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Impact of CDE Referral on A1C Control in Adult Type 2 DM Patients.
Full text linkType II Diabetes Mellitus is a chronic health condition impacting many adults in Tennessee. Certified Diabetic Educators (CDEs) are specifically trained in educating and addressing the health care needs of patients with diagnoses of Type I or Type II Diabetes. Research has shown that education conducted by CDEs leads to improved outcomes and self- care in those with diabetes (Bowen, et al., 2016, King et al., 2019). Not only are CDEs cost effective services leading to a decrease in healthcare costs, but they also aid in the improvement of hemoglobin A1C (Hgb A1C) levels and decrease complications associated with Type II Diabetes Mellitus. The purpose of this project is to compare the impact of CDE referrals in adult patients with Type II Diabetes on their Hgb A1C levels with Type II diabetic patients who do not have a visit with a CDE. We hope to show a positive impact of CDE visits on Type II diabetic patients and their Hgb A1C level
Assessing The Efficacy of Tranexamic Acid in Adjunct to Oxytocin in Reducing Blood Loss During Cesarean Deliveries: A Scoping Review
Full text linkPurpose/Background
Globally, postpartum hemorrhage (PPH) is the leading cause of morbidity and mortality during the peripartum and postpartum period in delivering people. Emerging evidence suggests that combining second-line uterotonics with tranexamic acid (TXA) improves maternal outcomes, reduces blood loss, and lowers morbidity and mortality related to PPH (Jones et al., 2023; Al-dardery et al., 2023). TXA, an antifibrinolytic, enhances clotting, reduces blood loss, transfusion needs, hemoglobin drop, and the use of additional uterotonics (Bellos & Pergialiotis, 2021). This review highlights the benefits of TXA.
Methods
A scoping review required a literature search conducted from August 2023 to February 2024 using PubMed, CINAHL, and Google Scholar with terms like cesarean section, hemorrhage, antifibrinolytics, blood loss, tranexamic acid, oxytocin, and postpartum hemorrhage. Inclusion criteria included studies in English involving pregnant women aged 18 or older undergoing cesarean delivery with oxytocin alone or with TXA. The initial return was 563 articles. After further refinement, ten relevant, high-quality articles were analyzed.
Results
Analysis of ten peer-reviewed studies revealed that TXA significantly reduces blood loss during cesarean deliveries. Eight studies showed reduced PPH rates, and nine reported less hemoglobin decline. Adverse events were rare, with one study noting seizures and renal dysfunction and another identifying thrombotic events. TXA demonstrated the potential to improve maternal outcomes with a generally safe profile.
Implications for Nursing Practice
TXA during cesarean deliveries significantly reduces blood loss and improves maternal outcomes, decreasing the need for additional uterotonics and transfusions. Its favorable safety profile and efficacy suggest TXA\u27s integration into routine obstetric care. However, further rigorous studies are needed to address current limitations, refine dosing strategies, and evaluate long-term safety. Advancing research will help maximize TXA\u27s benefits and enhance maternal health outcomes
Ultrasound-Guided Epidural Placement vs. Conventional Technique - Evaluating Effectiveness: A Scoping Review
Full text linkPurpose/Background
Epidural anesthesia is a cornerstone of perioperative pain management, offering effective analgesia and reduced opioid dependency. However, traditional landmark-based epidural placement (EP) techniques often result in variable first-pass success rates (FPSR) and increased risks of complications. Ultrasound-guided (USG) EP has emerged as an alternative, providing real-time anatomical visualization to improve accuracy and safety. This scoping review synthesizes evidence on the comparative efficacy of USG EP and conventional techniques in adult patients undergoing perioperative epidural anesthesia.
