Diagnosis of Tensilon-Negative Ocular Myasthenia Gravis By Daily Selfie

Analysis of clinical features and outcomes in patients with ocular myasthenia gravis according to anti-acetylcholine receptor antibody-seropositivity

PURPOSE

To comparatively analyze the clinical characteristics of patients with ocular myasthenia gravis (OMG) referred to an ophthalmology clinic, according to anti-acetylcholine receptor antibody (AchR Ab)-seropositivity.

STUDY DESIGN

Retrospective Cohort Study.

METHODS

Medical records of patients with OMG who presented to a tertiary eye care center between 2003 and 2020 were retrospectively reviewed. Demographics, ophthalmologic characteristics, response to medical treatment, presence of autoimmune thyroid disease and thyroid autoantibody were compared between the AchR Ab seropositive and seronegative groups.

RESULTS

A total of 130 patients with OMG were identified; among them, 46 patients (35.4%) had autoantibody against acetylcholine receptors. The mean age at symptom onset was 42.4 ± 18.9 years. There were no differences in mean age at symptom onset, gender ratio, and mean follow-up period between patients with seropositive and seronegative OMG. Graves ophthalmopathy was significantly more frequent in seronegative patients (p = 0.04), while thymic disease (p < 0.01) was more frequent in seropositive patients (p < 0.01). Among patients with seropositive OMG, 52.3% showed a good response to medical treatment, while only 31.4% of the seronegative patients were classified as good responders (p = 0.01). Thyroid dysfunction was found in 27.4% patients with OMG and the proportion of thyroid dysfunction was not different according to anti-acetylcholine receptor antibody-seropositivity.

CONCLUSION

Seropositivity to acetylcholine receptor antibody is associated with a better response to medical treatment and lower risk of concomitant autoimmune thyroid disease in patients with OMG.

Development and Assessment of an Artificial Intelligence-Based Tool for Ptosis Measurement in Adult Myasthenia Gravis Patients Using Selfie Video Clips Recorded on Smartphones

Introduction

Myasthenia gravis (MG) is a rare autoimmune disease characterized by muscle weakness and fatigue. Ptosis (eyelid drooping) occurs due to fatigue of the muscles for eyelid elevation and is one symptom widely used by patients and healthcare providers to track progression of the disease. Margin reflex distance 1 (MRD1) is an accepted clinical measure of ptosis and is typically assessed using a hand-held ruler. In this work, we develop an AI model that enables automated measurement of MRD1 in self-recorded video clips collected using patient smartphones.

Methods

A 3-month prospective observational study collected a dataset of video clips from patients with MG. Study participants were asked to perform an eyelid fatigability exercise to elicit ptosis while filming "selfie" videos on their smartphones. These images were collected in nonclinical settings, with no in-person training. The dataset was annotated by non-clinicians for (1) eye landmarks to establish ground truth MRD1 and (2) the quality of the video frames. The ground truth MRD1 (in millimeters, mm) was calculated from eye landmark annotations in the video frames using a standard conversion factor, the horizontal visible iris diameter of the human eye. To develop the model, we trained a neural network for eye landmark detection consisting of a ResNet50 backbone plus two dense layers of 78 dimensions on publicly available datasets. Only the ResNet50 backbone was used, discarding the last two layers. The embeddings from the ResNet50 were used as features for a support vector regressor (SVR) using a linear kernel, for regression to MRD1, in mm. The SVR was trained on data collected remotely from MG patients in the prospective study, split into training and development folds. The model's performance for MRD1 estimation was evaluated on a separate test fold from the study dataset.

Results

On the full test fold (N = 664 images), the correlation between the ground truth and predicted MRD1 values was strong (r = 0.732). The mean absolute error was 0.822 mm; the mean of differences was -0.256 mm; and 95% limits of agreement (LOA) were -0.214-1.768 mm. Model performance showed no improvement when test data were gated to exclude "poor" quality images.

Conclusions

On data generated under highly challenging real-world conditions from a variety of different smartphone devices, the model predicts MRD1 with a strong correlation (r = 0.732) between ground truth and predicted MRD1.

Pediatric Ocular Myasthenia Gravis: A Review

Pediatric ocular myasthenia gravis (OMG) is difficult to diagnose and manage, owing to its rarity and low index of suspicion in the early stage of the disease. Also, many other conditions having similar presentation cause a further delay in diagnosis. In this review, we highlighted various pointers in history and described bedside clinical tests that can aid in its timely diagnosis. The antibody spectrum in myasthenia is ever increasing and includes anti-muscle specific kinase and low-density lipoprotein-receptor related protein 4 antibodies in addition to acetylcholine receptor antibodies besides many others. However, pediatric OMG patients often test negative for all three antibodies, making the diagnosis even more difficult in triple seronegative patients. Edrophonium and electrophysiological tests, which help in confirming myasthenia in adults, have a limited utility in diagnosing pediatric ocular myasthenia cases. Various practical difficulties are encountered like nonavailability of edrophonium, risk of bradycardia associated with neostigmine use and its lower sensitivity, noncooperative children, and limited technical expertise in performing electrophysiological tests in children. In this article, we described a pragmatic approach to diagnose pediatric OMG along with the important aspects of its management.

Cell Phone Selfies: Clinching the Diagnosis of Iris Microhemangiomatosis

Four patients presented with a history of "blood" or a "dark spot" in the eye captured on cell phone photos. These episodes prompted presentation to an ophthalmologist where they all had normal slit lamp exams without a hyphema at initial evaluation. With evidence of a spontaneous hyphema seen on photos, further testing was performed including iris fluorescein angiography which revealed hyperfluorescent iris margin vascular tufts, confirming the diagnosis of iris microhemangiomatosis in each patient. All cases were managed conservatively, and only 1 needed topical antihypertensives. Without these patient-initiated photos, the diagnosis of iris microhemangiomatosis would likely remain elusive as slit lamp exam was normal at the time of initial examination in all 4 cases. Ophthalmologists should be aware of this rare diagnosis in the event a patient comes with a cell phone selfie documenting a spontaneous hyphema, especially when emanating from pupillary border.

Nonverbal communication in selfies posted on Instagram: Another look at the effect of gender on vertical camera angle

Background

Selfies are a novel social phenomenon that is gradually beginning to receive attention within the cognitive sciences. Several studies have documented biases that may be related to nonverbal communicative intentions. For instance, in selfies posted on the dating platform Tinder males but not females prefer camera views from below (Sedgewick, Flath & Elias, 2017). We re-examined this study to assess whether this bias is confined to dating selection contexts and to compare variability between individuals and between genders.

Methods

Three raters evaluated vertical camera position in 2000 selfies– 1000 by males and 1000 by females—posted in Instagram.

Results

We found that the choices of camera angle do seem to vary depending on the context under which the selfies were uploaded. On Tinder, females appear more likely to choose neutral, frontal presentations than they do on Instagram, whereas males on Tinder appear more likely to opt for camera angles from below than on Instagram.

Conclusions

This result confirms that the composition of selfies is constrained by factors affecting nonverbal communicative intentions.