Radiographic Horizontal Conjugate Gaze Deviation: Clinical Correlates.

Purpose of Review: The potential diagnostic value of radiographic, horizontal, conjugate gaze deviation (Rad h-CGD) was first recognized in 2003 by Simon et al. Thereafter, interest grew related to its potential use as a marker of different neurologic and vestibular disorders. Over the past 20 years, we have identified clinical correlates of Rad h-CGD including those caused by supratentorial and infratentorial lesions. We propose clinicians and radiologists will better diagnose and manage patients by knowing the different diagnostic possibilities for Rad h-CGD. Findings: We report different clinical correlates of Rad h-CGD relevant for localizing and lateralizing lesions. We measured the angle of deviation and correlated it with the clinical findings and underlying mechanisms. We then reviewed important data from the previous literature relevant to the localization of each lesion and combined it with our experience into the design of a practical algorithm to interpret Rad h-CGD. Summary: Using Rad h-CGD provides useful information about the diagnosis and localization and may reveal subtle ocular findings not clear on physical examination. However, Rad h-CGD alone cannot distinguish between supratentorial and infratentorial lesions, and therefore, the clinical context is critical. Moreover, although Rad h-CGD occurs with strokes due to large vessel occlusion, it could also be seen with an acute vestibular syndrome, secondary to a peripheral vestibular neuritis. Other possibilities include ischemic events in the cerebellum, brainstem, and labyrinth.

Approach to Acute Dizziness/Vertigo in the Emergency Department: Selected Controversies Regarding Specialty Consultation.

Acute dizziness and vertigo are common emergency department presentations (≈4% of annual visits) and sometimes, a life-threatening diagnosis like stroke is missed. Recent literature reviews the challenges in evaluation of these symptoms and offers guidelines for diagnostic approaches. Strong evidence indicates that when well-trained providers perform a high-quality bedside neurovestibular examination, accurate diagnosis of peripheral vestibular disorders and stroke increases. However, it is less clear who can and should be performing these assessments on a routine basis. This article offers a focused debate for and against routine specialty consultation for patients with acute dizziness or vertigo in the emergency department as well as a potential path forward utilizing new portable technologies to quantify eye movements.

Race and Ethnicity and Diagnostic Testing for Common Conditions in the Acute Care Setting.

Importance: Overuse of diagnostic testing is pervasive, but the extent to which it varies by race and ethnicity in the acute care setting is poorly understood. Objective: To use a previously validated diagnostic intensity index to evaluate differences in diagnostic testing rates by race and ethnicity in the acute care setting, which may serve as a surrogate for diagnostic test overuse. Design, Setting, and Participants: This was a cross-sectional study of emergency department (ED) discharges, hospital observation stays, and hospital admissions using administrative claims among EDs and acute care hospitals in Kentucky, Maryland, North Carolina, and New Jersey, from 2016 through 2018. The diagnostic intensity index pairs nonspecific principal discharge diagnoses (nausea and vomiting, abdominal pain, chest pain, and syncope) with related diagnostic tests to estimate rates of nondiagnostic testing. Adults with an acute care encounter with a principal discharge diagnosis of interest were included. Data were analyzed from January to February 2024. Exposure: Race and ethnicity (Asian, Black, Hispanic, White, other [including American Indian, multiracial, and multiethnic], and missing). Main Outcomes and Measures: Receipt of a diagnostic test. Generalized linear models with a hospital-specific indicator variable were estimated to calculate the adjusted odds ratio of receiving a test related to the principal discharge diagnosis by race and ethnicity, controlling for primary payer and zip code income quartile. Results: Of 3 683 055 encounters (1 055 575 encounters [28.7%] for Black, 300 333 encounters [8.2%] for Hispanic, and 2 140 335 encounters [58.1%] for White patients; mean [SD] age of patients with encounters, 47.3 [18.8] years; 2 233 024 encounters among females [60.6%]), most (2 969 974 encounters [80.6%]) were ED discharges. Black compared with White patients discharged from the ED with a diagnosis of interest had an adjusted odds ratio of 0.74 (95% CI, 0.72-0.75) of having related diagnostic testing. No other racial or ethnic disparities of a similar magnitude were observed in any acute care settings. Conclusions and Relevance: In this study, White patients discharged from the ED with a nonspecific diagnosis of interest were significantly more likely than Black patients to receive related diagnostic testing. The extent to which this represents diagnostic test overuse in White patients vs undertesting and missed diagnoses in Black patients deserves further study.

