National Longitudinal Database Research Articles

Chronic Use of Prescription Pain Medication and Outcomes in Patients With Burn Injury: A Burn Model System National Database Study.

This study attempts to examine long-term pain medication usage after burn injury and its association with functional and psychosocial outcomes. This is a multicenter retrospective cohort study utilizing the Burn Model System National Longitudinal Database. Participants injured from 2015 to 2021 were divided into two groups, those taking and not taking prescription pain medication at 12 mos after injury. Regression analyses examined associations between pain medication use and outcomes at 12 mos, adjusting for demographics, burn size, length of hospital stay, and preinjury pain medication use and employment status. Outcomes included VR-12 Physical and Mental Component Summary scores Patient-Reported Outcomes Measurement Information System Anxiety and Depression scores, Satisfaction with Life Scale, and employment status. Of 358 participants analyzed, prescription pain medication use was associated with worse outcomes at 12 mos: Physical Component Summary (β = -7.11, P < 0.001), Mental Component Summary (β = -6.01, P < 0.001), and Patient-Reported Outcomes Measurement Information System Depression (β = 4.88, P < 0.001) and Anxiety (β = 6.16, P < 0.001). Satisfaction with Life Scale was not significantly associated with pain medication use ( P = 0.069) and those taking pain medication were 52% less likely to be employed at 12 mos ( P = 0.035). There is a significant association between prescription pain medication use and worse physical, mental, and employment outcomes at 12 mos after burn injury.

Physical and psychosocial outcomes among burn-injured people with heterotopic ossification: A burn model system study

IntroductionHeterotopic ossification (HO), or ectopic bone formation in soft tissue, is a not so rare and poorly understood debilitating sequela of burn injury. Individuals developing HO following burn injuries to their hands often experience reductions in mobility, significant contractures, and joint pain. This study identifies demographic characteristics of individuals who develop HO and compares their physical and psychosocial outcomes to the general burn population. MethodsParticipant demographics, injury characteristics, and PROMIS-29 scores across three time points (discharge, six- and 12- months after injury) were extracted from the Burn Model System National Longitudinal Database representing participants from 2015–2022. Mixed-effects linear regression models were used to compare PROMIS scores across all three longitudinal measurements. Models were adjusted for age, sex, race/ethnicity, HO status, and burn size. ResultsOf the 861 participants with data concerning HO, 33 were diagnosed with HO (3.8% of participants). Most participants with HO were male (n = 24, 73%) and had an average age of 40 + /− 13 years. Participants with HO had significantly larger burn size (49 +/−23% Total Body Surface Area (TBSA)) than those without HO (16 +/−17%). Participants with HO reported significantly worse physical function, depression, pain interference and social integration scores than those without HO. After adjusting for covariables, participants with HO continued to report statistically significantly worse physical function than those without HO. Although physical functioning was consistently lower, the two populations did not differ significantly among psychosocial outcome measures. ConclusionsWhile HO can result in physical limitations, the translation to psychosocial impairments was not evident. Targeted treatment of HO with the goal of maximizing physical function should be a focus of their rehabilitation. Level of Evidence2b Type of StudySymptom Prevalence Study

Comparison of Postdischarge Outcomes Between Valve-in-Valve Transcatheter Mitral Valve Replacement and Reoperative Surgical Mitral Valve Replacement

Limited data are available comparing the postdischarge perioperative outcomes of isolated valve-in-valve transcatheter mitral valve replacement (VIV-TMVR) versus surgical reoperative mitral valve replacement (re-SMVR) on a nationwide scale. The objective of this study was to perform a robust head-to-head assessment of contemporary postdischarge outcomes between isolated VIV-TMVR and re-SMVR using a large national multicenter longitudinal database. Adult patients aged ≥18years with failed/degenerated bioprosthetic mitral valves who underwent either isolated VIV-TMVR or re-SMVR were identified in the 2015 to 2019 Nationwide Readmissions Database. The risk-adjusted differences in 30-, 90-, and 180-day outcomes were compared using propensity score weighting with overlap weights to mimic the results of a randomized controlled trial. The differences between a transeptal and transapical VIV-TMVR approach were also compared. A total of 687 patients with VIV-TMVR and 2,047 patients with re-SMVR were included. After the overlap weighting to attain balance between treatment groups, VIV-TMVR was associated with significantly lower major morbidity within 30 (odds ratio [95% confidence interval (CI)] 0.0.31 [0.22 to 0.46]), 90 (0.34 [0.23 to 0.50]), and 180 (0.35 [0.24 to 0.51])days. The differences in major morbidity were primarily driven by less major bleeding (0.20 [0.14 to 0.30]), new onset complete heart block (0.48 [0.28 to 0.84]) and need for permanent pacemaker placement (0.26 [0.12 to 0.55]). The differences in renal failure and stroke were not significant. VIV-TMVR was also associated with shorter index hospital stays (median difference [95% CI] -7.0 [4.9 to 9.1]days) and an increased ability for patients to be discharged home (odds ratio [95% CI] 3.35 [2.37 to 4.72]). There were no significant differences in total hospital costs; in-hospital or 30-, 90-, and 180-day mortality; or readmission. The findings remained similar when stratifying the VIV-TMVR access using a transeptal versus a transapical approach. The changes in outcomes over time suggest marked improvements for patients with VIV-TMVR relative to stagnant results for patients with re-SMVR from 2015 to 2019. In this large nationally representative cohort of patients with failed/degenerated bioprosthetic mitral valves, VIV-TMVR appears to confer a short-term advantage over re-SMVR in terms of morbidity, discharge home, and length of stay. It yielded equivalent outcomes for mortality and readmission. Longer-term studies are needed to assess further follow-up beyond 180days.

