Current concepts in acute vestibular syndrome and video-oculography

Distinguishing Peripheral from Central Causes of Dizziness and Vertigo without using HINTS or STANDING

Three validated diagnostic algorithms for diagnosing patients with acute onset dizziness or vertigo (HINTS, HINTS-plus and STANDING) exist. All are extremely accurate in distinguishing peripheral from central causes of dizziness when done by experienced clinicians. However, uptake of these diagnostic tools in routine emergency medicine practice has been sub-optimal, in part, due to clinicians' unease with the head impulse test, the most useful component contained of these algorithms. Use of these validated algorithms is the best way to accurately diagnose patients with acute dizziness. For clinicians who are unfamiliar with or uncomfortable performing or interpreting HINTS and STANDING, this article will suggest alternative approaches to help with accurate diagnosis of patients with acute dizziness or vertigo.

[Evaluation of e-NIHSS scale combined with HINTS for posterior circulation ischemic stroke with vestibular symptoms]

Objective:To explore the predictive value of HINTS bedside examination and e-NIHSS scale for posterior circulation ischemia with vestibular symptoms. Methods:136 cases in total patients with acute vestibular syndrome（AVS） hospitalized in our hospital from April 2021 to April 2023 were selected as the study subjects, According to the classification of AVS etiology, patients with central AVS, namely posterior circulation ischemia（PCI）, were divided into case group（68 cases） and peripheral AVS patients were control group（68 cases）, Collect data and perform head impulse test-nystagmus-test of skew deviation test beside the bed, two doctors evaluated the NIHSS and e-NIHSS scales for PCI patients with vestibular symptoms respecb tively, and recorded the results after they were consistent, and improved the head MRI examination. Results:The positive rate of head pulse test in PCI patients with vestibular symptoms was 3 cases（4.41%）, and 60 cases（88.24%） with peripheral symptoms; The positive rate of nystagmus test in PCI group was 64 cases（94.12%） and peripheral 21 cases（30.88%）; The positive rate of eye deviation test in PCI group was 55 cases（80.88%） and peripheral 8 cases（11.76%）. Comparing the data with the consistency of the final diagnosis, the sensitivity was 97.0%, the specificity was 95.7%, and the accuracy was 0.963. It passed the Kappa consistency test Kappa=0.926（P<0.01）. The patients in PCI group were scored, in which the NIHSS score of brainstem group was 1.51±0.59, and the e-NIHSS score was 4.05±1.71（P<0.05）; The NIHSS score of cerebellar group was 1.42±0.62, and the e-NIHSS score was 3.86±1.59（P<0.05）; NIHSS score of thalamus group was 1.31±0.73, e-NIHSS score was 3.56±1.27 （P<0.05）; NIHSS score of non-focus group was 1.11±0.43, e-NIHSS score was 3.06±1.20 （P<0.01）. The difference between e-NIHSS score and NIHSS score in each group was statistically significant. Conclusion:HINTS examination is highly consistent with the final diagnosis of the gold standard. The e-NIHSS scoring scale has a higher detection rate than the NIHSS scoring scale for patients with posterior circulation ischemia mainly characterize〓by vestibular symptoms.

The value of saccade metrics and VOR gain in detecting a vestibular stroke

OBJECTIVE

A normal video Head Impulse Test is the gold standard in the emergency department to rule-in patients with an acute vestibular syndrome and a stroke. We aimed to compare the diagnostic accuracy of vHIT metrics regarding the vestibulo-ocular reflex gain and the corrective saccades in detecting vestibular strokes.

METHODS

Prospective cross-sectional study (convenience sample) of patients presenting with acute vestibular syndrome in the emergency department of a tertiary referral centre between February 2015 and May 2020. We screened 1677 patients and enrolled 76 patients fulfilling the inclusion criteria of acute vestibular syndrome. All patients underwent video head impulse test with automated and manual data analysis. A delayed MRI served as a gold standard for vestibular stroke confirmation.

