United States

Objective: Health disparities in gynecology are understudied. Racial and ethnic minorities are less likely to receive minimally invasive hysterectomies and more likely to have surgical complications, and this gap is not fully explained by patient or health system factors. Socioeconomic status (SES) influences preventive care access and surgical outcomes, and may explain this gap. Higher Distressed Communities Index (DCI), a composite SES measure, is associated with worse outcomes in general surgery populations. We hypothesized that higher DCI scores would be associated with worse risk-adjusted outcomes and higher healthcare resource utilization after gynecologic surgery.

Design: This was a retrospective cohort study utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Gynecology Collaborative database. Generalized linear mixed-effect models and linear mixed-effect models were used to evaluate the association between Distressed Community Index (DCI) scores and surgical outcomes, with institution treated as a random effect and models adjusted for the ACS-NSQIP predicted probability of morbidity score.

Six ACS-NSQIP Gynecology Collaborative sites in the United States, between January 1, 2018, and June 30, 2023. Adult patients undergoing gynecologic operations during the study period. Patient records including ZIP Code data were merged with DCI scores ranging from 0 (low distress) to 100 (high distress), with DCI &gt;75 identifying distressed communities.

No therapeutic interventions were applied. Exposures of interest were community-level distress as measured by DCI. The primary outcome was a composite measure of postoperative morbidity. Secondary outcomes included markers of resource utilization (length of stay, discharge to nursing facility, and hospital readmission) and comparisons of outcomes between oncologic and benign procedures.

Results: Patients with DCI&gt;75 had a higher mean BMI (32.5 vs 30.6, p&lt;0.001) and greater burden of comorbidities, as represented by a larger number of patients with ASA classification &gt;2 (42.6 vs 35.7%, p&lt;0.001). In unadjusted analyses, the DCI&gt;75 group exhibited a higher ACS-NSQIP predicted probability of morbidity (6.4 vs 5.7%, p&lt;0.001), a greater composite outcome rate of postoperative complications (7.6 vs 6.3%, p=0.040), and a higher rate of cancer diagnosed during the operative procedures (35.7 vs 28.6% p&lt;0.001). Patients with DCI&gt;75 also experienced longer mean length of stay in the hospital (1.5 vs 1.3 days, p&lt;0.001).

In generalized linear mixed-effect models and linear mixed-effect models, DCI, whether modeled continuously or dichotomized at &gt; 75, was not independently associated with patients’ postoperative complications, discharge destination, need for unplanned surgical revision, need for unplanned hospital readmission, postoperative infection, hospital length of stay, or length of operative duration. When stratified by postoperative cancer status, DCI &gt;75 was not associated with composite complications in univariable or adjusted analyses.

By contrast, each 1% increase in ACS-NSQIP predicted probability of morbidity maintained strong associations with higher composite postoperative complication odds (OR 1.12, 95% CI 1.11-1.14, p&lt;0.001) and longer hospital stays (p&lt;0.001). DCI showed a weak positive Spearman correlation with NSQIP-predicted morbidity (ρ = 0.090), indicating slightly higher estimated risk with higher DCI scores.

Conclusion: In our multicenter cohort, DCI showed no independent association with postoperative outcomes in multivariable analysis. Future research should include samples with higher proportions of participants from highly distressed communities, as well as more precise SES measures (income, education, neighborhood), since ZIP code-based indicators may lack granularity. Such efforts could enhance individual risk stratification and targeted interventions. Linking clinical and community data is promising, but success requires rigorous harmonization, quality control, and methodological refinement.

AMA Research Challenge 2025 

A National Analysis of Community Level Socioeconomic Status and Surgical Outcomes in Gynecologic Surgery

Welcome to the **largest national, multi-specialty research** event featuring research from more than 750 medical students, residents, fellows, and international medical graduates.

Use the buttons below or navigation menu to access the event.
<br><br><br>

[![](https://assets.underline.io/markdown_image/1/image/20e1e77aa954efeac7a15d84c85eb383.jpg)](https://underline.io/events/468/sessions?searchGroup=all)
<br>
[![](https://assets.underline.io/markdown_image/1/image/068522d81aca0b68a369787c7dfccd1b.jpg)](https://underline.io/events/468/posters?searchGroup=all)
<br>
[![](https://assets.underline.io/markdown_image/1/image/d3971ece79d5e5575b178bdc2c8bbfae.jpg)](https://underline.io/events/468/help-desk)
<br><br>

#### Event Details

The 2024 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 presented by Laurel Road.<br><br>

### Grand Prize 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 winner selection process. The winner will be announced on February 20, 2025 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)](https://www.laurelroad.com/)

<br><br>

You need to log in with the email address you registered with. Access credentials have been sent to your email. 

