bluuebunny/crossref_metadata_2025_split huggingface dataset:
Enhancing the Management of Deployment-Limiting Medical Conditions in the U.S. Department of Navy Leveraging Electronic Health Records and Predictive Analytics Methods
Authors: Çağlayan Çağlar , Panaggio Mark J , Ramachandran Raghav , Wang Winnie , McShea Michael , Boggs-Wilkerson Denise , de Geus John , Mercado Michael 
Published: August 2024

ABSTRACT

Introduction
Deployment-limiting medical conditions (DLMCs) such as debilitating injuries and conditions may interfere with the ability of military service members (SMs) to deploy. SMs in the United States (U.S.) Department of the Navy (DoN) with DLMCs who are not deployable should be placed in the medically restricted status of limited duty (LIMDU) or referred to the Physical Evaluation Board (PEB) for Service retention determination. It is critical to identify SMs correctly and promptly with DLMCs and predict their return-to-duty (RTD) to ensure the combat readiness of the U.S. Military. In this study, an algorithmic approach was developed to identify DoN SMs with previously unidentified DLMCs and predict whether SMs on LIMDU will be able to RTD.

Materials and Methods
Five years of historical data (2016–2022) were obtained from inpatient and outpatient datasets across direct and purchased care from the Military Health System (MHS) Data Repository (MDR). Key fields included International Classification of Diseases diagnosis and procedure codes, Current Procedure Terminology codes, prescription medications, and demographics information such as age, rank, gender, and service. The data consisted of 44,580,668 medical encounters across 1,065,224 SMs. To identify SMs with unidentified DLMCs, we developed an ensemble model combining outputs from multiple machine learning (ML) algorithms. When the ML ensemble model predicted a SM to have high risk scores, despite appearing healthy on administrative reports, their case was reviewed by expert clinicians to investigate for previously unidentified DLMCs; and such feedback served to validate the developed algorithms. In addition, leveraging 1,735,422 encounters (60,433 SMs) from LIMDU periods, we developed four separate ML models to estimate RTD probabilities for SMs after each medical encounter and predict the final LIMDU outcome.

Results
The ensemble model had 0.91 area under the receiver operating characteristic curve (AUROC). Out of 236 (round one) and 314 (round two) SMs reviewed by clinicians, 127 (54%) and 208 (66%) SMs were identified with a previously unidentified or undocumented DLMC, respectively. Regarding predicting RTD for SMs placed on LIMDU, the best performing ML model achieved 0.76 AUROC, 68% sensitivity, and 71% specificity.

Conclusion
Our research highlighted potential benefits of using predictive analytics in a medical assessment to identify SMs with DLMCs and to predict RTD outcomes once placed on LIMDU. This capability is being deployed for real-time clinical decision support to enhance health care provider’s deployability assessment capability, improve accuracy of the DLMC population, and enhance combat readiness of the U.S Military.
Development of a Predictive Model to Determine Appropriate Length of Profile
Authors: Hazel David , Stewart Justin , Rivera-Nichols Triana , Little Jeanette 
Published: August 2024

ABSTRACT

Introduction
Musculoskeletal injuries are one of the primary causes of Soldiers’ inability to be medically ready, comprising over 80% of such causes. The electronic profile (e-Profile) is the way that musculoskeletal injuries are documented so that commanders will know the type of injury as well as the length of the time that the Soldier will need limited duty. A previous study of e-Profiles in an Army MTF Integrated Pain Management Center showed that the median length of an e-Profile was 30 days. It is in the best interest of the Army to have the Soldier out of the fight the minimum amount of time for recovery to ensure the unit readiness. The goal of this study was to utilize e-Profile data to see if a machine learning model can be developed to determine the appropriate time a Soldier needs to be on profile for a given diagnoses.

Materials and Methods
Institutional Review Board approval was obtained from the USAMRDC (protocol #M-10966). The initial dataset provided to the research team consisted of a single pipe delimited (“|”) text file containing 2.9 million rows of e-Profile data. Linear regression, decision trees, and random forests (RFs) were evaluated to see which model would best predict the number of days needed for an e-Profile.

