United States

BACKGROUND: About 30-40% of PDAs can be missed on CTs due to subtle imaging findings. Unfortunately, PDA can advance from being undetectable to widely metastatic in a matter of months which underscores the critical need to develop novel tools such as AI to improve its detection. Most current AI-based PDA detection approaches require manual segmentations that are not clinically scalable. Our objective was to develop a 3D Convolutional Neural Network (CNN) for fully automated detection of PDA on standard-of-care CTs.

METHODS: A fully-automated 3D-CNN was trained on a dataset of 696 portal venous phase diagnostic CTs with PDA and 1080 control CTs with normal pancreas. Model was evaluated on (a) test subset of 409 PDA and 829 control CTs; (b) simulated cohort with high pre-test probability of PDA (1-5% over 3-years), which matched the case-control distribution in high-risk groups (glycemically-defined new-onset diabetes and high ENDPAC score); (c) multi-institutional public dataset of 194 PDA and 80 control CTs; and (d) a cohort of 102 prediagnostic CTs (i.e. CTs with normal-appearing pancreas incidentally acquired 3–36 months before clinical diagnosis of PDA) and 134 control CTs.

RESULTS: In the test subset, the model correctly classified 360 (88%) PDA CTs and 783 (94%) normal CTs [accuracy (mean; 95% CI) 0·92 (0·91-0·94); AUROC 0·97 (0·96-0·98), sensitivity 0·88 (0·85-0·91), specificity 0·95 (0·93-0·96)]. Performance was comparable across tumor stages (sensitivity 0·80, 0·87, 0·95 and 1 on T1 through T4 stages, respectively), hypodense versus isodense tumors (sensitivity: 0·90 vs. 0·82), age, sex, CT slice thicknesses &amp; vendors (all p &gt;0·05), and generalizable on both the simulated cohort [accuracy 0·95 (0·94-0·95), AUROC 0·97 (0·94-0·99)] and public dataset [accuracy 0·86 (0·82-0·90), AUROC 0·90 (0·86-0·95), sensitivity 0·88, specificity 0·93] including for T1 and isodense tumors (sensitivity 0·76 and 0·88, respectively). Despite being trained on diagnostic CTs, the model could detect PDA at the prediagnostic stage from normal pancreas [accuracy 0·84 (0·79-0·88), AUROC 0·90 (0·87-0·94), sensitivity 0·75 (0·66-0·83), specificity 0·90 (0·85-0·95)] at a median interval of 475 days (range:93-1082 days) between prediagnostic CTs and the clinical diagnosis of PDA. 

CONCLUSION: A 3D-CNN developed on a large dataset shows high accuracy and generalizability for fully-automated detection of PDA (including small and isodense tumors) on diagnostic CTs as well as for early detection of PDA from normal pancreas on prediagnostic CTs at a substantial lead time prior to clinical diagnosis. Prospective validation with blood-based biomarkers could enable AI-augmented early detection of PDA in high-risk subjects.

AMA Research Challenge 2022

AI-Powered Fully automated Early Detection of Pancreatic Ductal Adenocarcinoma on Standard-of-care CT Scans.

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:
* **View posters and presentations** on a variety of topics and specialties
* **Score posters in the semifinals** to help decide the top five finalists (AMA member exclusive opportunity)
* **Connect with participants** and provide feedback to help advance their research

