Women's professional development programs for emergency physicians: A scoping review.

Background: Gender disparities in emergency medicine (EM) persist, with women underrepresented in leadership positions and faced with unique challenges, such as gender discrimination and harassment. To address these issues, professional development programs for women have been recommended. Objectives: The purpose of this scoping review was to examine current women's professional development programs for EM and develop a collection of program characteristics, meeting topics, and tips for success that can be useful to new or existing women's professional development programs. Methods: The authors systematically searched research databases for literature detailing current women's professional development programs for EM physicians. Studies detailing professional development programs for female physicians in EM were included. Results: After 149 unique articles were screened, 11 studies met inclusion criteria, describing 10 professional development programs for women in EM. The most commonly cited program objectives included providing mentors and role models (n = 9, 90%), offering career advice and promoting professional advancement and leadership skills (n = 5, 50%), increasing academic recognition for women (n = 4, 40%), and promoting work-life balance and integration (n = 2, 20%). The most common topics covered in program sessions included mentorship and coaching, compensation and/or negotiation, leadership skills, and career advancement and promotion. Challenges and barriers to the success of these programs included a lack of funding and support, difficulty in recruiting participants, lack of institutional recognition and support, lack of time, and difficulty in sustaining the program over time. Conclusions: The study's findings can inform the development of programs that promote gender equity and support the advancement of women in EM.

A Decade in Review: Trends in Female Authorship in Peer-Reviewed Toxicology Journals.

BACKGROUND: Gender diversity in both emergency medicine and medical toxicology has grown over the last decade. However, disparities in promotion, awards, and speakership still exist. No studies have examined gender disparities in authorship in medical toxicology journals. RESEARCH QUESTIONS: Does the proportion of female first authors and female senior authors in medical toxicology publications increase over time? What factors predict female authorship in the first author or last author positions in two major medical toxicology journals? METHODS: We performed a retrospective review of all non-abstract publications in two medical toxicology journals, Clinical Toxicology and Journal of Medical Toxicology, between 2011 and 2020. We collected author names, number of authors, publication type, and publication year. Author names were used to identify author gender using Gender-API integrative tool. Data on the percentages of female medical toxicology fellows and medical toxicologists was provided by the American Board of Emergency Medicine (ABEM). RESULTS: A total of 2212 publications were reviewed and 2171 (97.9%) were included in the dataset. Overall, 31.7% of first authors were identified as female and 67.0% were identified as male by the Gender-API tool. There were 46.8% male-male author dyads, 24.2% female-male author dyads, 12.1% male-female author dyads, and 5.7% female-female author dyads. Predictors of female first authorship included research and case report articles, and percentage of ABEM female toxicologists. Predictors of female senior authorship included number of authors and percentage of ABEM female toxicologists. The proportion of female authorship in both categories increased over the study period. CONCLUSIONS: The frequency of female authorship in the first author position has grown over the last decade and is associated with increasing female representation in medical toxicology and specific manuscript subtypes, specifically research manuscripts.

Self-reported Xylazine Experiences: A Mixed-methods Study of Reddit Subscribers.

OBJECTIVES: Xylazine is an α 2 -agonist increasingly prevalent in the illicit drug supply. Our objectives were to curate information about xylazine through social media from people who use drugs (PWUDs). Specifically, we sought to answer the following: (1) What are the demographics of Reddit subscribers reporting exposure to xylazine? (2) Is xylazine a desired additive? And (3) what adverse effects of xylazine are PWUDs experiencing? METHODS: Natural language processing (NLP) was used to identify mentions of "xylazine" from posts by Reddit subscribers who also posted on drug-related subreddits. Posts were qualitatively evaluated for xylazine-related themes. A survey was developed to gather additional information about the Reddit subscribers. This survey was posted on subreddits that were identified by NLP to contain xylazine-related discussions from March 2022 to October 2022. RESULTS: Seventy-six posts were extracted via NLP from 765,616 posts by 16,131 Reddit subscribers (January 2018 to August 2021). People on Reddit described xylazine as an unwanted adulterant in their opioid supply. Sixty-one participants completed the survey. Of those who disclosed their location, 25 of 50 participants (50%) reported locations in the Northeastern United States. The most common route of xylazine use was intranasal use (57%). Thirty-one of 59 (53%) reported experiencing xylazine withdrawal. Frequent adverse events reported were prolonged sedation (81%) and increased skin wounds (43%). CONCLUSIONS: Among respondents on these Reddit forums, xylazine seems to be an unwanted adulterant. People who use drugs may be experiencing adverse effects such as prolonged sedation and xylazine withdrawal. This seemed to be more common in the Northeast.