Understanding Diagnostic Errors: AJR Podcast Series on Diagnostic Excellence and Error, Episode 2.

In this episode of the AJR Podcast Series on Diagnostic Excellence and Error, Francis Deng, MD, and David Newman-Toker, MD, PhD, discuss the prevalence and harms of diagnostic error in medicine; the role and causes of error in diagnostic radiology; and disease-specific examples, including in patients with stroke who present with dizziness.

Computable phenotype for diagnostic error: developing the data schema for application of symptom-disease pair analysis of diagnostic error (SPADE).

OBJECTIVES: Diagnostic errors are the leading cause of preventable harm in clinical practice. Implementable tools to quantify and target this problem are needed. To address this gap, we aimed to generalize the Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) framework by developing its computable phenotype and then demonstrated how that schema could be applied in multiple clinical contexts. METHODS: We created an information model for the SPADE processes, then mapped data fields from electronic health records (EHR) and claims data in use to that model to create the SPADE information model (intention) and the SPADE computable phenotype (extension). Later we validated the computable phenotype and tested it in four case studies in three different health systems to demonstrate its utility. RESULTS: We mapped and tested the SPADE computable phenotype in three different sites using four different case studies. We showed that data fields to compute an SPADE base measure are fully available in the EHR Data Warehouse for extraction and can operationalize the SPADE framework from provider and/or insurer perspective, and they could be implemented on numerous health systems for future work in monitor misdiagnosis-related harms. CONCLUSIONS: Data for the SPADE base measure is readily available in EHR and administrative claims. The method of data extraction is potentially universally applicable, and the data extracted is conveniently available within a network system. Further study is needed to validate the computable phenotype across different settings with different data infrastructures.

The Role for Policy in AI-Assisted Medical Diagnosis.

This JAMA Forum discusses the promise and pitfalls of using large language models and artificial intelligence (AI) in the diagnosis of patients.

Burden of serious harms from diagnostic error in the USA.

BACKGROUND: Diagnostic errors cause substantial preventable harms worldwide, but rigorous estimates for total burden are lacking. We previously estimated diagnostic error and serious harm rates for key dangerous diseases in major disease categories and validated plausible ranges using clinical experts. OBJECTIVE: We sought to estimate the annual US burden of serious misdiagnosis-related harms (permanent morbidity, mortality) by combining prior results with rigorous estimates of disease incidence. METHODS: Cross-sectional analysis of US-based nationally representative observational data. We estimated annual incident vascular events and infections from 21.5 million (M) sampled US hospital discharges (2012-2014). Annual new cancers were taken from US-based registries (2014). Years were selected for coding consistency with prior literature. Disease-specific incidences for 15 major vascular events, infections and cancers ('Big Three' categories) were multiplied by literature-based rates to derive diagnostic errors and serious harms. We calculated uncertainty estimates using Monte Carlo simulations. Validity checks included sensitivity analyses and comparison with prior published estimates. RESULTS: Annual US incidence was 6.0 M vascular events, 6.2 M infections and 1.5 M cancers. Per 'Big Three' dangerous disease case, weighted mean error and serious harm rates were 11.1% and 4.4%, respectively. Extrapolating to all diseases (including non-'Big Three' dangerous disease categories), we estimated total serious harms annually in the USA to be 795 000 (plausible range 598 000-1 023 000). Sensitivity analyses using more conservative assumptions estimated 549 000 serious harms. Results were compatible with setting-specific serious harm estimates from inpatient, emergency department and ambulatory care. The 15 dangerous diseases accounted for 50.7% of total serious harms and the top 5 (stroke, sepsis, pneumonia, venous thromboembolism and lung cancer) accounted for 38.7%. CONCLUSION: An estimated 795 000 Americans become permanently disabled or die annually across care settings because dangerous diseases are misdiagnosed. Just 15 diseases account for about half of all serious harms, so the problem may be more tractable than previously imagined.

