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Prednisone insomnia help8/5/2023 ![]() 14 Possible opportunities for drug safety arising from automated analysis of social media data include routine pharmacovigilance, the study of drug safety in particular populations of interest, or studying the impact of side effects on patients’ lives. In recent years, text mining techniques which aim to automatically transform free text into structured data using Natural Language Processing (NLP) techniques, have proven useful in identifying potential drug safety concerns from text within Facebook and Twitter. 12, 13 This corpus of publically-facing data could generate new knowledge regarding drugs and their benefits and harms. In the 3rd quarter of 2015, Twitter and Facebook had 320 million and 1.6 billion active monthly users, respectively. A reported 72% of internet users say they looked online for health information within the past year. In the last two decades, increasing numbers of patients have become active on the World Wide Web seeking information about symptoms, disease and medications, as well as sharing their health related experiences online in forums, or social media platforms such as Twitter and Facebook. ![]() Social media as a public health data source 5 Given that clinician–patient disconnect and treatment concerns are two key factors in influencing medication adherence, 9, 10 further work which focuses on patient experience and opinion is needed to develop a more complete understanding of GC safety. 8 Similarly, a study of patient-reported side effects of GC therapy in patients with asthma demonstrated patients often report adverse events in differing priorities and patterns to clinicians. 7 For example, when groups of patients and rheumatologists were asked to rank the ten “most worrisome” GC-related adverse events, patients ranked renal function, fatigue and palpitations much higher than rheumatologists. This matters because decision-making is influenced by the value judgement of the outcome under consideration, be it a benefit or a risk, alongside its probability and its impact. 4, 5, 6Ĭlinicians and patients are known to have differing views on what the important side effects of GC therapy are. 2 Despite widespread use since the 1950s and an understanding of their mechanism of action, 3 evidence on the frequency and impact of long-term glucocorticoid toxicity are still lacking. Clinicians have long been aware of the many side effects of GC therapy, including osteoporosis, serious infection, diabetes mellitus and cardiovascular disease. 1 Their powerful therapeutic benefit is, however, offset by potential adverse events acting through non-selective disruption of immunological and metabolic processes. It is estimated that the prevalence of oral GC use in the UK population is around 1%. Glucocorticoid (GC) therapy is used widely in patients with inflammatory diseases. This information could help clinicians to inform patients about frequent and relevant non-serious side effects as well as more serious side effects. In particular, it can illustrate which drug side effects patients discuss most commonly, potentially because of important impacts on quality of life. Pharmacovigilance using Twitter data has the potential to be a valuable, supplementary source of drug safety information. Serious glucocorticoid related AEs were reported less frequently. These were proportionally over-reported in Twitter when compared to spontaneous reports in the UK regulator’s ADR reporting scheme. The top AE MedDRA® Preferred Terms were ‘insomnia’ and ‘weight increased’, both recognised non-serious but common side effects. Of 159,297 tweets mentioning either prednisolone or prednisone between 1st October 2012 and 30th June 2015, 20,206 tweets were deemed to contain information resembling an ADR. The aims of this study were to detect and quantify glucocorticoid-related adverse events using a computerised system for automated detection of suspected adverse drug reactions (ADR) from narrative text in Twitter, and to compare the frequency of specific ADR mentions within Twitter to the frequency and patterns of spontaneous ADR reporting to a national drug regulatory body. Despite this, there are few published reports of drug safety profiles derived in this way. In recent years, social media websites have been suggested as a novel, vast source of data which may be useful for deriving drug safety information.
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