Barriers to opioid use disorder treatment: A comparison of self-reported information from social media with barriers found in literature.

Introduction: Medications such as buprenorphine and methadone are effective for treating opioid use disorder (OUD), but many patients face barriers related to treatment and access. We analyzed two sources of data-social media and published literature-to categorize and quantify such barriers. Methods: In this mixed methods study, we analyzed social media (Reddit) posts from three OUD-related forums (subreddits): r/suboxone, r/Methadone, and r/naltrexone. We applied natural language processing to identify posts relevant to treatment barriers, categorized them into insurance- and non-insurance-related, and manually subcategorized them into fine-grained topics. For comparison, we used substance use-, OUD- and barrier-related keywords to identify relevant articles from PubMed published between 2006 and 2022. We searched publications for language expressing fear of barriers, and hesitation or disinterest in medication treatment because of barriers, paying particular attention to the affected population groups described. Results: On social media, the top three insurance-related barriers included having no insurance (22.5%), insurance not covering OUD treatment (24.7%), and general difficulties of using insurance for OUD treatment (38.2%); while the top two non-insurance-related barriers included stigma (47.6%), and financial difficulties (26.2%). For published literature, stigma was the most prominently reported barrier, occurring in 78.9% of the publications reviewed, followed by financial and/or logistical issues to receiving medication treatment (73.7%), gender-specific barriers (36.8%), and fear (31.5%). Conclusion: The stigma associated with OUD and/or seeking treatment and insurance/cost are the two most common types of barriers reported in the two sources combined. Harm reduction efforts addressing barriers to recovery may benefit from leveraging multiple data sources.

Opioid overdoses involving xylazine in emergency department patients: a multicenter study.

INTRODUCTION: Illicit opioids, consisting largely of fentanyl, novel synthetic opioids, and adulterants, are the primary cause of drug overdose fatality in the United States. Xylazine, an alpha-2 adrenergic agonist and veterinary tranquilizer, is being increasingly detected among decedents following illicit opioid overdose. Clinical outcomes in non-fatal overdose involving xylazine are unexplored. Therefore, among emergency department patients with illicit opioid overdose, we evaluated clinical outcome differences for patients with and without xylazine exposures. METHODS: This multicenter, prospective cohort study enrolled adult patients with opioid overdose who presented to one of nine United States emergency departments between 21 September 2020, and 17 August 2021. Patients with opioid overdose were screened and included if they tested positive for an illicit opioid (heroin, fentanyl, fentanyl analog, or novel synthetic opioid) or xylazine. Patient serum was analyzed via liquid chromatography quadrupole time-of-flight mass spectroscopy to detect current illicit opioids, novel synthetic opioids, xylazine and adulterants. Overdose severity surrogate outcomes were: (a) cardiac arrest requiring cardiopulmonary resuscitation (primary); and (b) coma within 4 h of arrival (secondary). RESULTS: Three hundred and twenty-one patients met inclusion criteria: 90 tested positive for xylazine and 231 were negative. The primary outcome occurred in 37 patients, and the secondary outcome occurred in 111 patients. Using multivariable regression analysis, patients positive for xylazine had significantly lower adjusted odds of cardiac arrest (adjusted OR 0.30, 95% CI 0.10-0.92) and coma (adjusted OR 0.52, 95% CI 0.29-0.94). CONCLUSIONS: In this large multicenter cohort, cardiac arrest and coma in emergency department patients with illicit opioid overdose were significantly less severe in those testing positive for xylazine.

Self-reported Xylazine Experiences: A Mixed Methods Study of Reddit Subscribers.

