Statistical Tests Research Articles

Geographical health inequalities in India: the impact of the COVID-19 pandemic on healthcare access and healthcare inequality.

With an emphasis on spatial health disparities, this study examines how COVID-19 has affected healthcare access and inequality in India. The study developed the Healthcare Access Index (HAI) and Healthcare Inequality Index (HII) to assess the pandemic's effects on healthcare. The study addresses spatial health disparities in healthcare access and inequality, filling gaps in the literature. The final aim of the study is to offer policy suggestions to lessen healthcare inequities in India, particularly in the context of COVID-19. The study incorporates secondary data from publicly accessible databases such as the National Family Health Survey, Niti-Ayog and Indian Census databases and employs a quantitative research design. The impact of the COVID-19 pandemic on healthcare access and healthcare inequality in India is examined using the HAI and the HII. The five dimensions of healthcare access - availability, accessibility, accommodation, cost and acceptability - were used in developing the HAI. The study uses a panel data analysis methodology to examine the HAI and HII scores for 19 states over the pre-COVID-19 (2015) and post-COVID-19 (2020) periods. In order to investigate the connection between healthcare access, healthcare inequality and the COVID-19 pandemic, the analysis employs statistical tests such as descriptive statistics, correlation analysis, factor analysis and visualization analysis. According to the study, COVID-19 impacted healthcare access and inequality in India, with notable regional inequalities between states. The pandemic has increased healthcare disparities by widening the gap between states with high and low HII ratings. Healthcare access is closely tied to healthcare inequality, with lower levels of access being associated with more significant levels of inequality. The report advises governmental initiatives to lessen healthcare disparities in India, such as raising healthcare spending, strengthening healthcare services in underperforming states and enhancing healthcare infrastructure. For Indian healthcare authorities and practitioners, the study has significant ramifications. In light of the COVID-19 pandemic, there has been a main focus on addressing geographic gaps in healthcare access and inequality. The report suggests upgrading transportation infrastructure, lowering out-of-pocket costs, increasing health insurance coverage and enhancing healthcare infrastructure and services in underperforming states. The HAI and the HII are tools that policymakers can use to identify states needing immediate attention and appropriately spend resources. These doable recommendations provide a framework for lowering healthcare disparities in India and enhancing healthcare outcomes for all communities. The study's originality resides in establishing the HAI and HII indices, using panel data analysis and assessing healthcare inequality regarding geographic disparities. Policy choices targeted at lowering healthcare disparities and enhancing healthcare outcomes for all people in India can be informed by the study's practical consequences.

Abstract B033: Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment

Abstract The tumor microenvironment (TME) comprises diverse cell types whose interactions are crucial for cancer progression. Traditional bulk tissue analyses mask cell-type-specific epigenetic changes that may drive disease progression. We used DNA methylation data and a reference- based cell-type deconvolution algorithm — hierarchical tumor immune microenvironment epigenetic deconvolution (HiTIMED) — to quantify cell types in the TME. Then, we employed CellDMC, a statistical interaction testing framework that can use cell type proportions in conjunction with differential methylation analysis to identify cell-specific differential methylation. Genome-scale DNA methylation profiles from breast cancer tissue (n=609) and normal breast tissue (n=230) samples were accessed in GEO and GTEx. Our novel approach leverages bulk DNA methylation data to infer cell-type-specific epigenetic landscapes, circumventing challenges and limitations associated with direct single-cell methylation profiling, such as high costs and technical variability. Reference-based computational tools allow us to dissect complex tissue compositions and reveal distinct methylation patterns and pathways that may be unique to individual cell types, providing insights that are not discernible from traditional bulk tumor analysis approaches. Compared with nontumor normal samples, we identified significant DNA methylation alterations (FDR≤0.05) across tumor, stromal, endothelial, epithelial, lymphocytes, and myeloid cells in breast tumors. Tumor cells exhibited the highest number, 8,510, differentially methylated cytosines (DMCs) with 1,966 of these unique to tumor cells. Stromal, endothelial, and epithelial cells also showed considerable methylation alterations, with a total of 530, 440, 339 DMCs, respectively, with 5 DMCs unique to epithelial cells. Despite lower immune cell proportions in our samples, we identified 104 lymphocyte specific DMCs and 185 myeloid specific DMCs, with 14 and 20 DMCs unique to these cell types respectively. The unique DMCs identified in each cell type suggest distinct epigenetic landscapes that may drive specific cellular functions and interactions within the TME. Importantly, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the annotated cell-type-specific DMCs revealed distinct pathways that were not apparent in the pathway analysis of bulk tumor versus normal tissue, underscoring the value of examining epigenetic alterations at the cell-type level. Our findings highlight the opportunity to leverage DNA-based cell typing with DNA methylation data to discern cell-specific molecular alterations. By focusing on cell-type-specific alterations, we can better understand the epigenetic mechanisms driving TME crosstalk, such as the activation of stromal cells and the modulation of immune responses by tumor cells. Our findings underscore the need for targeted therapeutic strategies that consider the unique epigenetic landscapes of individual cell types within the TME, offering new avenues for improving cancer treatment outcomes. Citation Format: Barbara Karakyriakou, Brock C. Christensen, Lucas A. Salas. Identification of cell-specific DNA methylation alterations in the breast tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr B033.

