United States

Background: Moderators of now-banned r/nonewnormal described its aims as the “free exchange of ideas and debate”, but it often hosted topics such as vaccine misinformation and questioning COVID-19 death report legitimacy. Previous studies on Reddit vaccine sentiment found that conglomerates of COVID-19 related subreddits had overall positive sentiment. However, no study analyzed specific characteristics of individual misinformation and information subreddits, such as r/nonewnormal and r/Coronavirus, respectively.

Methods: This study analyzed Reddit comments from 7/2020-6/2021 that are publicly available at http://files.pushshift.io/reddit/comments/ for similarity and topic analyses using Rstudio. For subreddit similarity, we counted distinct users commenting on a subreddit 10 or more times, to ensure consistent engagement. Subreddits were ranked by overlapping users with r/nonewnormal and r/Coronavirus to determine similarity. The 50 most popular subreddits overall were excluded because they target broad topics (e.g. r/news) that users engage, regardless of interests. Topic popularity in both subreddits was determined by incidence of the words “vaccine”, “lockdown”, “mask”, and “quarantine”. Word aliases were also counted (e.g. Vax for vaccine).

Results: The most similar subreddits to r/nonewnormal serially were r/LockdownSkepticism, r/Coronavirus, r/conspiracy, r/Conservative, and r/PoliticalCompassMemes. For r/Coronavirus the most similar serially were r/nottheonion, r/insanepeoplefacebook, r/PoliticalHumor, r/technology, and r/trashy. The topic analysis showed that in r/nonewnormal the difference in incidence of “vaccine” (+19,175) and “mask” (+7346) increased from 7/2020-6/2021 while “quarantine” (+263) and “lockdown” (+1608) stayed similar. In r/Coronavirus, “vaccine” (+16,907) increased from 7/2020-3/2021 then decreased through 7/2021 (-14,083) while “quarantine” (-2792), “mask” (-33,894), and “lockdown” (-4573) decreased from 7/2020-6/2021.

Conclusion: Similarity analysis showed that users of r/nonewnormal were likely to engage with other subreddits related to COVID-19, COVID-19 misinformation, and conspiracies. r/conservative’s presence contrasted with r/Coronavirus’s liberal-leaning similar subreddits r/nottheonion and r/PoliticalHumor. Pew Research surveys reflect this as liberal Americans believed the pandemic was serious more than conservatives. “Vaccine” became more popular over time, likely, because of 12/2020 vaccine rollouts sparking discussions. “Quarantine” and “lockdown” likely decreased overtime as CDC guidelines decreased quarantine times and statewide lockdowns lessened overall. The incongruent “mask” incidence causation is unclear. This study shows, as activity mirrors previous survey results, online activity can reflect interests, sentiment, and overall activity of specific corresponding populations.

AMA Research Challenge 2022

Analysis of COVID-19 Information and Misinformation Subreddits

ICPR 2020 is the premier international conference on Pattern Recognition, gathering leading researchers from around the world to present their latest achievements in Pattern Analysis and Recognition, applied Artificial Intelligence and Machine Learning. The topic of the year is " Putting Artificial intelligence to work on Patterns". 
For the first time, ICPR has employed a two-round review process similar to journal submissions, with new papers allowed to be submitted in either the first or second round and papers submitted in the first round and not accepted allowed to be revised and re-submitted for second round review. 

In this edition of the **ICPR 2020** Conference, there are 1407 Oral/Poster presentations organized in five Tracks: 
- Artificial Intelligence, Machine Learning for Pattern Analysis; 
- Biometrics, Human Analysis and Behavior Understanding; Computer Vision, Robotics and Intelligent Systems; 
- Document and Media Analysis; and 
- Image and Signal Processing. 

The **ICPR 2020** Main Conference program also includes 7 Keynotes from prominent world-renowned scientists, 8 Tutorials, 28 Demos, 8 Challenges, 2 Panels, as well as an Industry/Sponsor Exhibition. In addition, 41 Workshops on a range of important current and emerging research topics complete the ICPR 2020 program. 


