Epidemiology, symptomatology and treatment of patients with myasthenia gravis in an Australian hospital

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.

Risk factors for potential drug-drug interactions in patients with myasthenia gravis

OBJECTIVES

Our aim was to determine risk factors for and frequency of potential drug-drug interactions (pDDIs) among hospitalized patients with myasthenia gravis (MG).

METHODS

This was a retrospective cross-sectional study of the-first time hospitalized MG patients or patients hospitalized because of the exacerbation of MG at the Neurology Clinic of the Clinical Center of Serbia, Belgrade. Medical records and discharge summaries of hospitalized MG patients over a 10-year period were reviewed. The pDDIs were identified by means of Micromedex, and multivariate regression methods were used to reveal potential predictors of number of pDDIs per patient.

RESULTS

The study included 687 patients with MG. In total, 2041 pDDIs were detected in 608 (88.5%) patients. Among the discovered pDDIs, 329 different pDDIs were observed. The most frequent pDDIs were pyridostigmine-prednisone (487patients/70.9%) and aspirin-prednisone (90 patients/13.1%) classified as moderate, and enalapril-potassium chloride (71patients/10.3%) classified as major pDDI. Five drugs (aspirin, insulin, prednisone, cyclosporine, metformin) were responsible for 22.6% of different pDDIs. Dyspnea, generalized form of MG, diabetes mellitus, hypertension, total number of drugs-used, use of antiplatelets were identified as the relevant risk factors for total number of pDDIs (R2 = 0.626,F = 73.797, p < 0.001), while age of patients and history of cancer were inversely correlated with such an outcome.

CONCLUSION

The frequency of the pDDIs in hospitalized MG patients is high, and adversely influenced by dyspnea, generalized MG, diabetes mellitus, hypertension, total number of drugs-used and use of antiplatelets.