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.
<br>

#### Attend Live Forums
**Oct. 20, 6 — 7 p.m. Central**
<br>**How to plan a career in academic medicine** 
<br>Learn how to plan a career in academic medicine and get your questions answered. [Access Here](https://underline.io/events/363/lounge)
<br>
<br>**Speakers**
![](https://assets.underline.io/uploads/markdown_image/1/image/d5adb133dfc58eb0a6d469e9cedcd5d4.jpg)
Ricardo Correa, MD, EdD
![](https://assets.underline.io/uploads/markdown_image/1/image/5f9437ab87861538bf02b9ca7c0d926e.jpg)
Stuart M. Greenstein, MD
![](https://assets.underline.io/uploads/markdown_image/1/image/05b1b637c99286d558c371f8e8b185ce.jpg)
Stephanie Strohbeen, MD
<br>
<br>**Oct. 22, 11 a.m. — Noon Central**
<br>**How to get published**
<br>Learn tips to get your research published and get your questions answered. [Access Here](https://underline.io/events/363/lounge)
<br>
<br>**Speakers**
![](https://assets.underline.io/uploads/markdown_image/1/image/8ce6235e957d31cb5e6f9097cc6f6972.jpg)
Jessica Li, MD/PhD Candidate
![](https://assets.underline.io/uploads/markdown_image/1/image/9950ef2e0237f54cb3d8280334d42491.jpg)
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.

![](https://assets.underline.io/uploads/markdown_image/1/image/611e331d4a0eba0920f240cfc04b4d77.png)

<br>

**There is no registration fee for this event! **

Register to explore research in a variety of topics. AMA members get exclusive access to score posters in the semifinals.

**Please use the link below to register for free if you have not already done so:**

https://www.ama-assn.org/about/events/ama-research-challenge

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: About 30-40% of PDAs can be missed on CTs due to subtle imaging findings. Unfortunately, PDA can advance from being undetectable to widely metastatic in a matter of months which underscores the critical need to develop novel tools such as AI to improve its detection. Most current AI-based PDA detection approaches require manual segmentations that are not clinically scalable. Our objective was to develop a 3D Convolutional Neural Network (CNN) for fully automated detection of PDA on standard-of-care CTs.

METHODS: A fully-automated 3D-CNN was trained on a dataset of 696 portal venous phase diagnostic CTs with PDA and 1080 control CTs with normal pancreas. Model was evaluated on (a) test subset of 409 PDA and 829 control CTs; (b) simulated cohort with high pre-test probability of PDA (1-5% over 3-years), which matched the case-control distribution in high-risk groups (glycemically-defined new-onset diabetes and high ENDPAC score); (c) multi-institutional public dataset of 194 PDA and 80 control CTs; and (d) a cohort of 102 prediagnostic CTs (i.e. CTs with normal-appearing pancreas incidentally acquired 3–36 months before clinical diagnosis of PDA) and 134 control CTs.

RESULTS: In the test subset, the model correctly classified 360 (88%) PDA CTs and 783 (94%) normal CTs [accuracy (mean; 95% CI) 0·92 (0·91-0·94); AUROC 0·97 (0·96-0·98), sensitivity 0·88 (0·85-0·91), specificity 0·95 (0·93-0·96)]. Performance was comparable across tumor stages (sensitivity 0·80, 0·87, 0·95 and 1 on T1 through T4 stages, respectively), hypodense versus isodense tumors (sensitivity: 0·90 vs. 0·82), age, sex, CT slice thicknesses & vendors (all p >0·05), and generalizable on both the simulated cohort [accuracy 0·95 (0·94-0·95), AUROC 0·97 (0·94-0·99)] and public dataset [accuracy 0·86 (0·82-0·90), AUROC 0·90 (0·86-0·95), sensitivity 0·88, specificity 0·93] including for T1 and isodense tumors (sensitivity 0·76 and 0·88, respectively). Despite being trained on diagnostic CTs, the model could detect PDA at the prediagnostic stage from normal pancreas [accuracy 0·84 (0·79-0·88), AUROC 0·90 (0·87-0·94), sensitivity 0·75 (0·66-0·83), specificity 0·90 (0·85-0·95)] at a median interval of 475 days (range:93-1082 days) between prediagnostic CTs and the clinical diagnosis of PDA. 