Bidirectional Mendelian randomization links gut microbiota to primary biliary cholangitis.

Primary biliary cholangitis (PBC) and gut microbiota (GM) are epidemiologically correlated but the causal inter-relationships remain poorly understood. We aim to explore the causal relationships between GM and PBC. Using the MiBioGen consortium, GWAS data for GM at the species level and the largest publicly available PBC GWAS data to date, we performed a bidirectional two-sample Mendelian randomization by the inverse variance weighted, MR-Egger, weighted median, weighted model and MR-PRESSO to elucidate the potential causal role of GM in PBC. To measure the heterogeneity of instrumental variables (IV), Cochran's Q statistic and MR-Egger intercept test were used. Genetically instrumented order Coriobacteriales (odds ratio [OR] = 2.18, 95% confidence interval [CI] 1.30-3.66, P = 0.004) significantly increased the risk for PBC, while genetically driven class Deltaproteobacteria (OR = 0.52, 95% CI 0.36-0.74, P = 0.002) causally decrease the NAFLD risk. Reverse MR analysis showed no significant association between PBC and the two specific GM. However, it indicated that PBC progression significantly increases the abundance of the class Bacteroidia, order Bacteroidales, and phylum Bacteroidetes (OR = 1.02, 95% CI 1.002-1.03, P = 0.026), while decreasing the abundance of the genus Lachnospiraceae UCG010 (OR = 0.98, 95% CI 0.96-0.995, P = 0.026). Our study demonstrated that genetically driven order Coriobacteriales and class Deltaproteobacteria were causally related to PBC risk. This causality provided a new perspective on ameliorating PBC by modulating GM. Our study demonstrated that genetically driven order Coriobacteriales and class Deltaproteobacteria were causally related to PBC risk. PBC was causally related to the abundance of four GM taxa(class Bacteroidia, order Bacteroidales, phylum Bacteroidetes and genus Lachnospiraceae UCG010). This causality provided a new perspective on ameliorating PBC by modulating GM.

Analysing the impact of gamification training on reinforcing the relationship of ISA employee engagement and employee task performance – empirical study

Purpose This paper aims to examine the effect of gamification training on employee task performance within the context of intellectual, social and affective (ISA) employee engagement in India. The use of gamification in training as a possible precursor to increased employee engagement is a fascinating research topic, especially as employee engagement is becoming an increasingly important factor in workplace success. Design/methodology/approach To achieve the aim of this study, 300 responses were obtained from employees in an Indian company using online surveys to quantitatively assess levels of employee engagement and task performance. Statistical tests like SPSS 20.0 and Smart PLS 3.0 were run on the collected data to see if gamification training led to significantly higher levels of employee engagement and if this engagement had an effect on task performance. Findings Result tells that social and affective engagement mediates the relationship between gamification training and employee task performance in gamification-using organisations, relative to intellectual engagement. As social and affective engagement has considerable positive effects on employee job performance and gamification training, gamification training is a critical approach for organisations to implement to increase employee engagement and, consequently, performance. Originality/value Using an innovative variable of employee engagement – specifically, ISA employee engagement – the authors have sought to establish a mediating link between gamification and employee task performance. Therefore, the study’s designs have practical value for organisations because they incorporate the ISA engagement scale into a game-based learning environment.

An interpretable (explainable) model based on machine learning and SHAP interpretation technique for mapping wind erosion hazard.

