Risk Analysis Research Articles

Evaluation of Machine Learning Algorithms for Pressure Injury Risk Assessment in a Hospital with Limited IT Resources.

Clinical decision support systems for Nursing Process (NP-CDSSs) help resolve a critical challenge in nursing decision-making through automating the Nursing Process. NP-CDSSs are more effective when they are linked to Electronic Medical Record (EMR) Data allowing for the computation of Risk Assessment Scores. Braden scale (BS) is a well-known scale used to identify the risk of Hospital-Acquired Pressure Injuries (HAPIs). While BS is widely used, its specificity for identifying high-risk patients is limited. This study develops and evaluates a Machine Learning (ML) model to predict the HAPI risk, leveraging EMR readily available data. Various ML algorithms demonstrated superior performance compared to BS (pooled model AUC/F1-score of 0.85/0.8 vs. AUC of 0.63 for BS). Integrating ML into NP-CDSSs holds promise for enhancing nursing assessments and automating risk analyses even in hospitals with limited IT resources, aiming for better patient safety.

Assessment of groundwater suitability using water quality index and health risk analysis in upper catchment area of Kangsabati river, India

In the upper catchment area of the Kangsabati river basin, local people are highly dependent on groundwater for drinking purpose. The objectives of the present study are to assess the status of groundwater quality in this area and to examine the appropriateness of groundwater resource for drinking purpose in this region based on geochemical analysis. In this study, 20 sites have been selected to collect water samples from the four Community Development (CD) blocks under the study area amid the pre- and post-monsoon seasons during 2018, 2019, and 2020. A total of 13 hydro-chemical parameters have been selected to examine the groundwater quality status. In this study, the Water Quality Index (WQI) and Health Risk Analysis (HRA) have been applied to examine the health of groundwater resources and assess the non-carcinogenic risk to human health through the intake of fluoride-contaminated drinking water individually. The result reflects that the concentration of the selective hydro-chemical parameters has been accentuated from 2018 to 2020. The concentration of a few parameters like TH, Mg2+, K+, NO3–, and HCO3– has exceeded the desirable limit as per BIS guidelines. According to the WQI analysis, maximum groundwater samples (total of 12 samples) are categorized as poor, very poor, and not suitable for drinking purpose category. The outcomes of the HRA analysis reflect that local women are more vulnerable to the threats of fluoride contamination compared with male and children. The toxic agricultural and domestic effluents are considered vital factors in case of groundwater health deterioration in the study area.

Analyzing parametric influences driving age-associated changes in absorption using a PBPK-GSA approach

The advanced age population may be susceptible to an increased risk of adverse effects due to increased drug exposure after oral dosing. Factors such as high-interindividual variability and lack of data has led to poor characterization of absorption's role in pharmacokinetic changes in this population. Physiologically based pharmacokinetic (PBPK) models are increasingly being used during the drug development process, as their unique qualities are advantageous in atypical scenarios such as drug-drug interactions or special populations such as older people. Along with relying on various sources of data, auxiliary tools including parameter estimation and sensitivity analysis techniques are employed to support model development and other applications. However, sensitivity analyses have mostly been limited to localized techniques in the majority of reported PBPK models using them. This is disadvantageous, since local sensitivity analyses are unsuitable for risk analysis, which require assessment of parametric interactions and proper coverage of the input space to better estimate and subsequently mitigate the effects of the phenomenon of interest. For this reason, this study seeks to integrate a global sensitivity analysis screening method with PBPK models based in PK-Sim® to characterize the consequences of potential changes in absorption that are often associated with advanced age. The Elementary Effects (Morris) method and visualization of the results are implemented in R and three model drugs representing Biopharmaceutical Classification System classes I-III that are expected to exhibit some sensitivity to three age-associated hypotheses were successfully tested.