CONCLUSION: A 3D-CNN developed on a large dataset shows high accuracy and generalizability for fully-automated detection of PDA (including small and isodense tumors) on diagnostic CTs as well as for early detection of PDA from normal pancreas on prediagnostic CTs at a substantial lead time prior to clinical diagnosis. Prospective validation with blood-based biomarkers could enable AI-augmented early detection of PDA in high-risk subjects.

technical paper

Background: The rising prevalence of obesity, diabetes, and smoking among American adults has disproportionately affected female, Black, and younger patients. The purpose of this study was to evaluate for disparity in patient eligibility for Total Ankle Arthroplasty (TAA) based on race, ethnicity, gender, and age by applying Body Mass Index (BMI), smoking, and diabetes criteria to the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) database.

Methods: Patients in the ACS-NSQIP database who underwent TAA from 2011- 2020 were retrospectively reviewed. BMI cut-offs of <50kg/m², <45kg/m², <40kg/m², <35kg/m², diabetes, and smoking criteria were then applied. The eligibility rate for TAA was examined for each BMI cut-off, diabetes, and smoking; findings were stratified by race, ethnicity, gender, and age. Independent T-tests, Chi-squared tests, and Fisher’s exact tests were performed to compare differences at an α = 0.05.

Results: 1215/1865 TAA patients (65.1%) were included after applying the exclusion criteria. Black patients had disproportionately lower rates of eligibility at the most stringent BMI cut-off of <35kg/m² (p=0.004). In contrast, Asian American/Pacific Islander patients had higher rates of eligibility at the BMI cut-offs of <35kg/m² (p=0.033) and <40kg/m² (p=0.039). Black patients also had lower eligibility rates after diabetes (p=0.042) and smoking (p=0.008) criteria were applied. Whereas, white non-Hispanic patients had disproportionately higher rates of eligibility after the diabetes criterion was applied (p=0.04). Females had lower eligibility rates across all BMI cut-offs (p<0.05 for all). Younger patients had lower eligibility rates across all BMI cut-offs (p<0.05 for all) and smoking (57 ± 10, p<0.001).

Conclusion: Stringent BMI cut-offs, diabetes, and smoking criteria may disproportionately disqualify women, Black, and younger patients from receiving Total Ankle Arthroplasty. This data suggests that current eligibility criteria may exacerbate disparity in access to arthroplasty care for already vulnerable populations.

Are Body Mass Index (BMI), diabetes, and smoking cutoffs creating racial, ethnic, gender, or age disparities in patient eligibility for Total Ankle Arthroplasty?

Background
Manual ventilation with a self-inflating bag is a difficult clinical skill to perform safely and effectively. Hyperventilation is a common and harmful adverse effect, potentially causing deleterious hemodynamic changes, gastric insufflation, and/or direct volutrauma to the lungs. To improve manual ventilation safety and efficacy, we developed the Bag valve mask Emergency Narration Guided Instrument (BENGI), a handheld tidal volume feedback device that provides simple and intuitive audio-visual feedback in real-time on the correctness of the user’s ventilations. To test whether the BENGI improves manual ventilation, a randomized crossover manikin simulation study was performed.

Methods
Participants (n = 20) were recruited from LSUHS-Shreveport medical school to manually ventilate both with and without the BENGI. Participants were asked to manually ventilate a manikin for 5 min under four different scenarios at different target tidal volumes (500, 750, 300, and 20 mL) and respiratory rates (10 min−1 for Scenarios 1 through 3 and 60 min−1 for Scenario 4). Air pressure and flow waveforms were measured to calculate tidal volume, respiratory rate, inspiratory time, peak inspiratory pressure, and the work and power imparted to the test lungs by the manual ventilation. Intra-participant (standard deviations throughout a given test) and inter-participant variations (standard deviation among all participants for a given scenario) in respiratory parameters were assessed, and Poincaré plots were constructed to further reveal alterations in short-term (SD1) and long-term (SD2) variations in tidal volume and respiratory rate delivery.

