United States

Background: Recent studies in large databases characterize child abuse and investigate the utility of clinical decision tools to detect physical abuse. This study characterizes risk factors preceding a diagnosis of physical abuse (NAT) in the pediatric trauma population to explore the potential of administrative databases in detecting physical abuse.
Methods: The Maryland Health Services Cost Review Commission (HSCRC) public-use data was queried for patients aged 0-19 to balance the number of patient records with the constraints of the database. Suspected physical abuse, confirmed physical abuse, and trauma were outcomes identified using ICD10 codes. Using logistic regression, odds ratios for each diagnostic code were identified unadjusted and adjusted for age, sex, race, ethnicity, year of encounter, and payer. Significance equals p&lt;.05 after Bonferroni/Holm adjustment. Analysis was conducted in R (R Core Team, 2022).
Results: We identified 2,230 patients diagnosed with confirmed or suspected physical abuse totaling 10,546 encounters prior to NAT diagnosis. We identified 396,575 pediatric trauma patients totaling 606,146 encounters. The regression model comparing diagnostic codes of confirmed or suspected NAT with pediatric trauma yielded hundreds of statistically significant diagnostic codes. We report only the diagnoses with the highest frequency in the confirmed or suspected NAT population adjusted for demographic characteristics.
Conclusion: We identify known risk factors and findings associated with the child abuse population, such as racial disparities, psychiatric conditions, and congenital conditions. Several hundred statistically significant diagnoses were identified, demonstrating the limited immediate clinical utility of any single diagnostic code. We identified diagnostic codes such as cough, asthma, and visual pathologies that increase the odds of NAT but are poorly characterized in the literature. A large number of statistically significant diagnoses presents an opportunity to use machine learning in the child abuse population to assist clinicians in diagnosing and identifying NAT. 


AMA Research Challenge 2022

Identifying Risk Factors Preceding Non-Accidental Trauma Among Pediatric Trauma Patients in the HSCRC dataset

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Ricardo Correa, MD, EdD
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Jessica Li, MD/PhD Candidate
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Charles Lopresto, DO

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Welcome to the largest national, multi-specialty research event featuring research from 750 medical students, residents and fellows, and international medical graduates.


Background: Recent studies in large databases characterize child abuse and investigate the utility of clinical decision tools to detect physical abuse. This study characterizes risk factors preceding a diagnosis of physical abuse (NAT) in the pediatric trauma population to explore the potential of administrative databases in detecting physical abuse.
Methods: The Maryland Health Services Cost Review Commission (HSCRC) public-use data was queried for patients aged 0-19 to balance the number of patient records with the constraints of the database. Suspected physical abuse, confirmed physical abuse, and trauma were outcomes identified using ICD10 codes. Using logistic regression, odds ratios for each diagnostic code were identified unadjusted and adjusted for age, sex, race, ethnicity, year of encounter, and payer. Significance equals p<.05 after Bonferroni/Holm adjustment. Analysis was conducted in R (R Core Team, 2022).
Results: We identified 2,230 patients diagnosed with confirmed or suspected physical abuse totaling 10,546 encounters prior to NAT diagnosis. We identified 396,575 pediatric trauma patients totaling 606,146 encounters. The regression model comparing diagnostic codes of confirmed or suspected NAT with pediatric trauma yielded hundreds of statistically significant diagnostic codes. We report only the diagnoses with the highest frequency in the confirmed or suspected NAT population adjusted for demographic characteristics.
Conclusion: We identify known risk factors and findings associated with the child abuse population, such as racial disparities, psychiatric conditions, and congenital conditions. Several hundred statistically significant diagnoses were identified, demonstrating the limited immediate clinical utility of any single diagnostic code. We identified diagnostic codes such as cough, asthma, and visual pathologies that increase the odds of NAT but are poorly characterized in the literature. A large number of statistically significant diagnoses presents an opportunity to use machine learning in the child abuse population to assist clinicians in diagnosing and identifying NAT.