An integrated urban flooding risk analysis framework leveraging machine learning models: A case study of Xi'an, China

As global climate change intensifies and urbanization progresses, the frequency and extent of urban flooding have been increasing. This trend poses a significant threat to the safety and property of urban residents and severely impedes the advancement of sustainable development goals (SDGs). This study proposed an integrated urban flooding risk analysis framework to provide an essential basis for developing effective adaptation and mitigation measures. The kernel density estimation was adopted to analyze the distribution characteristics of urban flooding hotspots. The maximum entropy (MaxEnt) model was adopted for urban flooding risk probability assessment based on multi-source data. This study conducted an in-depth analysis from three perspectives including spatial analysis, risk planning and model comparison. The MaxEnt model and multiple exploratory spatial data analysis methods were combined to reveal spatial distribution patterns at grid cell scale. The MaxEnt and Zonation models were coupled to generate an urban flooding risk map. Further, six traditional machine learning models were compared with the MaxEnt model. The results indicate that rapid urbanization and intense human activities have significantly increased the number of buildings, leading to loss of previously existing blue and green spaces. These urban characteristics increase the vulnerability of cities to extreme rainfall. Compared to traditional machine learning models, the MaxEnt model has significant advantages. In the field of urban flooding risk, the MaxEnt model demonstrates significant potential for practical application. In summary, the framework empowers urban managers to comprehensively evaluate flooding risk in planning, supporting urban design and risk prevention.

Coordinated analysis of groundwater spatiotemporal chemical characteristics, water quality, and potential human health risks with sustainable development in semi-arid regions.

The emergence of large-scale time-series data and advancements in computational power have opened new avenues for analyzing the spatiotemporal evolution of groundwater chemistry, water quality, and human health risks. This paper utilizes hydrogeochemical methods to elucidate the controlling factors of water chemical components based on the test results of 124 groundwater samples collected from 31 monitoring wells in Fuxin City, Liaoning Province, China, from 2018 to 2021. By integrating the Random Forest and Enhanced Water Quality Index methods for water quality assessment and employing the Human Health Risk Assessment (HHRA) model to analyze human health risks, our findings indicate that the groundwater is mildly alkaline, with SO4·Cl-Ca·Mg and HCO3-Ca·Mg as the dominant hydrochemical types, primarily derived from the dissolution of carbonate and silicate minerals such as dolomite, limestone, and andesite, and cation exchange reactions. The EI_RF water quality evaluation model reveals that the overall water quality in the study area is poor, with Class I and II water quality zones mainly located in the northeastern and central parts of the study area, showing a gradual transition from Class I and II in the northeast to Classes IV and V in the southwest, significantly influenced by NO3-, TH, TDS, and SO42-. The HHRA model results indicate that the potential non-carcinogenic risk of groundwater nitrates has a severe impact on infants, with the spatial distribution being low in the northeast and high in the southwest. Due to industrial activities, agricultural practices, and population growth, certain areas in developing countries such as China and India exhibit nitrate concentrations significantly higher than those in most international regions, highlighting global environmental and public health challenges. This underscores the importance of enhancing groundwater monitoring and implementing measures to mitigate pollution. These research outcomes hold significant implications for the government in formulating rational protection and management measures to ensure the sustainable utilization of groundwater resources.

Health risk assessment of the concentrations of trace metals in some fruit juices from markets in Ghana

The study aimed to assess the risk exposure of processed fruit juices sold in Ghana by analyzing the concentrations of Cd, As, Ni, Hg, Cr and Pb. 27 processed fruit products were sampled from three markets and categorized based on packaging type. Heavy metals were quantified using Microwave Plasma Atomic Emission Spectroscopy (MPA-ES) The results showed that Cd was not detected in any of the samples, while the average measured concentrations of Ni, Pb, As, Cr and Hg were 0.186, 0.201, 0.299, 0.839 and 0.062 mg/L, respectively. Although Cr levels were within acceptable limits in most products, concentrations of Pb, Hg, As and Ni exceeded permissible levels in several samples. On average, canned products had higher metal concentrations than paper packs and bottles. Imported products also showed higher levels than locally processed items. Pollution assessment indicated low pollution load index below 1. Health risk analysis revealed potential non-carcinogenic risks associated with As, Cr and Hg intake, with a hazard index exceeding 1 in over 50 % of products. Cancer risk estimation showed concerning values for Cr in all samples and Pb in some products. toxic elements could pose health hazards to consumers of processed fruit juices sold on Ghanaian markets.