ICPR 2020

poster

Welcome to the largest national, multi-specialty research event **featuring research from 750 medical students, residents and fellows, and international medical graduates.**


#### Event Details
The 2022 American Medical Association Research Challenge includes a poster symposium hall and a semifinals hall with the top scored research. Log in at any time throughout the event to:
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At the conclusion of this event, the AMA will announce the top five finalists who will advance to the AMA Research Challenge finals, present their research to an elite panel of judges and compete to win a $10,000 grand prize sponsored by Laurel Road.
 

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 **Speakers**
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Ricardo Correa, MD, EdD
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Stuart M. Greenstein, MD
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Stephanie Strohbeen, MD
 
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Jessica Li, MD/PhD Candidate
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Charles Lopresto, DO

### Sponsor
AMA would like to thank Laurel Road for sponsoring a $10,000 grand prize for the winner of the AMA Research Challenge. Laurel Road is not involved in the judging or scoring process to select the winner. The winner will be announced on Dec. 7 during the AMA Research Challenge finals. Payment of the grand prize will be directly from Laurel Road. See the AMA Research Challenge Official Rules for terms and conditions.

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Registration Is Required

Welcome to the largest national, multi-specialty research event featuring research from 750 medical students, residents and fellows, and international medical graduates.


BACKGROUND: School safety is of growing interest with weapon carrying at the center. Weapon carrying in school causes physical injury and death among students and staff, and psychological trauma among those who witness the display or use of such weapons. Factors such as age, gender, mental and psychological status, bully victimization, family characteristics, poverty, and neighborhood crime have been associated with weapon carrying into schools. My main objective is to determine the prevalence of weapon carrying among US high school students and examine the association between bully victimization and weapon carrying in school.

METHODS: A nationally representative sample of high school students from the 2019 YRBSS data was utilized for this cross-sectional study (n= 13,677). Logistic regression was used to assess if bully victimization predicts the odds of weapon carrying, adjusting for age, sex, grade, and sexual identity. A stratified analysis using age groups was also carried out to determine the odds of weapon carrying among younger adolescents (15 years and younger) and older adolescents (older than 15 years).

RESULTS: In the final sample of 11,921 students, the prevalence of weapon carrying was 2.4%. 19.5% of the adolescents in the sample reported being bullied in school. Those who were bullied had 3.06 times greater odds of weapon carrying to school than those who were not bullied (aOR= 3.06; 95% CI 2.38,3.91]. These odds were lower among those aged
15 years and below (aOR= 2.05, 95% CI 1.33, 3.1) and higher among those greater than 15 years (OR= 3.45,95% CI 2.58, 4.6).

CONCLUSION: With about 16 million students in US high schools, the prevalence of weapon carrying suggests that about 368,000 students carry weapons to school. The results suggest that victims of bullying are more likely to carry weapons to school. Interventions to improve school safety should also focus on reducing bullying in schools. Particular attention should be paid to older adolescents who are victims of bullying.

Bully Victimization as a Predictor of Weapon Carrying in US High Schools: Is Age a Factor?

Background:
Bluelining is an outgrowth of redlining that is defined as overly aggressive policing while under-serving marginalized communities that results in space, place, and race consolidation. This zoning impacts health in various ways, such as higher levels of exposure to environmental toxins, inhabitation of food deserts resulting in malnutrition, higher rates of cancer incidence and death, and exposure to and transmission of infectious diseases for incarcerated individuals. Bluelining may contribute to toxic stress outcomes such as heart disease, substance use disorders, anxiety/depression, and auto-immune diseases. 

Bluelining research is scarce; thus this series fosters opportunities to educate providers, encourage advocacy, and support community healing. We hypothesize that participating in an advocacy workshop would increase awareness of bluelining as well as impart a base of knowledge on how to apply trauma-informed care (TIC) and Alternative Policing Response Models (APRM) to bluelining interventions. ​The objective was for students, physicians, educators, and community members to advocate for improvements to policy that perpetuate bluelining by investing in Alternative Police Response Models for Louisville, KY. 

Methods:
Recruitment ULSOM AMA/KMA listserv, University of Louisville-wide listservs, community flyers, social media, eventbrite, and email campaigns. Total attendees= 37 attendees. Sample size= 20.
Event structure
· Zoom and Facebook Live​
· Panelists – (6 Louisville Metro Councilmembers, Kentucky State Representative, Police Officer, and Law Professor). ​
· Overview of bluelining, how to advocate, open discussion and polling, and break out groups to contribute to a policy memo outline
Metrics De-identified pre/post surveys and demographics via QR code linked to QualtricsXM. IRB 22.089
Analysis: 2-tailed Fischer’s Exact Test and Wilcoxon Signed Rank. Statistical significance set at p<0.05. SPSS version 27.0 or SAS 9.4.

