United States

Background: Brain metastases, secondary brain tumors originating from cancers elsewhere in the body, can present with focal neurologic deficits without systemic symptoms and are usually evaluated using magnetic resonance imaging (MRI). Multimodal imaging methods are usually used to determine the primary cancer source. Radiomic analysis involves extracting quantitative features from medical images using data-characterization algorithms. Recent advances in deep learning and radiomics, which quantitatively analyze imaging data, offer the potential for improved prediction of primary tumor origin through MR imaging analysis. Using longitudinal MRI data, we developed and validated a mixed-effects neural network model for predicting the primary origin of brain metastases.

Methods: We used the open-source dataset from 5 different institutions made available by Ocaña-Tienda et al. (2023) to build the model. We extracted 2446 radiomic features, out of which 60 features were retained after feature selection using wrapper- and filter-based techniques. For the nested mixed-effects neural network model, we incorporated a dual-layer structure with ReLU activation for the fixed effects and unique embeddings for each cluster, leading to a nested structure. The model was compiled using an Adam optimizer and trained across several epochs with a steadily declining learning rate facilitated by exponential decay. Regularization was implicitly managed through embedding and learning rate adjustments. Model performance was evaluated using receiver operating characteristic curve (ROC) analysis.

Results: Our mixed-effects model demonstrated high accuracy (90.5%), precision (92.7%), recall (87.8%), and F1 score (90.2%), with an area under the ROC (AUC-ROC) curve of 0.944 in identifying the primary tumor site. The nested mixed-effects model was superior to the fixed-effects model with an AUC-ROC of 0.719.

Conclusion: Our mixed-effects neural network model accurately predicts the primary origin of brain metastases with high internal and external validity. Using advanced radiomic feature selection and deep learning techniques. Our model achieved high-performance metrics, thus providing a promising tool for enhancing diagnostic capability and tailoring patient-specific management strategies. We are exploring it&#39;s clinical utility further by adding more data from a tertiary cancer hospital. We have also deployed a patented prototype software for research use to study the effect of integrating this model in clinical workflows to optimize patient care.

AMA Research Challenge 2024 

Mixed-effects deep-learning based quantitative radiomic analysis of longitudinal magnetic resonance imaging of brain metastases predict primary tumor origin

Background: Brain metastases, secondary brain tumors originating from cancers elsewhere in the body, can present with focal neurologic deficits without systemic symptoms and are usually evaluated using magnetic resonance imaging (MRI). Multimodal imaging methods are usually used to determine the primary cancer source. Radiomic analysis involves extracting quantitative features from medical images using data-characterization algorithms. Recent advances in deep learning and radiomics, which quantitatively analyze imaging data, offer the potential for improved prediction of primary tumor origin through MR imaging analysis. Using longitudinal MRI data, we developed and validated a mixed-effects neural network model for predicting the primary origin of brain metastases.

Methods: We used the open-source dataset from 5 different institutions made available by Ocaña-Tienda et al. (2023) to build the model. We extracted 2446 radiomic features, out of which 60 features were retained after feature selection using wrapper- and filter-based techniques. For the nested mixed-effects neural network model, we incorporated a dual-layer structure with ReLU activation for the fixed effects and unique embeddings for each cluster, leading to a nested structure. The model was compiled using an Adam optimizer and trained across several epochs with a steadily declining learning rate facilitated by exponential decay. Regularization was implicitly managed through embedding and learning rate adjustments. Model performance was evaluated using receiver operating characteristic curve (ROC) analysis.

Results: Our mixed-effects model demonstrated high accuracy (90.5%), precision (92.7%), recall (87.8%), and F1 score (90.2%), with an area under the ROC (AUC-ROC) curve of 0.944 in identifying the primary tumor site. The nested mixed-effects model was superior to the fixed-effects model with an AUC-ROC of 0.719.

