Journal of Neuro-Ophthalmology最新文献

Background: Ocular manifestations of hyperviscosity, particularly associated with the hemodynamic changes in polycythemia, can lead to various ocular vascular events, ranging from transient monocular blindness to potentially irreversible vision loss if left untreated.

Methods: This is a multicenter, retrospective case series and review of literature involving 4 patients presenting with neuro-ophthalmic symptoms related to underlying polycythemia. A thorough search for prior reported cases with similar manifestations to ours was conducted through the PubMed database.

Results: Four patients, 3 men and 1 woman, ranging in age from 68 to 71 years, were evaluated in the neuroophthalmology clinic. The patients had variable clinical presentations, ranging from transient unilateral or bilateral painless vision loss, nonarteritic anterior ischemic optic neuropathy, and acephalgic migraine with precipitation of visual auras. Polycythemia was secondary to testosterone therapy in 3 cases and primary in 1 case of polycythemia vera. Diagnostic challenges and treatment strategies are discussed in the context of each case. We also describe an additional 14 cases published in prior literature, with the majority presenting with variable symptoms of vision loss associated with polycythemia, and 1 case of amaurosis fugax attributed to a migrainous visual phenomenon.

Conclusions: This case series highlights the role of polycythemia as a precipitating factor for ocular vascular events, necessitating a more careful approach in clinical assessment and management of such patients. Further research is needed to better understand the mechanisms underlying the hemodynamic alterations in polycythemia and their implications for ocular health to optimize therapeutic approaches.

Background: In many parts of the world including India, the prevalence of autoimmune inflammatory diseases such as neuromyelitis optica spectrum disorders (NMOSD), myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD), and multiple sclerosis (MS) is rising. A diagnosis is often delayed due to insufficient diagnostic tools. Machine learning (ML) models have accurately differentiated eyes of patients with MS from those of healthy controls (HCs) using optical coherence tomography (OCT)-based retinal images. Examining OCT characteristics may allow for early differentiation of these conditions. The objective of this study was to determine feasibility of ML analyses to distinguish between patients with different autoimmune inflammatory diseases, other ocular diseases, and HCs based on OCT measurements of the peripapillary retinal nerve fiber layer (pRNFL), ganglion cell-inner plexiform layer (GCIPL), and inner nuclear layers (INLs).

Methods: Eyes of people with MS (n = 99 patients), NMOSD (n = 40), MOGAD (n = 74), other ocular diseases (OTHER, n = 16), and HCs (n = 54) from the Mangalore Demyelinating Disease Registry were included. Support vector machine (SVM) classification models incorporating age, pRNFL, GCIPL, and INL were performed. Data were split into training (70%) and testing (30%) data and accounted for within-patient correlations. Cross-validation was used in training to choose the best parameters for the SVM model. Accuracy and area under receiver operating characteristic curves (AUROCs) were used to assess model performance.

Results: The SVM models distinguished between eyes of patients with each condition (i.e., MOGAD vs NMOSD, NMOSD vs HC, MS vs OTHER, etc) with strong discriminatory power demonstrated from the AUROCs for these comparisons ranging from 0.81 to 1.00. These models also performed with moderate to high accuracy, ranging from 0.66 to 0.81, with the exception of the MS vs NMOSD comparison, which had an accuracy of 0.53.

Conclusion s: ML models are useful for distinguishing between autoimmune inflammatory diseases and for distinguishing these from HCs and other ocular diseases based on OCT measures. This study lays the groundwork for future deep learning studies that use analyses of raw OCT images for identifying eyes of patients with such disorders and other etiologies of optic neuropathy.

Background: There is a global shortage of neuro-ophthalmologists, driven by an aging workforce and declining interest among residents. Emerging data indicate that this supply-demand mismatch results in prolonged patient wait times, leading to evaluation by additional physicians, delayed/incorrect diagnosis, and postponed therapy. However, data on referral patterns are primarily from resource-rich countries. This study examines referral patterns for a neuro-ophthalmology clinic in Bogota, Colombia.

Methods: A retrospective chart review analyzed patients referred to the clinic between July 2020 and July 2021. Data included demographics, time from symptom onset to neuro-ophthalmology appointment (NOA), referral-to-NOA time, initial specialty consulted, number of providers seen before NOA, diagnostic tests performed, and diagnoses at referral vs after NOA.

Results: Among 535 patients (62.1% female), the median wait from symptom onset to NOA was 365 days (interquartile range [IQR]: 60-500) and 30 days ([IQR: 10-45]) from referral to NOA. Most patients (80.2%) first saw an ophthalmologist, with a mean of 1.1 providers seen before NOA. Common diagnostic tests before NOA included brain MRIs (28.6%), posterior segment optical coherence tomography (24.3%), and visual fields (22.8%). Three hundred twenty-six (63.9%) of patients were either partially or completely misdiagnosed before NOA. Time from symptom onset to NOA was a predictor for fully correct diagnosis by referring provider ( P < 0.01), with a shorter time corresponding to a greater likelihood of partially correct diagnosis.