Results
BENGI use during manual ventilation significantly reduced deviations in tidal volume and respiratory rates from the target values. Both intra- and inter-participant variations in tidal volumes and respiratory rates were reduced. Poincaré plot analysis suggested that long-term (SD2) variations in tidal volume and respiratory rate were decreased in all scenarios, and short-term (SD1), or cycle-to-cycle, variations in tidal volume (Scenario 4) and respiratory rate (Scenarios 1 through 3) were also diminished.

Conclusion
Use of the BENGI improved both tidal volume and respiratory rate accuracy and consistency during manual ventilation in a manikin simulation study. The BENGI may have utility as a medical device for improving manual ventilation and reducing manual hyperventilation.

Audiovisual Feedback from a Handheld Monitoring Device Improves Manual Ventilation

Abstract Title 
Skin Conductance Measures as Possible Predictors of Response to Propranolol for Anxiety in Autism Spectrum Disorder

Bethany Thompson-Gordon,a Carrina Appling,b Matthew Prendergast, b Nanan Nuraini,b David Beversdorf,c Valerie Davila,d & Bradley Ferguson e*

Background
Autism Spectrum Disorder (ASD) is a neurodevelopmental condition affecting the way individuals communicate and interact with others. Central features of ASD include impaired social communication and restricted interests and repetitive behaviors. Several clinical studies have observed enhanced sympathetic tone in ASD patients with anxiety frequently co-occurring. Because sweating is solely controlled by sympathetic activity, as sweat gland activity rises, sympathetic activity can be quantified by increases in electrical skin conductance levels (SCL). These elevated SCL are also associated with higher levels of anxiety. To date, there is no diagnostic biomarker nor any proven pharmacological means of treating the hallmark features of ASD nor any clear efficacy of pharmaceutical agents for mood disturbances in ASD. Propranolol, a beta-adrenergic antagonist, blocks the physiologic effects of sympathetic tone and is widely used for its anxiolytic effects in those without ASD, however more research is needed to better understand its use for anxiety in ASD. Our team previously found improved communication behaviors and cognitive flexibility after a single dose of propranolol in ASD patients. We have also examined propranolol use for anxiety in ASD with a 12-week open-label study in autistic participants which found anxiety levels to be significantly improved with treatment. Based on these outcomes, we became interested in determining whether SCL may predict which patients will be most responsive to the anxiety-reducing effects of propranolol. 

Methods
19 ASD patients ages 7-24 participated in this study. Anxiety was one of several behavioral sub-domains observed and evaluated using the Clinical Global Impression of Severity (CGIS) scale. SCL and other indicators of sympathetic activity were measured at baseline and week 12 of an open-label propranolol trial. 

Results
No association was observed between SCL and reduction in anxiety with propranolol thus the null was retained. However, repetitive behavior, another sub-domain examined, does share a positive linear relationship with SCL on a regression analysis. 

Conclusion
Further research is warranted to identify which patients might benefit most from propranolol therapy. While SCL may predict propranolol response for repetitive behaviors, other biomarkers of beta-adrenergic activity need analysis to impact future clinical decision making when treating anxiety and other aberrant behaviors in ASD. 
_________
aUniversity of Missouri School of Medicine; bUniversity of Missouri Interdisciplinary Neuroscience Program, Columbia, MO, USA; University of Missouri Thompson Center for Autism & Neurodevelopmental Disorders, Columbia, MO, USA; cUniversity of Missouri Departments of Radiology, Neurology, & Psychological Sciences; William & Nancy Thompson Endowed Chair in Radiology; Thompson Center for Autism & Neurodevelopmental Disorders, dBaylor University Department of Psychology and Neuroscience, eUniversity of Missouri Departments of Health Psychology & Radiology; Thompson Center for Autism & Neurodevelopmental Disorders.

*Corresponding author

This work was supported by the Office of the Assistant Secretary of Defense for Health Affairs through the Autism Research Program under Award No. W81XWH-16-1-0321. Opinions, interpretations, conclusions and recommendations are those of the author and are not necessarily endorsed by the Department of Defense.