Soil erosion by wind poses a significant threat to various regions across the globe, such as drylands in the Middle East and Iran. Wind erosion hazard maps can assist in identifying the regions of highest wind erosion risk and are a valuable tool for the mitigation of its destructive consequences. This study aims to map wind erosion hazards by developing an interpretable (explainable) model based on machine learning (ML) and Shapley additive exPlanation (SHAP) interpretation techniques. Four ML models, namely random forest (RF), support vector machine (SVM), extreme gradient boosting (XGB), and quadratic discriminant analysis (QDA) were used. Thirteen features associated with wind erosion were mapped spatially and then subjected to a multivariate adaptive regression spline (MARS) feature selection algorithm, and then, tolerance coefficient (TC) and variance inflation factor (VIF) statistical tests were used to explore multicollinearity among the variables. MARS analysis shows that eight features consisting of elevation (or DEM), soil bulk density, precipitation, aspect, slope, soil sand content, vegetation cover (or NDVI), and lithology were the most effective for wind erosion, while no collinearity existed among these variables. The ML models were used for ranking the effective features, and the research introduces the application of an interpretable ML model for the interpretation of predictive model's output. The ranking of effective features by RF-as the most typical ML model-revealed that elevation and soil bulk density were the two most important features. According to the area under the receiver operating characteristic curve (AUROC) (with a value > 90%) and precision-recall (PR) (with a value > 90%) curves, all four ML models performed with great accuracy. According to the PR curve, the SVM model performed slightly better than others, and its results revealed that 20.9%, 23%, and 16.6% of the total area in Hormozgan Province is characterized by moderate, high, and very high hazard classes to wind erosion, respectively. SHAP revealed that soil sand content and elevation are the most important variables contributing to the predictive model output. Overall, our research is one of the pioneering applications of interpretable ML models in mapping wind erosion hazards in Southern Iran. We recommend that future research should address the aspect of interpretability in order to better understand predictive model outputs.

Assessing CMIP Models’ Ability to Detect Observed Surface Warming Signals Related to Climate Change

Abstract Assessing if CMIP models can detect observed climate change signals is crucial for evaluating their realism and strengthening confidence in future projections. These signals can only be compared once distinguishable from the background climate “noise.” Built for impact studies but not detection purpose, the time of emergence (ToE) estimates when this occurs using a fixed signal-to-noise ratio. To more accurately assess models’ ability to reproduce observed climate change signals, we introduce the time of detection (ToD), which employs a statistical significance test of the nonlinear trend, accounting for the time series length. ToD and ToE are computed for sea surface temperature (SST) and relative SST (RSST) across four observational and 69 CMIP5/6 historical and shared socioeconomic pathways 5–8.5 (SSP5–8.5) scenario datasets. ToD precedes ToE and is less sensitive to the chosen threshold. While already detectable in most of the tropics, SST warming in the equatorial Pacific is detectable in ∼90% of models but only one out of four observational datasets, due to a stronger modeled warming. Because RSST signals are weaker than SST signals, they do not emerge anywhere but are detectable in two regions. The enhanced warming in the western Indian Ocean, detected in ∼45% of models, is not robust in observations when excluding pre-1960 dubious data. Conversely, the subdued southeast Pacific warming detected in observations and ∼80% of models is robust and consistent with a poleward extension of the Southern Hemisphere Hadley cell. The ToD’s ability to detect subtle signals allows for assessing the realism of the CMIP warming pattern in this region. Significance Statement Recent studies emphasize the importance of the climate change warming pattern and its apparent discrepancy between climate models and observations in the equatorial Pacific. We argue that our newly proposed time of detection (ToD) is better suited than the well-known time of emergence (ToE) for investigating where modeled and observed warming patterns can be confidently compared. In agreement with previous studies, our analysis indicates model–observations disagreement over the equatorial Pacific. Using ToD instead of ToE allows for detecting a robust subdued warming (i.e., weaker than the tropical average) in the southeast Pacific and therefore confirms the realism of the CMIP warming pattern in this region.

Study of the Mental Health of the Elderly and Related Factors

Background: Aging and increase in the elderly population are the most important issues in recent years in developed countries and some developing countries. Mental health is one of the crucial aspects of elderly well-being and must be addressed to improve community health. This study is conducted to examine the mental health of the elderly and the related factors in Gorgan city, 2022. Methods: The present study is descriptive-analytical and was conducted using a two-stage cluster random sampling method. First, four comprehensive health service centers were selected as a cluster from among the centers of Gorgan city, and then 263 people were randomly selected from the chosen centers, proportionate to the number of registered elderly individuals in the electronic service system. The standard depression questionnaire for the elderly was utilized for assessment. Data were then entered into SPSS software version 18 and with descriptive and analytical statistical tests, including the Mann-Whitney test, Chi-square test, and logistic regression (The significance level was less than 0.05(. Results: A total of 263 elderly people were evaluated with a mean age of 68.64 ± 7.2 . 143 (54.4%) were male and 120 (45.6%) were female. The prevalence of depression was reported to be 27.8. The occurrence of depression was significantly associated with age, marital status, and the presence of underlying disease conditions (p < 0.05). However, gender, place of residence, and BMI did not show a statistically significant relationship with the occurrence of depression. Aging, underlying diseases, and not being married increase the chance of depression in the elderly. Conclusion: Although the prevalence of depression in the elderly is lower than the average of the whole country in this study, they are in a better condition. However, due to the fact that they are a special target group, as well as the various risk factors of the disease, including age, lack of marriage, and the presence of an underlying disease in this group, it is suggested that more appropriate planning be done to improve their mental health status.

