United States

Background
Immune checkpoint inhibitors (ICIs) have revolutionized non-small cell lung cancer (NSCLC) treatment, yet predicting durable benefit and toxicities like immune-related pneumonitis (IRP) remains challenging. We developed a novel deep-radiomics framework using baseline CT imaging to simultaneously forecast ICI efficacy and IRP risk, addressing critical unmet needs in precision immunotherapy selection. This integrates a patented CNN-enhanced methodology for unified tumor segmentation and multi-level feature extraction in a single neural network pass.
Methods
We analyzed baseline CT scans from 102 advanced NSCLC patients (stage IIIB-IV) receiving ICIs. Models predicted durable clinical benefit (DCB; response/stable disease ≥24 weeks per RECIST), IRP, overall survival (OS), and progression-free survival (PFS) across the cohort. Our integrated UNet extracted 348 radiomic features (shape, texture matrix, intensity, confidence metrics, deep vectors) from tumor and parenchyma. A 3D CNN fused these with clinical covariates (age, sex, ECOG, neutrophil-to-lymphocyte ratio, metastases including brain/bone, PD-L1) via ensemble learning with cross-validation. Performance used time-dependent AUROC, NPV, and Kaplan-Meier stratification.
Results
Among patients (median age 66, IQR 59.5-73.5; median follow-up 14 months, IQR 5-30), 58 (57.4%) achieved DCB, 13 (12.7%) developed IRP, and 80 deaths occurred. The framework yielded AUC 0.72 (95% CI 0.67-0.76) for DCB, 0.79 (0.73-0.86) for 12-month OS, 0.66 (0.52-0.80) for 36-month OS, 0.70 (0.67-0.73) for 12-month PFS, and 0.72 (0.61-0.83) for 36-month PFS. IRP prediction achieved AUC 0.72 with NPV 92.9% (sensitivity 53.8%, specificity 88.8%). Key predictors included radiomic features capturing tumor heterogeneity (particularly GLRLM descriptors), deep-learned embeddings, elevated NLR, and the presence of bone metastases, which collectively suggest that increased textural complexity may reflect underlying immune microenvironment characteristics contributing to both reduced efficacy and heightened toxicity. Risk stratification analyses revealed marked differences: high-risk patients exhibited a median OS of 11.8 months compared to not reached in the low-risk group (HR 2.97, 95% CI 1.84-4.80; p&lt;0.001), and IRP incidence 26.9% vs. 7.9% (HR 3.58, 95% CI 1.20-10.66; p=0.014).
Conclusion
Our dual-model radiomics framework represents a substantial advancement in the field of precision oncology, as it concurrently identifies patients most likely to derive benefit from ICIs while proactively screening for elevated IRP risks—all without imposing additional testing burdens beyond standard baseline imaging, outperforming sequential pipelines (AUC 0.79 vs 0.590.66) and enabling riskadapted therapy and monitoring. A clinicianfriendly web demo (precisiononcology.netlify.app) delivers realtime predictions and is undergoing patent protection. Prospective validation in larger, multicenter cohorts is ongoing to confirm these findings and support widespread adoption in oncology practice.

AMA Research Challenge 2025 

Deep Learning Radiomics Models Predict Both Immunotherapy Efficacy and Toxicity in Advanced NSCLC

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#### Event Details
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AMA Research Challenge 2022