Please be sure to check your spam and other email folders if you do not see an email confirmation right away.

Please log in to explore this event.

**There is no registration fee for this event! **

If you have used the AMA Research Challenge platform previously, please click the ‘Log-in’ button below. If you do not remember your password, please click “forgot password” and follow prompts to reset your password. After resetting your password, please refresh your webpage to access the platform.

Register to explore research in a variety of topics. AMA members get exclusive access to score posters in the semifinals. 

**Please use this link [here](https://www.ama-assn.org/member-benefits/events/ama-research-challenge) to register for free.**

Registration Is Required

AMA Research Challenge 2024 

Join the AMA Research Challenge poster symposium and semifinals to explore top research posters and score posters in the semifinals (an AMA member exclusive opportunity).

Objective: Health disparities in gynecology are understudied. Racial and ethnic minorities are less likely to receive minimally invasive hysterectomies and more likely to have surgical complications, and this gap is not fully explained by patient or health system factors. Socioeconomic status (SES) influences preventive care access and surgical outcomes, and may explain this gap. Higher Distressed Communities Index (DCI), a composite SES measure, is associated with worse outcomes in general surgery populations. We hypothesized that higher DCI scores would be associated with worse risk-adjusted outcomes and higher healthcare resource utilization after gynecologic surgery.

Design: This was a retrospective cohort study utilizing the American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) Gynecology Collaborative database. Generalized linear mixed-effect models and linear mixed-effect models were used to evaluate the association between Distressed Community Index (DCI) scores and surgical outcomes, with institution treated as a random effect and models adjusted for the ACS-NSQIP predicted probability of morbidity score.

Six ACS-NSQIP Gynecology Collaborative sites in the United States, between January 1, 2018, and June 30, 2023. Adult patients undergoing gynecologic operations during the study period. Patient records including ZIP Code data were merged with DCI scores ranging from 0 (low distress) to 100 (high distress), with DCI >75 identifying distressed communities.

No therapeutic interventions were applied. Exposures of interest were community-level distress as measured by DCI. The primary outcome was a composite measure of postoperative morbidity. Secondary outcomes included markers of resource utilization (length of stay, discharge to nursing facility, and hospital readmission) and comparisons of outcomes between oncologic and benign procedures.

Results: Patients with DCI>75 had a higher mean BMI (32.5 vs 30.6, p<0.001) and greater burden of comorbidities, as represented by a larger number of patients with ASA classification >2 (42.6 vs 35.7%, p<0.001). In unadjusted analyses, the DCI>75 group exhibited a higher ACS-NSQIP predicted probability of morbidity (6.4 vs 5.7%, p<0.001), a greater composite outcome rate of postoperative complications (7.6 vs 6.3%, p=0.040), and a higher rate of cancer diagnosed during the operative procedures (35.7 vs 28.6% p<0.001). Patients with DCI>75 also experienced longer mean length of stay in the hospital (1.5 vs 1.3 days, p<0.001).

In generalized linear mixed-effect models and linear mixed-effect models, DCI, whether modeled continuously or dichotomized at > 75, was not independently associated with patients’ postoperative complications, discharge destination, need for unplanned surgical revision, need for unplanned hospital readmission, postoperative infection, hospital length of stay, or length of operative duration. When stratified by postoperative cancer status, DCI >75 was not associated with composite complications in univariable or adjusted analyses.

By contrast, each 1% increase in ACS-NSQIP predicted probability of morbidity maintained strong associations with higher composite postoperative complication odds (OR 1.12, 95% CI 1.11-1.14, p<0.001) and longer hospital stays (p<0.001). DCI showed a weak positive Spearman correlation with NSQIP-predicted morbidity (ρ = 0.090), indicating slightly higher estimated risk with higher DCI scores.

Conclusion: In our multicenter cohort, DCI showed no independent association with postoperative outcomes in multivariable analysis. Future research should include samples with higher proportions of participants from highly distressed communities, as well as more precise SES measures (income, education, neighborhood), since ZIP code-based indicators may lack granularity. Such efforts could enhance individual risk stratification and targeted interventions. Linking clinical and community data is promising, but success requires rigorous harmonization, quality control, and methodological refinement.

poster

Congratulations to all the researchers who have qualified for the AMA Research Challenge virtual poster symposium and semifinals!

Welcome to the **largest national, multi-specialty research event** featuring research from nearly 1,000 medical students, residents, fellows, and international medical graduates across six topic areas - basic science, clinical and translational research, clinical vignettes, health systems science, medical education, and public health and health policy.

