AB1168 THE ANALYSIS OF “BIG DATA” AND PROCESSING OF UNSTRUCTURED INFORMATION (SEMANTIC HUB PLATFORM) TO IDENTIFY PATIENTS WITH SEVERE GOUT IN THE RUSSIAN FEDERATION.
Authors: E. Ilinykh, M. Elisеev
Journal: Annals of the Rheumatic Diseases (2020)

Background: the prevalence of gout and hyperuricemia (HU) in the world remains high, with a stable high incidence of severe gout [1]. There are no data on the prevalence and features of severe gout in the population of the Russian Federation (RF). Objectives: To determine the percentage of patients (pts) with severe gout in the RF among pts with gout who are looking for information about their disease on the Internet, to clarify their average age, gender distribution, comorbidity, difficulties in diagnosing and treating, to get an idea of the most relevant online requests in this cohort. Methods: We used technology for analyzing “big data” and processing unstructured information (semantic intelligence) (the Semantic Hub platform, which scans Google and Yandex environments). For efficient processing of text corpora, several specialized converters were used. The resulting format for these converters is an XML representation of the source data. The study was based on real-life patient cases (specialized social networks, forums, and other sources of user-generated content). Messages from pts with gout and their relatives were used. Severe gout is characterized by frequent polyarticular flares or chronic arthritis, subcutaneous tophi, the presence of concomitant conditions. Results: A total of 16253 messages were processed, with ‘gout’ entered as a search word. A total of 1691 gout pts were identified. The average age of online-active pts - 47.2 years. Men 60.5%. Severe gout was identified in 194 of 1691 (11.5%) pts, with 59% of pts aged 29 to 45 years. The proportion of men among pts with severe gout is 71%. Comorbidities most often include diabetes mellitus and metabolic syndrome - 24%, CKD - 51%, arterial hypertension-14%. Pts with severe gout have 1.9 comorbidities on average, while other pts with gout -1.1. The groups are comparable by age. Among 90 links related to medical specialties that pts visited before being referred to a rheumatologist, the first three leading positions were - orthopaedic surgeon (30%), general practitioner (25.8%), surgeon (21%). Sixty percent of pts reported that the time between the first attack and the diagnosis of gout was less than six months. The remaining 40% of pts report that this period lasted from 1 to 15 years. Less than 42% of pts were prescribed urate-lowering therapy (ULT) during internal consultation of a physician, and only 23% of physicians recommended ULT to pts with gout during online consultation. According to pts’ reports, treatment includes 3 main groups of drugs: NSAIDs, intra-articular corticosteroids and ULT. Compliance with life-time ULT is very low. The most commonly requested topic on the Internet - attacks during holidays - 2426 messages, the second is held by the topic of lifestyle – 1899 messages, the third place - problems of comorbidities – 1813 references, and only in the fourth position - 1662 messages- the topic of ULT. Conclusion: The percentage of pts with severe gout is 11.5% among gout pts who are looking for information about their condition on the Internet, which is consistent with the data from the largest original papers in the RF on the prevalence of severe gout [2]. More than a half of pts with severe gout (59%) are men aged 29 to 45 years. The decreased online activity of pts over 46 years old may be due to the low motivation for treatment of this cohort. Gout pts are rather more concerned about lifestyle than medical problems. This may also indicate the absence of the consistent compliance of this patient category to life-time therapy. Inadequate long-term therapy and late diagnosis may be the main factors for severe gout in young and active pts. References: [1]Kuo CF, Grainge MJ, Zhang W, Doherty M. Global epidemiology of gout: prevalence, incidence and risk factors. Nat Rev Rheumatol. 2015 Nov;11(11):649-62. [2]Eliseev MS, Barskova VG, Denisov IS. The dynamics of clinical manifestations of gout in men (data from 7-year retrospective surveillance). Terapevticheskii arkhiv. 2015;87(5):10–5 Disclosure of Interests: Ekaterina Ilinykh: None declared, Maxim Elisеev Speakers bureau: Novartis, Menarini Group, Alium