Conclusions: Referral delays are frequent, and misdiagnoses before neuro-ophthalmology consultations are common. Enhancing timely access to NOA could significantly improve patient outcomes and reduce unnecessary utilization of health care resources.

Background: Chronic lymphocytic inflammation with pontine perivascular enhancement responsive to steroids (CLIPPERS) is a rare and poorly understood inflammatory disorder of the central nervous system centered on the pons. It has a characteristic imaging appearance with enhancing and T2-hyperintense punctate and curvilinear lesions in the pons. The lesions lack restricted diffusion and have relatively little perilesional edema. Although patients typically present with gait ataxia and other sequelae of brainstem inflammation including diplopia, there is scant literature focusing on patients who present with primarily neuro-ophthalmic manifestations.

Methods: Case series of 3 patients presenting with diplopia who had a final diagnosis of CLIPPERS.

Results: Case descriptions of a 71-year-old man, 61-year-old woman, and 38-year-old man are reported. Diplopia was the chief presenting complaint, owing to internuclear ophthalmoplegia, sixth nerve palsy, or skew deviation. All patients had nystagmus and gait ataxia. Brain MRI displayed punctate or curvilinear enhancement of pontine/middle cerebellar peduncle lesions without restricted diffusion. All patients achieved rapid improvement after corticosteroid treatment.

Conclusions: In 3 patients with CLIPPERS, the main presenting complaint was diplopia. The distinctive imaging signs led to a strong presumption of CLIPPERS, permitting a truncated evaluation and early corticosteroid treatment, which provided rapid reversal of clinical and imaging manifestations.

Background: The rarity of optic nerve sheath meningiomas (ONSMs) complicates the guidelines surrounding optimal treatment strategies and prognostic factors. There are limited data on the visual outcomes of those treated with radiotherapy versus those observed without treatment. This study aimed to characterize the clinical and radiographic presentations of patients diagnosed with ONSMs and to identify factors predicting improvement in visual function after treatment.

Methods: This is a retrospective case series of 26 patients who presented to 2 tertiary neuro-ophthalmology practices for 10 years with the presumptive diagnosis of ONSM. Demographic, clinical, investigative, radiologic, treatment, and outcome data were collected. Visual improvement was defined as improvement in visual acuity (VA) by ≥2 Snellen lines or visual field (VF) mean deviation (MD) improvement by ≥2 dB. Statistical analyses were performed to compare patients who experienced improvement in visual function with those who did not poststereotactic radiotherapy to identify pretreatment predictors of visual recovery.

Results: Seventeen patients underwent radiotherapy (16 received 54 Gy in 30 fractions and 1 received 50 Gy in 25 fractions) and 4 elected observation. Five were lost to follow-up. Visual function improvement was seen in 10 patients who underwent radiotherapy. Pretreatment VA (logMAR 0.492 vs 1.42, P = 0.025), tumor size (8.50 vs 18.3 mm, P = 0.028), and a decrease in tumor size postradiotherapy ( P = 0.009 for VA and 0.035 for VF MD improvement) were significantly associated with objective visual improvement.

Conclusions: Pretreatment VA and tumor size may predict improvement in visual function in patients with ONSMs treated with radiotherapy. Future larger scale studies that include these data may be able to draw more definite conclusions.

Background: Idiopathic intracranial hypertension (IIH) is a vision-threatening disorder mainly affecting women of a reproductive age. Prompt diagnosis and intervention are vital to prevent vision loss, but validated tools to predict visual outcomes are lacking. The purpose of this study was to create a machine learning algorithm predicting poor visual outcomes at the time that the diagnosis of IIH is established, and stratifying risk among those with and without poor visual acuity at presentation.

Methods: Using electronic health records, a retrospective cohort study was conducted between June 1, 2012 and September 30, 2023. Any patient aged 0-70 years who was diagnosed with IIH and met the revised diagnostic criteria was included in the analysis. In total, 391 patients with IIH had final outcomes available and were included in this analysis. Final visual outcomes were reported between 3 months and 1 year after diagnosis. Poor visual outcomes served as the model outcome and was defined as a visual field mean deviation (VFMD) worse than -7 dB or a visual acuity of 20/80 or worse. Both logistic regression and decision trees were used to build predictive models. Models were evaluated using multiple parameters including accuracy, sensitivity, specificity, and area under the curve. The best performing models were validated using a k-fold cross-validation.

Results: The decision tree models performed the best and 4 prognostic risk groups were created: critical, high, medium, and low. In the critical risk group, patients who had both high baseline VFMD (worse than -12.59 dB) and identified as non-White had a poor visual outcome risk of 92.6%. A baseline VFMD worse than -9.1 dB resulted in a critical risk of a poor visual outcome at 69.8%. Any patient with a baseline VFMD better than -3.39 dB had a risk of a poor visual outcome at 1.04%.

Conclusions: Our study provides clinicians with valuable prognostic markers to assist in identifying patients who are at critical risk for significant vision loss. Patients with a VFMD worse than -9.1 dB have a critical risk of a poor visual outcome, and this further increased if they identified as a minority patient.