Results
Linear regression had an adjusted R-squared of 0.165. The positive predictive value of decision trees (0-to-30-day range of e-Profiles) was 73.6%, and the negative predictive value (30-90 days) was 60.9% with an area under the receiver operating characteristic curve (AUC) of 0.694 for the model. The positive predictive value of RFs was 85.3% (for the 0-30 range), and the negative predictive value was 58.7% (for the 30-90 range) with an AUC of 0.794. An AUC that approaches 1 indicates a more accurate prediction.

Conclusions
The 3 models (linear regression, decision trees, and RF) studied as part of this project did not predict the days on e-Profile with a high degree of certainty. Future research will focus on adding additional data to the e-Profile dataset in order to improve model accuracy.
Antibacterial Activity of Ag+ on ESKAPEE Pathogens In Vitro and in Blood
Authors: Garry Brittany , Samdavid Thanapaul Rex J R , Werner Lacie M , Pavlovic Radmila , Rios Kariana E , Antonic Vlado , Bobrov Alexander G 
Published: August 2024

ABSTRACT

Introduction
Bloodstream infections are a significant threat to soldiers wounded in combat and contribute to preventable deaths. Novel and combination therapies that can be delivered on the battlefield or in lower roles of care are urgently needed to address the threat of bloodstream infection among military personnel. In this manuscript, we tested the antibacterial capability of silver ions (Ag+), with long-appreciated antibacterial properties, against ESKAPEE (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, Enterobacter species, and Escherichia coli) pathogens.

Materials and Methods
We used the GENESYS (RAIN LLC) device to deliver Ag+ to Gram-positive and Gram-negative ESKAPEE organisms grown in broth, human blood, and serum. Following the Ag+ treatment, we quantified the antibacterial effects by quantifying colony-forming units.

Results
We found that Ag+ was bactericidal against 5 Gram-negative organisms, K pneumoniae, A baumannii, P aeruginosa, E cloacae, and E coli, and bacteriostatic against 2 Gram-positive organisms, E faecium and S aureus. The whole blood and serum inhibited the bactericidal activity of Ag+ against a common agent of bloodstream infection, P aeruginosa. Finally, when Ag+ was added in conjunction with antibiotic in the presence of whole blood, there was no significant effect of Ag+ over antibiotic alone.

Conclusions
Our results confirmed that Ag+ has broad-spectrum antibacterial properties. However, the therapeutic value of Ag+ may not extend to the treatment of bloodstream infections because of the inhibition of Ag+ activity in blood and serum.
Stimulus Color Wavelength Influences Performance in a Virtual Reality Go/No-Go Task
Authors: Martinez Candace , Ledesma Leandro M , Chinn Lisa K , Grigorenko Elena L 
Published: August 2024

ABSTRACT

Introduction
This study investigated the influence of stimulus color wavelength on cognitive performance in a virtual reality (VR) Go/No-Go task by assessing participant’s reaction time and accuracy. Previous research has indicated that color has a variety of cognitive, physiological, and behavioral effects on individuals, differentiating their performance. However, there is a gap in understanding the influence of color on performance on VR cognitive tasks. An understanding of how stimulus color wavelength influences human performance could enhance the control over the design and interpretation of assessment and training outcomes in VR.

Materials and Methods
Participants (n = 99, 57 males, aged 18 to 33 years) were recruited from the University of Houston and surrounding areas. Participants completed a VR-based Go/No-Go task. In this task, participants were instructed to strike 3D shape stimuli only if they matched the color of one of 2 virtual sabers that participants hand in their hands in VR (“Go” trials). If neither virtual saber matched the presented shape color (“No-Go” trials), participants were instructed not to respond. Stimulus colors could be violet (407 nm), blue (478 nm), green (507 nm), yellow (612 nm), and red (679 nm). Participants’ reaction times and accuracy were recorded. The study design and procedures were approved by the University of Houston’s Institutional Review Board.

Results
Stimulus color wavelength had a significant influence on accuracy during the Go/No-Go saber color match condition task. In both Go and No-Go trials, longer wavelengths were associated with reduced accuracy. However, no significant findings on wavelength and reaction time were present. These findings emphasize the impact of stimulus color on task performance.