Can Opportunistic Use of Computed Tomography Help Reveal the Association Between Hepatic Steatosis and Disease Severity in Hospitalized COVID-19 Patients?

To measure hepatic steatosis (HS) in hospitalized COVID-19 patients using unenhanced chest computed tomography (CT) imaging and to evaluate the relationship between disease severity and prognosis in adult patients.This retrospective study included 152 consecutive hospitalized COVID-19 patients with a positive reverse transcriptase polymerase chain reaction (RT-PCR) test. The COVID-19 Reporting and Data System (CO-RADS) and the chest CT score were evaluated. HS measurements were performed based on CT images using a single region of interest placed on the right liver lobe (segments V-VII). HS was defined as a liver attenuation value <40 Hounsfield units. Data were collected and compared with the patients' prognostic parameters.Of the 152 inpatients, 137 patients (90.1%) had a CT score ≥3 and 109 patients (71.7%) had a CO-RADS score ≥4, 43 (28.2%) had HS. All patients with HS (100%) and 94/109 (86.2%) patients without HS had a CT score ≥3. There was a statistically significant difference between the two groups in terms of chest CT score (p=0.006). There was no statistically significant difference between the two groups in terms of CO-RADS score (p=0.291). The median CRP levels were significantly increased in patients with HS compared to patients without HS (p=0.023). There was no significant difference in ICU hospitalization and mortality due to the presence of HS (p>0.05).The current study revealed significantly higher chest CT scores in COVID-19 patients with HS measured on CT compared to those without HS. Opportunistic use of CT images for the detection of HS can be considered as an adjunctive tool in the risk analysis of COVID-19 patients hospitalized due to COVID-19 pneumonia.The severity of COVID-19 disease is increased in hospitalized patients with hepatosteatosis compared to patients with a normal liver. Density measurements for the evaluation of HS using opportunistic CT applications can be considered as an adjunctive tool in the prognostic evaluation of hospitalized patients with COVID-19 pneumonia. · Parlak AE, Erdem Toslak İ, Turkoglu Selcuk N. Can Opportunistic Use of Computed Tomography Help Reveal the Association Between Hepatic Steatosis and Disease Severity in Hospitalized COVID-19 Patients?. Fortschr Röntgenstr 2024; DOI 10.1055/a-2369-8377.

Individual-level social determinants of health and disparities in access to kidney transplant and waitlist mortality.

Comprehensive, individual-level social determinants of health (SDOH) are not collected in national transplant registries, limiting research aimed at understanding the relationship between SDOH and waitlist outcomes among kidney transplant candidates. We merged Organ Procurement and Transplantation Network data with individual-level SDOH data from LexisNexis, a commercial data vendor, and conducted a competing risk analysis to determine the association between individual-level SDOH and the cumulative incidence of living donor kidney transplant (LDKT), deceased donor kidney transplant (DDKT), and waitlist mortality. We included adult kidney transplant candidates placed on the waiting list in 2020, followed through December 2023. In multivariable analysis, having public insurance (Medicare or Medicaid), less than a college degree, and any type of derogatory record (liens, history of eviction, bankruptcy and/ felonies) were associated with lower likelihood of LDKT. Compared with patients with estimated individual annual incomes ≤ $30,000, patients with incomes ≥ $120,000 were more likely to receive a LDKT (sub distribution hazard ratio (sHR), 2.52; 95% confidence interval (CI), 2.03-3.12). Being on Medicare (sHR, 1.49; 95% CI, 1.42-1.57), having some college or technical school, or at most a high school diploma were associated with a higher likelihood of DDKT. Compared with patients with incomes ≤ $30,000, patients with incomes ≥ $120,000 were less likely to receive a DDKT (sHR, 0.60; 95% CI, 0.51-0.71). Lower individual annual income, having public insurance, at most a high school diploma, and a record of liens or eviction were associated with higher waitlist mortality. Patients with adverse individual-level SDOH were less likely to receive LDKT, more likely to receive DDKT, and had higher risk of waitlist mortality. Differential relationships between SDOH, access to LDKT, DDKT, and waitlist mortality suggest the need for targeted interventions aimed at decreasing waitlist mortality and increasing access to LDKT among patients with adverse SDOH.