Methods
This review commenced September 2023 and included full-access, peer-reviewed journal articles published in English between 2014-2023. Databases searched included PubMed, CINAHL, Cochrane Library, or literature made accessible through the UTHSC Library’s Interlibrary Loan. Primarily utilized MeSH terms included: conventional techniques, ultrasound-guided epidural placement, and first-pass success. Studies were selected if they evaluated USG versus conventional EP techniques, focusing on FPSR, needle passes or redirections, skin punctures, and procedural time. Articles involving pediatric populations or patients with contraindications to epidural anesthesia were excluded. Data from eight high-evidence articles, including one systematic review and seven randomized controlled trials, were analyzed.
Results
USG EP demonstrated higher FPSR, reduced needle passes and skin punctures, and improved patient satisfaction in six out of eight studies reviewed. However, procedural time was prolonged in cases involving providers inexperienced with USG techniques. These findings suggest that USG EP may offer significant advantages over conventional techniques, particularly in improving accuracy and reducing complications.
Implications for Nursing Practice
Integrating USG EP into clinical practice can enhance the quality and safety of epidural anesthesia. Its implementation may require training programs to address proficiency gaps, particularly for novice providers. By adopting evidence-based practices, anesthesia providers can contribute to better patient outcomes, reduce procedural risks, and optimize perioperative care
Postpartum Depression Screening at First Year Well-Child Visits: Evaluating the Rate of Maternal PPD Detection
Full text linkPurpose/Background
Postpartum Depression (PPD) is a concerning mental health condition characterized by feelings of extreme sadness, exhaustion, and challenges with maternal-infant bonding. PPD effects mothers’ ability to adequately care for themselves and their newborns. Current research suggests that one in seven women experience symptoms of PPD as late as 12 months postpartum. Despite screening guidelines set forth by the American Academy of Pediatrics, 50% of mothers with PPD will not receive a diagnosis.
This study aims to evaluate the rate of PPD detection at well-child visits occurring within the first 12 months postpartum by administering the Edinburgh Postnatal Depression Scale (EPDS) to eligible postpartum mothers. The goal of this study is to highlight the effectiveness of administering a screening tool to detect PPD thereby increasing access to timely and appropriate care for mother and baby and improving health outcomes for this patient population.
Methods
In this retrospective chart review, data was extrapolated from the clinic from January 1, 2024, through June 30, 2024, and 30 charts were analyzed where the chief complaint or HPI contained the keywords. Of these 30 charts, data was collected on whether EDPS surveys were administered.
Results
Data analysis of the 30 charts reveals the most frequent reason for office visit was 12 month well child checkup. Of these 30 charts, 50% received an EDPS survey. 100% of the 1 month well child checkups received an EDPS, while 89% of the 12 month well child checkups did not receive an EDPS survey. 3
Implications for Nursing Practice
The chart review results highlight that the clinic did a fair job administering the surveys during the well-child visits, but there is still room for significant improvement in the 12-month age group. Primary care providers can have a substantial impact on helping to screen this vulnerable population
Advancing Pandemic Response: Integrated Strategies for Testing, Prediction, and Bias Mitigation
Full text linkThe COVID-19 pandemic, along with prior outbreaks such as SARS and Ebola, has revealed critical gaps in global pandemic preparedness, emphasizing the need for integrated approaches to infectious disease management. This dissertation addresses three key areas of pandemic response: developing scalable screening strategies, constructing reliable predictive models, and mitigating demographic biases in artificial intelligence (AI) models used for healthcare decision-making.
The first study introduces a global screening strategy designed to optimize resource use and increase testing capacity, particularly in low- and middle-income countries (LMICs) where resources are limited. This study leverages pooled testing methods, where multiple samples are combined into a single test to conserve resources, and advanced mathematical models to ensure accuracy. The stratified, algorithm-guided, multi-level testing strategies developed in this research dynamically adjust testing frequency and pool sizes based on infection prevalence, allowing large-scale screenings to be conducted efficiently without compromising detection accuracy. Simulations showed that pooled testing can significantly reduce the number of tests needed in regions with low infection rates while maintaining reliable results. This method has the potential to be deployed not only for COVID-19 but also for other infectious diseases that require mass testing, especially in resource-constrained environments.
