bluuebunny/crossref_metadata_2025 huggingface dataset:
Pediatric Brain Injuries are Associated With Intimate Partner Violence-Related Brain Injuries Among Women in Adulthood
Authors: Macaranas Anjeli R. , Tanriverdi Aylin E. , Joseph Annie-Lori , Iverson Grant L. , Valera Eve M.
Published: December 2024

Objective:

Prior studies have reported associations between childhood physical abuse and intimate partner violence (IPV). However, there has been limited literature examining the relationship between pediatric brain injuries and IPV-related brain injuries later in life. We examined the association between childhood brain injuries and brain injuries sustained from IPV in adulthood.

Setting:

Participants were recruited through Mass General Brigham’s “Rally,” social media, and information sheets distributed in locations likely to serve women in current or past abusive relationships (eg, domestic violence shelters, and IPV support programs).

Participants:

Women who have experienced IPV with and without brain injury (n = 129), ages 19 to 69.

Design:

Retrospective, cross-sectional study design.

Main Measures:

We administered the Ohio State University Traumatic Brain Injury Identification Method and the Brain Injury Severity Assessment to assess brain injury history, and the Childhood Trauma Questionnaire (CTQ). A logistic regression was used to examine the association between pediatric brain injuries and IPV-related brain injuries, adjusting for childhood trauma, years of education, and age.

Results:

A majority of participants (64.3%) reported experiencing at least 1 IPV-related brain injury, and 30.2% experienced at least 1 childhood brain injury. Child abuse-related brain injuries occurred in 10.9% of the sample, whereas childhood brain injuries from other causes occurred in 19.4% of participants. Participants who sustained at least 1 childhood BI were significantly more likely to sustain a future IPV-related brain injury as an adult (OR = 4.652, P = .004). For each additional childhood BI sustained, participants were more likely to sustain an IPV-related BI (OR = 3.198, P = .005).

Conclusion:

This study illustrates a high prevalence of childhood brain injuries among women who have experienced IPV and identifies an association between pediatric brain injuries and brain injuries due to partner violence in adulthood. Our findings speak to the urgency of increasing our understanding of childhood brain injuries and whether they or other related factors might confer an increased risk for brain injuries or possibly IPV later in life.
Medicare Accountable Care Organization Treatment of Serious Mental Illness
Authors: Newton Helen , Colla Carrie H. , Busch Susan H. , Tomaino Marisa , Hardy Brianna , Brunette Mary F. , Agravat Devang , Meara Ellen
Published: December 2024

Objective:

Characterize the association between Medicare Accountable Care Organizations’ (ACOs) behavioral health integration capability and quality and utilization among adults with serious mental illness (SMI).

Background:

Controlled research supports the efficacy of integrating physical and mental health care for adults with SMI, yet little is known about the organizations integrating care and associations between integration capability and quality.

Methods:

We surveyed Medicare ACOs (2017–2018 National Survey of ACOs, response rate 69%) and linked responses to 2016–2017 fee-for-service Medicare claims for beneficiaries with SMI. We examined the cross-sectional association between ACO-reported integration capability (tertiles of a 14-item index) and 7 patient-level quality and utilization outcomes. We fit generalized linear models for each outcome as a function of ACO integration capability, adjusting for ACO and beneficiary characteristics.

Results:

Study sample included 274,928 beneficiary years (199,910 unique beneficiaries) attributed to 265 Medicare ACOs. ACOs with high behavioral health integration capability (top-tertile) served more dual-eligible beneficiaries (67.8%) than bottom-tertile (63.7%) and middle-tertile ACOs (63.3%). Most beneficiaries received follow-up 30 days after mental health hospitalization and chronic disease monitoring–exceeding national quality benchmarks–but beneficiaries receiving care from top-tertile (vs bottom-tertile) ACOs were modestly less likely to receive follow-up [−2.17 percentage points (pp), P < 0.05], diabetes monitoring (−2.19 pp, P < 0.05), and cardiovascular disease monitoring (−6.07 pp, P < 0.05). Integration capability was not correlated with utilization.

Conclusions:

ACOs serving adults with substantial physical and mental health needs were more likely to report comprehensive integration capability but were not yet meeting the primary care needs of many adults with SMI.
The Lived Experience of Newly Graduated Nurses' Transition to Practice
Authors: Norton Denise , Reeve Shelly , Peacock Ashley , Ward-Smith Peggy
Published: December 2024

Reflection papers, written by new graduate nurses, at the completion of their 1-year residency program, were qualitatively analyzed. Separating the study population identified academic and/or clinical experiences that were impacted by the pandemic. These findings indicate variances in their transition to practice, which may necessitate an alteration of the content or timing of nurse residency programs.
Systematic Review and Meta-Analysis of Prevalence and Risk Factors for Psychological Birth Trauma
Authors: Xu Yaxuan , Wang Wenjuan , Zhou Lihua , Xu Wenli , Wang Hui , Zhang Fengying , Wang Xiaoqin , Zhang Hanmei
Published: December 2024

Background

Psychological birth trauma is common among women in labor and has severe implications for maternal and infant health. Although the prevalence and risk factors of psychological birth trauma have been widely reported, these findings have not been systematically synthesized, limiting screening and interventions.