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


Background
Immune checkpoint inhibitors (ICIs) have revolutionized non-small cell lung cancer (NSCLC) treatment, yet predicting durable benefit and toxicities like immune-related pneumonitis (IRP) remains challenging. We developed a novel deep-radiomics framework using baseline CT imaging to simultaneously forecast ICI efficacy and IRP risk, addressing critical unmet needs in precision immunotherapy selection. This integrates a patented CNN-enhanced methodology for unified tumor segmentation and multi-level feature extraction in a single neural network pass.
Methods
We analyzed baseline CT scans from 102 advanced NSCLC patients (stage IIIB-IV) receiving ICIs. Models predicted durable clinical benefit (DCB; response/stable disease ≥24 weeks per RECIST), IRP, overall survival (OS), and progression-free survival (PFS) across the cohort. Our integrated UNet extracted 348 radiomic features (shape, texture matrix, intensity, confidence metrics, deep vectors) from tumor and parenchyma. A 3D CNN fused these with clinical covariates (age, sex, ECOG, neutrophil-to-lymphocyte ratio, metastases including brain/bone, PD-L1) via ensemble learning with cross-validation. Performance used time-dependent AUROC, NPV, and Kaplan-Meier stratification.
Results
Among patients (median age 66, IQR 59.5-73.5; median follow-up 14 months, IQR 5-30), 58 (57.4%) achieved DCB, 13 (12.7%) developed IRP, and 80 deaths occurred. The framework yielded AUC 0.72 (95% CI 0.67-0.76) for DCB, 0.79 (0.73-0.86) for 12-month OS, 0.66 (0.52-0.80) for 36-month OS, 0.70 (0.67-0.73) for 12-month PFS, and 0.72 (0.61-0.83) for 36-month PFS. IRP prediction achieved AUC 0.72 with NPV 92.9% (sensitivity 53.8%, specificity 88.8%). Key predictors included radiomic features capturing tumor heterogeneity (particularly GLRLM descriptors), deep-learned embeddings, elevated NLR, and the presence of bone metastases, which collectively suggest that increased textural complexity may reflect underlying immune microenvironment characteristics contributing to both reduced efficacy and heightened toxicity. Risk stratification analyses revealed marked differences: high-risk patients exhibited a median OS of 11.8 months compared to not reached in the low-risk group (HR 2.97, 95% CI 1.84-4.80; p<0.001), and IRP incidence 26.9% vs. 7.9% (HR 3.58, 95% CI 1.20-10.66; p=0.014).
Conclusion
Our dual-model radiomics framework represents a substantial advancement in the field of precision oncology, as it concurrently identifies patients most likely to derive benefit from ICIs while proactively screening for elevated IRP risks—all without imposing additional testing burdens beyond standard baseline imaging, outperforming sequential pipelines (AUC 0.79 vs 0.590.66) and enabling riskadapted therapy and monitoring. A clinicianfriendly web demo (precisiononcology.netlify.app) delivers realtime predictions and is undergoing patent protection. Prospective validation in larger, multicenter cohorts is ongoing to confirm these findings and support widespread adoption in oncology practice.

poster

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**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.**

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Introduction: An anterior cruciate ligament (ACL) injury and reconstruction (ACLR) can trigger
systemic deviations in various inflammatory biomarkers. Previous studies have suggested that patients
with a prior history of ACLR may experience poorer outcomes after total knee arthroplasty (TKA). The
mechanisms leading to poorer TKA outcomes remain unclear but may be related to persistent systemic
inflammation. This study aimed to evaluate whether a previous ACLR procedure affects systemic
inflammatory and immune indices before TKA. We hypothesized that a previous ACLR procedure would
associate with an elevated systemic immune system and inflammatory profile before TKA.

Methods: A retrospective chart review was conducted on patients that underwent TKA between October,
2015 and February, 2023 at a single academic center. This study included TKA patients who underwent
prior ACLR at the center (cases, n = 14) and matched controls with no history of ACL injury (controls, n
= 21). One or more controls were matched to each case based on sex, body mass index (BMI), date of
TKA, and age at the time of TKA. The primary outcome variables were systemic immune and
inflammatory indices obtained within 30 days prior to TKA, which included the neutrophil-to-lymphocyte
ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic
immune-inflammation index (SII), systemic inflammation response index (SRI), and pan-immune-
inflammation (PIV). Indices were derived from a complete blood cell (CBC) counts obtained before
TKA. C-reactive protein (CRP) levels were also analyzed. Surgical notes and preoperative evaluations
were reviewed for evidence of arthrofibrosis, bone loss, synovitis, constrained implant use, and reduced
pre-TKA range of motion.

Results: There was no significant difference in systemic indices (i.e., NLR, MLR, PLR, SIRI, SII, PIV)
and CRP between cases and controls. Loss of extension of ≥3 degrees was observed in only one case
compared to four controls. Intraoperative arthrofibrosis, synovitis, bone loss requiring augmentation, and
constrained implant use were more frequently reported in the case group.