Results: Participants showed prior knowledge of bluelining, advocacy, and social determinants of health definitions.​ Statistically significant increase in ability for participants to advocate for legislative change and discuss bluelining as a social determinant of health. ​Statistically significant improvement in participants' confidence discussing and advocating for bluelining as a social determinant of health.​ The event encouraged confidence in advocating for public health policy. 
Conclusion:
This data demonstrates need and applicability for additional education and advocacy involving bluelining through the lens of TIC and APRMs.​

Caged Bird: Bluelining and Medicine Advocacy Workshop

Background

China has the largest population of older people and the largest number of Parkinson’s disease (PD) cases in a single country, but little is known about the determinants of PD in the Chinese population. Previous studies have reported different incidence rates of PD in Asian compared with Western populations, but few studies have assessed the determinants of PD in Asian populations. Prospective studies, conducted in Western populations, have also reported discrepant results for the associations of cardiovascular disease (CVD) risk factors with PD, with inverse associations with smoking, but positive associations with other CVD risk factors. Thus, the objectives of this study were to compare the risks of Parkinson's disease among those with versus those without prior stroke or heart disease at baseline in a prospective study of 0.5 million adults in China, and to examine associations of cardiovascular disease risk factors (cigarette smoking, hypertension, diabetes, obesity) with risk of PD.

Methods

During an average of 11.5 years of follow-up of 503,497 middle-aged participants in the China Kadoorie Biobank study, 603 incident cases were hospitalized with a diagnosis of PD. Cox proportional hazards models were used to assess associations of history of heart disease or stroke with PD in all participants, and of cardiovascular disease risk factors with PD in a subset without prior cardiovascular disease.

Results

In this population, the incidence rate of PD (mean [SD] age of cases, 61 [10] years) was 13.3 (95% confidence interval: 12.3–14.4) per 100,000 person-years. Incidence increased with age, and was higher in men than in women, and in urban than in rural residents. Prior stroke was associated with about twofold higher risk of PD (hazard ratio 1.94; 1.39–2.69). After adjustment for confounders in those without prior cardiovascular disease, a 5 kg/m2 higher body mass index was associated with 17% (1.17; 1.03–1.34: P = 0.019) higher risk of PD, but neither hypertension, diabetes, nor current cigarette smoking was significantly associated with PD.

Conclusion

Prior stroke and adiposity were each associated with higher risks of PD, but none of the other cardiovascular disease risk factors were significantly associated with PD in this population.

Cardiovascular risk factors and Parkinson's disease in 500,000 Chinese adults

Background
Through the American Medical Association-Medical Student Section (AMA MSS), medical students have advocated for policies related to a variety of challenges we face in healthcare. These policies are reviewed by the AMA MSS to decide the organization's level of support which then has an impact on the direction of healthcare in the country. This project is a novel analysis of both policy proposed and the resulting decisions from the AMA MSS which reflects the opinion and sociopolitical stance of medical student members in the organization.

Methods
Two authors reviewed 2208 AMA MSS policy proposals submitted between 1999-2021 and categorized them based on keywords within the title and resolved clauses. A third author settled any disputes. Policies were categorized as related to race, gender inequality, LGBTQIA+, reproductive health, immigration, socioeconomic status, medical education, pediatrics, AMA infrastructure, or Other. We categorized potential decisions as either positive, neutral or negative outcomes. Statistical analysis was performed using IBM SPSS Statistics Version 28.

Results
Linear regression revealed a positive correlation between policies proposed per year and time (R²= 0.63). A qualitative assessment demonstrated that past 2015 there was an increase in positive outcomes for proposals related to race, reproductive health, and AMA infrastructure. The average positive outcome rate of policies related to race, reproductive health, LGBTQIA+, and AMA infrastructure was significantly higher than the average positive outcome rate of all the proposals based on students t-test (p<0.05). Past 2015 there has been a qualitative increase in neutral outcomes over all topics. 