Objective

This study aimed to determine the pooled prevalence of and risk factors for psychological birth trauma.

Methods

The Cochrane Library, Web of Science, PubMed, Embase, and Scopus databases were systematically searched between their inception and October 1, 2023. Pooled prevalence, odds ratio, and 95% confidence intervals were calculated using fixed or random effects models using Stata 15.0.

Result

The pooled prevalence rate of psychological birth trauma was 19%. We performed subgroup analysis based on age, parity, region, and measurement tools. The results showed differences in the prevalence of psychological birth trauma between these subgroups, suggesting the need for clinical personalization in different populations. The pooled odds ratio showed that fear of childbirth, cesarean section, operative vaginal birth, pain during labor, and dissatisfaction with support from midwives were significantly associated with psychological birth trauma.

Discussion

The study found that the pooled prevalence of psychological birth trauma was 19%. PBT risk factors are diverse, and understanding the prevalence and risk factors for psychological birth trauma has important implications for health care and social care systems.
Predictors of Decisional Capacity in Alzheimer’s Disease Biomarker Test Candidates
Authors: Kim Jeong Eun , Sereika Susan M. , Tamres Lisa K. , Lingler Jennifer H.
Published: December 2024

Background

Deciding to learn one’s Alzheimer’s disease (AD) biomarker status is a high-stakes endeavor that requires comprehending and deliberating about complex and nuanced information. Assessing capacity to consent to AD biomarker testing and disclosure is further complicated when candidates have cognitive impairment and present with family care partners.

Objective

The objective of this analysis was to identify predictors of decisional capacity for an amyloid Positron Emission Tomography (PET) disclosure study among persons with mild cognitive impairment (MCI) and their family care partners.

Methods

This analysis used an analytical correlational design, using baseline data from a randomized controlled trial of amyloid PET results disclosure. Simple linear regression was used to examine predictors of decisional capacity. Focusing on persons with MCI, the predictor variables of interest were sociodemographic characteristics, level of knowledge of MCI/AD, global cognition, and neuropsychological tests of language and executive functioning. Dyadic analyses were conducted with data from 82 dyads of persons with MCI and care providers using the Actor Partner Interdependence Model to assess for presence of actor and partner effects among key variables.

Results

Capacity to consent scores demonstrated sufficient capacity for all participants to consent to the study. For persons with MCI, lower age, higher mental status scores, MCI/AD knowledge scores, and better performance on measures of language and executive functioning were predictors of decisional capacity. The model revealed positive actor relations for MCI/AD knowledge with decisional capacity for both persons with MCI and family care partners and negative partner relationships for family care partners MCI/AD knowledge with the decisional capacity of persons with MCI.

Discussion

Assessment of decisional capacity is imperative when considering participation in AD research, including studies with high-stakes procedures like biomarker results disclosure. Our findings highlight that not only do individual characteristics put persons with MCI at risk for lower decisional capacity, but dyadic effects from family care partners may also be present.
Frailty and Self-Care Maintenance Mediated by Social Support and Depression in Older Adults With Heart Failure
Authors: Bu Na , Leng Min , Cao Guorong , Dou Chao , Hou Rongchun , Lu Xiaohong , Xu Hong
Published: December 2024

Background

Older adults with heart failure often exhibit poor self-care maintenance. Frailty could exacerbate self-care, leading to deteriorating health. Social support and depression may play a role in self-care maintenance in older adults with heart failure combined with frailty. Confirming this potential mechanistic relationship could provide valuable reference for nurses to formulate and improve the targeted intervention strategies and health education programs for older adults with heart failure.

Objectives

This study analyze the relationship between frailty and self-care maintenance in older adults with heart failure and determined the sequential mediation effect of social support and depression. Its goal was to provide valuable theoretical insights for formulating targeted clinical nursing interventions for older adults with heart failure.

Methods

A cross-sectional study was conducted from July 2023 to February 2024, during which older adults with heart failure were recruited using a convenience sampling method from the cardiovascular department of a tertiary class A hospital in Qingdao, China. A total of 241 completed the Tilburg Frailty Indicator, the Self-Care of Heart Failure Index, the Social Support Rating Scale, and the Patient Health Questionnaire–9. T-tests and one-way analysis of variance were used to examine differences in self-care maintenance among participants with distinct characteristics; correlation analysis was used to ​identify variable relationships within the study. The mediation model was tested using the SPSS PROCESS macro and the bootstrap method.

Results

Frailty was negatively correlated with self-care maintenance, and both social support and depression were significantly related to frailty and self-care maintenance. Social support and depression not only independently mediated the relationship between frailty and self-care maintenance but also exhibited a significant sequential mediation effect.

Discussion

The frailty of older adults with heart failure and its correlation with self-care maintenance is a complex and multidimensional phenomenon. Frailty not only directly influenced self-care maintenance in participants but also indirectly affected it through the mediating factors of social support and depression. Future research should emphasize innovative, targeted interventions to enhance social support quality and accessibility and alleviate depression, ultimately boosting patients’ self-care capabilities and elevating their quality of life.
Integration in Mixed Methods Research With an Exemplar Explanatory Sequential Study
Authors: Hwang Youri , Knobf M. Tish , Sadler Lois S.
Published: December 2024

Background

Integration—a hallmark of mixed methods research (MMR)—is crucial throughout the entire research process. Despite its importance, integration remains an elusive concept often inadequately addressed by researchers, with many publications focusing solely on the final stages of data analysis and interpretation.