The second study focuses on the construction of a predictive model for real-time forecasting of COVID-19 infections and mortality. The model integrates real-time data from countries with different levels of epidemic control and is designed to adjust predictions continuously as new data becomes available. Factors such as population density, healthcare infrastructure, and public health interventions are incorporated into the model to improve its adaptability and accuracy. The model demonstrated its utility in predicting both the rise and fall of infection rates, as well as the effectiveness of various interventions. Countries that implemented early and strict public health measures saw reductions in predicted mortality, underscoring the importance of timely action in pandemic management. The predictive model provides governments and public health officials with valuable insights for resource allocation and intervention planning during ongoing and future pandemics.
The third study investigates the demographic biases inherent in AI models used to predict COVID-19 mortality, with a particular focus on racial and ethnic minority groups. Existing AI models often underperform for minority populations, exacerbating health disparities. Using population-based data from the Centers for Disease Control and Prevention (CDC), the study applied transfer learning techniques to adapt AI models trained on majority populations to better predict outcomes for underrepresented groups. The study focused on improving predictive accuracy for Non-Hispanic Black, Asian, and American Indian populations. Results demonstrated significant improvements in model fairness and performance, particularly in reducing mortality prediction bias for minority groups. The study highlights the importance of ensuring that AI models used in healthcare are equitable and do not perpetuate systemic biases that disproportionately affect vulnerable populations.
Together, these three studies provide a comprehensive approach to improving global pandemic preparedness. By addressing critical gaps in scalable testing, predictive modeling, and equitable healthcare delivery, this dissertation contributes to the development of more robust, adaptable, and fair strategies for managing future pandemics. The research offers valuable insights for policymakers, public health officials, and AI developers, ensuring that public health interventions are not only effective but also inclusive and equitable, particularly for underserved populations
Sickle Cell Disease Nursing Education: A Mixed Methods Program Evaluation
No full textINTRODUCTION AND BACKGROUND: Sickle cell disease (SCD) is a common disorder of the hemoglobin and affects more than 100,000 people in the United States and millions worldwide. In response to a drastic lack of available education a group of SCD experts developed the Sickle Cell Boot Camp to Promote Nursing Excellence Train the Trainer. This initiative provided the first opportunity for nurses worldwide to gain knowledge and skills curated by the leading experts in a safe and interactive environment. By adapting the program to a train the trainer modality, education materials are provided to the attendees, and they are encouraged to take the information to their home institutions and share it to educate others. AIMS: To determine the effect of the education provided in the SCD Nursing Bootcamp on nurses’ knowledge about SCD. To measure nurses’ attitudes and perceptions about individuals living with SCD. To explore nurses’ perceptions about the impact of the SCD Nursing Bootcamp. To determine the extent to which qualitative findings confirm, support, or enhance the quantitative findings. METHODS: Utilizing a mixed methods approach and the theoretical framework of Kirkpatrick’s Levels of Evaluation and the Theory of Planned Behavior, the knowledge of the attendees was quantitatively measured through pre and post testing as well as changes in the attitudes toward patients living with SCD. Qualitative interviews were then performed to expand upon the experience of the nurses attending the boot camp, educational offerings provided, and barriers that participants experienced upon their return. RESULTS: Thirty-four participants completed the train-the-trainer boot camp, representing US children’s and adult hospitals, international foundations, sixteen different states and three countries. A pre/post-knowledge assessment demonstrated a statistically significant improvement (p \u3c .001) when comparing scores. A significant decrease in negative attitudes (p \u3c .001), red-flag behaviors (p=0.02) and concern-raising behaviors (p=0.03) before and after attendance were demonstrated as well on the General Perceptions about Sickle Cell Disease Patients Survey. Qualitative interviews were overwhelmingly positive, and the qualitative analysis resulted with key themes to answer the research questions. The barriers were identified as scope, reluctance to