RESULTS

Out of 76 patients, 52 were diagnosed with acute unilateral vestibulopathy and 24 with vestibular strokes. The overall accuracy of detecting stroke with an automated vestibulo-ocular reflex gain was 86.8%, compared to 77.6% for cumulative saccade amplitude and automatic saccade mean peak velocity measured by an expert and 71% for cumulative saccade amplitude and saccade mean peak velocity measured automatically. Gain misclassified 13.1% of the patients as false positive or false negative, manual cumulative saccade amplitude and saccade mean peak velocity 22.3%, and automated cumulative saccade amplitude and saccade mean peak velocity 28.9% respectively.

CONCLUSIONS

We found a better accuracy of video head impulse test for the diagnosis of vestibular strokes when using the vestibulo-ocular reflex gain than using saccade metrics. Nevertheless, saccades provide an additional and important information for video head impulse test evaluation. The automated saccade detection algorithm is not yet perfect compared to expert analysis, but it may become a valuable tool for future non-expert video head impulse test evaluations.

Do monosymptomatic stroke patients with dizziness present a vestibular syndrome without nystagmus? An underestimated entity

BACKGROUND AND PURPOSE

Vestibular symptoms are common in emergency department (ED) patients and have various causes, including stroke. Accurate identification of stroke in patients with vestibular symptoms is crucial for timely management. We conducted a prospective cross-sectional study from 2015 to 2019 to determine stroke prevalence and associated symptoms in ED patients with vestibular symptoms, aiming to improve diagnosis and outcomes.

METHODS

As part of the DETECT project, we screened 1647 ED patients with acute vestibular symptoms. Following a retrospective analysis of 961 head and neck magnetic resonance imaging (MRI) scans, we included 122 confirmed stroke cases and assessed them for vestibular signs and symptoms.

RESULTS

Stroke prevalence in dizzy patients was 13% (122/961 MRI scans). Most patients (95%) presented with acute vestibular symptoms with or without nystagmus, whereas 5% had episodic vestibular syndrome (EVS). Nystagmus was present in 50% of stroke patients. Eighty percent had a purely posterior circulation stroke, and nystagmus was absent in 46% of these patients. Seven patients (6%) had lesions in both the anterior and posterior circulation. Vertigo was experienced by 52% regardless of territory.

CONCLUSIONS

A stroke was identified in 13% of ED patients presenting with acute vestibular symptoms. In 5%, it was EVS. Most strokes were in the posterior circulation territory; vertigo occurred with similar frequency in anterior and posterior circulation stroke, and absence of nystagmus was common in both.

Guideline Adherence to Benign Paroxysmal Positional Vertigo Treatment and Management in Primary Care

OBJECTIVE

To determine adherence to the 2017 American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) guidelines for the management and treatment of benign paroxysmal positional vertigo (BPPV) in primary care (PC) and compare whether key recommendations differed by sex, race, or insurance status.

STUDY DESIGN

Retrospective chart review.

SETTING

Twenty-six clinic locations within a single healthcare system.

METHODS

Charts of 458 patients diagnosed with BPPV in PC between 2018 and 2022 were reviewed. Encounters where the diagnosis of BPPV was made were identified. From the clinical encounter note, demographics, symptomatology, management, and treatment were extracted. Nonparametric analyses were used to identify whether AAO-HNS guidelines differed regarding sex, race, or insurance status.

RESULTS

Of 458 patients, 249 (54.4%) did not receive a diagnostic exam, and only 4 (0.9%) patients received imaging. Regarding treatment, only 51 (11.1%) received the Epley maneuver, with 263 (57.4%) receiving vestibular suppressant medication and 12.4% receiving a referral to a specialist. In regard to sex, race, or insurance status, there was no significant difference in receiving a Dix-Hallpike diagnostic maneuver, Epley maneuver, vestibular suppressant medication, imaging, or referral to a specialist.

CONCLUSION

Our data suggest that there continue to be gaps in the adherence to AAO-HNS guidelines; however, these gaps did not differ by sex, race, or insurance status. Care should be taken to increase the use of diagnostic and treatment maneuvers but decrease the use of vestibular-suppressant medications for the treatment of BPPV in PC.