Assessing clinical reasoning skills following a virtual patient dizziness curriculum.

OBJECTIVES: Dizziness is a common medical symptom that is frequently misdiagnosed. While virtual patient (VP) education has been shown to improve diagnostic accuracy for dizziness as assessed by VPs, trainee performance has not been assessed on human subjects. The study aimed to assess whether internal medicine (IM) interns after training on a VP-based dizziness curriculum using a deliberate practice framework would demonstrate improved clinical reasoning when assessed in an objective structured clinical examination (OSCE). METHODS: All available interns volunteered and were randomized 2:1 to intervention (VP education) vs. control (standard clinical teaching) groups. This quasi-experimental study was conducted at one academic medical center from January to May 2021. Both groups completed pre-posttest VP case assessments (scored as correct diagnosis across six VP cases) and participated in an OSCE done 6 weeks later. The OSCEs were recorded and assessed using a rubric that was systematically developed and validated. RESULTS: Out of 21 available interns, 20 participated. Between intervention (n=13) and control (n=7), mean pretest VP diagnostic accuracy scores did not differ; the posttest VP scores improved for the intervention group (3.5 [SD 1.3] vs. 1.6 [SD 0.8], p=0.007). On the OSCE, the means scores were higher in the intervention (n=11) compared to control group (n=4) for physical exam (8.4 [SD 4.6] vs. 3.9 [SD 4.0], p=0.003) and total rubric score (43.4 [SD 12.2] vs. 32.6 [SD 11.3], p=0.04). CONCLUSIONS: The VP-based dizziness curriculum resulted in improved diagnostic accuracy among IM interns with enhanced physical exam skills retained at 6 weeks post-intervention.

Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department.

This third Guideline for Reasonable and Appropriate Care in the Emergency Department (GRACE-3) from the Society for Academic Emergency Medicine is on the topic adult patients with acute dizziness and vertigo in the emergency department (ED). A multidisciplinary guideline panel applied the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach to assess the certainty of evidence and strength of recommendations regarding five questions for adult ED patients with acute dizziness of less than 2 weeks' duration. The intended population is adults presenting to the ED with acute dizziness or vertigo. The panel derived 15 evidence-based recommendations based on the timing and triggers of the dizziness but recognizes that alternative diagnostic approaches exist, such as the STANDING protocol and nystagmus examination in combination with gait unsteadiness or the presence of vascular risk factors. As an overarching recommendation, (1) emergency clinicians should receive training in bedside physical examination techniques for patients with the acute vestibular syndrome (AVS; HINTS) and the diagnostic and therapeutic maneuvers for benign paroxysmal positional vertigo (BPPV; Dix-Hallpike test and Epley maneuver). To help distinguish central from peripheral causes in patients with the AVS, we recommend: (2) use HINTS (for clinicians trained in its use) in patients with nystagmus, (3) use finger rub to further aid in excluding stroke in patients with nystagmus, (4) use severity of gait unsteadiness in patients without nystagmus, (5) do not use brain computed tomography (CT), (6) do not use routine magnetic resonance imaging (MRI) as a first-line test if a clinician trained in HINTS is available, and (7) use MRI as a confirmatory test in patients with central or equivocal HINTS examinations. In patients with the spontaneous episodic vestibular syndrome: (8) search for symptoms or signs of cerebral ischemia, (9) do not use CT, and (10) use CT angiography or MRI angiography if there is concern for transient ischemic attack. In patients with the triggered (positional) episodic vestibular syndrome, (11) use the Dix-Hallpike test to diagnose posterior canal BPPV (pc-BPPV), (12) do not use CT, and (13) do not use MRI routinely, unless atypical clinical features are present. In patients diagnosed with vestibular neuritis, (14) consider short-term steroids as a treatment option. In patients diagnosed with pc-BPPV, (15) treat with the Epley maneuver. It is clear that as of 2023, when applied in routine practice by emergency clinicians without special training, HINTS testing is inaccurate, partly due to use in the wrong patients and partly due to issues with its interpretation. Most emergency physicians have not received training in use of HINTS. As such, it is not standard of care, either in the legal sense of that term ("what the average physician would do in similar circumstances") or in the common parlance sense ("the standard action typically used by physicians in routine practice").