Identification of Factors Associated With 30-Day Readmissions After Posterior Lumbar Fusion Using Machine Learning and Traditional Models: A National Longitudinal Database Study.

Retrospective cohort study. To identify factors associated with readmissions after PLF using machine learning and logistic regression (LR) models. Readmissions following posterior lumbar fusion (PLF) place significant health and financial burden on the patient and overall healthcare system. The Optum Clinformatics® Data Mart database was used to identify patients who underwent posterior lumbar laminectomy, fusion, and instrumentation between 2004 and 2017. Four machine learning models and a multivariable LR model were used to assess factors most closely associated with 30-day readmission. These models were also evaluated in terms of ability to predict unplanned 30-day readmissions. The top performing model (Gradient Boosting Machine; GBM) was then compared to the validated LACE index in terms of potential cost savings associated with implementation of the model. A total of 18,981 patients were included, of which 3,080 (16.2%) were readmitted within 30 days of initial admission. Discharge status, prior admission, and geographic division were most influential for the LR model, while discharge status, length of stay, and prior admissions had greatest relevance for the GBM model. GBM outperformed LR in predicting unplanned 30-day readmission (mean AUC 0.865 vs. 0.850, P<0.0001). Use of GBM also achieved a projected 80% decrease in readmission-associated costs relative to those achieved by the LACE index model. Factors associated with readmission vary in terms of predictive influence based on standard logistic regression and machine learning models used, highlighting the complementary roles these models have in identifying relevant factors for prediction of 30-day readmissions. For posterior lumbar fusion procedures, Gradient Boosting Machine yielded greatest predictive ability and associated cost savings for readmission. 3.

Investigation of Schatzki Rings with Eosinophilic Esophagitis using Nationwide Database

Eosinophilic Esophagitis (EoE) is the most common cause of food impaction. In this retrospective multicenter study, we investigated the incidence and risk factors for Schatzki rings (SRs) using Cerner Health Facts, a national longitudinal database representing 519 million patient encounters.

HEALTH SURVEILLANCE OF PERSONS LIVING WITH DEMENTIA AND CAREGIVER DYADS

Abstract The relationship between individuals living with dementia and their caregivers is important and can impact their dementia journey. However, limited national longitudinal data exists about the caregiver-person living with dementia dyad. Availability of such data would provide important information about joint trajectories and help to better identify the needs of caregivers and persons living with dementia across the dementia journey. The objective of this study was to develop a linked national longitudinal database of persons living with dementia and their caregivers. The Canadian Primary Care Sentinel Surveillance Network (CPCSSN) extracts and de-identifies clinical data from electronic medical records (EMR) from approximately 2 million patients across Canada. CPCSSN data is used to identify persons living with dementia and caregivers willing to participate in the study. CPCSSN data from participating dyads are linked (e.g., chronic and mental health conditions, diagnoses, laboratory test results) and additional information about the experiences of persons living with dementia and their caregivers (e.g., ethnicity, amount and type of care provided, burden, availability of support) are collected yearly using surveys. The growing database contains linked, de-identified, comprehensive information about persons living with dementia and their caregivers that will become a rich source of data for researchers, clinicians, and policymakers. Specifics around how the database was developed, and lessons learned will be discussed as these findings can be used as a template to develop similar linked health surveillance databases.