Conclusion: Individuals with a prior history of ACLR was not associated with elevated systemic immune
or inflammatory indices before TKA. However, intraoperative arthrofibrosis, bone loss requiring
augmentation, constrained implant use, and performed synovectomy were more frequently observed in
the case group suggesting that these non-biological issues may potentially contribute to the risk of poorer
outcome of TKA following ACLR.

Previous ACLR Was Not Associated With Elevated Indices of Systemic Inflammation Prior to TKA


Background 
Cancer remains one of the leading causes of death worldwide, impacting millions of lives each year. Early detection and accurate diagnosis are critical to improving patient outcomes and reducing mortality. Among the most prevalent malignancies, liver, kidney, and colon cancers show markedly better prognoses when identified at an early stage. This research presents a novel machine learning model powered by artificial intelligence, designed to assist healthcare professionals in the early and precise diagnosis of liver, kidney, and colon cancers through medical imaging. By leveraging advanced computational techniques, the model aims to enhance diagnostic accuracy, support clinical decision-making, and ultimately contribute to better patient care.

Methods
Created with AI algorithms, the machine learning model was made using abdominal imaging for liver, kidney, and colon cancer diagnosis. It was applied to a data set of 1516 patients with liver cancers, 1393 patients with kidney cancers, and 1402 patients with colon cancers from hospitals and medical clinics throughout the United States. Training the AI model, 45% of the patient data was randomly selected and used. For testing the machine learning model, the diagnosis capabilities were tested with the other 55% of the patient data. 

Results
The developed artificial intelligence model accurately diagnosed 90.1% of the liver cancers, 90.2% of the kidney cancers, and 89.9% of the colon cancers using the testing datasets, exceeding currently published models. 

Conclusion
Thus, early and accurate diagnosis of liver, kidney, and colon cancers can be enhanced with the aid of artificial intelligence in abdominal imaging, a helpful tool for healthcare professionals worldwide. It improves patient outcomes for those with liver, kidney, and colon cancers, especially in resource limited areas with fewer medical professionals, and globally.


Diagnosing Liver, Kidney, and Colon Cancers Using Imaging and Artificial Intelligence

Background
Ayahuasca, a traditional hallucinogenic brew, is a rare but emerging cause of rhabdomyolysis- induced acute kidney injury (AKI). Unlike more common etiologies of rhabdomyolysis, such as cocaine use or statin therapy, these patients may present without positive toxicology or relevant medication history. This case provides clinical insight into how individualized fluid and diuretic management was used to prevent renal deterioration.
Case Presentation
A 32-year-old male with no significant past medical or family history presented with generalized weakness and muscle pain after ingesting ayahuasca. He was brought to our ED via EMS due to worsening symptoms. He arrived with severe rhabdomyolysis (CPK 170,329U/L), acute kidney injury (initial Cr 6.9mg/dL), hyperkalemia, hyponatremia, transaminitis, and leukocytosis. He was admitted to the ICU for close monitoring and serial labs with an uptrending creatinine of 12.8 mg/dL by hospital day 5. By discharge day 9, his creatinine had decreased without the need for renal replacement therapy. During his stay in the ICU, he received a full workup, aggressive IV fluids (4-6 L/day isotonic saline), and diuretics (bumetanide, metolazone). 
Discussion
This case of severe rhabdomyolysis and kidney injury involved the combined effects of ayahuasca ingestion and an uncertain degree of trauma. Ayahuasca, which contains N,N- dimethyltryptamine and β-carboline alkaloid, can increase sympathetic tone and vasoconstriction, impairing renal perfusion. The association of ayahuasca with severe rhabdomyolysis and AKI appears to be unique in the literature. While rhabdomyolysis from cocaine or statin use can directly cause myotoxic and mitochondrial dysfunction, ayahuasca induces muscle ischemia utilizing different vasoconstrictive and mitochondrial stress mechanisms, suggesting a distinct pathophysiology. The decision to pursue conservative management in this patient provides valuable guidance, especially for centers without specialty services. The patient's non-oliguric status after diuretic challenge with clear urine output was somewhat reassuring, however, renal function could still deteriorate [1]; which further exemplifies the complexity of managing a case like this. Guidelines emphasize the importance of fluid resuscitation and diuretics for the kidneys during the maintenance phase of AKI [2]. This method helped keep fluid balance and contributed to renal recovery without the need for RRT, which may be necessary for refractory hyperkalemia, severe acidosis, or volume overload [3]. With the increasing popularity of recreational ayahuasca use, further research is essential to optimize management strategies for ayahuasca-induced rhabdomyolysis and its long-term effects.