Conclusion: Our mixed-effects neural network model accurately predicts the primary origin of brain metastases with high internal and external validity. Using advanced radiomic feature selection and deep learning techniques. Our model achieved high-performance metrics, thus providing a promising tool for enhancing diagnostic capability and tailoring patient-specific management strategies. We are exploring it's clinical utility further by adding more data from a tertiary cancer hospital. We have also deployed a patented prototype software for research use to study the effect of integrating this model in clinical workflows to optimize patient care.

poster

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Introduction:
Traumatic brain injury (TBI) from closed-head trauma is a leading cause of disability, with limited effective interventions. Many murine models for researching TBI impact the brain parenchyma directly and are limited by the fact that these forces do not recapitulate clinically relevant closed head injury. An alternative model applying clinically relevant injury mechanics to the intact skull may lead to variable results and as a result, preclinical modeling of TBI remains a challenge. Current models often do not explore sex differences in TBI, which is critically important for translation to clinical practice. 

Objective:
The current study aims to characterize a clinically relevant murine model of closed-head TBI and analyze the impact of system parameters on motor coordination, spatial learning, and neuronal damage, with comparisons made between sexes.

Methods:
We systematically investigated sources of variability in a murine model of closed-head TBI and developed a framework to reduce variability across severity and sex. We manipulated pressure, dwell time, and displacement to determine effects on motor coordination, spatial learning, and neuronal damage in 10-week-old male and female mice. 

Results:
Increasing pressure beyond 70 psi had a ceiling effect on cellular and behavioral outcomes, while manipulating dwell time only affected behavioral performance. Increasing displacement precisely graded injury severity in both sexes across all outcomes. Physical signs of trauma occurred more frequently at higher displacements. Stratifying severity based on day-1 rotarod performance retained histological relationships and separated both sexes into injury severity cohorts with distinct patterns of behavioral recovery. Utilizing this stratification strategy, within-group rotarod variability over 6 days post-injury was reduced by 50%. 

Conclusions:
These results have important implications for translational research in TBI and provide a framework for using this clinically relevant model in both male and female mice.

Optimization of a translational murine model of closed-head traumatic brain injury

Abstract Title
Psychiatric outcomes in patients with mild concussion following differential treatment timing by age
Background
The temporary pathophysiological changes after a mild concussion may offer a therapeutic window in which timely intervention can influence long-term post-concussion sequelae. We sought to understand if the risk of depression or anxiety, two well-established sequelae following mild concussion, could be affected by the choice of immediate treatment versus delayed treatment. Our study provides quantifiable risks to different treatment windows across multiple ages and treatment time periods.

Our goal was to examine if patients who received an immediate treatment within one week of mild concussion had different risks for subsequent depression or anxiety compared with those who received delayed treatment after one week of the event, stratified by age groups.

Methods
This was a nationwide multicenter retrospective cohort study that used the TriNetX Analytics platform to access de-identified electronic health records of over 100 million patients. The study population was comprised of a total of 9,652 patients with a diagnosis of mild concussion, who received either immediate treatment defined as within 1 week (n = 5,266), or delayed treatment which was defined as 1 week to 6 months (n = 4,386) following the diagnosis of mild concussion. Each treatment group was separated into 3 age groups: <=25, 26-64, and 65+ years. Treatment was defined by CPT code and included one or more of the following neuro-rehabilitative services: CPT96132, CPT92507, CPT1013510, and CPT97165.

Results
Among patients aged <=25, those who received immediate treatment had a significantly higher lower risk for depression (HR: 0.782, 95% CI 0.613 –0.998) and anxiety (HR: 0.68, 95% CI: 0.564–0.819) compared with those who received delayed treatment. For those aged 26–64 years, there was a significantly reduced risk of depression (HR: 0.726, 95% CI: 0.593–0.89) and anxiety (HR: 0.635, 95% CI: 0.54–0.747) in the immediate treatment group. However, among patients in the oldest cohort of 65+, there was no significant decrease in risk of depression (HR: 0.735, 95% CI: 0.538–1.004), but there was a significant decrease in anxiety (HR: 0.608, 95% CI: 0.444–0.831) in the immediate treatment group compared to delayed treatment.