Conclusion
The results showed a consistent increase in policies proposed per year over the past two decades, suggesting greater student involvement. The greater amount of neutral outcomes since 2015 could indicate more indecision in the AMA possibly due to the increased complexity of issues the AMA now wants to address. This increase in neutral decisions may warrant expert consultation. Policies on race, reproductive health, LGBTQIA+ and AMA infrastructure showed a greater percentage of positive outcomes indicating a correlation between the topic and its approval rate but further analysis would need to determine a cause for this.

Changes in Approval Rate of AMA Policies by Topic

Background
Home rapid antigen tests (RATs) are widely available, partially due to government distribution programs. Time-sensitive clinical decisions about provision of ambulatory COVID-19 care can depend on the results of these studies, which are often more readily accessible than clinician-performed tests. It is assumed that the two are similarly accurate. However, few studies of self-test RAT accuracy exist. Here, we compare the accuracy of patient-performed and clinician-performed BinaxNOW RATs using PCR as a gold standard.

Methods
All adult patients between February 12, 2022 and May 18, 2022 at a free state testing site in Baltimore, USA, were offered enrollment. Demographic and symptom status were recorded. 3 samples were obtained from each participant: clinicians sampled bilateral nares for PCR and RAT, after which participants self-tested using identical RATs. Sensitivity and specificity were compared using Chi-square. 

Results
625 patients participated. 60.6% were female, 58.6% were white, 98.2% were English speaking, and median age was 34 (IQR: 28, 48.5). 34.1% were symptomatic and 14.9% were PCR positive by PCR. Clinician and self-performed RATs had similar sensitivity (88.2% [95% CI: 80.1%, 93.2%] vs 83.9% [95% CI: 75.1%, 90.0%] P= 0.40) and specificity (99.6% [95% CI: 98.5%, 99.9%] vs 99.8% [95% CI: 98.8%, 100%] P= 0.57). In symptomatic patients, self-test had a sensitivity of 94.5% (95% CI: 86.6-98.5) and specificity of 62.5% (95% CI: 24.5-91.5). For asymptomatic patients, self-test had a sensitivity of 66.7% (95% CI: 29.9-92.5) and specificity of 100% (95% CI: 29.2-100.0). These were similar to clinical PCR as well. 

Conclusion
Clinician-performed and self-performed RATs had similarly high accuracy. The high observed sensitivity of home RATs supports their continued usage in ambulatory decision-making to identify eligible candidates for COVID-19 therapeutics. Their accessibility is key, since federal policy now states that patients are treatment eligible for a maximum of 7 days. Self-performed RATs reduce barriers including time needed to search for and then attend clinician appointments, and allow patients to play a larger role in their own care. Low false positive rates mitigate concerns about poor technique or contamination, and ensure that treatment is appropriate. Our study supports continued use of home RATs for clinical decision making.

Comparison of Accuracy of Self-Test and Clinical Rapid Antigen Testing for Coronavirus-19 (COVID-19)

Background
Non-urgent use of the emergency department (ED) is costly for patients. It can lead to increased healthcare spending and ED overcrowding and negatively affect primary care physician (PCP)-patient relationships. We aim to evaluate the association between perceived medical urgency, PCP coverage (whether a patient has a PCP), and patient descriptive characteristics with utilization of the ED for non-urgent clinical care.

Methods
Adult ED patients were stratified to preventable and non-preventable ED visits according to their emergency severity index (ESI) at the UC Irvine ED. A REDCap questionnaire was used to assess descriptive information, self-perceived medical urgency, and PCP Coverage. Chi-Square tests at a 5% significance level were performed to examine differences between race, native language, self-perceived medical urgency, and PCP coverage between preventable and non-preventable ED visits. 

Results
Study participants included 348 adult patients (52% female), of which 160 (46%) were preventable visits (ESI 4-5). There were more preventable visits among Black patients compared to non-Black patients (69.6% vs 30.4%, p=0.028) and the preventable group had less native English speakers than the non-preventable group (38.8% vs 61.2%, p=0.035). Compared to patients in the non-preventable ED visit group, patients in the preventable group are more likely to agree that they could have been seen and treated effectively by a PCP (p=0.003). Fewer patients in the preventable group have a PCP that they can see regularly and make an appointment with compared to the non-preventable group (40.3% vs 59.7%, p=0.004). 