change and biases. The participants who disseminated the information cited passion to participate and supportive leadership as key facilitators. Lastly, the lived experience themes from the participants were that it was informative, enlightening, and they were able to develop a sense of connection to the other participants like it was a family. The education provided by the attendees to date has reached over 500 additional providers and continues to grow. CONCLUSIONS AND FUTURE RESEARCH: With a significant improvement of both knowledge and attitudes, the train-the trainer boot camp provided resources and information about SCD and empowered nurses to educate others in their scope thus improving the care of all patients living with SCD that they encounter. Further evaluation of formative education for all medical disciplines, diverse educational materials, and the development of a structured mentor program were all identified as future research to improve the lives of people living with SCD
Integrative Approaches in Colorectal Cancer: Prognostic Biomarkers and AI-Driven Hypothesis Generation for Early Diagnosis and Drug Resistance
No full textColorectal cancer (CRC) is a leading cause of cancer-related mortality worldwide, with early diagnosis being critical for improving patient outcomes. This study addresses two key aspects of CRC research: understanding its etiology and prognostic biomarkers and exploring the role of artificial intelligence (AI) in generating hypotheses for early diagnosis. In the first project, we analyzed prognostic biomarkers in CRC, revealing a significant negative correlation between TP53 and CD56 mutations, which have opposing effects on patient survival. TP53, a tumor suppressor gene, is frequently mutated in CRC, while CD56, a glycoprotein involved in cell adhesion, may act as a cancer enhancer. Immunohistochemical (IHC) analysis of 2,923 CRC cases highlighted the potential of these biomarkers in predicting treatment outcomes. In the second project, we evaluated ChatGPT 4.0\u27s capability to generate innovative hypotheses for overcoming challenges in early CRC diagnosis. ChatGPT produced 65 hypotheses across three areas: improving screening accuracy, addressing technological limitations, and identifying reliable biomarkers. While ChatGPT rated 25 hypotheses as excellent, human evaluators rated only five as highly novel and feasible, emphasizing the need for human oversight in assessing practicality and clinical relevance. Experimental plans for selected hypotheses were developed, with one rated as excellent and others as good or moderate. In the third project, we further examined ChatGPT’s ability to generate hypotheses, focusing on drug resistance in CRC treatment. ChatGPT was tasked with generating hypotheses to address five major mechanisms of drug resistance, including genetic mutations, drug transport proteins, alterations in signaling pathways, tumor-associated macrophages (TAMs), and tumor heterogeneity. 68 hypotheses were generated, with 9 rated as novel, 21 as relatively novel, and 38 as not novel. ChatGPT provided experimental designs for each hypothesis, but human evaluators found that AI-generated hypotheses often lacked consideration of key biological constraints and feasibility challenges, reinforcing the necessity of human validation. Together, these studies highlight the importance of biomarker research in understanding CRC progression and the potential of AI as a complementary tool in hypothesis generation. While AI demonstrates remarkable creativity and novelty, human expertise remains essential for evaluating feasibility and translating hypotheses into clinically actionable solutions. This research underscores the need for further validation and collaboration between AI and medical researchers to advance early CRC diagnosis and improve patient outcomes
Characterizing the Cellular Response to Astrovirus Infection in the Central Nervous System
Full text linkCentral nervous system (CNS) diseases caused by infectious agents pose significant health challenges, often leading to severe neurological dysfunction with high morbidity and mortality rates. Astroviruses (AstVs), traditionally known for causing gastroenteritis, have recently been identified as neuroinvasive pathogens capable of inducing neurological diseases. This study explores the cellular and molecular mechanisms by which AstV, specifically non-classical VA1 and classical HAstV1 genotypes, induce CNS pathology in human neurons and astrocytes. Utilizing primary human neurons and astrocytes from various brain regions, this research investigates the cytotoxic effects, apoptotic pathways, and inflammatory responses triggered by these viruses. This study reveals that VA1 exposure leads to significant cytotoxicity in neurons, marked by increased dead-cell protease activity and a substantial rise in caspase-3/7 activity, indicating apoptosis. Additionally, VA1 infection alters gene expression related to