Objectives: Xylazine is an alpha-2 agonist increasingly prevalent in the illicit drug supply. Our objectives were to curate information about xylazine through social media from People Who Use Drugs (PWUDs). Specifically, we sought to answer the following: 1) what are the demographics of Reddit subscribers reporting exposure to xylazine? 2) is xylazine a desired additive? and 3) what adverse effects of xylazine are PWUDs experiencing? Methods: Natural Language Processing (NLP) was used to identify mentions of "xylazine" from posts by Reddit subscribers who also posted on drug-related subreddits. Posts were qualitatively evaluated for xylazine-related themes. A survey was developed to gather additional information about the Reddit subscribers. This survey was posted on subreddits that were identified by NLP to contain xylazine-related discussions from March 2022 to October 2022. Results: 76 posts mentioning xylazine were extracted via NLP from 765,616 posts by 16,131 Reddit subscribers (January 2018 to August 2021). People on Reddit described xylazine as an unwanted adulterant in their opioid supply. 61 participants completed the survey. Of those that disclosed their location, 25/50 (50%) participants reported locations in the Northeastern United States. The most common eoute of xylazine use was intranasal use (57%). 31/59 (53%) reported experiencing xylazine withdrawal. Frequent adverse events reported were prolonged sedation (81%) and increased skin wounds (43%). Conclusions: Among respondents on these Reddit forums, xylazine appears to be an unwanted adulterant. PWUDs may be experiencing adverse effects such as prolonged sedation and xylazine withdrawal. This appeared to be more common in the Northeast.

Can accurate demographic information about people who use prescription medications nonmedically be derived from Twitter?

Traditional substance use (SU) surveillance methods, such as surveys, incur substantial lags. Due to the continuously evolving trends in SU, insights obtained via such methods are often outdated. Social media-based sources have been proposed for obtaining timely insights, but methods leveraging such data cannot typically provide fine-grained statistics about subpopulations, unlike traditional approaches. We address this gap by developing methods for automatically characterizing a large Twitter nonmedical prescription medication use (NPMU) cohort (n = 288,562) in terms of age-group, race, and gender. Our natural language processing and machine learning methods for automated cohort characterization achieved 0.88 precision (95% CI:0.84 to 0.92) for age-group, 0.90 (95% CI: 0.85 to 0.95) for race, and 94% accuracy (95% CI: 92 to 97) for gender, when evaluated against manually annotated gold-standard data. We compared automatically derived statistics for NPMU of tranquilizers, stimulants, and opioids from Twitter with statistics reported in the National Survey on Drug Use and Health (NSDUH) and the National Emergency Department Sample (NEDS). Distributions automatically estimated from Twitter were mostly consistent with the NSDUH [Spearman r: race: 0.98 (P < 0.005); age-group: 0.67 (P < 0.005); gender: 0.66 (P = 0.27)] and NEDS, with 34/65 (52.3%) of the Twitter-based estimates lying within 95% CIs of estimates from the traditional sources. Explainable differences (e.g., overrepresentation of younger people) were found for age-group-related statistics. Our study demonstrates that accurate subpopulation-specific estimates about SU, particularly NPMU, may be automatically derived from Twitter to obtain earlier insights about targeted subpopulations compared to traditional surveillance approaches.

WOMen profEssioNal developmenT oUtcome Metrics in Academic Emergency Medicine: Results from the WOMENTUM Modified Delphi Study.

INTRODUCTION: To address persistent gender inequities in academic medicine, women professional development groups (PDG) have been developed to support the advancement of women in medicine. While these programs have shown promising outcomes, long-term evaluative metrics do not currently exist. The objective of this study was to establish metrics to assess women's PDGs. METHODS: This was a modified Delphi study that included an expert panel of current and past emergency department (ED) chairs and Academy for Women in Academic Emergency Medicine (AWAEM) presidents. The panel completed three iterative surveys to develop and rank metrics to assess women PDGs. Metrics established by the expert panel were also distributed for member-checking to women EM faculty. RESULTS: The expert panel ranked 11 metrics with high to moderate consensus ranking with three metrics receiving greater than 90% consensus: gender equity strategy and plan; recruitment; and compensation. Members ranked 12 metrics with high consensus with three metrics receiving greater than 90% consensus: gender equity strategy and plan; compensation; and gender equity in promotion rates among faculty. Participants emphasized that departments should be responsible for leading gender equity efforts with PDGs providing a supportive role. CONCLUSION: In this study, we identified metrics that can be used to assess academic EDs' gender equity initiatives and the advisory efforts of a departmental women's PDG. These metrics can be tailored to individual departmental/institutional needs, as well as to a PDG's mission. Importantly, PDGs can use metrics to develop and assess programming, acknowledging that many metrics are the responsibility of the department rather than the PDG.