Impact of Clinician Training Background and Stroke Location on Bedside Diagnostic Test Accuracy in the Acute Vestibular Syndrome - A Meta-Analysis.

OBJECTIVE: Acute dizziness/vertigo is usually due to benign inner-ear causes but is occasionally due to dangerous neurologic ones, particularly stroke. Because symptoms and signs overlap, misdiagnosis is frequent and overuse of neuroimaging is common. We assessed the accuracy of bedside findings to differentiate peripheral vestibular from central neurologic causes. METHODS: We performed a systematic search (MEDLINE and Embase) to identify studies reporting on diagnostic accuracy of physical examination in adults with acute, prolonged dizziness/vertigo ("acute vestibular syndrome" [AVS]). Diagnostic test properties were calculated for findings. Results were stratified by examiner type and stroke location. RESULTS: We identified 6,089 citations and included 14 articles representing 10 study cohorts (n = 800). The Head Impulse, Nystagmus, Test of Skew (HINTS) eye movement battery had high sensitivity 95.3% (95% confidence interval [CI] = 92.5-98.1) and specificity 92.6% (95% CI = 88.6-96.5). Sensitivity was similar by examiner type (subspecialists 94.3% [95% CI = 88.2-100.0] vs non-subspecialists 95.0% [95% CI = 91.2-98.9], p = 0.55), but specificity was higher among subspecialists (97.6% [95% CI = 94.9-100.0] vs 89.1% [95% CI = 83.0-95.2], p = 0.007). HINTS sensitivity was lower in anterior cerebellar artery (AICA) than posterior inferior cerebellar artery (PICA) strokes (84.0% [95% CI = 65.3-93.6] vs 97.7% [95% CI = 93.3-99.2], p = 0.014) but was "rescued" by the addition of bedside hearing tests (HINTS+). Severe (grade 3) gait/truncal instability had high specificity 99.2% (95% CI = 97.8-100.0) but low sensitivity 35.8% (95% CI = 5.2-66.5). Early magnetic resonance imaging (MRI)-diffusion-weighted imaging (DWI; within 24-48 hours) was falsely negative in 15% of strokes (sensitivity 85.1% [95% CI = 79.2-91.0]). INTERPRETATION: In AVS, HINTS examination by appropriately trained clinicians can differentiate peripheral from central causes and has higher diagnostic accuracy for stroke than MRI-DWI in the first 24-48 hours. These techniques should be disseminated to all clinicians evaluating dizziness/vertigo. ANN NEUROL 2023;94:295-308.

Optimizing measurement of misdiagnosis-related harms using symptom-disease pair analysis of diagnostic error (SPADE): comparison groups to maximize SPADE validity.

Diagnostic errors in medicine represent a significant public health problem but continue to be challenging to measure accurately, reliably, and efficiently. The recently developed Symptom-Disease Pair Analysis of Diagnostic Error (SPADE) approach measures misdiagnosis related harms using electronic health records or administrative claims data. The approach is clinically valid, methodologically sound, statistically robust, and operationally viable without the requirement for manual chart review. This paper clarifies aspects of the SPADE analysis to assure that researchers apply this method to yield valid results with a particular emphasis on defining appropriate comparator groups and analytical strategies for balancing differences between these groups. We discuss four distinct types of comparators (intra-group and inter-group for both look-back and look-forward analyses), detailing the rationale for choosing one over the other and inferences that can be drawn from these comparative analyses. Our aim is that these additional analytical practices will improve the validity of SPADE and related approaches to quantify diagnostic error in medicine.

Short-term stroke risk after emergency department treat-and-release headache visit.