Objectives

The authors aim to synthesize methodologic discussions of the mixed method research integration process and provide an illustration of integration across all phases of an exemplar explanatory sequential study.

Methods

Integration in MMR includes four distinct dimensions encompassing philosophical assumptions and paradigms, methodological methods, and dissemination of integrated study findings. This paper presents our integrated study findings, illustrated by a research study conducted to investigate sleep health among women with breast cancer.

Results

Integration of quantitative and qualitative data analyses is demonstrated through consistently matching the guiding paradigm with design choice, meta-inferences, and visual joint displays. The connecting displays linking quantitative and qualitative data, compare sleep characteristics scores, and the relationship between anxiety and vasomotor symptoms. The results highlight the significance of visual tools in enhancing the analytic processes and providing a comprehensive understanding of complex clinical phenomena.

Discussion

Integrating across all stages of mixed method research studies presents many challenges. The proposed four-dimension model of integration contributes to understanding the unique value of fully integrated mixed methods results. The exemplary study findings confirm the value of integration in achieving a nuanced and comprehensive understanding of a significant clinical problem.
The Impact of Educational Handouts on the Compliance Rate for Bariatric Patient Follow-Up Appointments
Authors: Fedirko Nicolas , Wilson Kristi Jo , Buterakos Roxanne , Pechta Alyssa
Published: December 2024

Background and Objectives:

Compliance rates for follow-up appointments are an issue for postoperative sleeve gastrectomy (SG) patients. Without consistent reinforcement and monitoring of patient progress, patients tend to gain the weight back, all of the medical improvements made are lost, and the ability to access patients for potential complications is denied. Patients need much reinforcement during their forever bariatric lifestyle, and the lack of consistent reminders may contribute to follow-up noncompliance and recidivism in SG patients. As time progresses, the follow-up appointment compliance rate decreases. Decreased follow-up can lead to a higher risk for complications such as asymptomatic esophagitis, and current recommendations suggest that esophagogastroduodenoscopy screening should occur 3 years postoperatively. After 1 year, the follow-up compliance decreases dramatically so that by the 3-year postoperative period, very few patients are being seen and scheduled for interventions such as an esophagogastroduodenoscopy. The objective of this quality improvement project was to evaluate the effectiveness of a patient educational handout on SG bariatric patient follow-up visit compliance.

Methods:

A quasi-experimental design and retrospective chart review was chosen. An educational handout was developed. Preintervention retrospective chart review consisted of 441 SG patients expecting a follow-up in 12 to 48 months. Postintervention included 3 months of the handout intervention with data collection totaling 198 patients.

Results:

Follow-up compliance for 4 year visits noted 0% preintervention/12.2% postintervention (P = .008), for 3 year visits 13.4% preintervention/12% postintervention (P = .846), for 2 year visits 26.3% preintervention/28.6% postintervention (P = .755), for 18 months visits 26.3% preintervention/32.6% postintervention (P = .365), and for 12 months visits 54.2% preintervention/34.1% postintervention (P = .011).

Conclusion:

In this quality improvement project, educational handouts did not have a statistical impact on follow-up compliance.
Immunomodulatory effects of tumor Lactate Dehydrogenase C (LDHC) in breast cancer
Authors: Naik Adviti , Thomas Remy , Al-Khalifa Aljazi , Qasem Hanan , Decock Julie
Published: December 2024

Background

Immunotherapy has significantly improved outcomes for cancer patients; however, its clinical benefits vary among patients and its effectiveness across breast cancer subtypes remains uncertain. To enhance its efficacy, it is important to gain more insight into tumor-intrinsic immunomodulatory factors that could be used as therapeutic targets. We previously identified Lactate Dehydrogenase C (LDHC) to be a promising anti-cancer target due to its role in regulating cancer cell genomic integrity. In this study, we investigated the effects of tumor LDHC expression on immune responses.

Methods

TIMER AND TIDE deconvolution methods were used to investigate the relationship between tumorLDHCexpression, immune cell infiltration and T cell dysfunction. Multiplex cytokine assays and flow cytometry analyses of breast cancer cell monocultures, and direct and indirect cancer cell-immune cell co-culture models were performed to assess the effect of LDHC knockdown on the secretion of inflammatory mediators and the expression of immune checkpoint molecules. T cell activity was determined by IFN-γ ELISPot assays and 7-AAD viability flow cytometry of cancer cells in direct co-culture.

Results

TIMER and TIDE analyses revealed that tumorLDHCexpression is associated with T cell dysfunction in breast cancer and worse post-immunotherapy survival in melanoma. Depletion of LDHC in three breast cancer cell lines (MDA-MB-468, BT-549, HCC-1954) enhanced T cell activation and cytolytic function (4-hour direct co-culture). Analysis of cancer cell monocultures revealed an increase in secreted pro-inflammatory cytokines (IFN-γ, GM- CSF, MCP-1, CXCL1), a decrease in immunosuppressive factors (IL-6, Gal-9) and a reduction in tumor cell surface PD-L1 expression following LDHC knockdown. Using 72-hour direct co- cultures with LDHC-silenced cancer cells, we observed a decrease in tumor-promoting cytokines (IL-1β, IL-4 and IL-6) and an increase in the tumor-inhibiting cytokine CXCL1. Furthermore, LDHC knockdown reduced the number of CD8+ T cells expressing PD-1 and CTLA-4, as well as the cell surface expression of CTLA-4, TIGIT, TIM3, and VISTA.