Severe Rhabdomyolysis and Acute Kidney Injury Following Ayahuasca‐Related Trauma: A Case Report

Background: Posterior reversible encephalopathy syndrome (PRES) is a clinical syndrome characterized by headache, altered mental status, visual disturbances, and seizures. Neuroimaging often shows posterior cerebral white matter edema. PRES has been strongly associated with eclampsia—over 90% of eclamptic patients demonstrate imaging findings consistent with PRES. Recognition of PRES in the context of obstetric emergencies is essential to guide supportive management and prevent complications
Case Presentation: A 21-year-old female presented to the emergency department (ED) with syncope, headache, and dizziness. She had not received medical care since a dilation and curettage for missed abortion 8 months prior. On evaluation, the patient appeared anxious and had a palpable lower abdominal mass. Vitals revealed tachycardia and a diastolic BP of 110 mmHg. She experienced a seizure shortly after arrival. 
Differential diagnoses included molar pregnancy, eclampsia, and HELLP syndrome.
Workup revealed: β-hCG: 36,566 Urinalysis: 600 mg protein, moderate blood Head CT: subtle bilateral occipital hypodensities Ultrasound: ~25-week fetus with multiple anomalies and severe oligohydramnios Diagnosis: Eclampsia with concomitant PRES.
Discussion: This case highlights the importance of considering eclampsia and PRES in reproductive-aged females with seizures, even in the absence of prenatal care. PRES is a frequent complication of eclampsia and can be suspected based on neurologic symptoms and imaging. Early diagnosis, supportive treatment, and transfer to specialized care are critical for maternal and fetal outcomes

PRES Presenting with Syncope in the Setting of Eclampsia

Abstract Title
Variations in Management of Acute Pediatric Respiratory Emergencies Within a Single Health System

Background
Acute respiratory emergencies are leading causes of pediatric emergency department (ED) visits. Of these are conditions affecting the airways due to inflammation or hyperresponsiveness, such as croup, asthma, and associated respiratory conditions. Diagnostic challenges in younger patients occur due to overlapping clinical presentations. Despite the existence of academic institutional guidelines based on standardized assessment scores, they are underutilized. Only 15% of US children’s hospitals recommend standardized croup scores for treatment, with geographical variations in asthma score use. Other scores such as the Clinical Respiratory Score (CRS) have been studied to predict severity of respiratory distress and likelihood of critical care admissions but were utilized to guide clinical management. This suggests practice variability, which could be among ED providers or ED site. This study aims to analyze management variations in acute pediatric respiratory emergencies across ED sites and provider specialties, informing quality improvement and optimizing patient care.

Methods
We conducted a retrospective chart review of deidentified patients aged five years and younger who presented with respiratory complaints to EDs within a single health system to control for access to academic institutional guidelines. Descriptive statistics were used for demographic data, and inferential statistics, including odds ratios, correlation analyses, and MANOVA with logistic regression, were used to assess variability among ED sites (academic, satellite, and community) and specialty of the provider. Statistical significance will be defined as p < .05.