#### Access the Event
Use the buttons below or navigation menu to access the event. 

[![](https://assets.underline.io/markdown_image/1/image/d4076f2146939317a29eb9f69c53ad41.png)](https://underline.io/events/506/sessions?searchGroup=all)
[![](https://assets.underline.io/markdown_image/1/image/6bcee0b523a4874c4292ca0415d88dde.png)](https://underline.io/events/506/posters?searchGroup=all)

#### Event Details
The 2025 AMA Research Challenge includes the following symposium halls:
* **Semifinals hall:** Features research from 54 medical students, residents and international medical graduates that received top scores during first round scoring. 
* **Poster symposium hall:** Features research from nearly 1,000 medical students, residents and international medical graduates categorized by topics and subtopics.

**Here’s how to participate:**
* **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 presenters** and provide feedback to help advance their research
* **New this year: Watch live poster presentations** by topic area and engage directly with researchers

At the conclusion of this event, the AMA announced the top five finalists who advanced to the AMA Research Challenge final round, presented their research to an elite panel of judges, and competed to win a $10,000 grand prize presented by Laurel Road.

**Addison Shenk, a fourth-year medical student from Edward Via Virginia College of Osteopathic Medicine, was the winner of the 2025 AMA Research Challenge and was awarded the grand prize of $10,000, presented by Laurel Road.**

#### A message from Dr. Bobby Mukkamala, AMA President
<div style="position: relative; width: 100%; padding-bottom: 56.25%; height: 0; overflow: hidden;">
  <iframe 
    src="https://underline.io/embed/136894-ama-video?t=0"
    title="AMA Welcome Video"
    allowfullscreen
    style="position: absolute; top: 0; left: 0; width: 100%; height: 100%; border: 0;">
  </iframe>
</div>


#### Recognized Institutions
In 2025, 1,400 abstracts were submitted across six topic areas representing 174 medical schools and more than 150 residency and health care institutions. [See if your institution is represented this year!](https://drive.google.com/file/d/1eFrTqCmCeobx9pr5drJK2hllvsIpFNOY/view?usp=drive_link)

#### Grand Prize Sponsor
AMA would like to thank Laurel Road, a brand of KeyBank, for sponsoring a $10,000 grand prize for the winner of the AMA Research Challenge. Laurel Road and KeyBank are not involved in winner selection process. The winner will be announced during the AMA Research Challenge final round. Payment of the grand prize will be directly from Laurel Road/KeyBank. See the [AMA Research Challenge Official Rules for terms and conditions](https://www.ama-assn.org/system/files/research-challenge-official-rules.pdf).

[![](https://assets.underline.io/uploads/markdown_image/1/image/611e331d4a0eba0920f240cfc04b4d77.png)](https://www.laurelroad.com/)

#### Code of Conduct
<html>
AMA has a code of conduct for its meetings – we ask all attendees to adhere to this code to participate in this year’s meeting. Please read and <a href="https://www.ama-assn.org/about/code-conduct" target="_blank">learn more here</a> about your conduct requirements.
<br><br>
	</html>
	

#### Semifinals Judges

You need to log in with the email address you registered with. Access credentials have been sent to your email. 

Please be sure to check your spam and other email folders if you do not see an email confirmation right away.

Need help? Contact us at <support@underline.io>.

If you have used the AMA Research Challenge platform previously, please click the ‘Log-in’ button below. If you do not remember your password, please click “forgot password” and follow prompts to reset your password. After resetting your password, please refresh your webpage to access the platform. 

Register to explore research in a variety of topics. AMA members get exclusive access to score posters in the semifinals. 

**Please use [this link here](https://www.ama-assn.org/member-benefits/events/ama-research-challenge) to register for free. **

Purpose: 
SARS-CoV-2 has been shown to contribute to a number of negative pregnancy outcomes, including risks of preeclampsia, stillbirth, preterm birth and NICU admissions. To uncover the underlying molecular mechanisms, suitable in vitro models of SARS-CoV-2 infection of the placenta are required. While human stem cell-derived trophoblast organoids (SC-TOs) are a useful in vitro model of the placenta, previous studies showed limited SARS-CoV-2 infection in SC-TOs. This is hypothesized to result from an inside-out polarity, in which an inner syncytiotrophoblast (STB) layer is surrounded by outer cytotrophoblasts (CTBs). The orientation of the STB layer is important because this layer, which constitutes the outer layer of the placenta in vivo, expresses the ACE2 receptor that allows for infection with SARS-CoV-2. We recently developed a new method for generating SC-TOs with the proper polarity, termed STBOUT. The primary objective of this project was to determine the efficiency of this new protocol in generating STBOUT organoids and determine which day of organoid generation would be best for SARS-CoV-2 infection. 