Conclusions

Our findings suggest that targeting LDHC may improve anti-tumor immune responses by modulating the secretion of pro- and anti-tumorigenic cytokines and impairing immune checkpoint signaling. Further studies are needed to elucidate the molecular mechanisms by which LDHC modulates these responses in breast cancer.
Age is an intrinsic driver of inflammatory responses to malaria
Authors: Loughland Jessica R. , Dooley Nicholas , Pava Zuleima , SheelaNair Arya , Andrew Dean , Tipping Peta , Bourke Peter , Engwerda Christian , Lopez J. Alejandro , Piera Kim , William Timothy , Barber Bridget E , Grigg Matthew , Anstey Nicholas M , Minigo Gabriela , Boyle Michelle J.
Published: December 2024

Age is a critical factor influencing the host immune response to infection and disease pathogenesis. In malaria, the risk of severe disease increases with age in non-immune individuals. Malaria severity is in part driven by inflammation, but the specific cells and mechanisms contributing to age-dependent disease risk are incompletely understood. Here, we assessed inflammatory cytokines in non-immune children and adults with clinical malaria, and the phenotypic, functional and transcriptional differences of in vitro innate cell responders to malaria parasites in naive children and adults. During naturally acquired malaria, age was associated with increased plasma levels of inflammatory chemokines CCL2, CCL3, CXCL8, CXLC9, along with CRP, and IDO, which were associated with clinical symptoms. In malaria naive individuals, classical monocyte and Vδ2+γδ T cell responses from adults were characterized by higher inflammatory cytokine production, and transcriptional activation following stimulation with malaria parasites. Classical monocyte responses in adults were dominated by CCL2 production, while in children the response had increased IL10 production and enrichment in IL10 signaling pathways upon parasite stimulation. This heightened inflammatory response in adults was not mitigated by parasite induced Tregs. Taken together, these findings identify cellular mechanisms of age-dependent host responses that play crucial roles in driving inflammatory responses in malaria.
Inference-based time-resolved cortical stability and chaos analysis for focal epileptic seizures
Authors: Zhao Yun , Grayden David B. , Boley Mario , Liu Yueyang , Karoly Philippa J. , Cook Mark J. , Kuhlmann Levin
Published: December 2024

Epilepsy affects millions globally, with a significant subset of patients suffering from drug-resistant focal seizures. Understanding the underlying neurodynamics of seizure initiation and propagation is crucial for advancing treatment and diagnostics. In this study, we present a novel, inference-based approach for analyzing the temporal evolution of cortical stability and chaos during focal epileptic seizures. Utilizing a multi-region neural mass model, we estimate time-varying synaptic connectivity from intracranial electroencephalography (iEEG) data collected from individuals with drug-resistant focal epilepsy. Our analysis reveals distinct preictal and ictal phases characterized by shifts in cortical stability, heightened chaos in the ictal phase, and highlight the critical role of inter-regional communication in driving chaotic cortical behaviour. We demonstrate that cortical dynamics are consistently destabilized prior to seizure onset, with a transient reduction in instability at seizure onset, followed by a significant increase throughout the seizure. This work provides new insights into the mechanisms of seizure generation and offers potential biomarkers for predicting seizure events. Our findings pave the way for innovative therapeutic strategies targeting cortical stability and chaos to manage epilepsy.
Leveraging Deep Neural Network and Language Models for Predicting Long-Term Hospitalization Risk in Schizophrenia
Authors: Bao Yihang , Wang Wanying , Liu Zhe , Wang Weidi , Zhao Xue , Yu Shunying , Lin Guan Ning
Published: December 2024

Early warning of long-term hospitalization in schizophrenia (SCZ) patients at the time of admission is crucial for effective resource allocation and individual treatment planning. In this study, we developed a deep learning model that integrates demographic, behavioral, and blood test data from admission to forecast extended hospital stays using a retrospective cohort. By utilizing language models (LMs), our developed algorithm efficiently extracts 95% of the unstructured electronic health record data needed for this work, while ensuring data privacy and low error rate. This paradigm has also been demonstrated to have significant advantages in reducing potential discrimination and erroneous dependencies. By utilizing multimodal features, our deep learning model achieved a classification accuracy of 0.81 and an AUC of 0.9. Key risk factors identified included advanced age, longer disease duration, and blood markers such as elevated neutrophil-to-lymphocyte ratio, lower lymphocyte percentage, and reduced albumin levels, validated through comprehensive interpretability analyses and ablation studies. The inclusion of multimodal data significantly improved prediction performance, with demographic variables alone achieving an accuracy of 0.73, which increased to 0.81 with the addition of behavioral and blood test data. Our approach outperformed traditional machine learning methods, which were less effective in predicting long-term stays. This study demonstrates the potential of integrating diverse data types for enhanced predictive accuracy in mental health care, providing a robust framework for early intervention and personalized treatment in schizophrenia management.
Alternative dosing regimens of GLP-1 receptor agonists may reduce costs and maintain weight loss efficacy
Authors: Cengiz Anıl , Wu Calvin C. , Lawley Sean D.
Published: December 2024

Aims

To discover alternative dosing regimens of incretin mimetics that simultaneously reduce costs and maintain weight loss efficacy. As a secondary objective, we used our results to explore how allocating a limited incretin mimetics budget could affect public health on a national scale.