Conclusion
Our results indicate that Black patients and non-native English speakers were overrepresented in preventable ED visits compared to their counterparts, suggesting these patients may be more vulnerable to the plethora of negative consequences associated with utilizing the ED for non-emergent medical services. In addition, our study also revealed that patients in the preventable ED visit group were less likely to have a PCP, even though they were more likely to agree that a PCP could manage their symptoms. Future interventions are needed to address this lack of PCP coverage among preventable ED patients to reduce patient financial burden, ED overcrowding, and overall healthcare spending.

Comparison of Patient Characteristics and Perceived Medical Urgency between Preventable and Non-Preventable Emergency Department Visits

Background
For almost 2 years COVID-19 pandemic has put a myriad of stressors on Health Care Workers (HCW). HCWs were at high risk of exposure to COVID-19. Understanding the factors associated with getting COVID-19 in the hospital setting among the employees are critical to advancing better interventions in the future. 
Methods
Hospital employees who were infected with COVID-19 were assessed in a descriptive study by using IDEA data base and occupational health records in a Large Upper Midwest integrated health system, from March 2019 through June 2020. Categorical variables were analyzed using Chi-squared test (χ2). Logistic regression analysis was performed to explore the risk factors for acquiring the disease. A two-sided P < 0.05 was considered statistically significant. Also, odds ratios (OR) and 95% confidence intervals (95% CI) were carried out for the statistical analysis.
Results
During the period of analysis there were 33175 valid test results among that 2981 (9%) were positive for COVID-19. Majority of employees were Registered Nurses (31.4%). 69.2% employees who reported positive test results had community related exposures while 30.6% had work related exposures. 830 employees who had a positive test result and reported work related exposure had cared for a COVID-19 patient (91.9%). 49 employees had breech to a COVID-19 patient (5.5%) while 99 had a known exposure to a HCW who had COVID-19 (11.1%). Body aches were the primary reported symptom (61.9%, OR=2.703). Some of the other reported symptoms include Loss of smell and taste (59.6%, OR=7.52); Cough (31.2%, OR=2.51); Headache (25%, OR=1.8) and Shortness of Breath (25.4%, OR=1.33). Caring for COVID-19 patients was associated with acquiring COVID-19 (P=0.001, CI=0.058-0.142). Reported breeches from employees were not found to be risk factors for COVID-19 (P=0.25, CI=-0.05-0.00) 
Conclusion
Although work related exposure to COVID-19 was low during the early months of the pandemic, caring for COVID-19 patients identified as a risk factor.

COVID-19 Exposures And Risk for Transmission Among Allina Health Hospital Employees

Background:
The advent of artificial intelligence/machine learning (AI/ML) in medicine has opened opportunities for harnessing the power of ML to predict patient outcomes based on diverse data contained in the electronic medical records (EMR). Taken by themselves singular features represented by such diverse data are often not clearly predictive, but combined in an ML modeling framework such so-called weak learners have the power to yield highly predictive models of health outcomes. 
 
Methods:
We hypothesized that sociodemographic and basic, easily obtainable health characteristics of pregnant mothers strongly predict the risk of rehospitalization.
Using the nuMoM2b dataset from NICHD and reproducible, open access AI/ML techniques we tested and validated this hypothesis. 
 
Results:
Among a large (n=10,038) and geographically diverse cohort of nulliparous women with singleton gestations, the present findings show that while some of these characteristics highlight the known disparities in health outcomes (race/ethnicity), most of them are modifiable through social policies and health counseling. These include access to and support during education, comprehensive health insurance, alleviating coming out of poverty, smoking, and unhealthy lifestyle habits.
 
Conclusion:
Across the four ML models deployed, the results are mutually reinforcing yielding a clear cohesive picture. This solution can be used to develop a prospective risk prediction for this important health outcome in pregnant mothers. The strengths of the presented solution are its focus on preventable maternal morbidities and risk factors, demonstration of the impact on adversely affected populations, and reproducible step-by-step executable, documented open-access code with relatively low computational requirements. This enables easy adoption and further development on this and other similar datasets to study the contributions and predictive power of various factors to maternal morbidities.