Conclusions
Shorter color wavelengths were associated with higher accuracy in a VR Go/No-Go task. These findings support the importance of color selection in VR tasks and trainings, especially in scenarios that include decision-making and require accuracy. Realistic colors encountered in real-life military operations into VR training environments may better prepare individuals for real-world challenges. Future research in this area could explore color effects in additional tasks and incorporate realistic color-based cues in VR training scenarios.
Multiple thoracolumbar compression fractures induced by glucocorticoid-induced osteoporosis and cachexia in a young adult female patient with systemic lupus erythematosus: a case report with a 5-year follow-up
Authors: Fujimoto Kazuki , Akiyama Taro , Kakinuma Kohei , Kano Toshikazu , Maki Narumi , Hashiba Daisuke , Maeyama Toshifumi , Nakagawa Ryosuke , Arai Hajime , Ohtori Seiji 
Published: August 2024

Abstract
Background: High doses of glucocorticoids and severe weight loss can cause osteoporosis. We present a case of glucocorticoid-induced osteoporosis and cachexia in an 18-year-old woman who experienced severe appetite loss leading to weight loss, amenorrhea, and multiple thoracolumbar compression fractures. Case presentation: The patient had been receiving high-dose glucocorticoid treatment for systemic lupus erythematosus since the age of 13 and developed unexplained appetite loss since the age of 16. She subsequently developed thoracolumbar compression fractures, which necessitated repeated hospitalization. Gradual glucocorticoid tapering using belimumab and weight regain were achieved through high-calorie nutrition administration via the central vein, which helped the patient overcome her cachexic state. Romosozumab administration increased bone mineral density. Conclusion: Long-term administration of glucocorticoids may lead to osteoporosis and cachexia, resulting in amenorrhea, especially in young adults. Approaches that taper glucocorticoids and promote weight regain may be helpful in the management of such patients.
Exposure to agricultural pesticides and wheezing among 5–12-year-old children in the Imperial Valley, CA, USA
Authors: Ornelas Van Horne Yoshira , Johnston Jill E. , Barahona Dayane Duenas , Razafy Mitiasoa , Kamai Elizabeth M. , Ruiz Brandyn C. , Eckel Sandrah P. , Bejarano Esther , Olmedo Luis , Farzan Shohreh F. 
Published: August 2024

Background:
Exposure to pesticides has been linked to adverse respiratory health outcomes in children.

Methods:
We leveraged the Children’s Assessing Imperial Valley Respiratory Health and the Environment cohort located in the rural community of Imperial Valley near the US–Mexico border. We calculated the kilograms of total pesticides applied within 400 m of children’s residential addresses for the years 2016–2020. Estimated pesticide usage near homes was categorized into three groups (none vs. low vs. high [split at the median]). All health variables (i.e., asthma status and wheezing) were derived from a parent-reported questionnaire on respiratory health. We used generalized linear models, controlling for child sex, the language of survey, health insurance, respondents’ highest education, and exposure to environmental secondhand smoking, to calculate prevalence differences between none versus low and high exposure to agricultural pesticides.

Results:
Approximately 62% of the 708 children (aged 5–12 years) lived within 400 m of at least one pesticide application within 12 months prior to survey administration. Exposure to pesticides within 400 m of children’s residences was associated with 12-month prior wheeze. Those in the “high” exposure group had a prevalence of wheezing that was 10 (95% confidence interval: 2%, 17%) percentage points higher than among children not exposed to pesticide applications. Associations for high exposure to specific categories of pesticide applications, sulfur only, all pesticides except sulfur, chlorpyrifos, and glyphosate, also were observed with a higher prevalence of wheezing than among children not exposed to pesticide applications.

Conclusions:
We observed associations between living near pesticide applications and more wheeze symptoms among children.
Health Needs Assessment of Unhoused Youth in Charleston, South Carolina
Authors: Adams Cristin S. , Roach Chelsea A. , Berini Carole R. , Cooper Nicole A. , Kahle Robert W. , Player Marty S. , Diaz Vanessa A. 
Published: August 2024

Background:
Over 35 000 youth experience homelessness on any given night in the United States (US). Unhoused youth experience unique physical and mental health challenges and face barriers in every social determinant of health (SDoH), which may be amplified in the LGBTQ+ population.

Objective:
The objective of this study was to define characteristics of the unhoused youth population and their utilization of healthcare to inform programs to meet their needs.

Methods:
Secondary analysis of data from the College of Charleston’s YOUth Count survey was conducted, focusing on health-related characteristics, challenges, healthcare utilization, and SDoH of youth aged 18 to 25 experiencing homelessness in Charleston, SC.