Determinants of Domestic Violence during Pregnancy: A Case-Control Study

Background: Due to the importance of the issue and the fact that up-to-date studies in this topic have not been conducted in Yazd city, the present research was conducted to investigate and determine the intensity and frequency of domestic violence among pregnant women. Methods: This was a cross-sectional and descriptive study and sampling was done by simple random method. pregnant women referred to health centers in Yazd in 2021 participated in the study. For the study, 246 pregnant women were selected from 3 health centers in Yazd city in 2021. The tool used for the study was the standard questionnaire known as the Revised Conflict Tactics Scales (CTS2). This questionnaire was utilized to assess domestic violence, measures of dispute resolution, and demographic characteristics. After inputting the data into the SPSS version 26, Mann-Whitney and Kruskal-Wallis non-parametric statistical tests were used for data analysis. Results: The results showed that the average age of women was 31.47 ± 7.68 with a minimum age of 17 and a maximum of 55. The severity and frequency of the types of violence were measured, and the types of violence in the extreme state related to physical, mental, sexual, and verbal violence and resulting in physical injury were found to be 10%, 25%, 7%, 10%, and 19% respectively. Violence against pregnant mothers showed a significant relationship with the economic status of the family, the age of the mother's marriage, the education level of the parents, and the duration of their marriage (p<0.001). One of the most important variables affecting the severity and frequency of violence against pregnant women was the economic status of the family (p<0.001). Conclusion: The findings of this study show a connection between education level, economic status, and the prevalence of domestic violence. It is suggested to prioritize the development of diverse communication and problem-solving skills, as well as education related to family behavior on a wider scope.

Worse Clinical and Survival Outcomes in Breast Cancer Patients Living in Puerto Rico Compared to Hispanics, Non-Hispanic Blacks, and Non-Hispanic Whites from Florida.

Herein, we report the characterization of four cohorts of breast cancer patients including (1) non-Hispanic Whites in Florida, (2) non-Hispanic Blacks in Florida, (3) Hispanics in Florida, and (4) Hispanics in Puerto Rico. Data from female breast cancer patients were collected from cancer registry (n = 9361) and self-reported patient questionnaires (n = 4324). Several statistical tests were applied to identify significant group differences. Breast cancer patients from Puerto Rico were least frequently employed and had the lowest rates of college education among the groups. They also reported more live births and less breastfeeding. Both Hispanic groups reported a higher fraction experiencing menstruation at age 11 or younger (Floridian Hispanics [38%] and Puerto Ricans [36%]) compared to non-Hispanic Whites (20%) and non-Hispanic Blacks (22%). Non-Hispanic Black and Puerto Rican women were significantly older at breast cancer diagnosis than their non-Hispanic White and Floridian Hispanic counterparts. The Puerto Rican and non-Hispanic Black groups more frequently had pathology stage T2 or higher primary breast tumors at diagnosis (non-Hispanic Whites [29%], non-Hispanic Blacks [39%], Floridian Hispanics [33%], Puerto Ricans [46%]). The Puerto Rican (73%, 95% CI [66, 82]) and non-Hispanic Black (79%, 95% CI [75, 84]) groups demonstrate reduced 5-year survival compared to non-Hispanic Whites (89%, 95% CI [86, 92]) and Floridian Hispanics (89%, 95% CI [86, 90]). These findings demonstrate that Puerto Rican breast cancer patients suffer significant breast cancer health disparities relative to non-Hispanic Whites and Hispanics from Florida similar to the disparities observed for non-Hispanic Blacks. Future work must seek to better understand and address these disparities.

Validation of an interactive process mining methodology for clinical epidemiology through a cohort study on chronic kidney disease progression.

Process mining holds promise for analysing longitudinal data in clinical epidemiology, yet its application remains limited. The objective of this study was to propose and evaluate a methodology for applying process mining techniques in observational clinical epidemiology. We propose a methodology that integrates a cohort study design with data-driven process mining, with an eight-step approach, including data collection, data extraction and curation, event-log generation, process discovery, process abstraction, hypothesis generation, statistical testing, and prediction. These steps facilitate the discovery of disease progression patterns. We implemented our proposed methodology in a cohort study comparing new users of proton pump inhibitors (PPI) and H2 blockers (H2B). PPI usage was associated with a higher risk of disease progression compared to H2B usage, including a greater than 30% decline in estimated Glomerular Filtration Rate (eGFR) (Hazard Ratio [HR] 1.6, 95% Confidence Interval [CI] 1.4-1.8), as well as increased all-cause mortality (HR 3.0, 95% CI 2.1-4.4). Furthermore, we investigated the associations between each transition and covariates such as age, gender, and comorbidities, offering deeper insights into disease progression dynamics. Additionally, a risk prediction tool was developed to estimate the transition probability for an individual at a future time. The proposed methodology bridges the gap between process mining and epidemiological studies, providing a useful approach to investigating disease progression and risk factors. The synergy between these fields enhances the depth of study findings and fosters the discovery of new insights and ideas.

