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Wilson's disease (WD) is a genetic disorder with copper accumulation in various tissues leading to related clinical symptoms (mainly hepatic and neuropsychiatric) which can be in 85% of patients successfully treated with anti-copper agents. However, during WD treatment neurological deterioration may occur in several patients. D-penicillamine (DPA) is one of the most frequently used drugs in WD treatment. Despite its efficacy, DPA can produce many adverse drug reactions, which should be recognized early. We present the case of a 51-year-old man diagnosed with the hepatic form of WD and initially treated with DPA in whom after 15 months of treatment, diplopia and evening ptosis occurred. WD treatment non-compliance as well as overtreatment were excluded. Supported by neurological symptoms, a positive edrophonium test, and high serum levels of antibodies against acetylcholine receptors (AChR-Abs), as well as low concentrations of antibodies against muscle-specific kinase (MuSK-Abs), the diagnosis of myasthenia gravis (MG), induced by DPA, was established. DPA was stopped; zinc sulfate for WD and pyridostigmine for MG symptoms were introduced. Diplopia and ptosis subsided after a few days, which supported our diagnosis. During a follow-up visit after 6 months, the patient did not present any MG symptoms. AChR-Abs level gradually decreased and MuSK-Abs were no longer detected. Pyridostigmine was stopped, and within 9 months of follow-up, the neurological symptoms of MG did not reoccur. The authors discussed the patient's neurological deterioration, performed a systematic review of DPA-induced MG in WD and concluded that MG is a rare and usually reversible complication of DPA treatment. DPA-induced MG generally occurs 2-12 months after treatment initiation and ocular symptoms predominate. Response to pyridostigmine treatment is good and MG symptoms usually reverse within one year after DPA treatment cessation. However, symptoms may persist in some cases where DPA treatment is only a trigger factor for MG occurrence.

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BACKGROUND AND OBJECTIVES: We developed repetitive ocular vestibular-evoked myogenic potentials (roVEMP) as an electrophysiologic test that allows us to elicit the characteristic decrement of extraocular muscles in patients with ocular myasthenia gravis (OMG). Case-control studies demonstrated that roVEMP reliably differentiates patients with OMG from healthy controls. We now aimed to evaluate the diagnostic accuracy of roVEMP for OMG diagnosis in patients with ptosis and/or diplopia. METHODS: In this blinded prospective diagnostic accuracy trial, we compared roVEMP in 89 consecutive patients presenting with ptosis and/or diplopia suspicious of OMG with a multimodal diagnostic approach, including clinical examination, antibodies, edrophonium testing, repetitive nerve stimulation of accessory and facial nerves, and single-fiber EMG (SFEMG). We calculated the roVEMP decrement as the ratio between the mean of the first 2 responses compared with the mean of the sixth-ninth responses in the train and used cutoff of >9% (unilateral decrement) in a 30 Hz stimulation paradigm. RESULTS: Following a complete diagnostic work-up, 39 patients (44%) were diagnosed with ocular MG, while 50 patients (56%) had various other neuro-ophthalmologic conditions, but not MG (non-MG). roVEMP yielded 88.2% sensitivity, 30.2% specificity, 50% positive predictive value (PPV), and 76.5% negative predictive value (NPV). For comparison, SFEMG resulted in 75% sensitivity, 56% specificity, 55.1% PPV, and 75.7% NPV. All other diagnostic tests (except for the ice pack test) also yielded significantly higher positive results in patients with MG compared with non-MG. DISCUSSION: The study revealed a high sensitivity of 88.2% for roVEMP in OMG, but specificity and PPV were too low to allow for the OMG diagnosis as a single test. Thus, differentiating ocular MG from other neuro-ophthalmologic conditions remains challenging, and the highest diagnostic accuracy is still obtained by a multimodal approach. In this study, roVEMP can complement the diagnostic armamentarium for the diagnosis of MG. CLASSIFICATION OF EVIDENCE: This study provides Class I evidence that in patients with diplopia and ptosis, roVEMP alone does not accurately distinguish MG from non-MG disorders. TRIAL REGISTRATION INFORMATION: ClinicalTrials.gov: NCT03049956.

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BACKGROUND: Diagnosing ocular myasthenia gravis (OMG) remains challenging despite recent diagnostic advances. We addressed this challenge by developing and validating a multivariable prediction model that estimates the OMG probability given the results of any partial selection of available diagnostic tests. METHODS: The source data for our model were retrieved from our blinded prospective diagnostic accuracy study at the University Hospital Zurich (USZ). Patients with ptosis and/or diplopia whose presentation was suspicious for OMG underwent comprehensive diagnostic testing. An independent neuromuscular specialist made the final diagnosis. These data were used to fit and validate a Bayesian network model against additional retrospective USZ and the University of Toronto (UoT) patient data. The primary outcome was to predict the likelihood of a positive OMG diagnosis given the available diagnostic tests. For any set of tests, the model returns an OMG probability together with 95% credible intervals, indicating the prediction uncertainty. RESULTS: Of 89 patients included in the development of the model, 39 were diagnosed with OMG. Based on our Bayesian network model, the following variables were the most useful predictors in descending order: edrophonium test, acetylcholine receptor (AChR) antibodies), single-fiber electromyogram (sfEMG), repetitive nerve stimulations (RNS) facial nerve, RNS accessory nerve, Besinger score, ice test, sustained upgaze test, dysarthria, dyspnea, dysphagia, diplopia, ptosis, age, and sex. The model was validated by determining the mean error rate and the area under the curve (AUC) by both 10-fold cross-validation and prediction on the retrospective USZ and UoT validation data consisting of 69 and 24 patients, respectively. Of all variables, edrophonium (sensitivity 94%, specificity 90%) and AChR antibody testing (sensitivity 85%, specificity 96%) showed the highest predictive value during validation with an AUC of 0.912 and 0.872, respectively. Incorporating more predictors reduced the predictive error in both validation data sets. CONCLUSIONS: Our prediction model serves as a basis to predict the OMG likelihood. It underwent successful internal and external validation and can be used to assist in clinical decision making.

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