Methods: 
To generate STBOUT organoids, SC-TOs were grown in Matrigel tabs for three days before being moved into an AggreWell plate to grow in suspension. They were collected and fixed on days four, six, and eight for visualization of trophoblast cell layers by immunofluorescence followed by confocal microscopy. SC-TOs were stained with primary antibodies including SDC1, a marker for the STB layer, and E-cad, which marks the CTB layer, followed by fluorescent secondary antibodies. Additionally, we used DAPI as a nuclear counterstain. After staining, organoids were mounted in a glycerol-based mounting media and placed in between two coverslips to allow the organoids to remain suspended and preserve their three-dimensional structure. Imaging was performed using confocal microscopy at 20x magnification. Images were taken of at least fifteen organoids per replicate, with a minimum of three replicates collected on days four, six and eight. All images were evaluated for the presence of STB on the outer surface and a qualitative measurement of percent surface STB coverage was assigned. 



Results 
The data indicates a general trend in which the STB localization shifts towards the outer surface of the organoids over time when cultured in the AggreWell plate. On day 4, approximately 55% of organoids exhibited STBIN expression, while 45% showed STBOUT. Among those with STBout, only about 5% displayed greater than 50% surface coverage with the STB layer. By day 6, STBIN decreased to around 10%, and STBOUT increased to 87%, with 55% of organoids showing more than 50% external STB coverage. This trend continued on day 8, with only 5% of organoids exhibiting STBIN and approximately 90% showing STBout; 47% had greater than 50% surface coverage. These findings suggest that organoids cultured in the Aggrewell system undergo progressive STB relocalization to the outer surface over time. Finally, immunofluorescence revealed that STBOUT organoids express ACE-2 on the outer surface on day 6. 

Conclusions 
In conclusion, transferring organoids from Matrigel to AggreWell plates on day 3 promotes efficient relocalization of the STB layer to the outer surface. This reorganization is critical because external STB localization is hypothesized to enhance susceptibility to SARS-CoV-2 infection rate; indeed, STBOUT SC-TOs express ACE-2 on the outer surface. Based on our observations, day 6 represents the optimal time point for infection: the majority of organoids exhibit STBOUT polarity with sufficient surface coverage to enable viral entry. This model may serve as a valuable platform for investigating how SARS-CoV-2 impacts placental processes. 



Determining the efficiency of a new method for generating STBOUT trophoblast organoids

Background 
Nε-(carboxymethyl)lysine (CML) belongs to a larger group of pathologic molecules known as advanced glycation end products (AGEs) that develop in the body via non-enzymatic reactions via reducing sugars and are implicated in the pathogenesis of knee osteoarthritis (OA) fibroses and post-operative knee stiffness. Evidence suggests the presence of CML in synovial tissue is limited to histologic sections. We investigated the presence/absence and concentrations of CML in knee synovial membrane tissue of subjects with and without OA. 

Methods 
Medial and lateral synovial gutters were dissected from the capsules of 6 cadaveric knees. Harvested tissues were homogenized, dehydrated, and then lyophilized. The tissues were then hydrolyzed in 6M HCl for 18 hours, reconstituted in water, dehydrated, and then reconstituted in 0.1 M HCl. Protein extraction was performed using preconditioned Oasis MCX 6 cc vacuum cartridges and 5% ammonia/methanol as the eluting agent. The presence and concentration of CML was determined with ELISA (MyBioSource). All samples were run in triplicate. A one-factor ANOVA was used to test the hypothesis that synovial membrane CML concentrations are significantly higher in subjects with knee OA compared to the control. 

Results 
The average CML concentration in the OA synovial tissues was 15% higher than in the non-OA synovial tissues. The average CML concentration in the non-OA synovial tissue was 1074.9 (±413.7) pg/mL and 1236.5 (±639.3) pg/mL in the OA tissues. Single-factor ANOVA analysis indicated that these results were not significantly different (p=0.557). A power analysis indicates that the effect size based on these data is 0.30. Given this effect size, 176 samples per group are necessary to identify significant difference, assuming 80% power and an alpha of 0.05.

Conclusion 
Fibrotic tissue develops as OA progresses. It also develops post-operatively and contributes to stiff knee arthrofibrosis. Our overall goal is to determine whether (1) AGE levels are higher in patients that develop post-operative arthrofibrosis, and (2) pre-surgical AGE levels predict post-operative arthrofibrosis. Our study preliminarily investigated CML levels in the synovial tissue of native synovial tissues in non-OA and OA cadaver subjects. Although CML concentrations were 15% higher in the OA group, there were no differences in CML concentrations among our groups. However, this study opens the door for future endeavors by looking at the relative concentration of AGEs and OA. 