Demographic and socioeconomic factors predict maternal postpartum rehospitalization: a retrospective nuMoM2b dataset study

Background: Within New York City (NYC), certain communities have experienced greater rates of adverse COVID-19 outcomes. Current literature has evaluated the effectiveness of public health interventions during COVID-19 but fails to stratify across boroughs with varying demographic makeups. Understanding the effect of COVID-19 on different NYC communities may allow for the development of more efficacious public health policies that address populational disparities. Therefore, we compared trends in COVID-19 cases, hospitalizations, and deaths between the five NYC boroughs before and after the start of vaccine administration, using an interrupted time series analysis.

Methods: Data was collected from the Department of Health and Mental Hygiene’s dataset on daily COVID-19 cases, hospitalizations, and deaths. Our interrupted time series began on June 8th, 2020 and analyzed data through July 3rd, 2021. The intervention in our analysis was the availability of vaccinations to New Yorkers aged 16 years or older, beginning April 6th, 2021. Changes between pre- and post-intervention outcome trends were compared across each of the boroughs.

Results: In NYC as a whole, there was a significant decrease in the trend of cases, hospitalizations, and deaths following vaccinations. The greatest decreases in case trends were seen in the Bronx, Brooklyn, and Queens. Staten Island had a significantly greater decrease in hospitalizations, yet had the smallest change in deaths per unit time. In contrast, Brooklyn had a significantly greater decrease in death trends compared to all other boroughs.

Conclusion: We demonstrate a significant decrease in the trends of cases, hospitalizations, and deaths in NYC following vaccinations, illustrating its effectiveness in mitigating the spread of the pandemic. However, such decreases varied between boroughs, potentially owing to demographic and population-based disparities. Variations in post-intervention death trends may be attributed to Brooklyn’s larger population and a higher percentage of unmet medical care. Furthermore, boroughs with the highest proportion of Black/Hispanic inhabitants and unemployment experienced the greatest rise in pre-intervention death trends. This may indicate a need to target such populations in future public health crises. Nevertheless, boroughs with the highest minority populations showed the greatest decrease in case and death trends, suggesting the vaccine’s effectiveness among underserved populations. 


Differences in the Effectiveness of COVID-19 Vaccine Administration Between the Five New York City Boroughs: An Interrupted Time Series Analysis

Background
Asthma is a chronic respiratory condition affecting around 300 million people worldwide. In North America, the prevalence of asthma in children and young adults is about 11%. Multiple studies have shown that the burden of asthma was higher in the inner-city when compared to non-inner-city areas. In the United States, African and Hispanic Americans have a higher burden for asthma compared to White Americans. The goal of this study was to differentiate the burden of asthma between US-born and foreign-born Black New York City (NYC) residents. 
Methods
This is a secondary data analysis of the 2014 NYC Health and Nutrition Examination Survey (NYC HANES). The covariates of interest are age, sex, education, income, health insurance, and smoking status. We test for differences in asthma among Black residents of NYC by nativity using a multivariable Cox proportional hazard model with robust estimates by using a constant time for cross-sectional studies. We use domain analysis to maintain the complex survey structure of the data. Standard errors were estimated using Taylor’s Series Linearization, accounting for the complex survey nature of the data collection. We conducted all analyses in SAS OnDemand for Academics®. We set the threshold for significance at 5%.
Results
The final analytic sample represented a weighted proportion of 24.16% (SE = 1.40). The proportion of US-born Black residents was 61.1% and the proportion of foreign-born Black residents was 38.9%. Univariate analysis indicated that 29.2% of US-born Black NYC residents reported an asthma diagnosis compared to 10.7% of foreign-born Black residents of NYC (p-value < 0.001). The result of the covariate-adjusted model indicated that foreign-born Black NYC residents had a significantly lower prevalence of asthma compared to US-born (PR = 0.40, 95% CI = 0.21-0.76). Additionally, those who are 65 years and older had a lower asthma risk compared to those 20-34 years old.
Conclusion
This study shows that asthma is found in higher rates amongst US-born Black NYC residents as opposed to foreign-born. Further studies should investigate this result in a national sample. Also, studies should investigate association of acculturation to asthma outcome in foreign-born population.

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Bully Victimization as a Predictor of Weapon Carrying in US High Schools: Is Age a Factor?

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