Materials and Methods

We used mathematical modeling and simulation of semaglutide and tirzepatide. For semaglutide, we used a recent pharmacokinetic (PK) and pharmacodynamic (PD) model. For tirzepatide, we used a recent PK model and modeled PD by reparameterizing the semaglutide PD model to fit tirzepatide clinical data.

Results

Reducing dose frequency does not commensurately reduce weight loss. For example, merely switching from one dose per week (q1wk) to one dose every two weeks (q2wk) maintains roughly 75% of the weight loss. Furthermore, if the decrease in dose frequency involves an appropriate increase in dose size, then approximately 100% of the weight loss is maintained. In addition, we compared offering incretin mimetics to (1) a fraction of obese US adults with q1wk dosing versus (2) twice as many obese US adults with q2wk dosing. Though scenarios (1) and (2) require the same budget, our analysis suggests that (2) reduces national obesity and mortality to a much greater degree.

Conclusion

Our study highlights the potential utility of alternative dosing regimens of incretin mimetics. Compared to standard once-weekly dosing, costs can be halved and weight loss maintained. These cost-saving results have implications for patients, physicians, insurers, and governments.
Machine Learning-Based Identification of High-Risk Patterns in Atrial Fibrillation Ablation Outcomes
Authors: Oloko-Oba Mustapha , Liu Yijun , Wood Kathryn , Lloyd Michael S. , Ho Joyce C. , Hertzberg Vicki Stover
Published: December 2024

Background

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmias, often leading to serious health issues such as stroke, heart failure, and higher mortality rates. Its global impact is rising due to aging populations and growing comorbidities, creating an urgent need for more effective treatment methods. AF ablation, a key treatment option, has success rates that vary widely among patients. Conventional predictors of ablation outcomes, which primarily rely on sociodemographic and clinical factors, fall short of capturing the heterogeneity within patient populations, highlighting the potential for data-driven methods to provide deeper insights into procedural success.

Objectives

To uncover meaningful patient subgroups based on AF ablation outcomes and identify diagnostic codes associated with failure.

Methods

Machine learning clustering with must-link and cannot-link constraints was applied to electronic health records to discover meaningful clusters, revealing patient-specific factors influencing procedural success or failure. Statistical analyses, including chi-square tests, were used to identify diagnostic codes significantly associated with ablation failure.

Results

Out of the 145 diagnostic codes examined, thirteen significant codes were identified and categorized into four primary risk groups, ranked by their impact on procedural outcomes: (1) direct contributors affecting cardiovascular health, (2) indirect factors that contribute to systemic stress, (3) complications related to anticoagulation and hemorrhagic risks that can impact bleeding management, and (4) broader health indicators reflecting a general health burden that reduce patients resilience to procedural stress.

Conclusions

This study shows the importance of cardiovascular and non-cardiovascular factors in AF ablation outcomes, emphasizing the need for a more comprehensive pre-procedural evaluation. It also contributes to the application of machine learning in personalized risk assessment for AF and advancing individualized care strategies that may improve ablation success.
Quantifying and Visualizing Emergency Physician Workflow: Results of an Observational Time-Motion Study
Authors: Henreid Andrew J. , Ioannides Kimon L.H. , Pevnick Joshua M. , Cohen Tara N. , Torbati Sam S. , Nuckols Teryl K. , Berdahl Carl T.
Published: December 2024

Background

Emergency physicians face considerable workflow challenges due to unpredictable work environments, frequent interruptions, and mounting documentation requirements. Excessive time away from direct patient care is increasingly viewed as detrimental to care quality, communication, and patient safety. This study aimed to quantify and visualize the time emergency physicians spend on specific activities during their clinical shifts, particularly computer usage.

Methods

This observational time-motion study was conducted in a high-volume, urban emergency department (ED). An observer used a web-based application to track physician activities including computer use, direct patient care, and all other major tasks carried out on shift. Electronic health record (EHR) event log data was queried to measure computer use after each physician’s scheduled shift. The primary outcome was total minutes of computer time (during and after shift) per scheduled hour of clinical work.

Results

The observer tracked 20 emergency physicians for one 8-9h clinical shift each, which generated 150.0 hours of real-time observation data quantifying physicians’ ED workflow. In total, emergency physicians spent a median 29.8 minutes (IQR 25.6-38.5) on the computer per scheduled hour of their ED shift. Physicians spent a median 34.1% of their shift time using the computer and 26.9% with patients. Other activities included verbal communication with staff (15.9%), phone use (9.5%), miscellaneous tasks (5.5%), personal time (3.9%), electrocardiogram review (0.7%), and procedures (0.4%). EHR log analysis showed that physicians spent an additional median 1.3h (IQR 0.5-2.6) using the computer after their scheduled shifts.