OBJECTIVE: To evaluate whether patients discharged to home after an emergency department (ED) visit for headache face a heightened short-term risk of stroke. BACKGROUND: Stroke hospitalizations that occur soon after ED visits for headache complaints may reflect diagnostic error. METHODS: We conducted a retrospective cohort study using statewide administrative claims data for all ED visits and admissions at nonfederal hospitals in Florida 2005-2018 and New York 2005-2016. Using standard International Classification of Diseases (ICD) codes, we identified adult patients discharged to home from the ED (treat-and-release visit) with a benign headache diagnosis (cohort of interest) as well as those with a diagnosis of renal colic or back pain (negative controls). The primary study outcome was hospitalization within 30 days for stroke (ischemic or hemorrhagic) defined using validated ICD codes. We assess the relationship between index ED visit discharge diagnosis and stroke hospitalization adjusting for patient demographics and vascular comorbidities. RESULTS: We identified 1,502,831 patients with an ED treat-and-release headache visit; mean age was 41 (standard deviation: 17) years and 1,044,520 (70%) were female. A total of 2150 (0.14%) patients with headache were hospitalized for stroke within 30 days. In adjusted analysis, stroke risk was higher after headache compared to renal colic (hazard ratio [HR]: 2.69; 95% confidence interval [CI]: 2.29-3.16) or back pain (HR: 4.0; 95% CI: 3.74-4.3). In the subgroup of 26,714 (1.78%) patients with headache who received brain magnetic resonance imaging at index ED visit, stroke risk was only slightly elevated compared to renal colic (HR: 1.47; 95% CI: 1.22-1.78) or back pain (HR: 1.49; 95% CI: 1.24-1.80). CONCLUSION: Approximately 1 in 700 patients discharged to home from the ED with a headache diagnosis had a stroke in the following month. Stroke risk was three to four times higher after an ED visit for headache compared to renal colic or back pain.

aEYE: A deep learning system for video nystagmus detection.

Background: Nystagmus identification and interpretation is challenging for non-experts who lack specific training in neuro-ophthalmology or neuro-otology. This challenge is magnified when the task is performed via telemedicine. Deep learning models have not been heavily studied in video-based eye movement detection. Methods: We developed, trained, and validated a deep-learning system (aEYE) to classify video recordings as normal or bearing at least two consecutive beats of nystagmus. The videos were retrospectively collected from a subset of the monocular (right eye) video-oculography (VOG) recording used in the Acute Video-oculography for Vertigo in Emergency Rooms for Rapid Triage (AVERT) clinical trial (#NCT02483429). Our model was derived from a preliminary dataset representing about 10% of the total AVERT videos (n = 435). The videos were trimmed into 10-sec clips sampled at 60 Hz with a resolution of 240 × 320 pixels. We then created 8 variations of the videos by altering the sampling rates (i.e., 30 Hz and 15 Hz) and image resolution (i.e., 60 × 80 pixels and 15 × 20 pixels). The dataset was labeled as "nystagmus" or "no nystagmus" by one expert provider. We then used a filtered image-based motion classification approach to develop aEYE. The model's performance at detecting nystagmus was calculated by using the area under the receiver-operating characteristic curve (AUROC), sensitivity, specificity, and accuracy. Results: An ensemble between the ResNet-soft voting and the VGG-hard voting models had the best performing metrics. The AUROC, sensitivity, specificity, and accuracy were 0.86, 88.4, 74.2, and 82.7%, respectively. Our validated folds had an average AUROC, sensitivity, specificity, and accuracy of 0.86, 80.3, 80.9, and 80.4%, respectively. Models created from the compressed videos decreased in accuracy as image sampling rate decreased from 60 Hz to 15 Hz. There was only minimal change in the accuracy of nystagmus detection when decreasing image resolution and keeping sampling rate constant. Conclusion: Deep learning is useful in detecting nystagmus in 60 Hz video recordings as well as videos with lower image resolutions and sampling rates, making it a potentially useful tool to aid future automated eye-movement enabled neurologic diagnosis.

Eye and Head Movement Recordings Using Smartphones for Telemedicine Applications: Measurements of Accuracy and Precision.