Results
We analyzed 1141 ED patient encounters between November 2022 and July 2025. Significant correlation was observed between ED type and attending provider type (r=0.55, s²~0) and between clinical severity and ordered disposition (r = 0.38, CI: 0.31 to 0.44). Ordinal and multinomial regression stratified by age demonstrated significance of clinical severity on ordered disposition (Wald=92.38, p < .001), as did time from triage to first administered bronchodilator (Wald=4.57, p = .033). Age consistently predicted 72-hour revisits on multiple binomial regression models (Wald=11.7, p = .003) and the prescription of steroids for home. Younger children had significantly higher odds of being discharged with steroids (p < .001, Nagelkerke R² = 0.052). Other variables, such as sex, race, and ED location, were not significantly associated with outcomes.

Conclusion
Clinical severity and timeliness of initial bronchodilator therapy are key determinants of disposition in pediatric emergency encounters. Younger age is a consistent predictor of both bounce back risk and outpatient steroid prescribing, emphasizing the importance of age-specific management strategies and discharge planning in pediatric respiratory care.

Variations in Management of Acute Pediatric Respiratory Emergencies Within a Single Health System

Background:
Neuroplasticity is the brain's ability to adapt to intrinsic and extrinsic changes, forming the basis of learning. At cellular level it is the result of synaptogenesis, neurite extension including axonal sprouting and dendritic remodelling and neurogenesis. At the receptor/molecular level several mechanisms have been proposed like long-term depression, Glutamatergic signaling, Neurotrophic factors, immediate early genes and several cellular signaling pathways. A classic notion is that with aging neuroplasticity declines; however, the decline in neuroplasticity is heterogeneous and is modulated by factors such as ongoing cognitive engagement, physical activity, and environmental stimulation. While effects of neuroplasticity with aging are well studied, its relation with short term gaps is unclear. We reviewed literature to find evidence of decline in knowledge and skills during gap years in or after medical school, and examined how neuroplasticity might influence this process.
Methods:
A systematic search was conducted from Jan 2000 to July 2025. We searched PubMed, EMBASE, and Google Scholar. Studies were included if they addressed clinical skill retention, neurocognitive changes, neuroplasticity, or residency performance outcomes in medical graduates, especially those with post-graduation gaps.
Results:
The evidence indicates that procedural and clinical skills begin to degrade within months of non-use, with further losses over time. Factual knowledge, particularly in subjects like pharmacology and microbiology, also declines. Age-related studies show a reduction in fluid intelligence but preservation of crystallized intelligence and pattern recognition. While early in-training exam performance may be lower among older or non-recent graduates, structured support enables most to achieve expected competencies by the end of residency. Neuroscience research confirms that adult neuroplasticity remains robust, allowing for substantial relearning. For example, Wilkins and Rawson (2010) found that item-general learning effects were relatively stable (only 6.7% decline after two days), whereas item-specific learning decayed more sharply (25.9% decline in the same period).
Conclusion:
While time away from clinical practice is linked to measurable skill and knowledge decay, these effects are not irreversible. Reduction in neuroplasticity with aging is slow and not acutely sensitive to short breaks. Research shows the adult brain retains substantial structural and functional plasticity, and experience-driven changes can be reinitiated or amplified even after limited stimulation. Adult medical graduates can regain clinical competence through targeted re-training, supported by neuroplasticity principles. Rigid graduation-year cutoffs may unnecessarily exclude capable candidates, and more nuanced, individualized approaches to assessing residency readiness are warranted.


Neuroplasticity and Clinical Skill Retention in Medical Graduates: A Review

Abstract Title
Vascular Intestinal disorder and Ischemic Heart Disease Mortality in the U.S.: 1999–2023

Background
Vascular intestinal disorders and ischemic heart disease (IHD) share pathophysiologic mechanisms, particularly systemic atherosclerosis. Both conditions affect older adults and are associated with diabetes, hypertension, smoking, and hyperlipidemia. Understanding mortality trends in these diseases is key to guiding preventive strategies.

Methods
We conducted a mortality trend analysis using CDC WONDER data from 1999–2023. Deaths related to vascular intestinal disorders (ICD-10: K55) and IHD (ICD-10: I20–I25) were extracted across all U.S. states and age groups. Crude and age-adjusted mortality rates (AAMRs) were calculated per 100,000 population and stratified by sex, region, and ethnicity. Annual percent change (APC) in AAMR was assessed using Joinpoint regression with a 95% confidence interval; p<0.05 was considered statistically significant.