poster

Socio-demographic Characteristics of Childhood Asthma and its Association With Substance Abuse – US Cross-Sectional Survey Study

Background: In Puerto Rico (PR), statistics of developmental disorders have not been published since 2017 when nearly 3,000 cases were documented. Since the beginning of the COVID-19 pandemic, there’s been a decrease in visits to pediatrician’s office for both preventive and urgent reasons. Moreover, in January 2020, a magnitude 6.4 earthquake devastated part of PR leading to further suspension of pediatrician's office. It is this concern for the loss of surveillance, screening and follow up amid these events and the lack of current statistic in PR, that there is a need to evaluate the prevalence of developmental delays (PDD) in this population. For such we established two objectives: (1) explore the yearly PDD in children admitted to the pediatric unit and (2) identify if there’s been a change in PDD during and after natural disaster and COVID-19 pandemic. Methods: This is a retrospective cross-sectional study. Electronic charts of 1,082 patients, ages 1-60 month, with no previous neurodevelopmental condition and who were admitted to the pediatric unit, during January 2017- December 2021 were reviewed. We obtained their sociodemographic data and the results from the domains of gross motor, fine motor, communication. personal-social and problem solving of the Ages and Stages Questionare-3 (ASQ-3). Results: Of the patients evaluated 56% were male and 44% females, with more than 2/3 of them below the poverty index. The mean age of evaluation was 21.4 month. A steadily increase yearly PDD was noted in all ASQ-3 domains. Statistical analysis showed significance in 3 out of the 5 domains with p-values <0.05. Conclusion: Our study shows steadily increasing PDD in at all areas of development in 2020-2021, correlating with the years of the events. The growing trend is statically significant when compared with previous years, which may be explained by the loss of follow up during this period. To our knowledge, this the only study evaluating how the mentioned events correlate with the normal development of Puerto Rican children. It also provides a recent statistic of patients with some form of developmental delay, suggesting that the current estimate in PR is far lower than the actual PDD.

Trends in Developmental Delays During a Natural Disaster and Covid-19 Pandemic.

Background: Stigma surrounding mental health issues can prevent members of the Asian Indian diaspora living in the United States (US) from seeking adequate medical attention. Asian Indian Americans (AIAs), like other immigrant groups in the US, face increased psychological distress from migration, acculturation pressures, and other social determinants that can adversely impact functioning and quality of life. We sought to determine if self-reported data regarding attitudes towards mental health issues and rates of access to mental healthcare among AIAs were unique when compared to other racial/ethnic groups within the US using the nationally representative 2015-2018 National Health Interview Surveys (NHIS).

Methods: This cross-sectional study included 111,065 adults aged 18-84 years old. The data were first stratified by race. Chi-square tests of independence were performed by survey question using Python 3.10 to assess how race/ethnicity correlated with self-reported symptoms, diagnoses, and treatments of anxiety and depression. The Wilcoxon rank-sums test was then performed to determine the uniqueness of AIA responses within the US population. 

Results: Among 111,065 participants, 45.2% of respondents were male, 54.8% were female, 80.0% were white, 12.4% were black/African American, 1.3% were Native American, 1.2% were Asian Indian, 4.3% were other Asian, and 0.7% were other/multiple races. Race correlated with severity, symptoms, and treatment of both anxiety and depression. AIAs were most likely to self-report “never” experiencing symptoms such as nervousness (94.7%, p=0.0039), hopelessness (91.4%, p=0.010), worthlessness (94.7%, p=0.0039), and avolition (80.6%, p=0.0039) as compared to all other racial/ethnic groups at the 0.05 level of significance. AIAs were also more likely to report not receiving treatment for anxiety (95.7%, p=0.049) or depression (97.3%, p=0.049) in 2018. 