Development of a model to predict the risk of cerebral infarction in acute vestibular syndrome

Objectives

This study aimed to develop a model to predict the risk of cerebral infarction in acute vestibular syndrome and assist emergency physicians in quickly identifying patients with cerebral infarction.

Materials and methods

We looked at 262 patients who were split into cerebral infarction and peripheral vertigo groups. Stepwise regression and Lasso's approach were used to screen for variables, and Boothstrap's method was used to evaluate the model's discrimination and calibration. The model's performance was compared against TriAGe+, ABCD2, and PCI scores using the area under the receiver operator characteristic curve. Clinical decision-making was aided by the use of clinical impact and decision curves.

Results

In the end, nine risk factors were chosen for model 2, and ten risk factors were chosen for model 1. Model 2 was adopted as the final model. The areas under the receiver operator curve value of the model2 were 0.910(P = 0.000), much higher than the areas under the receiver operator curve value of the TriAGe + scores system and that of the PCI scores system. The clinical decision curve shows that when the threshold probability is 0.05, using the nomogram to predict cerebral infarction has more benefits than either the treat-all-patients scheme or the treat-none scheme. The clinical impact curve shows that when the threshold probability is 0.6 the model predicts disease occurrence in general agreement with the occurrence of the real disease.

Conclusion

This study model can help emergency room physicians quickly triage and treat patients by accurately identifying cerebral infarction patients.

Vestibular syndromes, diagnosis and diagnostic errors in patients with dizziness presenting to the emergency department: a cross-sectional study

OBJECTIVES

We aimed to determine the frequency of vestibular syndromes, diagnoses, diagnostic errors and resources used in patients with dizziness in the emergency department (ED).

DESIGN

Retrospective cross-sectional study.

SETTING

Tertiary referral hospital.

PARTICIPANTS

Adult patients presenting with dizziness.

PRIMARY AND SECONDARY OUTCOME MEASURES

We collected clinical data from the initial ED report from July 2015 to August 2020 and compared them with the follow-up report if available. We calculated the prevalence of vestibular syndromes and stroke prevalence in patients with dizziness. Vestibular syndromes are differentiated in acute (AVS) (eg, stroke, vestibular neuritis), episodic (EVS) (eg, benign paroxysmal positional vertigo, transient ischaemic attack) and chronic (CVS) (eg, persistent postural-perceptual dizziness) vestibular syndrome. We reported the rate of diagnostic errors using the follow-up diagnosis as the reference standard.

RESULTS

We included 1535 patients with dizziness. 19.7% (303) of the patients presented with AVS, 34.7% (533) with EVS, 4.6% (71) with CVS and 40.9% (628) with no or unclassifiable vestibular syndrome. The three most frequent diagnoses were stroke/minor stroke (10.1%, 155), benign paroxysmal positional vertigo (9.8%, 150) and vestibular neuritis (9.6%, 148). Among patients with AVS, 25.4% (77) had stroke. The cause of the dizziness remained unknown in 45.0% (692) and 18.0% received a false diagnosis. There was a follow-up in 662 cases (43.1%) and 58.2% with an initially unknown diagnoses received a final diagnosis. Overall, 69.9% of all 1535 patients with dizziness received neuroimaging (MRI 58.2%, CT 11.6%) in the ED.

CONCLUSIONS

One-fourth of patients with dizziness in the ED presented with AVS with a high prevalence (10%) of vestibular strokes. EVS was more frequent; however, the rate of undiagnosed patients with dizziness and the number of patients receiving neuroimaging were high. Almost half of them still remained without diagnosis and among those diagnosed were often misclassified. Many unclear cases of vertigo could be diagnostically clarified after a follow-up visit.

Updates in neuro-otology

PURPOSE OF REVIEW

Recent updates with clinical implications in the field of neuro-otology are reviewed.