neurotoxicity and cell death, promoting apoptotic pathways and inflammatory responses, as evidenced by the up-regulation of cytokines such as IL-6, IL-8, and IFN-λ1. In astrocytes, VA1 infection results in region-specific morphological changes and cytotoxicity without significant caspase-3/7 activation, suggesting non-apoptotic cell death pathways. Contrarily, HAstV1 exposure in neurons does not induce notable apoptosis but leads to heightened cytotoxicity, implying a different mechanism of cell death. HAstV1 infection in astrocytes, however, increases caspase-3/7 activity, pointing towards apoptosis as a primary mode of cell death. The studies in this dissertation underscore the distinct cellular responses elicited by different AstV genotypes, highlighting the complexities of their interaction with CNS cells. The findings here provide foundational insights into the mechanisms of AstV-induced neurovirulence, essential for developing therapeutic strategies to manage AstV-associated CNS diseases
Emergent potential of the terahertz CMOS microprocessor
Full text linkThe terahertz speed CMOS microprocessor that has been designed by Averoses Incorporated (US11063118B1) utilizes nano-vacuum tube elements with plasma interconnect of those elements, and has the capability to emit, detect, conduct, and analyze electromagnetic signals in the terahertz range. Nano-vacuum tube systems are resistant to ionizing radiation and to high temperatures, and there are emergent potentials of such systems beyond the obvious speed-up of data processing. Such a microprocessor can provide a platform for compact terahertz spectroscopy, especially for organic molecules, and this can also include DNA sequencing and DNA fingerprinting. Another emergent quality of such a system is that, for the first time, a complete operating electromagnetic wavelength (0.3 mm for a 1 THz wave) will fit within the geometric boundaries of the microprocessor, allowing picosecond comparisons of waves and wavelet Fourier transform functions
Referral to In-Person Smoking Cessation Counseling as a Smoking Cessation Aid
Full text linkReferral to In-Person Smoking Cessation Counseling as a Smoking Cessation Aid Purpose/Background
Smoking increases an individual’s risk of acute and chronic disease morbidity and mortality, as well as creating a financial burden for the individual and healthcare system. In the United States, tobacco smoking is the leading cause of preventable death. There are an estimated 5 million tobacco-related deaths each year due to tobacco smoking. Additional healthcare costs are also seen due to the need for increased treatments, medical supplies, and staffing. Previous research for smoking cessation resources has primarily focused on traditional primary care offices. Research shows that in-person counseling may be used as a behavioral modification tool to increase smoking cessation rates. Individual counseling alone was seen to be effective and increase the likelihood of cessation compared to less intense treatment. The purpose of this quality improvement project is to assess the number of patients who are current tobacco smokers and were referred to in-person smoking cessation counseling. Methods
Electronic medical records (EMR) from a metropolitan underserved primary care clinic in Memphis, TN were queried for patient-reported smoking and tobacco use from January 1, 2023-June 30, 2023. Fifty EMRs were identified and reviewed for the number of patients referred to an in-person smoking cessation counseling program. For the study population, patients were randomly selected and had to be 18 years or older. Included were adult patients ages 30-78 with a diagnosis of tobacco/ smoking use documented in the EMR. Of the individuals referred, groups were divided by gender and by those who attended in-person counseling and those who did not. Results
Of the 50 identified patients, 29 (58%) were referred to an in-person smoking cessation counseling program. Patients referred were predominantly female (72.4%) with a mean age of
52.8 [range 30-78] years. Among those referred, 55.2% attended the counseling program. Implications for Nursing Practice
In-person smoking cessation counseling is an effective aid for smoking cessation, with more than half of those referred attending the program. Females are more likely to be referred to smoking cessation counseling and attend. Implementing referrals to smoking cessation counseling may be an effective smoking cessation intervention, specifically for females. More research is needed regarding patient follow-up and long-term smoking cessation, as this study did not include these measures. This study is feasible and may be replicated in practice. In-person counseling is another method that may be used to aid in smoking cessation. Future research should include identification of patient demographics, like smoking history, socioeconomic status, current comorbidities, and previous attempts at smoking cessation