Conclusion: These data quantitatively indicate AIAs are less likely to self-report symptoms of anxiety and depression, and are less likely to seek treatment for the same. Given the prevalence of stigma concerning mental health in many South Asian cultures, it is essential to further investigate the nuances of how AIAs understand and advocate for their mental wellbeing. Further study is required to assess the role of stigma, overall mental health literacy, and possible success of targeted intervention with the AIA population.

Comparing Self-Reported Mental Health Data in Asian Indian Americans to National Trends

Abstract Title: Learning How to Cope: Medical Student Burnout and its Effect Over Emotional Development

Background: The medical curriculum is stressful due to its expanding academic workload, new responsibilities, and rigorous standardized testing. Some students have effective coping strategies to manage these stressors, while others may engage in maladaptive strategies that can lead to burnout syndrome. This study explores factors which may influence the development of burnout in future physicians.

Methods: Data was collected from self-report questionnaires of 131 medical students at the University of Puerto Rico-School of Medicine. Questionnaires were administered through REDCap and included the Maslach Burnout Inventory as a measure of burnout and Coping Strategies Survey. The study was approved by the UPR Institutional Review Board as protocol B1750121. Descriptive analyses were used to determine prevalence of burnout and coping strategies. Spearman’s Rho correlations were calculated to evaluate relationships between the variables. All analysis were performed using SPSS.


Results: Family support (rho=0.215, p=0.013) and visiting the Wellness center (rho= 0.193, p=0.027) were positively correlated with professional efficacy (PE). A negative correlation was observed between social withdrawal (rho=-0.341, p<0.001) and PE. Decreased eating (rho=0.259, p=0.003), social withdrawal (rho=0.372, p<0.001), compulsive shopping (rho=0.338, p< 0.001) and energy drink use (rho=0.202, p=0.020) were positively correlated to burnout. Seeking professional mental health help was associated with higher burnout (rho=0.185, p=0.35)

Conclusion: Dysfunctional coping strategies were correlated to increased mean burnout scores. In contrast, a moderate-strong correlation was observed between functional coping strategies with increased levels of PE and lower burnout levels. These results facilitate identification and promotion of effective strategies to decrease burnout among UPR-SoM students. Even though results were compelling, burnout could have been underestimated, therefore future longitudinal studies with similar cohorts are necessary to further investigate actual causal relationships.

Learning How to Cope: Medical Student Burnout and its Effect Over Emotional Development

Background: 
Studies suggest that LGBTQ+ youth are at increased risk of engaging in substance use and misuse, including alcohol, tobacco, and illicit drugs. The COVID-19 pandemic forced many students to transition to a virtual learning environment in 2020 and early 2021, and the impacts of this have been purported to be detrimental. This study examines the prevalence of alcohol and substance use among lesbian, gay, and bisexual US high school students prior to the pandemic in 2019 compared to early 2021. We hope to identify possible factors which contribute to substance use in this population and provide direction for future studies. 
Methods
Results from the 2019 Youth Risk Behavior Survey (YRBS) and 2021 Adolescent Behavior and Experiences Survey (ABES) were used for this study. These two surveys provide important data regarding the prevalence of substance use high school students before and during the COVID-19 pandemic. We selected 15 questions concerning alcohol and substance use common to both surveys and isolated results for lesbian, gay, and bisexual students. We directly compared results from 2019 and 2021 and calculated the relative change from 2019. 
Results
We found a decrease in prevalence for all 15 alcohol and substance use-related questions from 2019 to 2021 among lesbian, gay, and bisexual students. The largest relative decreases included “Ever used cocaine” (73% decrease), “Ever used ecstasy” (69% decrease), and “Were offered, sold, or given an illegal drug on school property” (62% decrease). “Ever used inhalants” demonstrated the most modest decrease at 7.4%.
Conclusion
This data illustrates what appear to be substantial decreases in alcohol and substance use among lesbian, gay, and bisexual high school students from 2019 to 2021. These decreases have occurred in the context of the COVID-19 pandemic, and reported increases in mental health problems among this population. These results should prompt further research into how social interactions at school (or the lack thereof) of LGBTQ+ youth contribute to patterns of alcohol and substance use. By identifying such factors, we can recognize potential points of intervention.