Results
A total of 69,897 deaths were attributed to vascular intestinal disorders from 1999–2023. AAMR declined significantly from 1.8 in 1999 to 0.6 in 2023. The most notable decreases occurred from 1999–2015, followed by a plateau thereafter. Female AAMR declined significantly from 2003–2017, while males showed a significant decline from 1999–2018, followed by stabilization. All U.S. regions experienced a decline until 2015–2017, then largely stabilized. Ethnic-specific
analysis revealed significant early declines among Black, Hispanic, and White populations, but some groups showed recent stagnation or slight increases, notably among Asian or Pacific Islanders and Hispanics post-2018.

Conclusion
Mortality from vascular intestinal disorders declined significantly in the U.S. through 2015, mirroring trends in IHD, reflecting the impact of improved risk factor control and therapeutic advances. However, the recent plateau in mortality, particularly among certain demographic groups, signals the need for renewed focus on cardiovascular and gastrointestinal health. Targeted preventive efforts and addressing healthcare disparities are essential to sustain
progress and reduce the burden of both diseases.

Vascular Intestinal Disorder and Ischemic Heart Disease Mortality in the U.S.: 1999-2023

Background:
In Texas, deaths due to opioid use disorder (OUD) and substance use disorder (SUD) are anotable public health concern, with 5,556 reported fatalities from 2022 to 2023. Disease prevalence, underutilization of treatment, and a lack of access to waivered providers make harm reduction a necessary strategy for addressing the OUD and SUD epidemics in Texas. This program development proposal proposes the creation of a supervised injection site (SIS) at University Hospital in San Antonio, Texas. Through supervision of opioid and stimulant use and increased access to treatment providers and programs, the implementation of an SIS is
hypothesized to decrease the number of OUD and SUD-related emergent, inpatient admissions and fatalities.

Methods:
Program implementation will proceed through securing and ensuring operational readiness of the physical supervised injection space, training clinical providers and staff providing SIS services, and engaging community stakeholders and government agencies. Proposed collaborators include UT Health Science Center San Antonio, the BeWell program at UTHSCSA, and the Texas Department of State Health Services, with the San Antonio Metropolitan Health District functioning as a negotiating and representative body to aid in ensuring legality of the SIS.

Results (Anticipated):
In Texas Public Health Region 8, a designated operative public health region in which San Antonio is the largest metropolitan area, the most recent data available reports 721 opioid-related emergent admissions. In San Antonio itself, 179 opioid-related deaths and 208 stimulant-related deaths were reported in 2024. The implementation of an SIS in San Antonio can be expected to target at least the number of emergent admissions and deaths reported in the data, as well as
mitigate costs associated with these admissions and fatalities.
Success of the SIS will be evaluated through a prospective cohort study. Measures include change in the number of overdose deaths, the number of SUD-related emergency admissions, and the number of instances of referral of SIS users to existing behavioral care programs available at BeWell Texas over the course of a two-year period.

Conclusion:
The implementation of an SIS is predicted to address a critical treatment and access gap in the South Texas region. Additionally, the proposed SIS is significant in its ability to act as a preventive measure addressing the evolving public health needs related to the burgeoning opioid and methamphetamine crisis in Texas. Furthermore, the harm reduction approach taken by the SIS is significant in its ability to mitigate the costs related to emergent care.

Harm Reduction in the South: Establishing a supervised injection site in San Antonio, Texas

Background 

Misdiagnosis of mild traumatic brain injury (mTBI) (concussion) in emergency departments (EDs) is underscored by historical controversy around the appropriate usage of traumatic intracranial injury diagnoses (S06 ICD-10 codes) intended for mTBI and head injury, unspecified codes (S09.9). The lack of consensus diagnostic criteria for mTBI has made the identification of this patient population challenging. Reducing variability in diagnosis is essential to advance research initiatives and align clinical recommendations across patient settings. We found that ED providers were divided in their preferences for selecting between these diagnoses, potentially impacting patient education about brain injury symptoms and clinical management. In this study, we sought to characterize patient and clinical factors that predict provider diagnosis. Additionally, we explored the effect of diagnosis on day 1 symptoms, patient education, and return to ED/hospital within 30 days. 



