Improving Understanding of Visual Snow by Quantifying its Appearance and Effect on Vision.

Purpose: Visual snow is the hallmark of the neurological condition visual snow syndrome (VSS) but the characteristics of the visual snow percept remain poorly defined. This study aimed to quantify its appearance, interobserver variability, and effect on measured visual performance and self-reported visual quality. Methods: Twenty-three participants with VSS estimated their visual snow dot size, separation, luminance, and flicker rate by matching to a simulation. To assess whether visual snow masks vision, we compared pattern discrimination thresholds for textures that were similar in spatial scale to visual snow as well as more coarse than visual snow, in participants with VSS, and with and without external noise simulating visual snow in 23 controls. Results: Mean and 95% confidence intervals for visual snow appearance were: size (6.0, 5.8-6.3 arcseconds), separation (2.0, 1.7-2.3 arcmin), luminance (72.4, 58.1-86.8 cd/m2), and flicker rate (25.8, 18.9-32.8 frames per image at 120 hertz [Hz]). Participants with finer dot spacing estimates also reported greater visibility of their visual snow (τb = -0.41, 95% confidence interval [CI] = -0.62 to -0.13, P = 0.01). In controls, adding simulated fine-scale visual snow to textures increased thresholds for fine but not coarse textures (F(1, 22) = 4.98, P = 0.036, ηp2 = 0.19). In VSS, thresholds for fine and coarse textures were similar (t(22) = 0.54, P = 0.60), suggesting that inherent visual snow does not act like external noise in controls. Conclusions: Our quantitative estimates of visual snow constrain its likely neural origins, may aid differential diagnosis, and inform future investigations of how it affects vision. Methods to quantify visual snow are needed for evaluation of potential treatments.

Visuo-Cognitive Phenotypes in Early Multiple Sclerosis: A Multisystem Model of Visual Processing.

BACKGROUND: Cognitive impairment can emerge in the earliest stages of multiple sclerosis (MS), with heterogeneity in cognitive deficits often hindering symptom identification and management. Sensory-motor dysfunction, such as visual processing impairment, is also common in early disease and can impact neuropsychological task performance in MS. However, cognitive phenotype research in MS does not currently consider the relationship between early cognitive changes and visual processing impairment. OBJECTIVES: This study explored the relationship between cognition and visual processing in early MS by adopting a three-system model of afferent sensory, central cognitive and efferent ocular motor visual processing to identify distinct visuo-cognitive phenotypes. METHODS: Patients with clinically isolated syndrome and relapsing-remitting MS underwent neuro-ophthalmic, ocular motor and neuropsychological evaluation to assess each visual processing system. The factor structure of ocular motor variables was examined using exploratory factor analysis, and phenotypes were identified using latent profile analysis. RESULTS: Analyses revealed three ocular-motor constructs (cognitive control, cognitive processing speed and basic visual processing) and four visuo-cognitive phenotypes (early visual changes, efferent-cognitive, cognitive control and afferent-processing speed). While the efferent-cognitive phenotype was present in significantly older patients than was the early visual changes phenotype, there were no other demographic differences between phenotypes. The efferent-cognitive and cognitive control phenotypes had poorer performance on the Symbol Digit Modalities Test compared to that of other phenotypes; however, no other differences in performance were detected. CONCLUSION: Our findings suggest that distinct visual processing deficits in early MS may differentially impact cognition, which is not captured using standard neuropsychological evaluation. Further research may facilitate improved symptom identification and intervention in early disease.

Exploring Factors That Prolong the Diagnosis of Myasthenia Gravis.

Background and Objectives: Myasthenia gravis (MG) is a condition with significant phenotypic variability, posing a diagnostic challenge to many clinicians worldwide. Prolonged diagnosis can lead to reduced remission rates and morbidity. This study aimed to identify factors leading to a longer time to diagnosis in MG that could be addressed in future to optimize diagnosis time. Methods: One hundred and ten patients from 3 institutions in Melbourne, Australia, were included in this retrospective cohort study. Demographic and clinical data were collected for these patients over the first 5 years from diagnosis and at 10 years. Nonparametric statistical analysis was used to identify factors contributing to a longer diagnosis time. Results: The median time for MG diagnosis was 102 (345) days. 90% of patients were diagnosed before 1 year. Female patients took longer than male patients to be diagnosed (p = 0.013). The time taken for first presentation after symptom onset contributed most to diagnosis time (median 17 [141] days), with female patients and not working as contributory factors. Neurology referral took longer if patients had diplopia (p = 0.022), respiratory (p = 0.026) symptoms, or saw an ophthalmologist first (p < 0.001). Outpatient management compared with inpatient was associated with a longer time to be seen by a neurologist from referral (p < 0.001), for the first diagnostic result to return (p = 0.001), and for the result to be reviewed (p < 0.001). Ocular MG had a median greater time to neurologist review than generalized MG (median 5 [25] days vs 1 [13] days, p = 0.035). Electrophysiology tests took longer for outpatients than inpatients (median 21 [35] days vs 2 [8] days, p < 0.001). Outpatients were also started on treatment later than inpatients (p < 0.001). There was no association of MG severity, ethnicity, age, medical and ocular comorbidities, and public or private health service on diagnosis time. There was also no impact of time to diagnosis on Myasthenia Gravis Foundation of America outcomes, number of follow-ups or hospitalizations, or prevalence of treatments used. This study is limited by low patient numbers and its retrospective nature. Discussion: This study identified several factors that can contribute to a prolonged diagnosis time of MG. Patient and clinician education about MG and outpatient diagnostic efficiency needs emphasis. Further studies are also needed to explore the delayed presentation time of women and nonworking patients in MG.