Prevalence of Substance Use among Lesbian, Gay, and Bisexual High School Students in 2019 vs. 2021

Background: Medicare reimbursements are federally determined, while Medicaid reimbursements are determined by each state. More variable Medicaid reimbursements can create financial and administrative burdens that may prevent patients from receiving care.
Objective: To evaluate and characterize state variation in Medicaid and Medicare published reimbursement rates for the 20 most commonly ordered computed tomography (CT), magnetic resonance imaging (MRI), ultrasound (US) and radiograph (XR) studies. 
Methods: The 20 most commonly performed CT, MRI, US, and XR studies (80 studies) based on Medicare’s 2019 National Summary Data File were evaluated. The technical and professional components of reimbursements were analyzed. Paired t-tests were used to compare the average provider reimbursement rates, the CV of reimbursement rates, and the proportion of each total reimbursement rate accounted for by the professional component between Medicare and Medicaid.
Results: Medicare reimbursement variation (CV range: 0.07-0.08) was significantly lower than Medicaid reimbursement variation (CV range: 0.217-0.548) (P < 0.05 for all studies). For Medicaid, US had the lowest variation (CV= 0.280), then CT (CV= 0.328), XR (CV= 0.345) and MRI (CV= 0.398). Medicare dedicated a higher percentage to professional components than Medicaid for CT and MRI (P < 0.001); Medicaid proportionally paid greater professional component fees for XR (P = 0.002). Most reimbursement volatility was due to fluctuations in the technical rather than professional components. 
Discussion: Medicaid reimbursements for the most commonly ordered imaging studies were significantly more variable than Medicare reimbursements. This reimbursement variation may limit access to imaging care for certain populations.

State Variation of Medicaid Reimbursement Rates in the 20 most commonly ordered CT, MRI, Ultrasound and Radiograph Studies May Contribute to Geographic Healthcare Disparities

Background
The 2013 United States Preventive Services Task Force (USPSTF) lung cancer screening (LCS) guidelines were derived from clinical trials of predominantly White men, and lower rates of LCS eligibility have subsequently been found for Black and Hispanic adults. We evaluated whether the revised 2021 USPSTF criteria reduced inequities in LCS eligibility among a racially diverse sample of lung cancer patients. 

Methods
We conducted a retrospective chart review of patients at an urban safety net hospital diagnosed with a primary lung malignancy between 2015-2020. LCS eligibility was determined based on age, pack-years, and smoking status. For all patients and exclusively ever-smokers, χ2 tests were used to evaluate differences in LCS eligibility among demographic variables (race, sex, ethnicity, education level, insurance type) for both the 2013 and 2021 USPSTF criteria. Patients who were ineligible for LCS were categorized by respective reasons.

Results
Among 678 lung cancer patients (46% female, mean age 66 ± 10 years), 51% were White and 39% were Black. Using the 2013 guidelines, White patients (183 [57%]) would have been more likely to be eligible than Black (89 [37%]) and other-race patients (23 [35%]) (p<0.0001). Using the 2021 guidelines, White patients (220 [68%]) remained more likely to be eligible for LCS than Black (130 [54%]) and other-race patients (31 [48%]) (p=0.0002). The most common reason for ineligibility using the 2013 (183 [50%]) and 2021 (90 [33%]) guidelines was not meeting the pack-years threshold. We identified 88 never-smokers [White (23%), Black (47%)]. Among exclusively ever-smokers, there was no significant difference in eligibility by race under the 2021 criteria [White (73%), Black (65%), other-race (65%); (p=0.48)]. For both the 2013 and 2021 guidelines, sex, ethnicity, education level, and insurance type were not associated with differential screening eligibility among the entire study sample nor exclusively ever-smokers.