Conclusion

Emergency physicians spent more than one-third of their ED shift working on the computer, which was more time than they spent with patients. They also spent 1-2 hours using the computer after their shifts. These findings demonstrate the need for strategies aimed at reducing unnecessary computer use during and after clinical shifts to enhance efficiency and improve patient care.
Automated Evaluation for Pericardial Effusion and Cardiac Tamponade with Echocardiographic Artificial Intelligence
Authors: Chiu I-Min , Vukadinovic Milos , Sahashi Yuki , Cheng Paul P. , Cheng Chi-Yung , Cheng Susan , Ouyang David
Published: December 2024

Background

Timely and accurate detection of pericardial effusion and assessment cardiac tamponade remain challenging and highly operator dependent.

Objectives

Artificial intelligence has advanced many echocardiographic assessments, and we aimed to develop and validate a deep learning model to automate the assessment of pericardial effusion severity and cardiac tamponade from echocardiogram videos.

Methods

We developed a deep learning model (EchoNet-Pericardium) using temporal-spatial convolutional neural networks to automate pericardial effusion severity grading and tamponade detection from echocardiography videos. The model was trained using a retrospective dataset of 1,427,660 videos from 85,380 echocardiograms at Cedars-Sinai Medical Center (CSMC) to predict PE severity and cardiac tamponade across individual echocardiographic views and an ensemble approach combining predictions from five standard views. External validation was performed on 33,310 videos from 1,806 echocardiograms from Stanford Healthcare (SHC).

Results

In the held out CSMC test set, EchoNet-Pericardium achieved an AUC of 0.900 (95% CI: 0.884– 0.916) for detecting moderate or larger pericardial effusion, 0.942 (95% CI: 0.917–0.964) for large pericardial effusion, and 0.955 (95% CI: 0.939–0.968) for cardiac tamponade. In the SHC external validation cohort, the model achieved AUCs of 0.869 (95% CI: 0.794–0.933) for moderate or larger pericardial effusion, 0.959 (95% CI: 0.945–0.972) for large pericardial effusion, and 0.966 (95% CI: 0.906–0.995) for cardiac tamponade. Subgroup analysis demonstrated consistent performance across ages, sexes, left ventricular ejection fraction, and atrial fibrillation statuses.

Conclusions

Our deep learning-based framework accurately grades pericardial effusion severity and detects cardiac tamponade from echocardiograms, demonstrating consistent performance and generalizability across different cohorts. This automated tool has the potential to enhance clinical decision-making by reducing operator dependence and expediting diagnosis.
AI-HOPE: An AI-Driven conversational agent for enhanced clinical and genomic data integration in precision medicine research
Authors: Yang Ei-Wen , Velazquez-Villarreal Enrique
Published: December 2024

Introduction: The increasing complexity of clinical cancer research necessitates the development of automated tools capable of integrating clinical and genomic data while accelerating discovery efforts. Artificial Intelligence agent for High-Optimization and Precision mEdicine (AI-HOPE) is introduced as an innovative conversational AI platform powered by Large Language Models (LLMs), designed to empower domain experts to perform integrative data analyses through natural language input, eliminating the need for programming expertise. AI-HOPE offers robust analytical capabilities, enabling the generation of actionable insights in clinical and translational research. Methods: AI-HOPE interprets user instructions in natural language and translates them into executable code to analyze locally stored data. It facilitates subset comparisons for clinical prevalence and survival analysis, generating statistical outputs such as odds ratios, Kaplan-Meier survival curves, and hazard ratios. Its capabilities were demonstrated through two case-control studies using The Cancer Genome Atlas (TCGA): (1) analyzing TP53 mutation enrichment in early-stage versus late-stage colorectal cancer (CRC) patients, and (2) comparing progression-free survival among FOLFOX-treated patients with or without RAS mutations. Results: In the first study, AI-HOPE identified a significant enrichment of TP53 mutations in late-stage (III/IV) CRC compared to early-stage (I/II) cases. In the second study, AI-HOPE revealed a significant association between KRAS mutations and poorer progression-free survival in FOLFOX-treated patients. These findings align with established literature, demonstrating AI-HOPE’s capability to independently uncover meaningful insights without prior user assumptions. Conclusions: AI-HOPE represents a transformative advancement in precision medicine research, offering a scalable, user-friendly framework for integrating clinical and genomic data. Its versatility extends beyond cancer research, supporting applications across diverse biomedical fields. Future enhancements, such as real-time data integration and multi-omics capabilities, will further solidify its role as a pivotal resource for advancing translational research and improving patient outcomes. AI-HOPE bridges the gap between data complexity and research needs, accelerating discoveries in precision medicine research.
Financial incentives to motivate treatment for hepatitis C with direct acting antivirals among Australian adults (The Methodical evaluation and Optimisation of Targeted IncentiVes for Accessing Treatment of Early-stage hepatitis C: MOTIVATE-C): Statistical analysis plan
Authors: Jones Mark , Totterdell James , Fathima Parveen , Snelling Thomas L
Published: December 2024