Quantification of Nε-(carboxymethyl)lysine in Knee Tissues with and without Osteoarthritis 

Background
The legalization of marijuana has progressed steadily over the past decade, accompanied by a rise in its recreational and medicinal use. However, its implications in anesthesiology remain insufficiently explored. Existing literature has cautioned against the administration of general anesthesia following recent cannabis use due to increased risks of myocardial infarction and airway hyperreactivity. It is still uncertain what the effects of marijuana could have on benzodiazepine requirements for deep sedation and the potential effects on patient safety marijuana use could have on patients under deep sedation. This study aims to assess whether the use of marijuana prior to being placed under deep sedation affects the amount of benzodiazepines required to keep the patient properly anesthetized.
Methods
This was a retrospective, single center study reviewing the anesthesia notes from 291 patients undergoing cosmetic surgical procedures under deep sedation between 2023 and 2024. Data extracted included self-reported marijuana and alcohol use, comorbidities, midazolam (bolus and continuous infusion) dosages, nitrous oxide (N₂O) use, procedure duration, adverse events, ASA classification, and preoperative urine drug screening results. Cannabis use was confirmed by preoperative urine THC testing. Statistical analyses were performed using independent t-tests with corresponding p-values.
Results
Among the 291 patients analyzed, the mean age was 48.57 years (range: 16–83). Cannabis users were significantly younger than non-users (mean age: 42.44 vs. 50.27 years, p=0.001). Cannabis users required higher midazolam doses than non-users, with an average initial dose of 2.67 mg in cannabis users, compared to 2.34 mg in non-users (p=0.033, Cohen’s d: -0.303). Average continuous dosing of midazolam intraoperatively was also demonstrated to be higher in cannabis users, 3.20 mg, than non-users, 1.75 mg (p<0.001, Cohen’s d: -0.303). In effect, average total midazolam requirements were found to be significantly higher in cannabis users, 5.87 mg, compared to non-users, 4.09 mg (p=0.001, Cohen’s d: -0.618). Additionally, the data demonstrated a strong association of nitrous oxide (N2O) use with cannabis users, with 48.4% of cannabis users requiring N2O use for deep sedation, compared to 13.2% of non-users (p<0.001).
Conclusion
Cannabis use is associated with significantly increased sedative requirements in patients undergoing deep sedation, including elevated midazolam and nitrous oxide use. These findings underscore the importance of routine marijuana screening as part of preoperative anesthetic evaluation and highlight the need to tailor sedation plans for cannabis users to ensure patient safety and optimal anesthetic management.

Impact of Cannabis Use on Benzodiazepine Requirements for Deep Sedation in Outpatient Plastic Surgery: A Retrospective Analysis

Background 
Lung cancer is a highly invasive cancer that metastasizes rapidly and remains the second-most 
common cancer overall in both women and men. With a 5-year survival rate below 20% and a 
20-70% 2-year recurrence rate dependent on stage, there is a need for gene specific 
therapeutic targets and prognostic markers. The COL5A1, COL5A2, and COL1A1 genes have 
been found to promote proliferation and migration of tumor cells in multiple cancers through the 
PI3K-AKT and MAPK pathways. However, no studies have assessed overall survival factors or 
overall survival by primary site in lung cancer for these genes. 
Methods 
The Cancer Genomic Atlas (TCGA) was queried for clinical and STAR counts RNA gene 
expression data within the TCGA-LUAD, TCGA-LUSC, and TCGA-MESO projects. 3,411 
patients with primary tumor tissue STAR count data were stratified by median expression as 
high or low expression groups (HEG, LEG). Kaplan-Meier survival curves were created 
comparing HEG vs LEG by primary site. All curves were compared to a comparison group made 
up of all lung cancer patients from TCGA datasets. Univariate and multivariate Cox Proportional 
Hazards Analyses were completed for these factors: ethnicity, gender, race, AJCC pathological 
© 2025 American Medical Association. All rights reserved. 
stage, AJCC pathological M, AJCC pathological N, AJCC pathological T, tissue or organ of 
origin, laterality, and primary diagnosis. 
Results 
The survival probability of the HEG vs LEG was significantly different with low expression 
experiencing the best survival (p<0.0001). By primary site, lower lobe of lung (HEG vs 
comparison p=0.0125), pleura of the lung (HEG vs comparison p=0.000222, LEG vs 
comparison p= 0.0215, LEG vs HEG p= 0.000222), and upper lobe of the lung (HEG vs 
comparison p=0.0198, LEG vs HEG p=0.0198) were all significant. On multivariate COX 
analysis, AJCC pathologic N3, stage IIIB, and middle lobe of lung primary site were uniquely 
associated with higher hazard in the HEG. White race and papillary squamous cell carcinoma 
were uniquely associated with lower hazard in the HEG. AJCC T2, T2b, T3, T4, and lung 
primary site were uniquely associated with higher hazard in the LEG. AJCC N1, Stage 1B, and 
squamous cell carcinoma were uniquely associated with lower hazard in the LEG. 
Conclusion 
High expression of COL5A1, COL5A2, and COL1A1 leads to worsened survival in lower lobe, 
pleura, and upper lobe lung cancer. High expressing patients with AJCC pathologic N3 or stage 
IIIB may have increased mortality. High expressing papillary squamous cell carcinoma patients 
may have decreased mortality.