Conclusion
The 2021 USPSTF LCS guidelines may not be sufficient to eliminate racial inequities in LCS eligibility among patients who go on to be diagnosed with lung cancer. Differential rates of lung cancer among never-smokers may contribute to this inequity. Further research is needed to refine LCS guidelines, with particular consideration of non-smoking risk factors.

Black Race Remains Associated with Lower Eligiblity for Screening Using 2021 US Preventive Services Task Force Recommendations among Lung Cancer Patients at an Urban Safety Net Hospital

Previous studies have evaluated comorbidities and sociodemographic factors individually or by type but not comprehensively. This study aims to analyze the influence of a wide variety of factors in a single study to better understand the big picture of their effects on case-fatalities. This cross-sectional study used county-level comorbidities, social determinants of health such as income and race, measures of preventive healthcare, age, education level, average household size, population density, and political voting patterns were all evaluated on a national and regional basis. Analysis was performed through Generalized Additive Models and adjusted by the COVID-19 Community Vulnerability Index (CCVI). Effect estimates of COVID-19 fatality rates for risk factors such as comorbidities, sociodemographic factors and determinant of health. Factors associated with reducing COVID-19 fatality rates were mostly sociodemographic factors such as age, education and income, and preventive health measures. Obesity, minimal leisurely activity, binge drinking, and higher rates of individuals taking high blood pressure medication were associated with increased case fatality rate in a county. Political leaning influenced case case-fatality rates. Regional trends showed contrasting effects where larger household size was protective in the Midwest, yet harmful in Northeast. Notably, higher rates of respiratory comorbidities such as asthma and chronic obstructive pulmonary disease (COPD) diagnosis were associated with reduced case-fatality rates in the Northeast. Increased rates of chronic kidney disease (CKD) within counties were often the strongest predictor of increased case-fatality rates for several regions. Our findings highlight the importance of considering the full context when evaluating
contributing factors to case-fatality rates. The spectrum of factors identified in this study must be analyzed in the context of one another and not in isolation.


Comorbidities and Sociodemographic Factors Effect on COVID-19 Fatalities: A Comprehensive Analysis

Background: The United States endured one of the hardest hits of the COVID-19 pandemic. The ethnic minority groups were affected the most due to skepticism about the vaccines. Concerning vaccine hesitancy in the US, fewer studies were performed for the South Asian American population compared to other groups. This review summarizes the essential factors that contributed to vaccine hesitancy in South Asian Americans and other minority groups and outlines the strategies to circumvent these factors to increase vaccination rates in these populations.

Methods: We conducted a comprehensive search for peer-reviewed articles in electronic databases, PubMed and Google scholar. The key search terms were "COVID-19 vaccine hesitancy", "South Asian Americans and COVID-19 vaccine hesitancy," and "minority population in US and COVID-19 vaccine hesitancy". Studies that aimed to investigate the detailed and comprehensive analysis of attitudes and perceptions of people towards the COVID-19 vaccine were included in our review. We included cross-sectional studies, surveys, and narrative and systematic reviews published during the pandemic (up to December 2021). Studies published in a language other than English and preprint articles with no evidence of a peer review process were excluded from our review.

Results: A total of 70 articles were included in our review that met the inclusion criteria. The commonly encountered reasons for vaccine hesitancy were the expedited development of the COVID-19 vaccine, concerns regarding the vaccine safety, potential side effects and long-term consequences, doubt about the efficacy of the vaccine, and lack of trust in the health care system due to systemic racism and discrimination endured by minority population. Political biases and anti-vaccine propaganda through social media also contributed to vaccine hesitancy.

Conclusion: Concerns regarding the adverse effects and efficacy of the vaccine, lack of trust in the healthcare system, inadequate access to healthcare, and underrepresentation of minorities in clinical research contributed to vaccine hesitancy among the minority population, including South Asian Americans. Implementing health education programs with culturally & linguistically appropriate materials to create awareness regarding vaccination against COVID-19 and representing minority populations in health care research to gain trust will be beneficial.




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