Abstract

The MOTIVATE-C study explores a critical question in hepatitis C treatment: How do financial incentives influence patients’ decisions to initiate direct-acting antiviral (DAA) therapy? Using an innovative Bayesian adaptive design, the research aims to determine the precise relationship between monetary support and treatment initiation among individuals with untreated hepatitis C virus. The study’s unique approach involves response-adaptive randomization, which dynamically allocates participants to different financial incentive levels. As the trial progresses, doses more likely to encourage treatment will receive increased emphasis, while less effective incentive levels may be systematically eliminated through pre-defined futility stopping rules. Participants will be tracked for DAA therapy initiation within 12 weeks of enrollment, with dedicated study navigators assisting them through the treatment access process. The primary analysis will adhere to the intention-to-treat principle, ensuring a comprehensive and unbiased evaluation of the intervention’s effectiveness. This manuscript details the statistical analysis plan, presenting the precise methodological framework, decision-making criteria, and analytical thresholds that will guide the study’s interpretation of how financial incentives might overcome barriers to hepatitis C treatment.
Clients’ Satisfaction With The Services Of An Outpatient Pharmacy At A University Hospital In Nigeria: A Cross-Sectional Study
Authors: Agu Mercy Chisom , Chima Uzochukwu Emmanuel , Eze Oluebubechukwu Praise , Maduekwe Stanley Ndubuisi , Okafor Victor Udochukwu , Chibuoke Ozioma Maryfrances , Nwankwo Chioma Bertha , Okoye Christabel Ogechukwu , Ngige Amauche Pearl , Chigbo Desirée Chimdimma , Akunne Maureen Ogochukwu
Published: December 2024

Background

Pharmaceutical care involves the pharmacist’s responsibility to optimize medication therapy and improve patient outcomes. Hence, patient/client satisfaction is regarded as an important measure of the effectiveness of pharmaceutical services in achieving treatment objectives. This study assessed the level of client satisfaction with the services of an outpatient pharmacy at a university hospital in Nigeria.

Method

An institution online-based cross-sectional study was conducted among clients who visited the University Medical Centre at the University of Nigeria Nsukka, Nsukka campus within the period of 15thSeptember to 15thOctober 2023. A 2-section, 30-item validated, semi-structured, interviewer-administered questionnaire was used in the study. Descriptive statistics were used to describe all the study variables while independent samplet-test and one-way ANOVA were used to determine the mean difference in satisfaction level among various sociodemographic characteristics. The statistical significance level was set atp<0.05.

Results

Out of the 166 participants in the study, the majority were students (n = 111, 66.9%), and receiving free medications (n = 117, 70.5%). The overall mean satisfaction score for pharmacy services was 3.11 out of a maximum 5.00 score. Notably, mean scores for most of the items exceeded 3.00 with the highest mean score obtained for the items:“The privacy of my conversations with the pharmacist”(3.59), and“The fairness of cost of medications in the pharmacy”(3.46) while the lowest score for the items:“The way my pharmacist works together with my doctor to make sure my medications are the best for me”(2.50) and“The availability of medications that are prescribed to me in the pharmacy”(2.63). First-time visitors reported significantly higher levels of satisfaction than return visitors (3.77 (0.686) vs 3.07 (0.637),p=<0.001)].

Conclusion

The study revealed a moderate level of satisfaction among the clients of the outpatient pharmacy represented in this study. The reasons for this level of satisfaction lay a foundation for the improvement of pharmacy services.
Self-medication practices for oral health problems: A community-based cross-sectional study in Sri Lanka
Authors: Gammulle Kavithrini Anunadika , Premarathne Sudeha M
Published: December 2024

The prevalence of self-medication is a common practice among Sri Lankans. However, the practice of self-medication for oral health problems has not been studied in the country. The current study aimed to assess the prevalence and the associated factors of self-medication practices for oral conditions. This community-based cross-sectional study was conducted among 441 adults in Piliyandala, Sri Lanka. The participants who had experienced an oral health-related concern within the past year were selected using a multi-stage cluster sampling method with probability proportionate to size technique. An interviewer-administered questionnaire was used for data collection. The results revealed that 68.9% practiced self-medication for an oral health condition during the past year. Dental pain was the most common reason for self-medicating. Allopathic medications were used by 85.2%. Amoxicillin and Metronidazole were taken by 10.2% and 12.8% respectively. Poor attitude towards oral healthcare services and low family income were significant predictors of self-medication and despite the availability of oral health services, a considerable number of participants resorted to self-medication due to the perceived simplicity of the condition and the high cost of dental treatments.
Early Pandemic Associations of Latitude, Sunshine Duration, and Vitamin D Status with COVID-19 Incidence and Fatalities: A Global Analysis of 187 Countries
Authors: Mogire Reagan M.
Published: December 2024

In the face of the COVID-19 pandemic, understanding the interplay between environmental factors and virus spread is crucial for global preparedness strategies. This study explores how geographic latitude, sunshine duration, and vitamin D status were associated with the incidence and fatality rates of COVID-19 across 187 countries during the crucial early months of the outbreak. Data on the total number of COVID-19 cases by country were obtained from the United Nations database as of June 30, 2020. Univariate and multivariate regression analyses were conducted to determine the associations between COVID-19 cases and latitude, average hours of sunshine from January to June, and mean 25-hydroxyvitamin D (25(OH)D) levels. The average COVID-19 prevalence and mortality per million population were 2,087 and 69, respectively, with a case fatality rate of 3.19%. COVID-19 case fatality rate was positively associated with latitude (β = 0.030; 95% CI: 0.008, 0.052) and negatively associated with hours of sunshine (β = -1.51; 95% CI: -4.44, 1.41) and 25(OH)D levels (β = - 0.054; 95% CI: -0.089, -0.019) in adjusted regression analyses. Findings were similar for COVID-19 prevalence and mortality rate. These findings indicate that higher latitude and lower 25(OH)D levels was associated with increased COVID-19 severity and mortality.