Conclusion

This study indicates that patients with a mild concussion who received treatment within one week had significantly reduced risk of depression and anxiety disorders than those who received treatment after one week. Prompt treatment of even mild concussions may mitigate adverse psychiatric outcomes following mild concussion.

Psychiatric Outcomes in Patients with Mild Concussion Following Differential Treatment Timing by Age

Introduction: Cannabis use among adults in the United States is growing, and while case reports and animal studies suggest a relationship between its use and delirium, no clinical studies have assessed the potential association. Therefore, this study aims to determine whether there is an association between a history of cannabis use disorder and delirium. 
Methods: The TriNetX Analytics Network, a research platform containing de-identified electronic health records from over 116 million patients and 63 healthcare organizations across the United States was utilized. History of cannabis use disorder was defined as at least 1 diagnosis of Cannabis related disorders (ICD-10-CM F12) within 1 year prior to hospitalization or surgery. Propensity score matching based on demographic characteristics (age, sex, race, and ethnicity) and comorbidities (diabetes, cardiovascular disease, neurological disease, dementia, depression, substance use, physical disabilities) was performed. The primary outcome is a diagnosis of delirium due to a known physiological condition (ICD-10-CM F05) within either 2 weeks (in-patient hospitalization analyses) or 1 week (post-operative analyses) of the respective hospital event.
Results: Following a propensity score match, 178,275 individuals were included in the 18-64 years in-patient cohort, 16,307 individuals in the 65+ in-patient cohort, 85,314 individuals in the 18-64 post-operative cohort, and 11,136 individuals in the 65+ post-operative cohort. In the in-patient hospitalization analysis, there was a significant association between cannabis use and delirium in the 18-64 cohort (HR: 1.43, 95% CI: 1.11 – 1.85) but not in the 65+ cohort (HR: 1.19, 95% CI: 0.66 – 2.12). In the postoperative setting, there was a significantly increased risk of delirium in the cannabis cohort in both the 18-64 (HR: 3.37, 95% CI: 2.59 – 4.39) group and 65+ years old group (HR: 2.37, 95% CI: 1.51 – 3.72).
Conclusions and Relevance: The findings of this investigation suggest that documented cannabis-use disorder within one year of hospitalization or surgery is associated with a significantly increased risk of delirium. Delirium is associated with considerable patient morbidity, which can be mitigated through early diagnosis. Documented cannabis use may, therefore, warrant additional delirium screening measures and clinical discretion.



The Association between Cannabis Use and Delirium in the Postoperative and Inpatient Settings

Background
Stroke ranks as the fifth leading cause of death in the United States and is the primary contributor to neurological impairments and cognitive deficits, responsible for 5.2% of global deaths. Approximately half of stroke survivors suffer from long-term disabilities, making it a leading cause of disability worldwide. Currently approved treatments for ischemic stroke focus on restoring cerebral blood flow through intravenous thrombolysis and mechanical thrombectomy. Minocycline, a lipophilic protease inhibitor capable of crossing the blood-brain barrier, exhibits anti-inflammatory, antioxidant, and antiapoptotic properties both centrally and peripherally. This literature review aims to assess the efficacy and safety of Minocycline as an adjunctive therapy in treating ischemic stroke and improving post-stroke functional outcomes.
Methods
We searched PubMed, Google Scholar, and clinicaltrials.gov databases. We used a combination of keywords: acute ischemic stroke, Minocycline, neuroprotection, and neuroinflammation. We included full-text peer-reviewed scholarly articles published within the last decade, randomized controlled trials, and systematic reviews with meta-analyses. We excluded articles in languages other than English, experimental studies and animal studies.
Results
We systematically reviewed nine articles that met our predefined eligibility criteria and involved 1,010 participants. These studies assessed the effectiveness and safety of Minocycline by comparing groups treated with Minocycline to control groups using the National Institute of Health Stroke Scale. Across the nine studies, there was consistent evidence of substantial clinical improvement among patients treated with Minocycline. However, two of the studies indicated that although Minocycline was deemed safe, it did not result in improved outcomes for patients with acute stroke.
Conclusion
Minocycline shows promise in mitigating both immediate and prolonged effects of ischemic stroke, demonstrating efficacy with minimal adverse effects even at high dosages. Nonetheless, conflicting results in two studies suggest that small sample sizes might contribute to varying conclusions. Despite the scarcity of data from clinical trials, Minocycline could serve as a valuable adjunctive therapy, particularly for patients in remote areas lacking access to specialized stroke care or those unsuitable for intravenous thrombolysis. Additional randomized clinical studies on a large scale are needed to verify the Minocycline's neuroprotective effects and its potential to improve outcomes and reduce long-term disabilities in ischemic stroke patients.