Post-Roe emergency medicine: Policy, clinical, training, and individual implications for emergency clinicians.

In June 2022, the United States Supreme Court decision Dobbs v. Jackson Women's Health Organization overturned Roe v. Wade, removing almost 50 years of precedent and enabling the imposition of a wide range of state-level restrictions on abortion access. Historical data from the United States and internationally demonstrate that the removal of safe abortion options will increase complications and the health risks to pregnant patients. Because the emergency department is a critical access point for reproductive health care, emergency clinicians must be prepared for the policy, clinical, educational, and legal implications of this change. The goal of this paper, therefore, is to describe the impact of the reversal of Roe v. Wade on health equity and reproductive justice, the provision of emergency care education and training, and the specific legal and reproductive consequences for emergency clinicians. Finally, we conclude with specific recommended policy and advocacy responses for emergency medicine clinicians.

The Toxicology Investigators Consortium Case Registry-the 2021 Annual Report.

The Toxicology Investigators Consortium (ToxIC) Core Registry was established by the American College of Medical Toxicology in 2010. The Core Registry collects data from participating sites with the agreement that all bedside and telehealth medical toxicology consultations will be entered. This twelfth annual report summarizes the registry's 2021 data and activity with its additional 8552 cases. Cases were identified for inclusion in this report by a query of the ToxIC database for any case entered from January 1 to December 31, 2021. Detailed data was collected from these cases and aggregated to provide information, which included demographics, reason for medical toxicology evaluation, agent and agent class, clinical signs and symptoms, treatments and antidotes administered, mortality, and whether life support was withdrawn. Gender distribution included 50.4% of cases in females, 48.2% of cases in males, and 1.4% of cases in transgender or gender non-conforming individuals. Non-opioid analgesics were the most commonly reported agent class (14.9%), followed by opioids (13.1%). Acetaminophen was the most common agent reported. Fentanyl was the most common opioid reported and was responsible for the greatest number of fatalities. There were 120 fatalities, comprising 1.4% of all cases. Major trends in demographics and exposure characteristics remained similar to past years' reports. Sub-analyses were conducted to describe new demographic characteristics, including marital status, housing status and military service, the continued COVID-19 pandemic and related toxicologic exposures, and novel substances of exposure.

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.

Large-Scale Social Media Analysis Reveals Emotions Associated with Nonmedical Prescription Drug Use.

Background: The behaviors and emotions associated with and reasons for nonmedical prescription drug use (NMPDU) are not well-captured through traditional instruments such as surveys and insurance claims. Publicly available NMPDU-related posts on social media can potentially be leveraged to study these aspects unobtrusively and at scale. Methods: We applied a machine learning classifier to detect self-reports of NMPDU on Twitter and extracted all public posts of the associated users. We analyzed approximately 137 million posts from 87,718 Twitter users in terms of expressed emotions, sentiments, concerns, and possible reasons for NMPDU via natural language processing. Results: Users in the NMPDU group express more negative emotions and less positive emotions, more concerns about family, the past, and body, and less concerns related to work, leisure, home, money, religion, health, and achievement compared to a control group (i.e., users who never reported NMPDU). NMPDU posts tend to be highly polarized, indicating potential emotional triggers. Gender-specific analyses show that female users in the NMPDU group express more content related to positive emotions, anticipation, sadness, joy, concerns about family, friends, home, health, and the past, and less about anger than males. The findings are consistent across distinct prescription drug categories (opioids, benzodiazepines, stimulants, and polysubstance). Conclusion: Our analyses of large-scale data show that substantial differences exist between the texts of the posts from users who self-report NMPDU on Twitter and those who do not, and between males and females who report NMPDU. Our findings can enrich our understanding of NMPDU and the population involved.

Methotrexate Toxicity from Unintentional Dosing Errors: Calls to a Poison Center and Death Descriptions.