The effect of REACT model implementation on learning outcomes and critical thinking skills of students of SMAN 9 KENDARI

Quality human resources will be formed if education focuses on improving students’ skills. Of course, the foundation of education must be quality. Qualified human resources will later be responsible for making Indonesia a good country in all fields. This study aims to examine the effect of applying the REACT learning model (Relating, Experiencing, Applying, Cooperating, Transferring) on learning outcomes and critical thinking skills of students of SMAN 9 KENDARI. Quantitative research method with experimental research type. The research design used was post experimental control design. The research location was at SMAN 9 KENDARI. The instruments used include learning outcomes test and critical thinking skills test. The data obtained were explained using statistical tests to see the differences between the experimental group and the control group in chemistry subjects. The results showed that the application of REACT model significantly improved students’ learning outcomes and critical thinking skills compared to conventional learning methods in chemistry subjects. The findings indicated that the REACT model was effective in improving the quality of learning and developing critical thinking skills of students of SMAN 9 KENDARI, especially in chemistry learning.

Does the COVID-19 Vaccines Effect on the Menstrual Cycle, Cross-Sectional Study Among Adult Females at King Saud University

COVID-19 vaccinations have been associated with irregularities in the menstrual cycle and symptoms occurring pre and post-menstruation, affecting women’s reproductive health. This study aimed to demonstrate the impact of COVID-19 vaccines on women’s reproductive health by examining the association between COVID-19 vaccines and disturbed menstrual cycles. This cross-sectional survey-based study was conducted among adult females at King Saud University, Saudi Arabia, from April 2022 to August 2022. A total of 380 participants were selected through a stratified random sampling technique. Ethical approval was obtained from the Deanship of Scientific Research at King Saud University. The data were analysed using descriptive statistics and appropriate statistical tests. The results revealed that 53.9% of the participants experienced disturbances in the menstrual cycle after receiving the COVID-19 vaccination. Adult females aged 18-25 showed the highest rate of disorders. Menstrual disruptions were substantially correlated with marital status (p = 0.05), with a significant association between the number of COVID-19 vaccine doses and the occurrence of menstrual disturbances (p = 0.001). The administration of the vaccination during menstruation was linked to a notable occurrence of menstrual disturbances, although the p-value showed no statistical significance. A significant correlation was examined (p < 0.05) between pre-existing menstrual problems and the occurrence of disorders after receiving the COVID-19 vaccine (p < 0.05). The study emphasised the importance of tailored healthcare treatments for women following COVID-19 vaccination and the need for regular evaluation of reproductive health outcomes post-COVID-19 vaccination.

HPB SO78 - A Novel Application of ISGPS Guidelines for Calculating Pancreatic Fistula Rates Post-Distal Pancreatectomy

Abstract Background Post-operative pancreatic fistula (POPF) remains a major cause of morbidity and mortality following distal pancreatectomy and there is continual debate regarding the optimal peri-operative practice. The impact of drain displacement on outcome is poorly understood and limited information is documented on how the ISGPS guidelines are used to determine a clinically significant POPF. This study aims to assess the POPF and drain displacement rate at our institution and identify factors predicting a clinically significant POPF. We have proposed an algorithm to standardise the interpretation of the ISGPS guidelines. Method Case records of patients undergoing left sided pancreatectomy at our institution from January 2019 to January 2024 were analysed to assess the incidence of biochemical and clinically significant POPF using ISGPS criteria. Post operative CT scans were reviewed to record drain displacement with respect to the pancreatic stump. Continuous data was represented as mean +/- SD or median(IQR) depending on normality. Appropriate statistical tests were used for comparison of continuous and categorical variables (alfa error of 5%). Receiver operating characteristic curves were performed to assess the suitability of drain fluid amylase level as a predictor of clinically significant POPF. Results A total of 56 patients qualified for analysis. There was no difference between the clinically insignificant and significant groups with respect to age, gender, BMI, pathology and surgical technique (open/laparoscopic, splenic preservation, stump reinforcement). The clinically significant group had higher day three and peak drain amylase levels. The day of peak drain amylase was significantly later in this group. The drain displacement rate was 41% and did not differ significantly between the two groups. A day 3 drain fluid amylase level of 1120(U/L) had a 74% sensitivity of predicting a clinically significant POPF. Conclusion The ISGPS guidelines do not provide explicit criteria for stratifying the grade of POPF. We propose an algorithm to standardise the interpretation of these guidelines. Drain displacement did not impact POPF rate allowing for small sample size. Day 3 fluid amylase level is a useful predictor of clinically significant POPF. Program permission yes

Role of visual information in multimodal large language model performance: an evaluation using the Japanese nuclear medicine board examination.

