Bridging the Gap between Ophthalmology and Emergency Medicine in Community-Based Emergency Departments (EDs): A Neuro-Ophthalmology Guide for ED Practitioners

Application of a Deep Learning System to Detect Papilledema on Nonmydriatic Ocular Fundus Photographs in an Emergency Department

PURPOSE

The Fundus photography vs Ophthalmoscopy Trial Outcomes in the Emergency Department (FOTO-ED) studies showed that ED providers poorly recognized funduscopic findings in patients in the ED. We tested a modified version of the Brain and Optic Nerve Study Artificial Intelligence (BONSAI) deep learning system on nonmydriatic fundus photographs from the FOTO-ED studies to determine if the deep learning system could have improved the detection of papilledema had it been available to ED providers as a real-time diagnostic aid.

DESIGN

Retrospective secondary analysis of a cohort of patients included in the FOTO-ED studies.

METHODS

The testing data set included 1608 photographs obtained from 828 patients in the FOTO-ED studies. Photographs were reclassified according to the optic disc classification system used by the deep learning system ("normal optic discs," "papilledema," and "other optic disc abnormalities"). The system's performance was evaluated by calculating the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity using a 1-vs-rest strategy, with reference to expert neuro-ophthalmologists.

RESULTS

The BONSAI deep learning system successfully distinguished normal from abnormal optic discs (AUC 0.92 [95% confidence interval {CI} 0.90-0.93]; sensitivity 75.6% [73.7%-77.5%] and specificity 89.6% [86.3%-92.8%]), and papilledema from normal and others (AUC 0.97 [0.95-0.99]; sensitivity 84.0% [75.0%-92.6%] and specificity 98.9% [98.5%-99.4%]). Six patients with missed papilledema in 1 eye were correctly identified by the deep learning system as having papilledema in the other eye.

CONCLUSIONS

The BONSAI deep learning system was able to reliably identify papilledema and normal optic discs on nonmydriatic photographs obtained in the FOTO-ED studies. Our deep learning system has excellent potential as a diagnostic aid in EDs and non-ophthalmology clinics equipped with nonmydriatic fundus cameras. NOTE: Publication of this article is sponsored by the American Ophthalmological Society.

The BONSAI (Brain and Optic Nerve Study with Artificial Intelligence) deep learning system can accurately identify pediatric papilledema on standard ocular fundus photographs

BACKGROUND

Pediatric papilledema often reflects an underlying severe neurologic disorder and may be difficult to appreciate, especially in young children. Ocular fundus photographs are easy to obtain even in young children and in nonophthalmology settings. The aim of our study was to ascertain whether an improved deep-learning system (DLS), previously validated in adults, can accurately identify papilledema and other optic disk abnormalities in children.

METHODS

The DLS was tested on mydriatic fundus photographs obtained in a multiethnic pediatric population (<17 years) from three centers (Atlanta-USA; Bucharest-Romania; Singapore). The DLS's multiclass classification accuracy (ie, normal optic disk, papilledema, disks with other abnormality) was calculated, and the DLS's performance to specifically detect papilledema and normal disks was evaluated in a one-vs-rest strategy using the AUC, sensitivity and specificity, with reference to expert neuro-ophthalmologists.

RESULTS

External testing was performed on 898 fundus photographs: 447 patients; mean age, 10.33 (231 patients ≤10 years of age; 216, 11-16 years); 558 normal disks, 254 papilledema, 86 other disk abnormalities. Overall multiclass accuracy of the DLS was 89.6% (range, 87.8%-91.6%). The DLS successfully distinguished "normal" from "abnormal" optic disks (AUC 0.99 [0.98-0.99]; sensitivity, 87.3% [84.9%-89.8%]; specificity, 98.5% [97.6%-99.6%]), and "papilledema" from "normal and other" (AUC 0.99 [0.98-1.0]; sensitivity, 98.0% [96.8%-99.4%]; specificity, 94.1% (92.4%-95.9%)].

