOC) in a neurology emergency department.
METHODS: A prospective cohort of 159 patients with initial TLOC episodes underwent clinical observation and answered a nine-question screening questionnaire. The questionnaire\'s predictive ability was compared to final diagnoses determined through detailed neurology, electrophysiology, and cardiology assessments during a minimum 12-month follow-up. Logistic regression (LR) analysis was performed with final diagnosis as the outcome variable. The calibration and discrimination of the models were assessed.
RESULTS: revealed that the screening score accurately classified 72.33% of patients. Among those with positive screening scores, 65 (67.71%) had seizures compared to 31 (32.29%) with syncope. Introducing a novel risk-scoring model incorporating age and gender, in addition to the screening score, significantly improved performance achieving an accurate classification rate of 81.48%. Among patients with a positive prediction, 63 (80.77%) had seizure, whereas 15 (19.23%) had syncope.
CONCLUSIONS: Employing a structured questionnaire based on common historical criteria is a valuable tool for distinguishing between seizure and syncope in the dynamic setting of the emergency department.

The clinical decision-making of non-conveyance is perceived as complex and difficult by emergency medical services (EMS) professionals. Patients with a transient loss of consciousness (TLOC) based on syncope constitute a significant part of the non-conveyance population. Risk stratification is the basis of the clinical decision-making process by EMS professionals. This risk stratification is based on various patient factors. This study aimed to explore patient factors significantly associated with conveyance decision-making by EMS professionals in patients with a TLOC based on syncope.
A cross-sectional vignette study with a factorial survey design was conducted. Patient factors were derived from the \"National Protocol Ambulance Care\", and all possible combinations of these factors and underlying categories were combined, resulting in 256 unique vignettes (2*4*4*4*2 = 256). Patient factors presented either low-risk or high-risk factors for adverse events. Data were collected through an online questionnaire, in which participants received a random sample of 15 vignettes. For each vignette, the respondent indicated whether the patient would need to be conveyed to the emergency department or not. A multilevel logistic regression analysis with stepwise backward elimination was performed to analyse factors significantly associated with conveyance decision-making. In the logistic model, we modelled the probability of non-conveyance.
110 respondents were included, with 1646 vignettes being assessed. Mean age 45.5 (SD 9.3), male gender 63.6%, and years of experience 13.2 (SD 8.9). Multilevel analysis showed two patient factors contributing significantly to conveyance decision-making: \'red flags\' and \'prehospital electrocardiogram (ECG)\'. Of these patient factors, three underlying categories were significantly associated with non-conveyance: \'sudden cardiac death < 40 years of age in family history\' (OR 0.33, 95% CI 0.22-0.50; p < 0.001), \'cardiovascular abnormalities, pulmonary embolism or pulmonary hypertension in the medical history\' (OR 0.62, 95% CI 0.43-0.91; p = 0.01), and \'abnormal prehospital ECG\' (OR 0.54, 95% CI 0.41-0.72; p < 0.001).
Sudden cardiac death < 40 years of age in family history, medical history, and abnormal ECG are significantly negatively associated with non-conveyance decision-making by EMS professionals in patients with a TLOC based on syncope. Low-risk factors do not play a significant role in conveyance decision-making.

Syncope management is fraught with unnecessary tests and frequent failure to establish a diagnosis. We evaluated the potential of implementing the 2018 European Society of Cardiology (ESC) Syncope Guidelines regarding diagnostic yield, accuracy and costs.
A multicentre pre-post study in five Dutch hospitals comparing two groups of syncope patients visiting the emergency department: one before intervention (usual care; from March 2017 to February 2019) and one afterwards (from October 2017 to September 2019). The intervention consisted of the simultaneous implementation of the ESC Syncope Guidelines with quick referral routes to a syncope unit when indicated. The primary objective was to compare diagnostic accuracy using logistic regression analysis accounting for the study site. Secondary outcome measures included diagnostic yield, syncope-related healthcare and societal costs. One-year follow-up data were used to define a gold standard reference diagnosis by applying ESC criteria or, if not possible, evaluation by an expert committee. We determined the accuracy by comparing the treating physician\'s diagnosis with the reference diagnosis.
We included 521 patients (usual care, n = 275; syncope guidelines intervention, n = 246). The syncope guidelines intervention resulted in a higher diagnostic accuracy in the syncope guidelines group than in the usual care group (86% vs.69%; risk ratio 1.15; 95% CI 1.07 to 1.23) and a higher diagnostic yield (89% vs. 76%, 95% CI of the difference 6 to 19%). Syncope-related healthcare costs did not differ between the groups, yet the syncope guideline implementation resulted in lower total syncope-related societal costs compared to usual care (saving €908 per patient; 95% CI €34 to €1782).
ESC Syncope Guidelines implementation in the emergency department with quick referral routes to a syncope unit improved diagnostic yield and accuracy and lowered societal costs.
Netherlands Trial Register, NTR6268.