Data-Informed Risk Analysis of Power Grids: Application of Method for Managing Heterogeneous Datasets

Abstract Power utilities are continuously set under high pressure to ensure the best performance of their grid. Nevertheless, power outages continue to be periodically observed ? for instance dure to vegetation in proximity of the power lines. The digitalization of our society offers new opportunities to acquire information relevant for the management of such problems. The access to more data sources also increases the pertinence of Dynamic Risk Analysis (DRA) and facilitates its implementation in power grid operations. However, the management of the considered datasets is a challenging task. In particular, it requires the definition of a comparison framework enabling to continuously and dynamically estimate the informative potential of those datasets. We address this problem by using a the Three-Phases Method to manage 17 different datasets originating from 12 different types of data sources. We look at how these datasets can inform eight parameters identified as impacting the probability of tree falls on power lines. For this, we calculate the informative potential of the datasets by applying a degradation factor due to spatiotemporal discrepancies and a degradation factor based on trust on the Default Maximum Potential of Knowledge (DMPK) provided by the data sources these datasets originate from. This enables to rank the datasets and select the one that best informs each of the parameters. We conclude that the approach used in the present work provides multiple opportunities for a more meaningful management of datasets in risk analysis, but also needs some adaptations to be implementable in an industrial context.

Analysis of interventional cardiological risk in emergency aid: Indications and procedures

Introduction: Interventional cardiology procedures require special preparation recommended in the form of a protocol for each service. It is understood that the need for this is an advance for the ICHS, mainly because anxiety and fear accompany patients. Objetives: The aim of this study is to carry out an up-to-date literature review on information about hemodynamics and interventional cardiology services. Material and Methods: The methodology used was a literature review. The health terminologies consulted in the Health Sciences descriptors (DeCS/BIREME) were used; information on Hemodynamics and Interventional Cardiology services. Results and Discussions: Hemodynamics and interventional cardiology is an area of cardiology that diagnoses and treats diseases of the heart and blood vessels using catheters. The Hemodynamics service is responsible for performing cardiac catheterization for the diagnosis and treatment of heart disease. The department performs the procedure on adults and children. Many patients are referred to the interventional cardiologist after an assessment with the clinical cardiologist. However, some go to the emergency department first because they have symptoms that could be considered serious, such as chest pain or even because they are already having a heart attack. Conclusions: Through procedures such as catheterization, angioplasty, intracoronary ultrasound, among others, interventional cardiology is a procedure without cuts, which allows patients to recover quickly. In this case, it can be used both to treat coronary artery disease, such as angina and heart attacks, as well as structural heart disease, such as problems with heart valves like severe aortic stenosis.

Analysis of Personal Privacy Risks and Protection Countermeasures under the Privacy Paradox Dimension

Analysis of Personal Privacy Risks and Protection Countermeasures under the Privacy Paradox Dimension

Social-Emotional Profiles of Preschool Children: An Investigation of Demographic Disparities and Intersectionality.

This study aims to enhance our understanding of the diverse nature of social-emotional development and explore the demographic disparities and intersectionality of social determinants among children, with an emphasis on underserved populations of children in low-resource environments. Young children living in low-income families are exposed to a wide array of social and systemic risks that increase the propensity for poor learning and social-emotional development. Using data from the Head Start Family and Childhood Experiences Survey (FACES, this study focuses on the social-emotional development of a nationally representative sample of young children enrolled in the Head Start program (n = 1921, 50.18% male). Employing a person-centered approach, we assessed teacher-rated social-emotional competence, including approach to learning, social cooperation, aggression, hyperactivity, and anxiety/depression/withdrawal, to classify young children's social-emotional development. This study identified four distinct social-emotional profiles-Adaptive, Average, Moderate Risk, and High Risk-through latent profile analysis. Furthermore, multinomial regression analysis revealed demographic disparities within each social-emotional profile, and significant intersectionality was found between race/ethnicity, age, and disability status in the social-emotional profiles. This research provides valuable insights for better supporting each child's unique needs.