RECENT FINDINGS

Important updates relating to several neuro-otologic disorders have been reported in recent years. For benign positional paroxysmal vertigo (BPPV), we provide updates on the characteristics and features of the short arm variant of posterior canal BPPV. For the acute vestibular syndrome, we report important updates on the use of video-oculography in clinical diagnosis. For autoimmune causes of neuro-otologic symptoms, we describe the clinical and paraclinical features of kelch-like protein 11 encephalitis, a newly-identified antibody associated disorder. For cerebellar ataxia, neuropathy, vestibular areflexia syndrome, we report recent genetic insights into this condition.

SUMMARY

This review summarizes important recent updates relating to four hot topics in neuro-otology.

Isolated transient vertigo due to TIA: challenge for diagnosis and therapy

As a prevalent vertigo disease in the clinic, isolated transient vertigo can present as a vertigo episode without focal signs and always free of symptoms on presentation. Previous studies showed a part of isolated transient vertigo events had a high risk of stroke during follow-up. However, how to discern posterior circulation ischemia become a great challenge for clinicians, especially in emergency, neurology, and ENT departments. Routine besides, hematological, and imaging examinations are often difficult provide a clear etiological diagnosis. Hence, this article reviews current knowledge about the epidemiology, risk factors, offending lesions, and clinical manifestation of transient ischemic attack (TIA) presenting as isolated transient vertigo. In addition, we summarize several advances in besides examinations, serum biomarkers, and imaging technologies to better identify stroke events. Finally, the current situation of therapy was briefly retrospected. Here we present a critical clinical puzzle that needs to be solved in the future. Of note, there is a still lack of high-quality studies in this field. The article reviews the keys to the diagnosis of isolated transient vertigo due to TIA and provides us with more methods to screen for high-risk stroke populations.

Deep learning in acute vertigo diagnosis

Recent advances in artificial intelligence are transforming healthcare and there are increasing efforts to apply these breakthroughs to the diagnosis of acute vertigo. Because the diagnosis of vertigo relies on the analysis of eye movements, there are several unique considerations that must be made when implementing deep learning approaches to vertigo. This review discusses the need for diagnostic aids for acute vertigo, the techniques used to preprocess eye movement data and adapt deep learning models to vertigo, and summarizes and analyzes all published models to date.

Smartphone video nystagmography using convolutional neural networks: ConVNG

Background

Eye movement abnormalities are commonplace in neurological disorders. However, unaided eye movement assessments lack granularity. Although videooculography (VOG) improves diagnostic accuracy, resource intensiveness precludes its broad use. To bridge this care gap, we here validate a framework for smartphone video-based nystagmography capitalizing on recent computer vision advances.

Methods

A convolutional neural network was fine-tuned for pupil tracking using > 550 annotated frames: ConVNG. In a cross-sectional approach, slow-phase velocity of optokinetic nystagmus was calculated in 10 subjects using ConVNG and VOG. Equivalence of accuracy and precision was assessed using the “two one-sample t-test” (TOST) and Bayesian interval-null approaches. ConVNG was systematically compared to OpenFace and MediaPipe as computer vision (CV) benchmarks for gaze estimation.

Results

ConVNG tracking accuracy reached 9–15% of an average pupil diameter. In a fully independent clinical video dataset, ConVNG robustly detected pupil keypoints (median prediction confidence 0.85). SPV measurement accuracy was equivalent to VOG (TOST p < 0.017; Bayes factors (BF) > 24). ConVNG, but not MediaPipe, achieved equivalence to VOG in all SPV calculations. Median precision was 0.30°/s for ConVNG, 0.7°/s for MediaPipe and 0.12°/s for VOG. ConVNG precision was significantly higher than MediaPipe in vertical planes, but both algorithms’ precision was inferior to VOG.

Conclusions

ConVNG enables offline smartphone video nystagmography with an accuracy comparable to VOG and significantly higher precision than MediaPipe, a benchmark computer vision application for gaze estimation. This serves as a blueprint for highly accessible tools with potential to accelerate progress toward precise and personalized Medicine.