Characterization of Survival Outcomes for Differentially Expressed COL5A1, COL5A2, and COL1A1 Genes in Gastrointestinal Cancers


Background: Sleep serves an important role in waste clearance and neurologic function maintenance. As a result, sleep has gained attention as a potential modulator of neurologic disease progression. More specifically, recent research has shown an increased prevalence of sleep disturbances in patients with Multiple Sclerosis (MS), a chronic inflammatory disease, and gone as far as to hypothesize that poor sleep may relate to increased rate of disease relapse. Given these discoveries, this study sought to further explore the associations between sleep quality and MS disease status.
Methods: A retrospective review of 264 cases that presented to the Marcus Neuroscience Institute between July 1st, 2023, and April 30th, 2025, was performed. Included patients were diagnosed with a definitive subtype of MS, provided specific sleep quality metrics and presented for a baseline visit with two follow-ups. Additional data regarding comorbidities and disease modifying therapy (DMT) status was also collected. The objectives of this study were to characterize sleep quality in a cohort of MS patients and to assess the relationship between sleep quality and MS disease subtype (Clinically Isolated Syndrome, Relapsing-Remitting, Secondary Progressive and Primary Progressive).
Results: Descriptive analysis showed that 32% of MS patients reported fair sleep and 27% reported poor sleep at baseline. When broken down by subtype, 33% of RRMS had fair and 29% had poor sleep at initial presentation while 27% of SPMS showed fair and 25% noted poor sleep. Average sleep scores were lower in RRMS vs SPMS at baseline and two follow-ups, but scores did show improvement over time. Assessment of disease duration and DMT status showed no significant impacts on sleep quality in any clinical subtype of MS. However, it was discovered that MS patients concurrently suffering from migraines had 24.1% lower average sleep scores compared to those without migraines, demonstrating a trend between migraine status and lower sleep scores, but this failed to reach statistical significance.
Conclusion: The preliminary results of this study show an association between sleep quality and MS disease; however, this association could not be explained by our analyzed variables. This study was limited in power and by the utilized sleep scale measurement, but it does warrant further investigation into the impact that sleep may have on disease progression and other related factors. In a clinical setting, incorporating sleep measures may help illustrate a more robust picture of a patient’s disease status and provide additional modifiable factors to improve patient outcomes.

Characterization of Sleep Quality in Multiple Sclerosis

Background: Despite its central role in inducing unconsciousness, anesthesia is still largely dosed without direct, patient-specific measurement of brain state. Current approaches rely on indirect proxies like heart rate and EEG monitoring with arbitrary frequency cutoffs, offering limited insight into real-time neural dynamics. This is problematic for drugs like opioids and propofol, whose EEG effects vary widely with age, neurocognitive status, and drug interactions. For example, propofol-induced alpha rhythms (8–12 Hz) may drift into theta in older adults, while opioid-related theta activity (4–8 Hz) may be challenging to detect in altered brain states. These limitations hinder precision dosing and increase risks of over- or under-sedation. To address this, we developed a switching state-space oscillator model that decomposes EEG signals into data-driven oscillatory components and dynamically identifies transitions between baseline and drug-induced brain activity—laying the foundation for personalized anesthetic monitoring.

Methods: We analyzed intraoperative EEG data from patients undergoing fentanyl or propofol induction. A state-space oscillator model decomposed EEG into rhythmic components, and a switching model compared baseline-only versus baseline-plus-drug oscillator hypotheses to identify drug-specific brain state changes. Baseline models were generalized using cluster-based analysis, and model fit was evaluated using logistic regression and posterior switching probabilities.