CONCLUSIONS

Our DLS reliably distinguished papilledema from normal optic disks and other disk abnormalities in children, suggesting it could be utilized as a diagnostic aid for the assessment of optic nerve head appearance in the pediatric age group.

Optic neuropathy diagnosis in the emergency room - retrospective observational study of the last 18 years

INTRODUCTION

Optic neuropathies (ON), a broad spectrum of disorders of the optic nerve, are a frequent cause of visual loss, presenting either in isolation or associated to neurological or systemic disorders. They are often first evaluated in the Emergency Room (ER) and a rapid determination of the etiology is imperative for implementing timely and appropriate treatment. We aim to describe ER demographic data and clinical characteristics, as well as the performed imaging exams, of patients subsequently hospitalized and diagnosed with ON. Furthermore, we seek to explore the accuracy of ER discharge diagnosis and evaluate possible predictive factors that may influence it.

METHODS

We retrospectively reviewed the medical records of 192 patients admitted to the ward of the Neurology Department of Centro Hospitalar Universitário São João (CHUSJ), with a discharge diagnosis of ON. Subsequently, we selected those admitted from the ER, with clinical, laboratory and imaging data, between January 2004 and December 2021.

RESULTS

We included 171 patients. All participants were discharged from the ER and admitted in the ward with a main diagnostic suspicion of ON. Patients were stratified according to suspected etiology at the time of discharge: 99 inflammatory (57.9%), 38 ischemic (22.2%), 27 unspecified (15.8%) and 7 other (4.1%). By comparing with current follow-up diagnosis, 125 patients had an accurate ER diagnosis category (73.1%), 27 had an ON diagnosis of unspecified etiology that was defined only during follow-up (15.8%) and 19 had an inaccurate diagnosis category (11.1%). Diagnostic change was more common with ER ischemic diagnosis (21.1%) compared to inflammatory diagnosis (8.1%) (p = 0.034).

CONCLUSIONS

Our study reveals that most patients with ON can be accurately diagnosed in the ER through clinical history neurological and ophthalmological evaluation.

Neuro-ophthalmology Emergency Department and Inpatient Consultations at a Large Academic Referral Center

PURPOSE

Prompt neuro-ophthalmology consultation prevents diagnostic errors and improves patient outcomes. The scarcity of neuro-ophthalmologists means that the increasing outpatient demand cannot be met, prompting many emergency department (ED) referrals by non-neuro-ophthalmologists. We describe our quaternary care institution's ED and inpatient neuro-ophthalmology consultation patterns and patient outcomes.

DESIGN

Prospective observational study.

PARTICIPANTS

Consecutive neuro-ophthalmology ED and inpatient consultation requests over 1 year.

METHODS

We collected patient demographics, distance traveled, insurance status, referring provider details, consultation question, final diagnosis, complexity of consultation, time of consultation, and need for outpatient follow-up.

MAIN OUTCOME MEASURES

Consultation patterns and diagnoses, complexity, and follow-up.

RESULTS

Of 494 consecutive adult ED and inpatient neuro-ophthalmology consultations requested over 1 year, 241 of 494 consultations (49%) occurred at night or during weekends. Of ED consultations (322 of 494 [65%]), 127 of 322 consultations (39%) occurred during weekdays, 126 of 322 consultations (39%) occurred on weeknights, and 69 of 322 consultations (22%) occurred on weekends or holidays. Of 322 ED consultations, 225 of 322 consultations (70%) were patients who initially sought treatment in the ED with a neuro-ophthalmic chief symptom. Of the 196 patients sent to the ED by a health care professional, 148 patients (148/196 [76%]) were referred by eye care specialists (74 optometrists and 74 ophthalmologists). The most common ED referral questions were for papilledema (75 of 322 [23%]) and vision loss (72 of 322 [22%]). A total of 219 of 322 patients (68%) received a final active neuro-ophthalmic diagnosis, 222 of 322 patients (69%) were cases of high or very high complexity, and 143 of 322 patients (44%) required admission. Inpatient consultations (n = 172) were requested most frequently by hospitalists, including neurologists (71 of 172 [41%]) and oncologists (20 of 172 [12%]) for vision loss (43 of 172 [25%]) and eye movement disorders (36 of 172 [21%]) and by neurosurgeons (58 of 172 [33%]) for examination for mass or a preoperative evaluation (19 of 172 [11%]). An active neuro-ophthalmic diagnosis was confirmed in 67% of patients (116 of 172). Outpatient neuro-ophthalmology follow-up was required for 291 of 494 patients (59%).