Objective: Smartphones have shown promise in the assessment of neuro-ophthalmologic and vestibular disorders. We have shown that the head impulse test results recorded using our application are comparable with measurements from clinical video-oculography (VOG) goggles. The smartphone uses ARKit's capability to acquire eye and head movement positions without the need of performing a calibration as in most eye-tracking devices. Here, we measure the accuracy and precision of the eye and head position recorded using our application. Methods: We enrolled healthy volunteers and asked them to direct their eyes, their heads, or both to targets on a wall at known eccentricities while recording their head and eye movements with our smartphone application. We measured the accuracy as the error between the eye or head movement measurement and the location of each target and the precision as the standard deviation of the eye or head position for each of the target positions. Results: The accuracy of head recordings (15% error) was overall better than the accuracy of eye recordings (23% error). We also found that the accuracy for horizontal eye movements (17% error) was better than for vertical (27% error). Precision was also better for head movement (0.8 degrees) recordings than eye movement recordings (1.3 degrees) and variability tended to increase with eccentricity. Conclusion: Our results provide basic metrics evaluating the utility of smartphone applications in the quantitative assessment of head and eye movements. While the new method may not replace the more accurate dedicated VOG devices, they provide a more accessible quantitative option. It may be advisable to include a calibration recording together with any planned clinical test to improve the accuracy.

Vascular vertigo and dizziness: Diagnostic criteria.

This paper presents diagnostic criteria for vascular vertigo and dizziness as formulated by the Committee for the Classification of Vestibular Disorders of the Bárány Society. The classification includes vertigo/dizziness due to stroke or transient ischemic attack as well as isolated labyrinthine infarction/hemorrhage, and vertebral artery compression syndrome. Vertigo and dizziness are among the most common symptoms of posterior circulation strokes. Vascular vertigo/dizziness may be acute and prolonged (≥24 hours) or transient (minutes to  < 24 hours). Vascular vertigo/dizziness should be considered in patients who present with acute vestibular symptoms and additional central neurological symptoms and signs, including central HINTS signs (normal head-impulse test, direction-changing gaze-evoked nystagmus, or pronounced skew deviation), particularly in the presence of vascular risk factors. Isolated labyrinthine infarction does not have a confirmatory test, but should be considered in individuals at increased risk of stroke and can be presumed in cases of acute unilateral vestibular loss if accompanied or followed within 30 days by an ischemic stroke in the anterior inferior cerebellar artery territory. For diagnosis of vertebral artery compression syndrome, typical symptoms and signs in combination with imaging or sonographic documentation of vascular compromise are required.

Are Mental Health and Substance Use Disorders Risk Factors for Missed Acute Myocardial Infarction Diagnoses Among Chest Pain or Dyspnea Encounters in the Emergency Department?

STUDY OBJECTIVE: To assess if having a mental health and/or substance use disorder is associated with a missed acute myocardial infarction diagnosis in the emergency department (ED). METHODS: This was a retrospective cohort analysis (2009 to 2017) of adult ED encounters at Kaiser Permanente Southern California. We used the validated symptom-disease pair analysis of diagnostic error methodological approach to "look back" and "look forward" and identify missed acute myocardial infarctions within 30 days of a treat-and-release ED visit. We use adjusted logistic regression to report the odds of missed acute myocardial infarction among patients with a history of mental health and/or substance use disorders. RESULTS: The look-back analysis identified 44,473 acute myocardial infarction hospital encounters; 574 (1.3%) diagnoses were missed. The odds of missed diagnoses were higher in patients with mental health disorders (odds ratio [OR] 1.48, 95% confidence interval [CI] 1.23 to 1.77) but not in those with substance abuse disorders (OR 1.22, 95% CI 0.91 to 1.62). The highest risk was observed in those with co-occurring disorders (OR 1.90, 95% CI 1.30 to 2.76). The look-forward analysis identified 325,088 chest pain/dyspnea ED encounters; 508 (0.2%) were missed acute myocardial infarctions. No significant associations of missed acute myocardial infarction were revealed in either group (mental health disorder: OR 0.92, 95% CI 0.71 to 1.18; substance use disorder: OR 1.22, 95% CI 0.80 to 1.85). CONCLUSION: The look-back analysis identified patients with mental illness at increased risk of missed acute myocardial infarction diagnosis, with the highest risk observed in those with a history of comorbid substance abuse. Having substance use disorders alone did not increase this risk in either cohort. The look-forward analysis revealed challenges in prospectively identifying high-risk patients to target for improvement.