Salivary Gland Neoplasm of Uncertain Malignant Potential (SUMP) (Milan IVB) and Its Subgroups: A Multi-Institutional Analysis of Risk of Neoplasm and Malignancy.

Fine needle aspiration (FNA) plays a crucial role in their initial assessment of salivary gland neoplasms. In the Milan System for Reporting Salivary Gland Cytopathology (MSRSGC), the category of Salivary Gland Neoplasm of Uncertain Malignant Potential (SUMP) categorizes lesions with ambiguous features. This study aims to investigate the risk of neoplasm (RON) and risk of malignancy (ROM) within different subgroups of SUMP lesions using data from three large academic institutions. We analyzed salivary gland (FNA) cases from three academic institutions post-MSRSGC implementation. Salivary gland FNA cases categorized as Milan IVB (SUMP) with subsequent surgical pathology follow-up were analyzed. Cases were divided into basaloid, oncocytic, and clear cell SUMP subtypes, with RON and ROM assessed and compared. Out of 1377 MSRSGC cases, 231 were SUMP (16.8%), with 101 subjected to surgical pathology follow-up. The overall ROM for SUMP was 20.8%, with variations of 10% to 29.5% observed amongst institutions, but no significant difference was observed among three institutions (p = 0.15). Basaloid and oncocytic SUMP displayed 17.1% and 20.5% ROM, respectively, without significant disparity. However, all clear cell SUMP cases were malignant on surgical resection. This study highlights the variability in ROM for SUMP lesions and the significantly higher ROM in SUMP cases with clear cell features. These findings emphasize the importance of accurately subcategorizing SUMP lesions, particularly those with clear cell features, for appropriate clinical management.

The role of marital status in gallbladder cancer: a real-world competing risk analysis

BackgroundThe association between marital status and gallbladder cancer (GBC) remains uncertain. This study aimed to verify the relationship between marital status and GBC and construct a prognostic nomogram to predict the impact of marital status on GBC patients.MethodGBC patients were divided into married and unmarried groups using data from the Surveillance, Epidemiology, and End Results (SEER) database. We employed competing risk analyses, propensity score matching (PSM), and Kaplan-Meier survival analyses. The relationship between marital status and GBC was then verified, and the predicted nomogram was constructed.ResultsA total of 3913 GBC patients were obtained from the SEER database, and an additional 76 GBC patients from Hangzhou Traditional Chinese Medicine Hospital were selected as the external validation group. The competing risk analysis revealed a significant disparity in the 5-year cumulative incidence of cancer-specific death (CSD) between the two cohorts (59.1% vs. 65.2%, p = 0.003). Furthermore, the multivariate competing hazards regression analysis identified a significant association (HR, 1.17; 95% CI, 1.04–1.31; p = 0.007) between marital status and CSD. To assess the 1-, 3-, and 5-year risks of CSD, a comprehensive competing event nomogram was constructed using factors derived from the multivariate analysis. The area under the receiver operating characteristic curve (AUC) values for the 1-, 3-, and 5-year training cohorts were 0.806, 0.785, and 0.776, respectively. In the internal validation cohort, these values were 0.798, 0.790, and 0.790, while the external validation cohort exhibited AUC values of 0.748, 0.835, and 0.883 for the corresponding time intervals. Furthermore, calibration curves demonstrated a commendable level of concordance between the observed and predicted probabilities of CSD.ConclusionMarriage was a protective factor for GBC patients after taking competing risk into consideration. The proposed nomogram demonstrated exceptional predictive power.

How ChatGPT defines risk?