UNASSIGNED: Various conditions may trigger episodic vertigo or dizziness, with positional changes being the most frequently identified condition. In this study, we describe a rare case of triggered episodic vestibular syndrome (EVS) accompanied by transient loss of consciousness (TLOC) linked to retrostyloidal vagal schwannoma.
UNASSIGNED: A 27-year woman with known vestibular migraine presented with a 19-month history of nausea, dysphagia, and odynophagia triggered by swallowing food and followed by recurrent TLOC. These symptoms occurred independently of her body position, resulting in a weight loss of 10 kg within 1 year and in an inability to work. An extensive cardiologic diagnostic work-up undertaken before she presented to the neurologic department was normal. On the fiberoptic endoscopic evaluation of swallowing, she showed a decreased sensitivity, a slight bulging of the right lateral pharyngeal wall, and a pathological pharyngeal squeeze maneuver without any further functional deficits. Quantitative vestibular testing revealed an intact peripheral-vestibular function, and electroencephalography was read as normal. On the brain MRI, a 16 x 15 x 12 mm lesion in the right retrostyloidal space suspicious of a vagal schwannoma was detected. Radiosurgery was preferred over surgical resection, as resection of tumors in the retrostyloid space bears the risk of intraoperative complications and may result in significant morbidity. A single radiosurgical procedure (stereotactic CyberKnife radiosurgery, 1 x 13Gy) accompanied by oral steroids was performed. On follow-up, a cessation of (pre)syncopes was noted 6 months after treatment. Only residual infrequent episodes of mild nausea were triggered by swallowing solid food remained. Brain MRI after 6 months demonstrated no progression of the lesion. In contrast, migraine headaches associated with dizziness remained frequent.
UNASSIGNED: Distinguishing triggered and spontaneous EVS is important, and identifying specific triggers by structured history-taking is essential. Episodes being elicited by swallowing solid foods and accompanied by (near) TLOC should initiate a thorough search for vagal schwannoma, as symptoms are often disabling, and targeted treatment is available. In the case presented here, cessation of (pre)syncopes and significant reduction of nausea triggered by swallowing was noted with a 6-month delay, illustrating the advantages (no surgical complications) and disadvantages (delayed treatment response) of first-line radiotherapy in vagal schwannoma treatment.

OBJECTIVE: A substantial number of patients with a transient loss of consciousness (T-LOC) are referred to a tertiary syncope unit without a diagnosis. This study investigates the final diagnoses reached in patients who, on referral, were undiagnosed or inaccurately diagnosed in secondary care.
METHODS: This study is an in-depth analysis of the recently published Fainting Assessment Study II, a prospective cohort study in a tertiary syncope unit. The diagnosis at the tertiary syncope unit was established after history taking (phase 1), following autonomic function tests (phase 2), and confirming after critical follow-up of 1.5-2 years, with the adjudicated diagnosis (phase 3) by a multidisciplinary committee. Diagnoses suggested by the referring physician were considered the phase 0 diagnosis. We determined the accuracy of the phase 0 diagnosis by comparing this with the phase 3 diagnosis.
RESULTS: 51% (134/264) of patients had no diagnosis upon referral (phase 0), the remaining 49% (130/264) carried a diagnosis, but 80% (104/130) considered their condition unexplained. Of the patients undiagnosed at referral, three major causes of T-LOC were revealed: reflex syncope (69%), initial orthostatic hypotension (20%) and psychogenic pseudosyncope (13%) (sum > 100% due to cases with multiple causes). Referral diagnoses were either inaccurate or incomplete in 65% of the patients and were mainly altered at tertiary care assessment to reflex syncope, initial orthostatic hypotension or psychogenic pseudosyncope. A diagnosis of cardiac syncope at referral proved wrong in 17/18 patients.
CONCLUSIONS: Syncope patients diagnosed or undiagnosed in primary and secondary care and referred to a syncope unit mostly suffer from reflex syncope, initial orthostatic hypotension or psychogenic pseudosyncope. These causes of T-LOC do not necessarily require ancillary tests, but can be diagnosed by careful history-taking. Besides access to a network of specialized syncope units, simple interventions, such as guideline-based structured evaluation, proper risk-stratification and critical follow-up may reduce diagnostic delay and improve diagnostic accuracy for syncope.

Syncope is a short-term transient loss of consciousness, characterized by rapid onset and complete spontaneous recovery. According to the 2018 European Society of Cardiology guidelines, three different types of syncope have been identified. However, all forms of syncope share a common final pathophysiological event, global cerebral hypoperfusion, which results from the inability of the circulatory system to maintain blood pressure at the level required to efficiently supply blood to the brain. The vasovagal syncope (VVS) is the most common form of syncope. Although, VVS is generally harmless, its frequent occurrence can negatively affect quality of life and increase the risk of adverse events. The pathophysiological mechanisms underlying VVS remain obscure. The multifaceted nature of VVS presents a veritable challenge to understanding this condition and developing preventative strategies. Thus, the aim of this review was to discuss the factors contributing to the pathogenesis of VVS and provide guidance for future research.