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IgG4-related disease (IgG4-RD), a multi-organ autoimmune disease, causes diverse manifestations that can lead to symptoms and distress. We developed and validated the Symptom Severity Index (SSI) to assess symptom burden. A pilot SSI was tested in n = 5; several gaps were identified. Twenty semi-structured qualitative interviews were performed to expand the item set and identify missing symptoms. Subsequent changes resulted in the current SSI; it was administered with quality of life (QOL) measures to n = 136. We assessed symptom burden and the construct validity of the SSI. A distress score for each symptom is calculated by multiplying symptom frequency ("Never" [0 points] to "Every Day" [3 points]) by associated distress ("None" [0 points] to "Very Much" [4 points]). Each distress score is summed to calculate a total SSI score. The SSI assesses the frequency and distress of 24 symptoms. Among n = 136 with ≥ 1 SSI, 90% experienced ≥ 1 symptom and 88% had distress. The median SSI score was 6.5 (IQR 3.0, 18.0). Fear of more severe disease was observed in 49%. The SSI inversely correlated with the SF-36 (r = - 0.51, p <0.001), the feeling thermometer (r = - 0.28, p <0.001), and the EQ-5D (r = - 0.28, p <0.001). The median SSI score was higher during active vs non-active disease among n = 52 who completed >1 SSI (15 [6, 26] vs. 3 [2, 14], p = 0.008). Symptoms and distress are common in IgG4-RD and associated with worse health-related QOL. The SSI has face, content, and construct validity; it corresponds with QOL measures. [ABSTRACT FROM AUTHOR]

Allergen immunotherapy (AIT) treatment for allergic rhinitis and asthma is used by 2.6 million Americans annually. Clinical and sterility testing studies identify no risk of contamination or infection from extracts prepared using recommended aseptic techniques, but regulatory concerns persist. Social media can be used to investigate rare adverse effects not captured by traditional studies. We sought to investigate large social media databases for suggestion of AIT skin and soft tissue infection (SSTI) risk and compare this risk to a comparator procedure with a sterile pharmaceutical. We analyzed US-restricted data from more than 10 common text-based social media platforms including Facebook, Twitter, and Reddit between 2012 and 2016. We used natural language processing (NLP) to identify posts related to AIT and, separately, influenza vaccination (comparator procedure). NLP was followed by manual review to identify posts suggesting a possible SSTI associated with either AIT or influenza vaccination. SSTI frequencies with 95% CIs were compared. We identified 25,126 AIT posts, which were matched by social media platform to 25,126 influenza vaccination–related posts. NLP identified 4088 (16.3%) AIT posts that required manual review, with 6 posts (0.02%; 95% CI, 0.005%-0.043%) indicative of possible AIT-related SSTI. NLP identified 2689 (10.7%) influenza posts that required manual review, with 7 posts (0.03%; 95% CI, 0.007%-0.048%) indicative of possible influenza vaccination–related SSTI. Social media data suggest that SSTI from AIT and influenza vaccination are equally rare events. Given that AIT's SSTI risk appears comparable to the risk using a sterile pharmaceutical based on social media data, current aseptic technique procedures seem safe. [ABSTRACT FROM AUTHOR]