AUTOIMMUNE DISEASE BURDEN IN CHILDREN WITH EOSINOPHILIC ESOPHAGITIS: A NATIONWIDE LONGITUDINAL STUDY.

<h3>Introduction</h3> Eosinophilic Esophagitis (EoE) is a chronic immune mediated disorder involving eosinophils leading to esophageal dysfunction. In this retrospective multi-center study, we investigated the incidence and risk factors for comorbid autoimmune diseases (AiD) in children using Cerner Health Facts, a national longitudinal database representing approximately 69 million patients. <h3>Methods</h3> All patients under 18 years of age with EoE were included in our analysis. Patient characteristics were evaluated as potential risk factors for comorbid AiD using multivariable regression built using all variables with p<0.05 on univariable analysis. <h3>Results</h3> We identified 6,285 patients with EoE. Mean age was 9.41±5.04 years, 32.04% (2,014) were female. In terms of race, 75.27% (4,731) were white and 11.81% (742) were African American. Overall, 7.0% (440/6,285) of children with EoE had at least one comorbid AiD. The most common AiD in those with EoE was ulcerative-colitis (143) followed by celiac (116) and autoimmune-thyroid disease (89). On multivariable regression, the factors associated with a higher risk of AiD included type-2 diabetes (odds-ratio (OR) 4.46), steroid use (OR 3.51), long-term medication use (OR 2.42), and digestive disorders (OR 1.85). African American race decreased the risk of AiD (OR 0.64). <h3>Conclusion</h3> We utilized a national database of patients with diag nosed EoE to identify the incidence and risk factors for AiD. Ulcerative colitis, celiac, and autoimmune thyroid disease were the most common AiD comorbid with EoE. The greatest risk factor for AiD was type-2 diabetes. Given that nearly 7% of identified EoE patients had comorbid AiD, careful evaluation for AiD in EoE setting may be warranted. We compared patient characteristics and variables of interest between the cohorts of patients with and without comorbid AiD using the chi-squared test for categorical variables, the t-test for normally distributed continuous variables, and the Mann-Whitney U test for non-normally distributed continuous variables. Factors with p<0.05 on univariable analysis were included in multivariable regression model. Statistical significance was defined as p<0.05. Independent risk factors for comorbid AiD were presented as adjusted Odds Ratios with 95% Confidence Intervals. All analyses were performed using SAS version 9.4 (SAS Institute, Cary, North Carolina).

3.7 Prevalence and Risk Factors for the Development of ADHD in Patients with Childhood Trauma

ADHD is the most common mental health disorder among children. We aim to investigate incidence, characteristics, and risk factors for ADHD in patients diagnosed with childhood trauma (CT) using Cerner Health Facts, a national longitudinal database representing approximately 69 million patients.

The Effect of Distance to Treatment Center on Long-Term Outcomes of Burn Patients.

Geospatial proximity to American Burn Association (ABA)-verified burn centers or self-designated burn care facilities varies across the country. This study evaluates the effect of distance to treatment center on long-term, patient-reported outcomes. Data from the Burn Model System (BMS) National Longitudinal Database were analyzed. Demographic and clinical data were compared between three cohorts stratified by distance to BMS center (<20, 20-49.9, ≥50 miles). Distance to BMS center was calculated as driving distance between discharge and BMS center ZIP code centroids. The following patient-reported outcomes, collected at 12-months follow-up, were examined: Veterans RAND 12-Item Health Survey (VR-12), Satisfaction with Life (SWL) scale, employment status, and days to return to work. Mixed model regression analyses were used to examine the associations between distance to BMS center and each outcome, controlling for demographic and clinical variables. Of 726 patients included in this study, 26.3% and 28.1% were <20 and between 20 and 49.9 miles to a BMS center, respectively; 46.6% were ≥50 miles to a BMS center. Greater distance was associated with white/non-Hispanic race/ethnicity, preinjury employment, flame injury, and larger burn size (P < .001). Regression analyses did not identify significant associations between distance to BMS center and any patient-reported outcomes. This study suggests that patients treated at BMS centers have similar long-term, patient-reported outcomes of physical and psychosocial function, as well as employment, despite centralization of burn care and rehabilitation services. Given a steady decline in the incidence of burn injury, continued concentration of key resources is logical and safe.