Baseline Skin Conductance Level as a Predictor of Response to Propranolol for Anxiety and Other Clinical Outcomes in Autism Spectrum Disorder

Boosting Babies’ Immunity through Toll-like Receptor-2: A transcriptomic-based analysis

Abstract Title: Comparative Efficacy of Mohs Micrographic Surgery and Traditional Surgical Treatment Modalities in Periocular Skin Cancers: A Systematic Review and Meta-analysis

Background: Periocular skin cancers are especially challenging to treat due to the proximity of the lesions to essential and sensitive anatomical structures. Surgical options for periocular skin cancers include standard surgical excision (GSE), Mohs micrographic surgery (MMS), wide local excision (WLE) and frozen section evaluation (FSE). Currently, a randomized study comparing the efficacy of MMS and other traditional surgical treatment modalities in the treatment of various of periocular skin cancers does not exist. 

Methods: A meta-analysis was done using a random-effects model to account for clinical heterogeneity. A meta-analysis of proportions was also conducted for recurrence rates and was evaluated through meta-regression for subgroup analysis to compare results among periocular skin cancer subtypes. 

Results: Meta-regression analysis of proportions showed that the recurrence rate of basal cell carcinoma for MMS was significantly lower compared to the WLE technique (p<0.003); the recurrence rate of BCC for FSE was also significantly lower compared to the WLE technique (p<0.001). Meta-regression also demonstrated that the recurrence rates of sebaceous carcinoma for MMS was also significantly lower than compared to WLE (p<0.001). Meta-regression on squamous cell carcinoma also demonstrated significantly lower recurrence rates in MMS than that of FSE (p<0.001) and GSE (p=0.001).

Conclusion: We conclude that patients who had MMS had lower recurrence rates of sebaceous carcinoma or non-melanomas compared to patients who underwent the WLE technique. Proportionally among all studies, MMS was also demonstrated to have significantly lower recurrence rates in basal cell carcinoma and sebaceous carcinoma compared to WLE. Recurrence rates are also lower post-MMS compared to FSE and GSE in squamous cell carcinoma. Overall, these results illuminate that MMS is an excellent surgical technique for periocular skin cancers. While other surgical modalities such as WLE, FSE, GSE, and nonsurgical CYT can be equally comparable for some periocular skin cancer subtypes, further larger scale studies are needed to determine robust efficacy and guidelines for optimal surgical modality and treatment to improve patient outcomes. 



Comparative Efficacy of Mohs Micrographic Surgery and Traditional Surgical Treatment Modalities in Periocular Skin Cancers: A Systematic Review and Meta-analysis

Decoding Pregnancy Loss: Validating a Novel Genetic Biomarker of Poor Egg Quality

Prior studies using intracranial electroencephalography (iEEG) have shown that thermo-nociceptive stimuli enhances high-frequency (gamma) activity within the insular cortex. Such high frequency activity is thought to be a marker for neural brain activity However, it remains unclear whether this activity is specific to the thermal or nociceptive quality of the stimulus. It is also thought that pain processing differs depending on the region of the insula. We utilized a custom thermoelectric device and psychometric software to investigate thermo-nociception in patients with intracranial electrodes within their insular cortex. Improved understanding of cerebral pain processing will facilitate identification of neuromodulatory targets. 

We recruited 16 (7 females; age: 21-66) patients undergoing iEEG for seizure focus localization to perform our thermo-nociceptive task following all institutional guidelines. Using a maximum-likelihood adaptive procedure, we generated psychometric pain perception curves for each patient. Psychometric curves facilitated the probabilistic classification of insular signals corresponding to thermo-nociceptive stimuli (>hot pain threshold, HPT) and innocuous thermal stimuli (<HPT). Hypothesis tests were performed for statistical distribution comparisons of local field potential spectra for the thermo-nociceptive and innocuous-thermal stimuli. 