Artificial intelligence for early stroke diagnosis in acute vestibular syndrome

Objective

Measuring the Vestibular-Ocular-Reflex (VOR) gains with the video head impulse test (vHIT) allows for accurate discrimination between peripheral and central causes of acute vestibular syndrome (AVS). In this study, we sought to investigate whether the accuracy of artificial intelligence (AI) based vestibular stroke classification applied in unprocessed vHIT data is comparable to VOR gain classification.

Methods

We performed a prospective study from July 2015 until April 2020 on all patients presenting at the emergency department (ED) with signs of an AVS. The patients underwent vHIT followed by a delayed MRI, which served as a gold standard for stroke confirmation. The MRI ground truth labels were then applied to train a recurrent neural network (long short-term memory architecture) that used eye- and head velocity time series extracted from the vHIT examinations.

Results

We assessed 57 AVS patients, 39 acute unilateral vestibulopathy patients (AUVP) and 18 stroke patients. The overall sensitivity, specificity and accuracy for detecting stroke with a VOR gain cut-off of 0.57 was 88.8, 92.3, and 91.2%, respectively. The trained neural network was able to classify strokes with a sensitivity of 87.7%, a specificity of 88.4%, and an accuracy of 87.9% based on the unprocessed vHIT data. The accuracy of these two methods was not significantly different (p = 0.09).

Conclusion

AI can accurately diagnose a vestibular stroke by using unprocessed vHIT time series. The quantification of eye- and head movements with the use of machine learning and AI can serve in the future for an automated diagnosis in ED patients with acute dizziness. The application of different neural network architectures can potentially further improve performance and enable direct inference from raw video recordings.

Videooculography “HINTS” in Acute Vestibular Syndrome: A Prospective Study

Objective

A three-step bedside test (“HINTS”: Head Impulse-Nystagmus-Test of Skew), is a well-established way to differentiate peripheral from central causes in patients with acute vestibular syndrome (AVS). Nowadays, the use of videooculography gives physicians the possibility to quantify all eye movements. The goal of this study is to compare the accuracy of VOG “HINTS” (vHINTS) to an expert evaluation.

Methods

We performed a prospective study from July 2015 to April 2020 on all patients presenting at the emergency department with signs of AVS. All the patients underwent clinical HINTS (cHINTS) and vHINTS followed by delayed MRI, which served as a gold standard for stroke confirmation.

Results

We assessed 46 patients with AVS, 35 patients with acute unilateral vestibulopathy, and 11 patients with stroke. The overall accuracy of vHINTS in detecting a central pathology was 94.2% with 100% sensitivity and 88.9% specificity. Experts, however, assessed cHINTS with a lower accuracy of 88.3%, 90.9% sensitivity, and 85.7% specificity. The agreement between clinical and video head impulse tests was good, whereas for nystagmus direction was fair.

Conclusions

vHINTS proved to be very accurate in detecting strokes in patients AVS, with 9% points better sensitivity than the expert. The evaluation of nystagmus direction was the most difficult part of HINTS.

[The "difficult" patient-Vestibular testing under difficult conditions : Part 1: History taking and clinical neurotological examination]

Der Patient mit dem Leitsymptom Schwindel stellt häufig eine Herausforderung für den Hals-Nasen-Ohren-Arzt dar. Die folgende Artikelserie beleuchtet unterschiedliche Aspekte des „schwierigen“ Schwindelpatienten. Der vorliegende erste Teil widmet sich den Besonderheiten und Fallstricken bei der Anamneseerhebung und der klinisch-neurootologischen Untersuchung. Dabei werden situationsspezifische Lösungsansätze zu folgenden Themen der Anamneseerhebung aufgezeigt: Definition von Erwartungen und Zielen, „ausschweifende“ Anamnese, Beschreibung des Symptoms Schwindel, mehrere Schwindelentitäten bei einem Patienten, Diskrepanz zwischen Symptomschwere und vestibulären Befunden, kognitive Verzerrungen und der Umgang mit Emotionen. Des Weiteren werden praxisbezogene Hinweise für die neurootologische Untersuchung von Patienten mit Halswirbelsäulenproblemen und Augenbewegungsstörungen sowie bei ängstlichen Patienten gegeben.