Large Language Models (LLMs) are prominent AI tools potentially useful in various applications involving natural language interactions and exchanges of information with human users. These models, however, have the potential to spread misinformation and misconceptions, especially when used by individuals lacking the necessary expertise to critically assess their output. ChatGPT, developed by OpenAI, is a public available LLM and one of the most renowned. The paper explores whether the information it provides about the concept of risk and some related basic notions can be considered sufficiently correct. Specifically, ChatGPT was first utilized to build a glossary of basic concepts for the risk analysis field, modeled after that of the Society for Risk Analysis (SRA). The model was then used to assess the quality of the generated entries for clarity, precision, completeness and presence of examples, and to compare such entries to those of the SRA glossary again for quality and for semantic similarity. Independent ChatGPT user sessions were used throughout so as to avoid influencing one output by the previous ones. The results suggest that, while the SRA and ChatGPT entries may differ in focus and scopes, they share a common core and do not conflict in substantial ways. Therefore, we can develop the working hypothesis that ChatGPT does not promote major misconceptions as to the foundational definitions about risk, at least with respect to those provided by the SRA.

Post-Kidney Transplant Cancer: A Real-World Retrospective Analysis From a Single Italian Center.

We describe the epidemiology of cancer after kidney transplantation (KTx), investigating its risk factors and impact on therapeutic management and survival in KTx recipients (KTRs). The association between modification of immunosuppressive (IS) therapy after cancer and survival outcomes was analyzed. We collected data from 930 KTRs followed for 7 [1-19]years. The majority of KTRs received KTx from a deceased donor (84%). In total, 74% of patients received induction therapy with basiliximab and 26% with ATG. Maintenance therapy included steroids, calcineurin inhibitors, and mycophenolate. Patients with at least one cancer (CA+) amounted to 19%. NMSC was the most common tumor (55%). CA+ were older and had a higher BMI. Vasculitis and ADPKD were more prevalent in CA+. ATG was independently associated with CA+ and was related to earlier cancer development in survival and competing risk analyses (p = 0.01 and <0.0001; basiliximab 89 ± 4 vs. ATG 40 ± 4months). After cancer diagnosis, a significant prognostic impact was derived from the shift to mTOR inhibitors compared to a definitive IS drug suspension (p = 0.004). Our data confirm the relevance of cancer as a complication in KTRs with ATG as an independent risk factor. An individualized choice of IS to be proposed at the time of KTx is crucial in the prevention of neoplastic risk. Finally, switching to mTORi could represent an important strategy to improve patient survival.

Contamination levels of water sources and the associated nitrate health risks to six age groups

Advancements in health risk assessment are vital for protecting public health. This study’s objectives were to analyze the degree of nitrate contamination, the multi-route health risks to six age groups, and the potential sources of water contaminants in a Nigerian suburban area. Nitrate pollution index (NPI) results were between −1.00 and 0.06, indicating low human impact. According to the nitrate health risk analysis, infants between the ages of 6 and 12 months were more vulnerable, whereas humans between the ages of 20 and > 60 have lower risks. This may be due to the fact that infants have bodily tissues that are more vulnerable to potentially toxic contaminants. For all six age categories, the risk associated with ingestion was greater than the risk associated with dermal contact. Varimax-rotated factor analysis with five principal component extractions revealed that the sources of the water contaminants varied from geogenic processes to human-initiated activities.

Slope stability assessment and landslide susceptibility mapping in the Lesser Himalaya, Mussoorie, Uttarakhand

The present study aims to assess slope stability and landslide susceptibility mapping of road-cut slopes along Mussoorie road in the Lesser Himalayan region. A total of 18 suspected unstable slope sites were selected for the investigation, and performed geo-mechanical classification techniques, including Rock Mass Rating (RMR), Slope Mass Rating (SMR), Geological Strength Index (GSI), and kinematic analysis. For the Landslide susceptibility mapping, the Frequency Ratio (FR) method was employed using the weightage of various causative factors which includes slope, aspect, curvature, elevation, distance from streams, distance from lineaments, lithology, and rainfall. The finding indicates that out of 18 selected slopes, 4 slopes are bad slope or unstable, which includes slope 3,4 and 6 in the lower part of the Mussoorie area near Jharipani, while slope 10 near Hathi Paon-Mussoorie Road is also unstable. The slopes around Junu waterfall are stable. Partially unstable slopes may vulnerable to slope failure in the future due to heavy rainfall and unstructured construction. Additionally, the Area Under Curve (AUC) and predictive rate curve values are 61% and 78% respectively, indicating acceptable overall accuracy. This study highlights the landslide issues in Mussoorie region due to rapid urbanization & climate change and demonstrates the effectiveness of the employed methods for future risk analysis.