Methods 

We analyzed 1348 prospectively identified adults diagnosed with traumatic intracranial injury head injury, unspecified across 7 EDs from September 24, 2024, to May 25, 2025. We used logistic regression to identify demographic, injury, and clinical predictors of provider diagnosis and associations between diagnosis and day 1 symptom burden, provision of educational handouts, and 30-day readmission. 



Results 

Diagnosis of intracranial injury was independently predicted by younger age (p<0.001), higher level of care (p = 0.017), presentation >24 hours post-injury (p<0.001), and patient trauma activation on admission (p = 0.015). Patients diagnosed with mTBI had a mean symptom burden (Rivermead Questionnaire total score) of 22.6 (SD = 16.3), significantly higher than those diagnosed with head injury (M = 10.9, SD = 12.5; p<0.001). Patients diagnosed with mTBI were more likely to receive an educational handout at discharge (Est [SE] = 0.54 [0.13], p<0.001). Return to EDs/hospitals within 30 days was not predicted by provider diagnosis. 



Conclusion 

Understanding which factors influence provider diagnosis is invaluable to successful efforts to improve the recognition and management of mTBI in EDs. We report that, albeit to a lesser extent, patients diagnosed with head injury commonly report mTBI symptoms and receive educational materials. Interestingly, these educational materials describe common signs and symptoms of mTBI during recovery. ED provider diagnosis of head injury might not be driven by a lack of recognition of possible mTBI. Shifting towards a diagnosis consistent with intracranial injury may facilitate more consistent and accurate dispersal of educational resources. Clarifying influences on provider preference will aid in developing interventions to unify diagnostic practices across clinical and research settings.

Characterizing Emergency Department Provider Decision to Diagnose Traumatic Brain Injury Versus Head Injury

Effective endotracheal intubation requires both adequate glottic visualization and the physical maneuverability necessary to advance the endotracheal tube (ETT) into the trachea. In patients with anatomical limitations such as reduced oral aperture or thyromental distance, conventional laryngoscopy techniques may be rendered ineffective despite optimal visualization. This case report describes a strategic modification of standard video laryngoscopy (VL) technique to facilitate successful intubation in a patient with unanticipated difficult airway anatomy.
Case Presentation
A young, otherwise healthy female patient, approximately 5’2” tall with no significant past medical history, presented for elective outpatient carpal tunnel release under general anesthesia. Preoperative airway assessment revealed a Mallampati Class III score and reduced thyromental distance, though the airway was not formally flagged as difficult. Following standard preoxygenation, the patient was induced with intravenous anesthetics and paralyzed using rocuronium. Bag-mask ventilation was performed without difficulty. Initial intubation was attempted using a size 3 video laryngoscope (Glidescope) and a 6.5 mm cuffed ETT. A Cormack-Lehane Grade I view of the vocal cords was obtained. However, due to the patient’s small oral aperture, the ETT could not be adequately manipulated into position using conventional post-blade insertion technique. The approach was revised: the ETT was inserted first into the right buccal space while the mouth was maintained open via manual scissoring by an assistant. The VL blade was then inserted at midline, and the ETT was rotated 90 degrees to align with the airway. The tube entered the video field smoothly and was advanced through the vocal cords under direct visualization. Capnography and auscultation confirmed correct placement. A size 3 laryngeal mask airway (LMA) was prepared as a backup but not required.

The intubation was completed without hypoxia, trauma, or hemodynamic instability. The revised sequence allowed for controlled advancement of the ETT despite anatomic limitations. This approach preserved glottic visualization while accommodating mechanical challenges posed by limited oral aperture.
Discussion/Conclusion
In patients with small oral apertures and reduced thyromental distance, reversing the conventional sequence of VL—advancing the ETT prior to blade insertion—may offer a safe and effective alternative technique. When performed under appropriate conditions with adequate preparation and visualization, this method can serve as a valuable adjunct in the management of unanticipated difficult airways.


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