Results:
Almost three-quarters of respondents (74.6%) reported mental health challenges and 35% reported physical health challenges. A significantly higher proportion of those who engaged in survival sex were LGBTQ+ . More than half (68.4%) visited the emergency department (ED) and 29.3% were admitted to the hospital in the past 12 months. Housing status, safety, food insecurity, sexual orientation, prior foster care, and survival sex were all significantly associated with ED utilization. Housing status and survival sex were significantly associated with hospital admission.

Conclusions:
Addressing SDoH is essential to improving health outcomes and healthcare utilization among unhoused youth, particularly in the LGBTQ+ population.
Influences of Intraoperative Warming on Surgical Outcomes of Pancreaticoduodenectomy With Portal Vein Reconstruction: A Retrospective Cohort Study
Authors: Xu Yecheng , Huang Shenhui , Guo Yujie , Jiang Yongjian , Yang Feng , Di Yang , Yao Lie , Li Ji , Jin Chen , Fu Deliang 
Published: August 2024

Aim:
To test the hypothesis that intraoperative warming (IOW) can improve surgical outcomes after pancreaticoduodenectomy with portal vein reconstruction (PD-PVR).

Methods:
Patients diagnosed with pancreatic head ductal adenocarcinoma who underwent PD-PVR at Huashan Hospital between January 1, 2017, and January 1, 2022, were retrospectively divided into two groups according to whether IOW was implemented. The primary outcome was the incidence of textbook outcome (TO) after pancreatectomy. The secondary outcomes were intraoperative hypothermia and adjuvant chemotherapy (AC) completion rate.

Results:
Among the 196 included patients, 122 underwent IOW while 74 did not. Both average (35.2℃ vs. 36.2℃, p < 0.001) and minimum (34.0℃ vs. 35.6℃, p < 0.001) intraoperative body temperature were significantly higher in the IOW group compared with the non-IOW one. Satisfactory surgical outcomes were observed in the IOW group, due to a higher incidence of TOs (51.4% vs. 68.9%, p = 0.021), lower incidence of post-pancreatectomy hemorrhage (13.5% vs. 3.3%, p = 0.010), earlier AC initiation (48 day vs. 40 day, p < 0.001), and AC completion rate (59.5% vs. 76.2%, p = 0.020). IOW was the independent influential factor for TOs, intraoperative hypothermia, and AC completion. In survival analysis, the median overall survival was longer with AC completion (month, 8.6 vs. 27.5, p < 0.001) or TO (month, 16.2 vs. 20.0, p = 0.002). Intraoperative hypothermia (hazard ratio, 1.53; 95% confidence interval: 1.03–2.25, p = 0.033) was the independent risk factor of overall survival.

Conclusions:
Intraoperative hypothermia occurred frequently in patients with PD-PVR. IOW had a positive impact on surgical outcomes of PD-PVR, resulting in higher rates of TOs and postoperative AC completion.
Test–retest and interrater reliability of experimental within-subject variability of pain reports as assessed by the focused analgesia selection test
Authors: Agostinho Mariana , Shani Adi , Canaipa Rita , Treister Roi 
Published: August 2024

Abstract

Introduction:
Within-subject variability (WSV) of pain intensity reports has been shown to predict the placebo response. The focused analgesia selection test (FAST), which allows to experimentally assess WSV of pain reports, has been used as a screening tool to identify participants who are likely to have a strong placebo response in drug-development clinical trials. Yet, the reliability of FAST has not been reported.

Objectives:
To assess test–retest and interrater reliability of the FAST outcomes. To mimic pharma-sponsored clinical trials, we enlisted inexperienced assessors who underwent limited training.

Methods:
Healthy volunteers performed the FAST twice within a week and were randomly assigned to either the test–retest group or the interrater group. T-tests, partial Pearson correlations, intraclass correlations (ICC), and Bland–Altman plots were generated to assess FAST outcomes' reliability.