Results: The switching oscillator model detected robust, drug-specific EEG transitions at both individual and group levels. In fentanyl cases, the probability of detecting an opioid-induced theta signature increased by 59.8% [95% CI: 47.3%, 72.0%] from baseline to 4 minutes after administration. Among patients exhibiting this biomarker (16/21), the probability of theta-band oscillation rose significantly with increasing fentanyl effect site concentration (mean slope = 4.56, 95% CI [0.98, 9.31]). In a representative propofol case, the model captured the rapid, dose-dependent transition into an alpha-oscillatory state, with probability rising from 0.5% at baseline to 99.5% at 4 minutes after administration. These findings establish the model’s sensitivity and specificity in identifying real-time, patient-specific neurophysiologic effects of anesthetic drugs.

Conclusion: We introduce a novel EEG-based switching state-space oscillator model that precisely identifies individualized, drug-specific brain state transitions. Unlike traditional EEG monitoring, our approach robustly captures nuanced neural signatures, providing superior accuracy and patient-specificity. By demonstrating significant, dose-dependent relationships between anesthetic concentration and EEG changes, this model offers a transformative framework for precision dosing and safer anesthesia management, supporting scalable personalized neurophysiologic monitoring across clinical settings.

A Novel Switching Oscillator Model for EEG Based Detection of Unique Drug States During Anesthesia

Wilson’s disease is a rare autosomal recessive disorder of abnormal copper accumulation, typically presenting with hepatic or neurological symptoms. While psychiatric manifestations are well-documented, they are rarely the initial clue to diagnosis and even less commonly progress to severe neurologic decline following standard treatment.
A 28-year-old male with a history of mild hypertension presented with six months of worsening depression, anxiety, suicidal ideation, and impulsivity. Persistent headaches and diplopia prompted an emergency department visit, where head CT revealed basal ganglia hypodensities. MRI and copper studies, along with the presence of Kayser-Fleischer rings, confirmed Wilson’s disease. Due to financial barriers, he was unable to initiate outpatient chelation and remained untreated for nine months, during which his neuropsychiatric symptoms worsened. New-onset somnolence, ataxia, dysarthria, and urinary retention led to hospitalization. Penicillamine therapy was started but discontinued after ten days due to neurostorming and clinical progression to locked-in syndrome. Repeat MRI revealed marked cytotoxic edema in the basal ganglia, thalami, midbrain, and pons. The neurology team hypothesized rapid mobilization of copper or penicillamine hypersensitivity as contributing factors. As of 283 days into hospitalization, the patient remains profoundly obtunded with minimal responsiveness, occasionally able to communicate through blinking.
This case highlights an unusual psychiatric entry point to Wilson’s disease and a rare, devastating complication of chelation therapy. Psychiatric symptoms occur in up to one third of patients with Wilson’s disease but are infrequently the presenting complaint. Furthermore, progression to locked-in syndrome following chelation therapy is not well documented in existing literature.
Clinicians should maintain a high index of suspicion for Wilson’s disease in younger individuals with atypical or rapidly progressive psychiatric symptoms. This case also raises critical considerations regarding the safety and timing of chelation therapy in patients with prolonged untreated disease, particularly when initiating treatment in those with advanced neuropsychiatric involvement.

When the Mind Speaks First: Psychiatric Entry into Wilson Disease Followed by Chelation-Induced Locked-In Syndrome

Background
Diverticulitis, a common complication of diverticulosis, typically presents with left lower quadrant pain, leukocytosis, and changes in bowel habits. The incidence increases with age and risk factors include obesity, low-fiber, high-red meat diets, constipation, a sedentary lifestyle, chronic aspirin or NSAID use, and genetic predispositions. Early diagnosis typically relies on CT imaging, but inflammatory biomarkers, such as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) may offer cost-effective, radiation-sparing diagnostic tools. Although typically uncomplicated, severe cases can result in abscesses, fistulas, or perforations. Diverticulitis places a significant burden on the healthcare system, being a leading cause of ambulatory visits, hospital admissions, and colon surgeries among gastrointestinal conditions.

Case Presentation
This case report discusses a 75-year-old morbidly obese female who developed acute perforated diverticulitis with a colovaginal fistula, identified five to six months after gynecologic operations. The patient initially experienced postoperative leukocytosis considered reactive to surgery. She later presented to the emergency department with stool passing through her vagina, abdominal pain, and nausea. A CT scan revealed diverticulosis complicated by a pericolonic abscess and colovaginal fistula. She was treated with IV antibiotics and underwent abscess drainage with plans for outpatient colonoscopy and elective single-stage surgery involving resection and anastomosis.

Discussion
This case emphasizes the importance of early recognition of diverticulitis through comprehensive clinical assessment, timely imaging, and laboratory testing. While prompt CT imaging enhances diagnostic accuracy and can reduce emergency department revisits, inflammatory markers such as the NLR and PLR, easily derived from a routine CBC, may offer additional diagnostic insight. These ratios have demonstrated high sensitivity and specificity in identifying diverticulitis and could help reduce reliance on imaging, thereby minimizing unnecessary radiation exposure in appropriate cases. Having a lower threshold for clinical suspicion for those with significant risk factors can direct further imaging and laboratory tests to prevent the development of complications such as abscesses or fistulas. Early intervention can mitigate morbidity and reduce healthcare utilization in such cases.