The Role of Minocycline as Adjunctive Therapy in Acute Ischemic Stroke: Literature Review

Background
Single CGRP regimens may not improve migraine outcomes and could worsen symptoms in some patients. Combining small molecule antagonists (SMA) and ligand monoclonal antibodies (L-mAb) targets CGRP molecules and receptors, potentially providing increased synergistic relief. Our study aims to assess the effects of this dual-CGRP approach.

Methods
A retrospective matched cohort study was conducted at a neurological care center in Hawaii, analyzing 90 chronic migraine patients aged ≥18 years treated with CGRP inhibitors (L-mAbs: fremanezumab, galcanezumab, eptinezumab; SMAs: ubrogepant, rimegepant, atogepant; or a combination). The study compared dual L-mAb and SMA CGRP treatments with mono-L-mAb or mono-SMA CGRP treatments, matched by age and sex. Variables included age, age at diagnosis, sex, onabotulinumtoxinA use, headache frequency, duration, severity, and associated symptoms before and three months post-treatment. Adverse events were recorded for the dual-treatment group at three-month follow-up. Statistical analyses were made using Wilcoxon, Kruskal-Wallis, and Fisher's exact tests, with significance set at < 0.05.

Results
Patients on dual-CGRP therapy had an average reduction of four headache days, with some experiencing up to 14 fewer days, while mono-CGRP patients experienced no change (p = 0.112). Headache severity was reduced by 20% for dual-CGRP patients and 10% for mono-CGRP patients (p = 0.039). Aura symptoms were significantly reduced in the dual-CGRP group, with 48% (13 patients) becoming aura-free compared to 20% in the mono-CGRP group (p = 0.004). Adverse events in the dual-CGRP group were mild, with three patients experiencing fatigue, drowsiness, or mild constipation. No patients discontinued treatment, and no serious adverse events were reported.

Conclusion
Dual-CGRP regimens may provide improved effectiveness for controlling migraine symptoms by significantly reducing headache severity and aura symptoms without significant adverse events.

The Safety and Effectiveness of Dual Calcitonin Gene-Related Peptide (CGRP) Therapies for Migraine Treatment: A Focus on Small Molecule Antagonist and Ligand Monoclonal Combinations

Background
Neurodegenerative diseases (NDs), such as Alzheimer’s disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS), significantly affect the daily lives of patients. Shared risk factors for this group of diseases include age, genetic background, socioeconomic status, metabolic conditions, and environmental toxin exposure. Veterans are particularly vulnerable to these conditions due to their unique military experiences and exposures. This study aims to identify distinct risk factors for NDs in the veteran population, providing insights for tailoring clinical interventions to this unique patient population.

Methods
This systematic review was performed in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. In June 2024, a comprehensive search was conducted using the following electronic databases: PubMed, MEDLINE, EMBASE, Cochrane Database, and Scopus, focusing on studies published between 2000 and 2024. Search terms included combinations of MeSH terms and keywords such as “neurodegenerative diseases,” “veterans,” “military,” “risk factors,” “Alzheimer’s disease,” “Parkinson’s disease,” “ALS,” and “MS.” Inclusion criteria focused on peer-reviewed articles, cohort studies, case-control studies, and case series investigating ND risk factors in veterans. Publications not in English, opinion pieces, and non-human studies were excluded. 