BACKGROUND: Methotrexate is a folate analog prescribed for varying disease with weekly administration as opposed to daily. Dosing errors can prove clinically significant and sometimes fatal. METHODS: We performed a retrospective poison center review of methotrexate calls between 2009 and 2019. RESULTS: Of 111 human-related poison center calls, most patients taking methotrexate were women ages 41 to 80 years old and were prescribed methotrexate for rheumatoid arthritis. Eighty-eight (79%), and 41 (36%) were admitted to the hospital. Thirty-one (75%) of hospitalized patients received leukovorin treatment for their exposure. Two patients died from methotrexate dosing errors. DISCUSSION: Most methotrexate accidental ingestions reported to poison centers result from dose frequency errors. However, we note a higher incidence of unintentional therapeutic errors (79% vs 13.7%) than reported in the National Poison Data System in 2019. Patients are often hospitalized for lab monitoring, and many receive leucovorin. CONCLUSIONS: Most methotrexate calls to our poison center resulted from taking the drug more often than prescribed. Efforts may focus on patient education, physician or pharmacist monitoring during initiation, improved dispensing devices, or weekly drug dispensing.

The Toxicology Investigators Consortium 2020 Annual Report.

The Toxicology Investigators Consortium (ToxIC) Registry was established by the American College of Medical Toxicology in 2010. The registry collects data from participating sites with the agreement that all bedside and telehealth medical toxicology consultation will be entered. This eleventh annual report summarizes the Registry's 2020 data and activity with its additional 6668 cases. Cases were identified for inclusion in this report by a query of the ToxIC database for any case entered from January 1 to December 31, 2020. Detailed data was collected from these cases and aggregated to provide information which included demographics, reason for medical toxicology evaluation, agent and agent class, clinical signs and symptoms, treatments and antidotes administered, mortality, and whether life support was withdrawn. Gender distribution included 50.6% cases in females, 48.4% in males, and 1.0% identifying as transgender. Non-opioid analgesics were the most commonly reported agent class, followed by opioid and antidepressant classes. Acetaminophen was once again the most common agent reported. There were 80 fatalities, comprising 1.2% of all registry cases. Major trends in demographics and exposure characteristics remained similar to past years' reports. Sub-analyses were conducted to describe race and ethnicity demographics and exposures in the registry, telemedicine encounters, and cases related to the COVID-19 pandemic.

Automatic gender detection in Twitter profiles for health-related cohort studies.

OBJECTIVE: Biomedical research involving social media data is gradually moving from population-level to targeted, cohort-level data analysis. Though crucial for biomedical studies, social media user's demographic information (eg, gender) is often not explicitly known from profiles. Here, we present an automatic gender classification system for social media and we illustrate how gender information can be incorporated into a social media-based health-related study. MATERIALS AND METHODS: We used a large Twitter dataset composed of public, gender-labeled users (Dataset-1) for training and evaluating the gender detection pipeline. We experimented with machine learning algorithms including support vector machines (SVMs) and deep-learning models, and public packages including M3. We considered users' information including profile and tweets for classification. We also developed a meta-classifier ensemble that strategically uses the predicted scores from the classifiers. We then applied the best-performing pipeline to Twitter users who have self-reported nonmedical use of prescription medications (Dataset-2) to assess the system's utility. RESULTS AND DISCUSSION: We collected 67 181 and 176 683 users for Dataset-1 and Dataset-2, respectively. A meta-classifier involving SVM and M3 performed the best (Dataset-1 accuracy: 94.4% [95% confidence interval: 94.0-94.8%]; Dataset-2: 94.4% [95% confidence interval: 92.0-96.6%]). Including automatically classified information in the analyses of Dataset-2 revealed gender-specific trends-proportions of females closely resemble data from the National Survey of Drug Use and Health 2018 (tranquilizers: 0.50 vs 0.50; stimulants: 0.50 vs 0.45), and the overdose Emergency Room Visit due to Opioids by Nationwide Emergency Department Sample (pain relievers: 0.38 vs 0.37). CONCLUSION: Our publicly available, automated gender detection pipeline may aid cohort-specific social media data analyses (https://bitbucket.org/sarkerlab/gender-detection-for-public).

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.