Faculty Bibliography

BACKGROUND:The early conversations on social media by emergency physicians offer a window into the ongoing response to the COVID-19 pandemic. OBJECTIVE:This retrospective observational study of emergency physician Twitter use details how the health care crisis has influenced emergency physician discourse online and how this discourse may have use as a harbinger of ensuing surge. METHODS:Followers of the three main emergency physician professional organizations were identified using Twitter's application programming interface. They and their followers were included in the study if they identified explicitly as US-based emergency physicians. Statuses, or tweets, were obtained between January 4, 2020, when the new disease was first reported, and December 14, 2020, when vaccination first began. Original tweets underwent sentiment analysis using the previously validated Valence Aware Dictionary and Sentiment Reasoner (VADER) tool as well as topic modeling using latent Dirichlet allocation unsupervised machine learning. Sentiment and topic trends were then correlated with daily change in new COVID-19 cases and inpatient bed utilization. RESULTS:A total of 3463 emergency physicians produced 334,747 unique English-language tweets during the study period. Out of 3463 participants, 910 (26.3%) stated that they were in training, and 466 of 902 (51.7%) participants who provided their gender identified as men. Overall tweet volume went from a pre-March 2020 mean of 481.9 (SD 72.7) daily tweets to a mean of 1065.5 (SD 257.3) daily tweets thereafter. Parameter and topic number tuning led to 20 tweet topics, with a topic coherence of 0.49. Except for a week in June and 4 days in November, discourse was dominated by the health care system (45,570/334,747, 13.6%). Discussion of pandemic response, epidemiology, and clinical care were jointly found to moderately correlate with COVID-19 hospital bed utilization (Pearson r=0.41), as was the occurrence of "covid," "coronavirus," or "pandemic" in tweet texts (r=0.47). Momentum in COVID-19 tweets, as demonstrated by a sustained crossing of 7- and 28-day moving averages, was found to have occurred on an average of 45.0 (SD 12.7) days before peak COVID-19 hospital bed utilization across the country and in the four most contributory states. CONCLUSIONS:COVID-19 Twitter discussion among emergency physicians correlates with and may precede the rising of hospital burden. This study, therefore, begins to depict the extent to which the ongoing pandemic has affected the field of emergency medicine discourse online and suggests a potential avenue for understanding predictors of surge.

BACKGROUND:Buprenorphine is an effective medication for the treatment of opioid addiction, but current barriers to buprenorphine access limit treatment availability for many patients. We identify and characterize regions within the United States (US) with poor buprenorphine access relative to the observed burden of overdose deaths. METHODS:This cross sectional study includes US county-level data on the number of available buprenorphine providers (Substance Abuse and Mental Health Services Administration Buprenorphine Treatment Practitioner Locator) and the number of opioid-related overdose deaths between 2013 and 2015 (Centers for Disease Control and Prevention WONDER Database). Counties with fewer than 10 deaths during this time period were excluded to maintain patient privacy. Population-adjusted county death rates and provider availability were compared to identify locations with high disease burdens and limited buprenorphine access. The presence of significant clustering across the dataset was evaluated using Global Moran's I and zones of significant spatial clusters and anomalies were identified using Local Indicator of Spatial Autocorrelation. RESULTS:County data were available for 846 counties from 49 states and the District of Columbia, comprising 83% of the US population. The median number of opioid overdose deaths per county was 20.0 deaths per 100,000 residents (interquartile range 13.4-29.9, range 2.9 to 108.8). The number of buprenorphine providers per 100,000 county residents ranged from 0 to 45, with a median of 5.9 (interquartile range 3.2 to 9.5). Global Moran's I analysis yielded significant clustering in the distribution of both providers and deaths, with notable significant clusters of higher than average providers and deaths in the Northeast, and scattered mismatched regions of lower-than-average providers and higher-than-average deaths across the Southern, Midwestern, and Western US. Graphical analysis of buprenorphine provider availability and overdose burden reveals limited treatment access relative to overdose deaths throughout much of the Midwestern and Southern US. CONCLUSIONS:Substantial county-level imbalances between the availability of buprenorphine providers and the burden of opioid overdose deaths are present within the US.

OBJECTIVES/OBJECTIVE:To determine the accuracy of the recruitment status listed on ClinicalTrials.gov as compared with the actual trial status. DESIGN/METHODS:Cross-sectional analysis. SETTING/METHODS:Random sample of interventional phase 2-4 clinical trials registered between 2010 and 2012 on ClinicalTrials.gov. PRIMARY OUTCOME MEASURE/METHODS:For each trial which was listed within ClinicalTrials.gov as ongoing, two investigators performed a comprehensive literature search for evidence that the trial had actually been completed. For each trial listed as completed or terminated early by ClinicalTrials.gov, we compared the date that the trial was actually concluded with the date the registry was updated to reflect the study's conclusion status. RESULTS:Among the 405 included trials, 92 had a registry status indicating that study activity was either ongoing or the recruitment status was unknown. Of these, published results were available for 34 (37%). Among the 313 concluded trials, the median delay between study completion and a registry update reflecting that the study had ended was 141 days (IQR 48-419), with delays of over 1 year present for 29%. In total, 125 trials (31%) either had a listed recruitment status which was incorrect or had a delay of more than 1 year between the time the study was concluded and the time the registry recruitment status was updated. CONCLUSIONS:At present, registry recruitment status information in ClinicalTrials.gov is often outdated or wrong. This inaccuracy has implications for the ability of researchers to identify completed trials and accurately characterise all available medical knowledge on a given subject.