Quick Introduction into the General Framework of Portfolio Theory

This survey offers a succinct overview of the General Framework of Portfolio Theory (GFPT), consolidating Markowitz portfolio theory, the growth optimal portfolio theory, and the theory of risk measures. Central to this framework is the use of convex analysis and duality, reflecting the concavity of reward functions and the convexity of risk measures due to diversification effects. Furthermore, practical considerations, such as managing multiple risks in bank balance sheets, have expanded the theory to encompass vector risk analysis. The goal of this survey is to provide readers with a concise tour of the GFPT’s key concepts and practical applications without delving into excessive technicalities. Instead, it directs interested readers to the comprehensive monograph of Maier-Paape, Júdice, Platen, and Zhu (2023) for detailed proofs and further exploration.

An Approach to Reduce the Incidence of Submarine Medical Evacuations by Identifying Individual Risk Characteristics: Preliminary Findings.

Military medical evacuations (MEDEVACs) are resource intensive and can disrupt operations and decrease readiness. Medical evacuations are a concern for the submarine force because of the limited medical resources onboard, the impact of manpower loss on smaller crews, and the compromise of operational stealth. Although some medical emergencies cannot be avoided, some MEDEVACs may be preventable. However, there is limited knowledge of the underlying causes and risk factors associated with submarine MEDEVACs. This work describes an approach to identify individual characteristics associated with submarine MEDEVACs by presenting preliminary results and next steps. Identifying those most at risk for a MEDEVAC will foster prevention strategies that lead to fewer MEDEVACs, military operation disruptions, missed work and limited duty days, unplanned losses, early separations, and disability compensation claims among navy submariners. This retrospective study examines MEDEVACs from U.S. Navy submarines from January 1, 2012 to December 31, 2020. Medical evacuation causes were classified by 3 major diagnostic categories: Injury, psychiatric, and medical (i.e., all other non-injury medical events, including dental issues). Diagnostic subcategories were grouped by body region (for injuries) and body system (for non-injuries). Identifiable information from MEDEVAC records were linked to personnel files to capture demographic and occupational variables. Trends across the years were examined, and frequencies and percentages of MEDEVAC cases by both major and sub-diagnostic categories were presented. For cases where both the major diagnostic categories and characteristics were both available, we assessed associations between major diagnostic categories and demographic and occupational characteristics, using Pearson's χ2 test for proportions and Fisher Freeman-Halton exact tests. Pairwise z-tests for proportions were used to determine which proportions differed significantly. A total of 1,283 MEDEVACs were confirmed from 2012 to 2020, with an annual average of 143. Across the years, 24.3% were caused by psychiatric issues (e.g., suicidal ideation), 18.4% were caused by injuries (e.g., blunt trauma), and the remaining 57.3% were caused by other medical emergencies (e.g., gastrointestinal issues). Among the cases linked to personnel files, the major diagnostic category was associated with age, rank, department, and submarine qualification status (group size varied). By age (n = 973), large differences in MEDEVAC causes were seen among submariners 21 to 25 years old who represented 52.4% of psychiatric versus 37.5% of medical MEDEVACs. In contrast, those 35 and older represented 17.0% medical versus 2.7% psychiatric MEDEVACs. Medical, non-injury cases were the most common cause for a MEDEVAC. There were proportionately more psychiatric than medical cases among younger, less experienced submariners. Conversely, there were proportionately more medical than psychiatric cases among older submariners. A centralized approach to collecting MEDEVAC data is needed. This is the most comprehensive study examining risk factors associated with submarine MEDEVACs. Follow-on work will include adding prior medical waiver requests, health indicators, and confirmed diagnoses to the dataset to conduct a risk analysis. Considering submarines have smaller crews than most surface ships, limited medical assets, and often operate in austere environments, examination of submarine MEDEVACs should be distinct from other navy and military MEDEVACs.