This study aimed to assess the performance of state-of-the-art multimodal large language models (LLMs), specifically GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro, on Japanese Nuclear Medicine Board Examination (JNMBE) questions and to evaluate the influence of visual information on the decision-making process. This study utilized 92 questions with images from the JNMBE (2019-2023). The LLMs' responses were assessed under two conditions: providing both text and images and providing only text. Each model answered all questions thrice, and the most frequent answer choice was considered the final answer. The accuracy and agreement rates among the model answers were evaluated using statistical tests. GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro exhibited no significant differences in terms of accuracy between the text-and-image and text-only conditions. GPT-4o and Claude 3 Opus demonstrated accuracies of 54.3% (95% CI: 44.2%-64.1%) each when provided with both text and images; however, they selected the same options as in the text-only condition for 71.7% of the questions. Gemini 1.5 Pro performed significantly worse than GPT-4o under text and image conditions. The agreement rates among the model answers ranged from weak to moderate. The influence of images on decision-making in nuclear medicine is limited to the latest multimodal LLMs, and their diagnostic ability in this highly specialized field remains insufficient. Improving the utilization of image information and enhancing the answer reproducibility are crucial for the effective application of LLMs in nuclear medicine education and practice. Further advancements in these areas are necessary to harness the potential of LLMs as assistants in nuclear medicine diagnosis.

Fertiloscopy and its place in the gynaecologist's armamentarium.

Infertility is a prevalent issue worldwide. Current investigation of female pelvic infertility uses transabdominal laparoscopy, exposing patients to its associated risks. An alternative method is fertiloscopy, comprising hysteroscopy, tubal dye studies, and transvaginal hydrolaparoscopy (TVHL), falling under the broader category of VNOTES. This study reviews fertiloscopy cases in Australia to assess its role in managing infertility. Retrospective analysis of 76 cases was performed with review of imaging results, fertiloscopy findings and interventions, and fertility outcomes. Statistical analysis was conducted via R Studio v4.1 with means and averages used for descriptive data and a Kruskal-Wallis analysis of variance test used to evaluate differences in continuous variables. Kaplan-Meier curves were constructed to describe cumulative pregnancy incidence, with differences evaluated using log-rank tests. Statistical tests were two-tailed, and a P-value < 0.05 was considered significant. Of 76 cases, 70 underwent fertiloscopy and 35 an intra-operative intervention. Of the cohort, 53 conceived, 18 spontaneously. The highest chance of spontaneous conception was 44% by day 283. The failure rate of fertiloscopy was 5.3%, and complications occurred in 1.3% of cases. The highest chance of spontaneous conception post-fertiloscopy was 44% by day 283, possibly indicating the time between the procedure and referral to reproductive therapies. This study identified a low associated failure and complication rate, supporting fertiloscopy as a low-risk procedure. Despite limitations, this study highlights spontaneous pregnancy outcomes and associated low complication and failure rates, emphasising fertiloscopy's role in managing infertility in Australia as a lower risk surgical alternative to standard laparoscopy.

Abstract A051: Identifying patterns of cell-free DNA associated with elevated risk of diffuse large B-cell lymphoma in adult dogs