Across all 17 patients, we recorded from 24 insula contacts (14 posterior, 10 anterior). Twelve contacts (8 posterior, 4 anterior) across 6 unique patients showed thermo-nociceptive stimuli followed a different distribution than innocuous thermal stimuli for 70-150 Hz (p<0.05). A decrease in power was observed within the contacts showing differential thermo-nociceptive processing for all significant posterior contacts (8/10, p<0.05). Power increased in all three significant anterior contacts (3/3, p<0.05). 

Thermo-nociception appears to cause distinct changes within the posterior insula compared to innocuous thermal stimuli. The 70-150 Hz power changes within the posterior insula during thermo-nociceptive processing are likely specific to the nociceptive quality of the stimulus and not the thermal quality. Additional recording from anterior insula contacts is necessary to investigate differential power changes along the anterior-posterior insula axis. Such work will be an important next step for improved understanding of neuromodulatory targets within the brain.


Differential changes in power within the insular cortex during thermal pain

Background: SARS-CoV-2 has been rapidly evolving with over 1,300 identified lineages. While variants are often first detected in urban centers, the origins of these variants and their patterns of spread remain unclear. Further, little is known about how the virus emerges and spreads among rural communities. Beginning in late 2020, rural areas experienced higher incidences of COVID-19 disease and mortality compared to urban regions, suggesting an increased pandemic burden in rural populations. Despite this, disease mitigation efforts are largely informed by urban-centric data. Here, we study the urban-rural transmission patterns of SARS-CoV-2 variants in Southwest Missouri. 

Methods: COVID-19-positive nasopharyngeal swab samples were collected from CoxHealth, a large medical center in Southwest Missouri. To understand the early evolution and transmission dynamics of SARS-CoV-2 in a vaccine-naïve population, our study period was set to July through December 2020 to exclude biases from the limited testing during the early pandemic, the variations of vaccine distribution and intake, and the sweeping predominance of the variants of concern. We analyzed 1,161 geocoded SARS-CoV-2-positive samples, 966 of which contained sufficient viral load for genomic sequencing (446 rural, 520 urban). Evolutionary dynamics and transmission patterns were studied using Bayesian inference phylogenetic and phylogeographic analyses.

Results: Our results revealed high genomic diversity within our study population, encompassing 51 recognized lineages. Further, we identified five mutations that were first detected in rural and urban communities and three of these have spread globally. Within the eight predominant lineages containing at least 10 urban and 10 rural samples (B.1, B.1.1, B.1.1.337, B.1.2, B.1.234, B.1.240, B.1.311, and B.1.509), 60.5% (n=52) of statistically significant transmission events (Bayes factor ≥ 3, posterior probability ≥ 0.7) originated from rural areas. 

Conclusion: In this study, we demonstrated that rural communities have become an important source of new SARS-CoV-2 variants and of transmission to both rural and urban areas. These results suggest that rural communities have a critical role in SARS-CoV-2 evolution and transmission. Genomic studies should strengthen sampling from rural communities, and granular geographic metadata should be integrated into the analyses to better our understanding of the evolution and disease burdens of SARS-CoV-2.

Early Urban-Rural Evolution and Transmission of SARS-CoV-2

Background
Obesity prevalence is increasing in the US and is particularly prevalent among Black Americans. Increasing clinical and policy attention focuses on the role of education and income in disparities. Prior evidence linked education to lower obesity prevalence among Black and Hispanic men. Understanding heterogeneity in the relationships between these factors and obesity may guide interventions and shed further light on the role of these factors in health broadly.

Methods
We use the 2019 National Health Interview Survey (NHIS) to examine the relationships between obesity (body mass index ≥ 30), education, and per-capita household income among US adults. Stratifying by race, ethnicity, and sex, we use logistic regression to identify varying effects of education and income on the likelihood of having obesity conditional on age.