Results
Unique risk factors for NDs in veterans include environmental toxin exposure, combat-related physical injuries, and psychological impact of military service. Environmental agents, like Agent Orange, herbicides, neurotoxins, chlorinated solvents, and other chemical warfare agents were significant factors. Physical military injuries, such as traumatic brain injuries (TBI), hearing loss, and visual impairments, have been linked to a higher incidence in NDs and neurotrauma. Veterans have long been known to be affected by the psychiatric effects of military experiences, specifically post-traumatic stress disorder (PTSD). Recent research has suggested a connection between the PTSD and eventual cognitive decline associated with NDs. 

Conclusion
Identifying the military-related risk factors in developing NDs underscores the multifactorial nature of NDs while highlighting the unique life experiences of veterans that contribute to their neurological decline. This study emphasizes the importance of understanding patient backgrounds to devise effective preventive measures and therapeutic approaches. Future research should prioritize longitudinal studies to further elucidate these associations and enhance intervention strategies.

Unique Military-Related Risk Factors Contributing to Neurodegenerative Diseases Among Veterans: A Systematic Review

Background
Encephalitis (inflammation of the brain) is primarily divided into Autoimmune Encephalitis (AE) and Infectious Encephalitis (IE). Encephalitis poses a substantial burden on the U.S. healthcare system with an annual prevalence of 5-10 patients per 100,000 individuals and an inpatient mortality of nearly 10% [1-3]. Additionally, most patients are discharged with sequelae of impaired cognitive function [4]. Previous studies suggest both autoimmune (e.g. multiple sclerosis) and infectious (e.g. SARS-CoV-2) condition severity is associated with Vitamin D (VitD), where it can modify disease activity or where hypovitaminosis is a causal risk [5-6]. VitD supplementation, an extremely accessible and cost-effective intervention, in some cases resulted in disease prevention and risk reduction [5,6]. Despite these findings, the relationship between VitD and both autoimmune- and infection-mediated encephalitis is unknown. We sought to assess this relationship between VitD and clinical measures and outcomes in patients with encephalitis. 

Methods
373 adult encephalitis patient charts from 03-31-2013 to 03-31-2023 were reviewed from the Texas Medical Center/Greater Houston area. VitD levels, demographics, physical exam findings, treatments, imaging findings, diagnostics, and outcome variables were collected. VitD values were trichotomized into “Deficient”, “Insufficient”, and “Sufficient” [7]. 

Results 
Chi Square Tests of Independence analysis revealed significant associations between VitD Status and Disposition (p = 0.01), Cause of Death (p < 0.001), and # Rituximab therapies (p = 0.006). Additionally, statistically significant associations existed between low VitD levels (VitD Deficiency and Insufficiency) and immunocompromised state (p = 0.008), poorer outcomes referencing the Glasgow Outcome Scale (GOS) (p = 0.014), Hospital Readmission (p < 0.001), severe comorbid conditions referencing the Charlson Comorbidity Score (p = 0.032), and Mortality (p < 0.001). Binary Regression analysis revealed confounds; African-American patients and those receiving mechanical ventilation had poorer outcomes based on the GOS (p = 0.008, 0.048).

Conclusion 
Our study provides evidence that VitD status has a significant relationship with AE and IE clinical measures and outcomes post-hospitalization. However, we were limited by lack of VitD documentation; ~10% of study patients had documented measurements taken during their hospital stay. This illuminates the need for clinicians to 1) collect VitD data for all AE/IE patients and 2) consider VitD supplementation, an accessible and cost-effective intervention, for AE/IE patients. Future studies, currently being pursued, include incorporating 300 additional AE/IE patients from the Johns Hopkins medical system to further define the relationship between VitD status with clinical outcomes. 