Abstract Background: Nonrandom patterns of cell-free DNA (cfDNA) are closely associated with malignancy. We hypothesize that they are also found in the systemic microenvironment that gives rise to cancer, and that such signatures can inform a risk stratification test. To achieve this, we have initiated the Lymphoma Risk Assessment (LyRA) study, using machine learning on a training set of dogs with known health status and a test set of otherwise healthy adult pet dogs to identify cfDNA signatures that are associated with elevated risk of developing diffuse large B- cell lymphoma (DLBCL). We will validate the predictive accuracy of these signatures, including the persistence of the risk environment and the interval between risk detection and development of clinical disease. Since cfDNA is the primary input of the LyRA test, we first performed a pilot study to assess how sample characteristics affect cfDNA quality and subsequent low-pass whole genome sequencing (WGS) data. Methods: Blood samples were collected from pet dogs with the owner’s informed consent. Paired samples were collected into potassium (K3)EDTA tubes and additive-free red top tubes (n = 5 dogs) or K3EDTA tubes and Cell-free DNA BCT® Streck Tubes (n = 6 dogs). Additional serum samples (n=3) were generously provided by the Morris Animal Foundation Golden Retriever Lifetime Study. cfDNA was isolated using the QIAamp® Circulating Nucleic Acid kit. Total cfDNA concentration was measured by PicoGreen™ and fragment distribution by Agilent High Sensitivity D500 ScreenTape® Assay, with comparisons made by starting material (plasma vs. serum) and collection tubes. Results: Serum had both higher total concentrations of cfDNA (PicoGreen™) and calibrated concentrations of long fragment cfDNA (515-658 bp Agilent traces) compared to plasma. In addition, total cfDNA concentrations increased with malignancy, following the pattern: no cancer &amp;lt; cancer &amp;lt; hematological cancer. Median fragment lengths of Agilent peaks also increased with malignancy for short (125-181 bp) and medium (340-425 bp) fragments, in both serum and plasma, but decreased for long fragments. In these pilot data the trends seen were consistent with our hypothesis and with prior studies, although due to sample size, no statistical testing was performed. Conclusions: The pilot study demonstrated that the effects of sample parameters on cfDNA quality are consistent with existing literature, validating our methods and supporting the rationale for the LyRA study. These features may prove valuable when integrated with genomic data to identify high-risk microenvironments. Recent research has shown that a majority of cfDNA in tumor patients originates from non-malignant cells and current methods often overlook potentially important patterns in this so-called 'discard cfDNA.' By focusing on these overlooked patterns, with an emphasis on risk stratification, the LyRA test could shift clinical management to a prevention-focused approach, serving as a model of testing and interception for DLBCL and other cancers in dogs, and potentially in humans. Citation Format: Lauren E Burt, Amy E Treeful, Mitzi Lewellen, Kimberly Demos-Davies, Andrea Chehadeh, Sara Pracht, Ashley J Schulte, Caitlin Feiock, Julia Medland, Davis Seelig, Kelly M Makielski, Ali Khammanivong, Antonella Borgatti, Michael S Henson, Michael Linden, Daniel Vallera, Gary R Cutter, Aaron L Sarver, Jaime F Modiano. Identifying patterns of cell-free DNA associated with elevated risk of diffuse large B-cell lymphoma in adult dogs [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A051.

OGC O02 - Measurement of functional, psychosocial, and quality of life impacts of Robotic versus Hybrid Oesophago-gastrectomy

Abstract Background Since the introduction of Robotic-Assisted Minimally-Invasive Oesophago-gastrectomy (RAMIO), comparisons to other surgical approaches have focussed primarily on peri-operative and oncological outcomes. Few studies have focused on quality-of-life measures once the patient has been discharged home. We sought to compare physical, psychosocial, sleep, pain and employment related measures at six weeks following discharge in patients undergoing RAMIO versus Hybrid Oesophago-gastrectomy. Method We performed a prospective cohort study comparing RAMIO and Hybrid Oesophago-gastrectomy. Twenty-five consecutive patients on a curative surgical pathway were recruited to each group. Participants were contacted via telephone pre-operatively and six weeks post-operatively. Parameters studied were: physical activity, social activity, sleep, pain control, and employment. Psychological wellbeing was measured using the Hospital Anxiety and Depression Scale, and quality of life with the European Organisation for Research and Treatment of Cancer questionnaires C30 (all cancer patients) and OG25 (patients undergoing oesophago-gastric cancer treatment). Results were analysed using Chi Square and Mann-Whitney-U statistical tests. Results There were no differences in age, ASA, or anaerobic threshold between study groups. At six weeks the RAMIO group was more likely than Hybrid to have returned to pre-operative physical and social activity (physical 7/25 vs. 1/25, p=0.04, social 13/25 vs. 5/25, p=0.03). The RAMIO group stopped regular analgesia earlier, and required fewer opiates. Patients were more likely to return to work in the RAMIO group (7/15 vs. 1/12,p=0.04). The RAMIO group had fewer cases of depression (2 vs. 9, p=0.03), lower QLQ C30 and OG25 scores, and reported higher overall health and quality of life scores (p=0.001). Conclusion We have demonstrated an improvement in physical and social activity, a faster return to work, a reduction in analgesia requirements, lower rates of depression and improved health and quality of life, six weeks post-operatively when comparing RAMIO to hybrid oesophago-gastrectomy. This study has highlighted additional considerations for the selection of surgical modality in oesophago-gastrectomy beyond peri-operative outcomes. Further investigation across a larger sample size and longer time frame to quantify the full spectrum of potential benefits of robotic oesophago-gastric surgery is warranted.

Nurses' models of spiritual care: Predictors of spiritual care competence.