Results
Among Black men, increasing education is not associated with higher levels of obesity. This contrasts sharply with Hispanic men, non-Black non-Hispanic men, and Black women, among whom the odds ratios for having obesity are 0.48, 0.56, and 0.53 with a college degree (p<0.01), and contrasts with older evidence. Regarding income, among non-Black non-Hispanic men, doubling income lowers odds of obesity (OR=0.87, p<0.01). Over 50% of this relationship is education related – conditional on education; the odds ratio rises to 0.94 (p<0.05). The income-obesity relationship runs in the opposite direction among black men. Doubling income is related to a 1.15x increase in the odds of obesity (p<0.1). Among Hispanic men, income and obesity are unrelated. Among non-Black non-Hispanic women, the income-obesity relationship is stronger– decreasing odds by 0.74x when income doubles. Among Black and Hispanic women, the odds of having obesity decline by 0.85x and 0.79x, respectively, when income doubles (p<0.01).

Conclusion
Education and income are considered fundamental social determinants of health. Concerning obesity, their role is not straightforward, varying substantially by race and sex. Black men stand out in this regard, as education is unrelated to obesity, and higher-income raises the risk of obesity, contrasting with every other demographic group. Clinical and policy efforts which address economic and education-linked determinants of health are not likely to alone be sufficient in closing obesity disparities by race.


Examining race, ethnicity, and gender disparities in obesity by socioeconomic status in the United States

Introduction: 
Among all professionals, physicians suffer from some of the highest burnout rates. While physician burnout has recently come to the forefront of many media cycles because of the COVID-19 pandemic, these high rates of burnout have long persisted in the field of medicine. In this study, we evaluate general trends of physician burnout and analyze gender differences over the last half-decade. 

Methods: Data provided by Medscapes Annual Burnout and Depression Surveys was analyzed for differences in reported burnout rates among all physicians in the United States (2017-2021). Univariate logistic regression was performed in order to compare differences in burnout rates between the various years and between different genders.

Results: Of the 71,000 physicians surveyed during the study period, the odds of reported burnout were significantly higher in 2018 (OR: 1.18, 95%CI 1.13-1.23), 2019 (OR: 1.09, 95%CI 1.04-1.14), 2020 (OR: 1.09, 95%CI 1.04-1.14), and 2021 (OR: 1.33, 95%CI 1.27-1.39) when compared to the year 2017. Over the five-year period, burnout was more commonly reported among female physicians (OR versus males: 1.65, 95%CI 1.60-1.70), with the effect estimate for burnout being greater among women versus men across all years as compared to 2017. In 2018 (versus 2017), odds of burnout among male physicians were 1.04, 95%CI 0.98-1.21, while ORfemales 1.08, 95%CI 1.00-1.16; 2019 ORmales 0.96, 95%CI 0.90-1.02, while ORfemales 1.00, 95%CI 0.93-1.07; 2020 ORmales 0.92, 95%CI 0.86-0.97 while ORfemales 1.13, 95%CI 1.04-1.22; and 2021 ORmales 1.13, 95%CI 1.07-1.21 while ORfemales 1.38, 95%CI 1.28-1.49.

Conclusion:
The general trend of increasing burnout rates, particularly among female physicians, highlights the need to implement modern solutions. Further investigation is warranted to discern specific variables & their impact on these findings, so these solutions can be optimized.

Premium content

AI-Powered Fully automated Early Detection of Pancreatic Ductal Adenocarcinoma on Standard-of-care CT Scans.

Downloads

Next from AMA Research Challenge 2022

Are Body Mass Index (BMI), diabetes, and smoking cutoffs creating racial, ethnic, gender, or age disparities in patient eligibility for Total Ankle Arthroplasty?

Similar lecture

Institutional Experience of Linear Accelerator-Based Stereotactic Radiosurgery For Brain Arteriovenous Malformations