CONCLUSIONS

Neuro-ophthalmology consultations are critical to the diagnosis and management in the hospital setting. In the face of a critical shortage of neuro-ophthalmologists, this study highlights the need for technological and diagnostic aids for greater outpatient access.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Telemedicine for Acute Monocular Visual Loss: A Retrospective Large Telestroke Network Experience

Introduction: Central retinal artery occlusion (CRAO) is an under-recognized stroke subtype that may benefit from hyperacute reperfusion therapies. We aimed to evaluate the ability of telestroke activations to provide CRAO diagnosis and thrombolysis. Methods: This retrospective observational study investigates all encounters conducted for acute visual loss between 2010 and 2021 in our multicentric Mayo Clinic Telestroke Network. Demographics, time from visual loss to telestroke evaluation, ocular examination, diagnostic, and therapeutic recommendations were collected for CRAO subjects. Results: Out of 9,511, 49 encounters (0.51%) were conducted for an acute ocular complaint. Five patients had possible CRAO, and 4 presented within 4.5 h from symptom onset (range 1.5-5 h). None received thrombolytic therapy. All telestroke physicians recommended ophthalmology consultation. Conclusion: Current telestroke assessment of acute visual loss is suboptimal and patients eligible for acute reperfusion therapies may not be offered treatment. Teleophthalmologic evaluations and advanced ophthalmic diagnostic tools should complement telestroke systems.

The patient journey with NMOSD: From initial diagnosis to chronic condition

Objective

To better understand the patient experience with neuromyelitis optica spectrum disorder (NMOSD) through the course of the illness.

Background

NMOSD is a rare autoimmune disorder that causes recurrent inflammatory attacks of the optic nerve, spinal cord, and brain. Knowledge and awareness of NMOSD in the general medical community are often limited, resulting in potential delays in diagnosis and treatment.

Design/methods

We developed a comprehensive 101-question survey to understand the patient's perspective on their journey from initial presentation to present condition. The survey covered basic demographics, symptoms, medical tests used to reach a diagnosis, and the patient's psychosocial responses to their diagnosis. The survey included questions to determine internal consistency in responses. We shared the survey with members of the Neuromyelitis Optica (NMO) Clinic Facebook group and received responses from 151 patients. All data collected were self-reported and presented as summary statistics.

Results

The majority of survey responses were from patients who were female (83%) and White (76%), Asian (7%), or African American (7%). Initial symptoms of disease included fatigue, pain, stiffness/spasticity, bladder and bowel dysfunction, cognitive/emotional symptoms, and visual disturbances. Initial reactions to NMOSD diagnosis were frequently fear, anxiety, and/or depression. Mean (SD) time to diagnosis was 2.2 (3.2) years. First contact with a medical professional was felt to be not helpful or somewhat helpful for many patients (71%), in part due to uncertain diagnosis and/or treatment. However, once referred to specialists (primarily neurologists), the majority of patients (87%) reported finding a professional who could help. Tests leading to diagnosis included magnetic resonance imaging, lumbar puncture, and blood tests for autoantibodies including aquaporin-4 (AQP4) and myelin oligodendrocyte glycoprotein (MOG). While approximately 30% of patients still felt challenged for a variety of reasons, most patients reported that having a diagnosis and being under the care of a specialist contributed to a comprehensive plan with hope for their future.

Conclusions

The NMOSD patient journey frequently begins with anxiety, fear, and frustration. Finding the right specialist and identifying appropriate screening tests can lead to earlier diagnosis and progression toward better patient outcomes.