Previous studies have shown that nurses' spiritual care competence is related to characteristics of personal spirituality, training adequacy, and comfort, confidence, and frequency of provision of spiritual care. However, these studies assumed that all participants understood spiritual care in the same way, and used self-ratings of spiritual care competence, which are problematic. Our previous study found that spiritual care was understood in 4 qualitatively different ways that can be arranged in order of competence. This study aimed to re-examine the relationships between nurse characteristics and spiritual care competence, using spiritual care understanding as a proxy for competence. Data was collected from a convenience sample of nurses who completed an anonymous, online survey. The survey provided qualitative data about what spiritual care means for them. The survey also provided quantitative data regarding nurse characteristics. This study created sub-groups of nurses based on their understanding of spiritual care, and used the quantitative data to construct a profile of nurse characteristics for each sub-group. Kruskal-Wallis statistical tests determined whether nurse characteristics differed across the 4 sub-groups. Spiritual care competence was not related to confidence or comfort in providing spiritual care. Relationships with spirituality, training adequacy, and frequency of provision of spiritual care were not linear; i.e., higher competence did not always correspond with higher scores of these characteristics. The results raise concerns about the construct validity of using comfort and confidence as estimates of spiritual care competence. That the relationships between competence and spirituality, training adequacy, and frequency of spiritual care provision was not as linear as portrayed in extant literature, suggests that outcomes of training may depend on the type of spiritual care understanding subscribed to by training participants. The findings offer insights about how nurses could achieve high levels of spiritual care performance.

Factors Related to Sleep Quality in Final Semester Pharmacy Students of Mandala Waluya University

Introduction: Sleep is a recovery process for the body and brain and is very important for achieving optimal health. Lack of sleep can cause students to become tired or easily tired, emotional instability, lack of self-confidence, excessive impulsiveness and carelessness. A preliminary study with 32 final year pharmacy students revealed that 32 said they experienced symptoms of irregular sleep patterns, stress, decreased appetite, anxiety and restlessness. Objective: This study aims to determine the relationship between stress, screen time, eating patterns and anxiety with sleep quality in final semester pharmacy students at Mandala Waluya University in 2024. Method: The type of research used in this research is quantitative with a cross sectional study design. The population in this study was 158 final semester pharmacy students at Mandala Waluya University. A sample of 62 respondents was obtained using simple random sampling techniques. The analysis method uses Fisher's Exact Test. Result: The statistical test results show that Stress obtained a value of p=0.004 and ? 0.05, namely 0.004 &lt; 0.05, Screen Time obtained a value of p=0.004 and ? 0.05, namely 0.004 &lt; 0.05, Eating Pattern obtained a value of p=0.001 and ? 0.05, namely 0.001 &lt; 0.05, and Anxiety obtained a value of p = 0.000 and ? 0.05, namely 0.000 &lt; 0.05. Conclusion: Suggestions for students are that they hope to be able to improve sleep quality well so that it does not hinder the lecture process, then for further research, it is highly recommended to use online questionnaires such as Google Forms or similar and use other variables such as disease, caffeine consumption and the environment.

Abstract B063: DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments

Abstract Background: Decoding the origins of cell-free DNA (cfDNA) released from dying cells in a liquid biopsy sample offers the potential to provide insight into the dynamic, organism-wide changes reflective of health and disease, making cfDNA an ideal target for serial, minimally invasive monitoring of disease-related changes. To this end, cell-type specific DNA methylation patterns offer a promising target to facilitate tissue of origin analysis, yet limited methods exist to identify differentially methylated regions that distinguish cell-types. Methods: We develop a robust differentially methylated marker region identification pipeline, DiMMER, that leverages cfDNA fragment level information of neighboring, co-regulated CpG sites on methylome-wide sequencing reads. Compared to prior methods that utilize simple heuristics in one-vs-all average methylation rate comparisons, we implement an individual pairwise statistical test procedure across all cell-types or groups under consideration. We assess the cell-specific nature of identified differentially methylated marker regions by generating in-silico mixtures from known cell-type of origin at each region, and calculating the area under the receiver operating characteristic curve (AUROC). We utilize our differentially methylated marker finding pipeline to identify melanocyte specific methylation marker regions and assess their functional role through annotations. We show these cell-specific regions are conserved in melanoma cell-lines and are distinct from the aberrant changes in a cancer context. Results: We identified the most cell-type specific differentially methylated marker regions across 24 distinct cell-type groups using our pipeline. Compared to a simpler one-vs-all heuristic, we demonstrate improved cell-type specificity evidenced by a higher AUROC on average. Using our pipeline we identified melanocyte-specific marker regions, which were commonly found in intronic and promoter regions of genes related to melanocyte development and differentiation. When comparing methylation patterns between melanocytes and melanoma cell-lines, we demonstrate melanocyte specific methylation marks are conserved through the transformation to malignant melanoma. Conclusion: As methylome-wide sequencing methods continue to rapidly develop and more cell-specific methylation data is generated, there is unmet need for more statistically robust differentially methylated marker finding tools. Here we present one such tool, DiMMER, and demonstrate the potential utility of identifying such regions to be used to assess organ-specific load as a measure of residual disease, as opposed to traditional circulating tumor DNA quanitification. Citation Format: Arthur P McDeed, Sidharth S Jain, Megan E McNamara, Amber Alley, Anton Wellstein, Jaeil Ahn. DiMMER: A robust computational pipeline for differential methylation marker evaluation in R of cell-free DNA fragments [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B063.