{'fraction_non_alphanumeric': 0.03956604977664327, 'fraction_numerical': 0.03382259093809828, 'mean_word_length': 5.4, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Identifying Patients with Myasthenia for Epidemiological Research by Linkage of Automated Registers

Background: We validated a new method of identifying patients with incident myasthenia in automated Danish registers for the purpose of conducting epidemiological studies of the disorder. Methods: For residents of a Danish county (population 484,862) in 1993–2008, we identified any hospital contacts coded for myasthenia in a nationwide patient register and any prescriptions for pyridostigmine in the county prescription register. Results from an acetylcholine receptor antibody register were linked to the data. We verified the diagnosis by a review of medical records. Results: Subjects identified in the Patient Register (n = 83) were comparable with individuals found in the Prescription Register (n = 89) with regard to age and gender, but were more often seropositive (83.1 vs. 74.2%). Seropositivity increased to 91.6% by restricting the data to individuals recorded in both Patient and Prescription Registers (n = 71). We found that for subjects identified in both Patient and Prescription Registers the positive predictive value of the register diagnosis was 92.9% (95% confidence interval, CI, 84.3–97.7), the false-positive rate was low (2.8%), and the sensitivity was acceptable (81.2%; 95% CI 71.2–88.8). Conclusions: Our data indicate that this novel approach of combining diagnosis register and prescription register information provides a feasible and valid method to trace incident myasthenia patients for population-based epidemiological studies.