1. Graus F, Titulaer MJ, Balu R, Benseler S, Bien CG, Cellucci T, Cortese I, Dale RC, Gelfand JM, Geschwind M, Glaser CA, Honnorat J, Höftberger R, Iizuka T, Irani SR, Lancaster E, Leypoldt F, Prüss H, Rae-Grant A, Reindl M, Rosenfeld MR, Rostásy K, Saiz A, Venkatesan A, Vincent A, Wandinger KP, Waters P, Dalmau J. A clinical approach to diagnosis of autoimmune encephalitis. Lancet Neurol. 2016 Apr;15(4):391-404. doi: 10.1016/S1474-4422(15)00401-9. 
2. Ellul M, Solomon T. Acute encephalitis - diagnosis and management. Clin Med (Lond). 2018 Mar;18(2):155-159. doi: 10.7861/clinmedicine.
3. Hansen MA, Samannodi MS, Hasbun R. Predicting Inpatient Mortality Among Encephalitis Patients: A Novel Admission Risk Score. Open Forum Infect Dis. 2020 Oct 7;7(11):ofaa471. doi: 10.1093/ofid/ofaa471.
4. Kvam KA, Stahl JP, Chow FC, Soldatos A, Tattevin P, Sejvar J, Mailles A. Outcome and Sequelae of Infectious Encephalitis. J Clin Neurol. 2024 Jan;20(1):23-36. doi: 10.3988/jcn.2023.0240. PMID: 38179629; PMCID: PMC10782093.
5. Sintzel MB, Rametta M, Reder AT. Vitamin D and Multiple Sclerosis: A Comprehensive Review. Neurol Ther. 2018 Jun;7(1):59-85. doi: 10.1007/s40120-017-0086-4. Epub 2017 Dec 14. PMID: 29243029; PMCID: PMC5990512.
6. Xu Y, Baylink DJ, Chen CS, Reeves ME, Xiao J, Lacy C, Lau E, Cao H. The importance of vitamin d metabolism as a potential prophylactic, immunoregulatory and neuroprotective treatment for COVID-19. J Transl Med. 2020 Aug 26;18(1):322. doi: 10.1186/s12967-020-02488-5. PMID: 32847594; PMCID: PMC7447609.
7. Holick MF. Vitamin D status: measurement, interpretation, and clinical application. Ann Epidemiol. 2009 Feb;19(2):73-8. doi: 10.1016/j.annepidem.2007.12.001. Epub 2008 Mar 10. PMID: 18329892; PMCID: PMC2665033.

Vitamin D Status in Autoimmune and Infectious Encephalitis

Background 
Preterm birth (PTB) is a significant challenge in the U.S., disproportionately affecting Black women, especially in Cuyahoga County, Ohio, where rates exceed national averages. In 2020, PTB rates were 11.4% overall and 15.1% among Black women, compared to national averages of 10.1% and 14.4% respectively. These disparities persist across socioeconomic groups, highlighting the need for further investigation into specific contributing factors for Black women. This study aims to characterize risk factors associated with PTB among Black women in Cuyahoga County using data from singleton preterm births in 2021.

Methods
This descriptive cohort study involved non-Hispanic Black women aged 18 or older who delivered prematurely at two Cleveland Clinic hospitals. PTB was defined as delivery before 37 weeks gestation, excluding patients with late transfers of obstetric care or incomplete medical records. Demographic, medical, and obstetric variables were extracted from electronic medical records and analyzed using REDCap.

Results
A total of 141 patients met inclusion criteria, with a mean age of 28.3 (±5.7) years and a mean pre-gravid BMI of 32.1 (±10.1). Most participants were single (78.0%, n = 110) and insured (97.9%, n = 138). The median household income was $45,087 [31690.0, 58714.0]. 73.8% (104) of patients had at least one underlying health condition, notably hypertension (23.4%, n = 33), anemia (26.2%, n = 37), and psychiatric disorders (30.5%, n = 43), including depression and anxiety. 24.8% (25) reported tobacco use.

In regards to obstetric history, 30.5% (43) had a previous PTB, and over half (55.3%, n = 78) had complications in a prior pregnancy. During the index pregnancy, the mean gestational age at delivery was 35.4 [33.2, 36.4] weeks. Prenatal care began at 2.0 months gestation on average, with an average of 14 prenatal visits. Most patients (70.2%, n = 99) had gestational comorbidities, notably pre-eclampsia or eclampsia (29.1%, n = 41), anemia (22.0%, n = 31), gestational diabetes (12.1%, n = 17), and gestational hypertension (9.2%, n = 13). High percentages (83.7%, n = 118) completed recommended ultrasound screenings.

