Reddit discussions about buprenorphine associated precipitated withdrawal in the era of fentanyl.

BACKGROUND: Induction of buprenorphine, an evidence-based treatment for opioid use disorder (OUD), has been reported to be difficult for people with heavy use of fentanyl, the most prevalent opioid in many areas of the country. In this population, precipitated opioid withdrawal (POW) may occur even after individuals have completed a period of opioid abstinence prior to induction. Our objective was to study potential associations between fentanyl, buprenorphine induction, and POW, using social media data. METHODS: This is a mixed methods study of data from seven opioid-related forums (subreddits) on Reddit. We retrieved publicly available data from the subreddits via an application programming interface, and applied natural language processing to identify subsets of posts relevant to buprenorphine induction, POW, and fentanyl and analogs (F&A). We computed mention frequencies for keywords/phrases of interest specified by our medical toxicology experts. We further conducted manual, qualitative, and thematic analyses of automatically identified posts to characterize the information presented. Results: In 267,136 retrieved posts, substantial increases in mentions of F&A (3 in 2013 to 3870 in 2020) and POW (2 in 2012 to 332 in 2020) were observed. F&A mentions from 2013 to 2021 were strongly correlated with mentions of POW (Spearman's ρ: 0.882; p = .0016), and mentions of the Bernese method (BM), a microdosing induction strategy (Spearman's ρ: 0.917; p = .0005). Manual review of 384 POW- and 106 BM-mentioning posts revealed that common discussion themes included "specific triggers of POW" (55.1%), "buprenorphine dosing strategies" (38.2%) and "experiences of OUD" (36.1%). Many reported experiencing POW despite prolonged opioid abstinence periods, and recommended induction via microdosing, including specifically via the BM. CONCLUSIONS: Reddit subscribers often associate POW with F&A use and describe self-managed buprenorphine induction strategies involving microdosing to avoid POW. Further objective studies in patients with fentanyl use and OUD initiating buprenorphine are needed to corroborate these findings.HIGHLIGHTSIncrease in mentions of precipitated opioid withdrawal (POW) on Reddit from 2012 to 2021 was associated with the increase in fentanyl and analog mentions.Experiences of precipitated opioid withdrawal (POW) were described by individuals despite reporting prolonged periods of abstinence compared to standard buprenorphine induction protocols.People with Opioid Use Disorder (OUD) on Reddit are using and recommending microdosing strategies with buprenorphine to avoid POW.People who used fentanyl report experiencing POW following statistically longer periods of abstinence than people who use heroin.

Methadone and suboxone® mentions on twitter: thematic and sentiment analysis.

BACKGROUND: According to the latest medical evidence, Methadone and buprenorphine-naloxone (Suboxone®) are effective treatments for opioid use disorder (OUD). While the evidence basis for the use of these medications is favorable, less is known about the perceptions of the general public about them. OBJECTIVE: This study aimed to use Twitter to assess the public perceptions about methadone and buprenorphine-naloxone, and to compare their discussion contents based on themes/topics, subthemes, and sentiment. METHODS: We conducted a descriptive analysis of a small and automatic analysis of a large volume of microposts ("tweets") that mentioned "methadone" or "suboxone". In the manual analysis, we categorized the tweets into themes and subthemes, as well as by sentiment and personal experience, and compared the information posted about these two medications. We performed automatic topic modeling and sentiment analysis over large volumes of posts and compared the outputs to those from the manual analyses. RESULTS: We manually analyzed 900 tweets, most of which related to access (15.3% for methadone; 14.3% for buprenorphine-naloxone), stigma (17.0%; 15.5%), and OUD treatment (12.8%; 15.6%). Only a small proportion of tweets (16.4% for Suboxone® and 9.3% for methadone) expressed positive sentiments about the medications, with few tweets describing personal experiences. Tweets mentioning both medications primarily discussed MOUD broadly, rather than comparing the two medications directly. Automatic topic modeling revealed topics from the larger dataset that corresponded closely to the manually identified themes, but sentiment analysis did not reveal any notable differences in chatter regarding the two medications. CONCLUSIONS: Twitter content about methadone and Suboxone® is similar, with the same major themes and similar sub-themes. Despite the proven effectiveness of these medications, there was little dialogue related to their benefits or efficacy in the treatment of OUD. Perceptions of these medications may contribute to their underutilization in combatting OUDs.

Self-reported COVID-19 symptoms on Twitter: an analysis and a research resource.

OBJECTIVE: To mine Twitter and quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions across studies, and create a symptom lexicon for future research. MATERIALS AND METHODS: We retrieved tweets using COVID-19-related keywords, and performed semiautomatic filtering to curate self-reports of positive-tested users. We extracted COVID-19-related symptoms mentioned by the users, mapped them to standard concept IDs in the Unified Medical Language System, and compared the distributions to those reported in early studies from clinical settings. RESULTS: We identified 203 positive-tested users who reported 1002 symptoms using 668 unique expressions. The most frequently-reported symptoms were fever/pyrexia (66.1%), cough (57.9%), body ache/pain (42.7%), fatigue (42.1%), headache (37.4%), and dyspnea (36.3%) amongst users who reported at least 1 symptom. Mild symptoms, such as anosmia (28.7%) and ageusia (28.1%), were frequently reported on Twitter, but not in clinical studies. CONCLUSION: The spectrum of COVID-19 symptoms identified from Twitter may complement those identified in clinical settings.