A Case of Perforated Diverticulitis With Colovaginal Fistula: The Value of Early Diagnostic Strategies

Background
Social media plays a significant role in patient education as about 80% of US internet users obtain health information online. YouTube is a popular search engine amongst people looking for dermatologic advice. Our study assesses the content on homeopathic remedies for non-melanoma skin cancers available on YouTube.

Methods
We searched YouTube in a private browsing tab for “natural skin cancer remedies,” “alternative skin cancer treatment,” and “holistic skin cancer treatment” in separate searches. The top 40 videos meeting inclusion criteria in each search were analyzed. For data extraction, the video characteristics, engagement metrics and content themes were recorded. Duplicates were removed.

Results
61 videos were analyzed in total. 36.1% of the videos were created by homeopathic YouTube channels, 32.8% by laypeople and/or influencers, 18% by physicians and pharmacists, 6.7% by news channels and 6.7% by other personnel. The 10 most frequently mentioned remedies included green tea (19.7%), turmeric/curcumin (19.7%), coconut oil (14.8%), black salve (11.5%), apple cider vinegar (11.5%), baking soda (11.5%), garlic (11.5%), frankincense oil (9.8%), eggplant (9.8%) and milk thistle (9.8%).

Conclusion

Although most videos were created by homeopathic channels, they had the lowest engagement. Videos created by healthcare professionals achieved significantly higher engagement. Thus, even when seeking natural remedies on social media, viewers prefer content created by professionals. There is some existing literature on the role the recommended remedies play in preventing and/or treating skin cancers.

Dermatologists should be aware of the various at-home therapies patients may try for their skin cancer. They should consider creating their own reliable and accurate social media content to educate the public about the risks of these dangerous trends and emphasize the importance of seeking evaluation for suspicious skin lesions.


Alternative Treatments for Non-melanoma Skin Cancers on YouTube: A Cross-
Sectional Analysis

Trust and Transparency in Teaching: Medical Student Attitudes Toward Educator AI Use

Background:
Generative artificial intelligence (AI) is rapidly transforming medical education by offering teaching and learning tools. As AI becomes integrated into academia, it is often used by educators without clear guidelines or etiquette. Understanding how key shareholders, particularly students, perceive educator AI use is increasingly important to develop best practices that center the learner. We aimed to explore student perceptions of faculty AI use to understand learner concerns and use these insights to guide recommendations for responsible faculty AI use.

Methods:
We conducted a mixed-methods study at the University of Louisville School of Medicine using surveys and semi-structured interviews to investigate student perceptions of faculty AI use in medical education. Surveys were distributed to medical students and asked respondents to rate AI use for various educational activities that have been described/recommended in the medical education literature. These results were summarized with descriptive statistics. Online, semi-structured interviews with student and faculty participants were then completed to explore the topic more in-depth. We used thematic analysis with two coders as part of a grounded theory approach to analyze transcripts with the qualitative software Dedoose.

Results:
Sixty-nine students participated in the survey, with 83% reporting prior AI use themselves. Students expressed significant concern with faculty using AI to create exam questions (56%), write clerkship evaluations (63%), and compose letters of evaluation (61%). Fifteen interviewees (ten students, five faculty) expressed overall positive sentiments about potential AI uses in medical education, but we identified the following themes regarding concerns: 

1. AI as a Tool – respondents identified the potential of AI to enhance learning but stressed the importance of proper training and guidelines for faculty to ensure its effective use. 
2. Transparency & Trust – lack of disclosure about AI use from faculty undermined trust between educators and students, highlighting transparency about AI use in education as a key factor to maintain and restore trust. 
3. Human Touch – many feared a “loss of humanity,” especially in the realm of personalized feedback, and expressed concern that the lack of human oversight would diminish the accuracy and impact of AI-created materials.

Conclusion:
While most medical students recognized AI’s potential to enhance and personalize learning, many are also concerned that faculty may use AI in ways that they do not anticipate or agree with. Clear institutional guidelines specifying appropriate use, disclosure, and quality-control would help foster trust between educators and students. Including students in AI guideline development will be key.

Premium content

Next from AMA Research Challenge 2025

Determining the efficiency of a new method for generating STBOUT trophoblast organoids

Similar lecture

Optimizing the ACS NSQIP Risk Calculator in Microsurgical Free Flap Breast Reconstruction