Conclusion
The study highlights that social support, socioeconomic status, and underlying health conditions continue to be key risk factors associated with PTB among Black women. The COVID-19 pandemic may have exacerbated these vulnerabilities. Notably, lack of insurance and inadequate prenatal care did not emerge as significant risks in this cohort.


A Study on Factors that Influence Preterm Birth among Black Women in Cuyahoga County, Ohio.

Introduction: In pregnancies at elevated risk for developing gestational diabetes mellitus patients undergo an early glucose tolerance test (eGTT) before 20 weeks gestation. This study aimed to assess the predictive value of a 1-hour eGTT as it relates to the repeat 1-hour glucose tolerance test (rGTT) at 24-28 weeks gestation. 

Methods: Sixty individuals with BMI >30 who received an eGTT and a rGTT were identified via retrospective chart review. Covariates included age and ethnicity. Risk ratios, 95% (Score) confidence intervals, and significance (Fisher’s Exact Test) were estimated. A logistic regression model was fit with rGTT (dependent variable) and eGTT (independent variable). Odds ratios and 95% confidence intervals were extrapolated from the model. Significance of each independent variable was identified via a likelihood ratio test. IRB #5802 Exempt Status Granted on 5/13/2024 by Colorado State University. 

Results: Seventy-one percent of those who failed eGTT failed rGTT. After adjusting for age and ethnicity, individuals who failed eGTT had 3.70x greater odds (95% CI:1.03x-15.80x) of failing rGTT compared to those who passed eGTT (χ2=4.05;p=0.04). 

Conclusions/Implications: These data suggest that failing a 1-hour eGTT is significantly associated with failing a 1-hour rGTT which indicates a potential benefit in proceeding directly to a 3-hour rGTT at 24-28 weeks. Further investigation of this predictive value with a larger sample size and broader range of patient risk factors is needed to fully understand the necessity of a 1-hour rGTT as it relates to failure of eGTT in clinical practice. 


Analyzing the Predictive Value of an Early 1-hour Glucose Tolerance Test in High-Risk Pregnancies

Introduction
Hysterectomies have become one of the most performed procedures in the United States with one in nine women undergoing a hysterectomy in their lifetime, mostly for benign gynecologic indications. Currently, the American College of Obstetrics (ACOG) recommends performing vaginal hysterectomies over laparoscopic, citing faster return to work, association with greater patient satisfaction, shorter operating times, and lower costs. However, there is a paucity of comprehensive cohort studies examining postoperative outcomes and mortality differences between vaginal and laparoscopic hysterectomies.

Materials and Methods
A retrospective cohort study was conducted using information from the National Surgical Quality Improvement Program database (NSQIP). Women aged 18 to 65 who underwent vaginal or laparoscopic hysterectomies for benign indications between 2018 and 2021 were reviewed. Outcome variables included mortality or presence of a major postoperative complication, including surgical site infections, urinary tract infection, sepsis, and serious systemic events. Unadjusted and adjusted (multiple binary logistic regression) odds ratios and 95% confidence intervals were computed.

Results
The sample in this study consisted of 157,628 women. Of these women, 87% underwent laparoscopic hysterectomy and vaginal hysterectomy was performed on the remaining 13%. The incidence of the composite outcome was higher among patients who underwent vaginal hysterectomy (6.4%) compared to laparoscopic hysterectomy (4.1%), (adjusted OR 1.66; 95% CI 1.56-1.76).

Conclusions
Laparoscopic hysterectomies have lower rates of postoperative complications and mortality. The findings of our study suggest that laparoscopic hysterectomies are just as effective and likely safer than vaginal hysterectomies. This indicates a potential need to reevaluate the ACOG's current recommendations.

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Mixed-effects deep-learning based quantitative radiomic analysis of longitudinal magnetic resonance imaging of brain metastases predict primary tumor origin

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