While the data highlight potential links between vitamin D status and COVID-19 outcomes, causality cannot be inferred. Further research, including large-scale, well-controlled trials, is essential to determine whether vitamin D plays a definitive role in COVID-19 prevention and management.
Causal relationship between inflammatory cytokines, metabolites and arrhythmia: a mendelian randomization study
Authors: Xie Yu-fei , Tang Ling-hui , Huang Feng , Zeng Zhi-yu
Published: December 2024

Abstract

Background

This study aims to explore the causal relationships between inflammatory cytokines (ICs), metabolites, and the risk of arrhythmia through Mendelian Randomization (MR) analysis.

Methods

The causal associations were analyzed using five different MR analysis methods. Additionally, reverse MR analysis was performed to assess the impact of arrhythmias on these ICs and their metabolites.

Results

The MR analysis revealed that Oncostatin-M receptor (OSM) was significantly associated with an increased risk of arrhythmia (OR = 1.0812, p < 0.05), along with other ICs such as CXCL11 (OR = 1.0586), SIRT2 (OR = 1.0521), and FGF5 (OR = 1.0520). Five were positively correlated with arrhythmia risk, including X-22776 (OR = 1.071, p = 0.022) and tricosanoylsphingomyelin (OR = 1.066, p = 0.035).Mediation analysis demonstrated that FGF5 influences arrhythmia risk through its metabolite 1-palmitoyl-2-oleoyl-GPE, with a mediated effect accounting for 5.1% of the total effect.

Conclusions

Our findings suggest that specific ICs and metabolites contribute to the pathogenesis of arrhythmia. In particular, FGF5 and its metabolite 1-palmitoyl-2-oleoyl-GPE are implicated in increased arrhythmia risk, highlighting potential metabolic targets for therapeutic intervention.
Dynamics of Reactive Oxygen Species and Nitrogen Cycling in Soils as a Mechanism for Volatile Reactive Nitrogen Oxide Production
Authors: Purchase Megan L. , Raff Jonathan D. , Gale Alexander G. , Vaughan Alannah , Bending Gary D. , Mushinski Ryan M.
Published: December 2024

Heterotrophic bacteria and fungi are responsible for the decomposition of organic matter in soil. During this process, reactive oxygen species (ROS) can be produced directly and indirectly as extracellular byproducts of respiration. It is well known that nitrogen (N) cycle processes lead to the formation of volatile reactive nitrogen oxides (NOy), a group of climate-active gases that contribute to atmospheric chemistry and negatively impact human health. Primary microbial sources of NOyinclude ammonia- oxidising bacteria and denitrifying bacteria and fungi. Despite soil being a significant source of global NOyemissions, studies to date have primarily focused on N emissions from agricultural soils and there remains a large scope for investigating mechanisms of soil NOyproduction in a wider context in order to better constrain terrestrial and climate process models. Here, we propose a potential microbial mechanism involving ROS that could influence the production of NOyfrom soil. We utilised metagenomics and metatranscriptomics alongside continuous gas flux measurements and analysis of soil properties to evaluate the connection between microbial ROS and soil-sourced NOy. Our findings suggest that more NOy, particularly nitric oxide (NO), is produced in the presence of increased abundance of ammonia-oxidising and denitrifying taxa. NO can be lost to the environment or reacts with superoxide, an ROS produced via the enzymatic activity of soil organic matter (SOM) decomposers. This reaction produces peroxynitrite (ONOO-), which we have demonstrated to enhance nitrogen dioxide (NO2) emissions from soil. We have shown that the extent of NOyproduction through this pathway may be dependent on SOM composition, and the associated variability in carbon and nitrogen content.
A dual role in virion attachment and entry makes the human cytomegalovirus gHgLgO trimer the central player in virion infectivity
Authors: Thiessen Lena , Garuti Roberto , Kubic Lucie , Kösters Miwako , Selvakumar Divya Amarambedu , Krey Thomas , Görzer Irene , Fröhlich Thomas , Adler Barbara
Published: December 2024

Glycoproteins in the viral envelope of human cytomegalovirus (HCMV) orchestrate virion tethering, receptor recognition and fusion with cellular membranes. The glycoprotein gB acts as fusion protein. The gHgL complexes gHgLgO and gHgLpUL(128,130,131A) define the HCMV cell tropism. Studies with HCMV lacking gO had indicated that gO, independently of binding to its cellular receptor PDGFRα, plays an important second role in infection. Here, we identified a gO mutation which abolished virus particle infectivity by preventing the interaction of gHgLgO with host cell heparan sulfate proteoglycans (HSPGs). We could not only show that gHgLgO – HSPG interactions are a genuine second role of gHgLgO, but also that gHgLgO is the main player in determining the infectivity of HCMV virus particles. This challenges long-accepted textbook knowledge on the role of gB and gMgN complexes in virion tethering. Additionally, it adds the gHgLgO complex to the antigens of interest for future HCMV vaccines or treatments.