Results:
Sixty-three participants completed the study and were assigned to the test–retest (N = 33) or interrater (N = 30) arms. No statistically significant differences in the FAST outcomes were detected between the 2 sessions, except for the FAST covariance (FAST CoV) in the interrater assessment (P = 0.009). Test–retest reliabilities of the FAST-main outcomes were r = 0.461, ICC = 0.385 for the FAST R
2 and r = 0.605, ICC = 0.539 for the FAST ICC and in the interrater cohort, they were FAST R
2: r = 0.321, ICC = 0.337 and FAST ICC: r = 0.355, ICC = 0.330.

Conclusion:
Using inexperienced assessors, the FAST outcomes test–retest ranged from moderate to strong, whereas the interrater reliability ranged from weak to poor. These results highlight the importance of adequately training study staff members before using this tool in multicentre clinical trials.
CLINICAL APPLICATION STUDY OF 3D-ASL PERFUSION IMAGING AND MAGNETIC RESONANCE DIFFUSION IMAGING IN TRANSIENT ISCHEMIC ATTACK
Authors: Lan Quan 
Published: August 2024

ABSTRACT

Objective: This study aimed to explore the clinical application of three-dimensional arterial spin labeling (3D-ASL) and diffusion-weighted magnetic resonance imaging (DWI) in transient ischemic attacks. Methods: Forty patients with transient cerebral ischemia in our hospital were selected and included from July 2020 to March 2022. All subjects were detected by DWI and 3D-ASL technology. The positive rate, relative cerebral blood flow (rCBF), and the receiver operating characteristic curve of the two methods in the diagnosis of transient cerebral ischemia were compared; the objective was to compare the relationship between the frequency of transient ischemic attack and hypoperfusion, and vascular stenosis. Results: The 3D-ASL examination showed two cases of hypoperfusion in the healthy control group (5.00), and the magnetic resonance imaging examination showed four cases of vascular stenosis in the healthy control group (10.00). The rCBF ratio in the cerebral ischemia group was significantly lower than that in the cerebral ischemia group, which was significantly lower than that in the healthy control group (P < 0.05). The area under the curve (AUC) of 3D-ASL in the diagnosis of transient cerebral ischemia was 0.800, and the AUC of DWI in the diagnosis of transient cerebral ischemia was 0.725. The AUC of the combination of the two methods in transient cerebral ischemia was 0.850. There was a significant difference in the attack frequency of patients with transient cerebral ischemia with different perfusion (P < 0.05). There was a significant difference in attack frequency between patients with transient ischemic attack and patients without vascular stenosis (P < 0.05). Conclusion: 3D-ASL and DWI technology have higher diagnostic efficiency for transient cerebral ischemia.
Preparing to act follows Bayesian inference rules
Authors: Tarasi Luca , de Fatis Chiara Tabarelli , Covelli Margherita , Ippolito Giuseppe , Avenanti Alessio , Romei Vincenzo 
Published: August 2024

AbstractPredictive brain theories suggest that human brain sets-up predictive models to anticipate incoming sensory evidence. Recent studies demonstrated these models to be integrated already in sensory areas, shaping even perceptual outcomes. Here, we hypothesized that this integration process informs the entire functional hierarchy, thus scaling all the way down to the motor system. Operationally, we propose that cue-oriented cortico-spinal excitability (CSE) modulation serves the pre-activation of motor representations aligned to prior-congruent decisions. To this end, 62 participants completed a probabilistic discrimination task while we delivered bilateral single-pulse TMS over the two primary motor cortices (M1s) and recorded motor-evoked potentials (MEPs) to assess motor excitability associated to prior-congruent vs. incongruent actions separately encoded by the two hands. Our findings revealed that prior expectations shaped CSE well before action execution, predominantly by inhibiting the M1 cortex coding for the prior-incongruent action. Importantly, this physiological modulation underpinned the prior-induced bias in participants’ choices, highlighting the link between motor preparatory modulation and actual decision-making. Furthermore, we observed significant interindividual variability in prior-driven CSE modulations, revealing two distinct predictive strategies: thebelievers’style, who heavily rely on prior, and theempiricistsone, who downplay its role, maintaining CSE level mostly unbiased. Crucially, autistic and schizotypal traits drove these differences in prior-driven motor strategy, withbelieverscharacterized by schizotypal traits, whereasempiricistsdisplaying autistic-like features. These results demonstrate how predictive models are integrated into action representations and highlight the role of prior-driven CSE modulations as a potential marker able to intercept interindividual differences in predictive styles.