Impact of community-level socioeconomic disparities on quality of life after burn injury: A Burn Model Systems Database study

IntroductionIndividual-level socioeconomic disparities impact burn-related incidence, severity and outcomes. However, the impact of community-level socioeconomic disparities on recovery after burn injury is poorly understood. As a result, we are not yet able to develop individual- and community-specific strategies to optimize recovery. Therefore, we aimed to characterize the association between community-level socioeconomic disparities and long-term, health-related quality of life after burn injury. MethodsWe queried the Burn Model System National Longitudinal Database for participants who were> 14 years with a zip code and who had completed a health-related quality of life (HRQOL) questionnaire (VR-12) 6 months after injury. BMS data were deterministically linked by zip code to the Distressed Communities Index (DCI), which combines seven census-derived metrics into a single indicator of economic well-being, education, housing and opportunity at the zip code level. Hierarchical linear models were used to estimate the association between community deprivation and HRQOL 6 months after burn injury, as measured by mental (MCS) and physical (PCS) component summary scores of the SF12/VR12. Results342 participants met inclusion criteria. Participants were mostly male (n = 239, 69 %) and had a median age of 48 years (IQR 33–57 years). Median %TBSA was 10 (IQR 3–28). More than one-third of participants (n = 117, 34 %) lived in a community within the highest two distress quintiles. After adjusting for age, race/ethnicity, number of trips to the operating room (OR) and pre-injury PCS, neighbourhood distress was negatively associated with 6-month PCS (ß-0.05, 95 % CI [−0.09,−0.01]). Increasing age and lower pre-injury PCS were also negatively associated with 6-month PCS. There was no observed association between neighbourhood distress and 6-month MCS after adjustment for age, participant race/ethnicity, number of trips to the OR and pre-injury MCS. Higher pre-injury MCS was associated with 6-month MCS (ß0.54, 95 % CI [−0.41,0.67]). ConclusionsCommunity distress is associated with lower PCS at 6 months after burn injury but no association with MCS was identified. Pre-injury HRQOL is associated with both PCS and MCS after injury. Further study of the factors underlying the relationship between community distress and physical functional recovery (e.g., access to rehabilitation services, availability of adaptations) is required to identify potential interventions.

Impacts of Financial Assistance on Quality of Life Among People Living With Burn Injury: Matched Cohort Analysis of the National Institute on Disability, Independent Living and Rehabilitation Research Burn Model System Database.

Disparities in socioeconomic status and minority status affect the risk of burn injury and the severity of that injury, thus affecting the subsequent cost of care. We aimed to characterize the demographic details surrounding receipt of financial assistance due to burn injury and its relationship with health-related quality of life scores. Participants ≥18 from Burn Model System National Longitudinal Database (BMS) with complete demographic data were included (n = 4330). Nonresponders to financial assistance questions were analyzed separately. The remaining sample (n = 1255) was divided into participants who received financial assistance because of burn injury, those who received no financial assistance, and those who received financial assistance before injury and as a result of injury. A demographic and injury-characteristic comparison was conducted. Health-related quality of life metrics (Satisfaction with Life, Short Form-12/Veterans RAND 12-Item Health Survey, Community Integration Questionnaire Social Component, and the Post-Traumatic Growth Inventory) were analyzed preinjury, then 6-months, 1-year, and 2-years postinjury. A matched cohort analysis compared these scores. When compared to their no financial assistance counterparts, participants receiving financial assistance due to burns were more likely to be minorities (19% vs 14%), have more severe injuries (%TBSA burn 21% vs 10%), and receive workers' compensation (24% vs 9%). They also had lower health-related quality of life scores on all metrics except the post-traumatic growth inventory. Financial assistance may aid in combating disparities in posttraumatic growth scores for participants at the greatest risk of financial toxicity but does not improve other health-related quality of life metrics.

Risk factors for development of severe gastrointestinal dysmotility in patients with systemic sclerosis

Abstract Background Systemic Sclerosis (SSc) is an autoimmune condition of unknown etiology. We aim to investigate incidence, characteristics, and risk factors for gastrointestinal (GI) dysmotility in patients diagnosed with SSc using Cerner HealthFacts, a national longitudinal database representing approximately 69 million patients. Methods All patients over 18 years of age with SSc were included in our analysis. Incidence of GI dysmotility was identified using ICD coding. Patient characteristics were evaluated as potential risk factors for development of GI dysmotility using multivariable regression built using all variables with p&amp;lt;0.1 on univariable analysis. Results Overall, 0.4% (58/13,930) of patients with SSc developed GI dysmotility. Mean age was 57.23±15.22 years and 16% (2,228/13,930) were male and 86.1% (11,502/13,930) were female. In terms of race, 70.15% (9,772/13,930) were white and 14.82% (2,064/13,930) were African American. 92.51% (12,886/13,930) received care at an acute care facility and 81.51% (11,354/13,930) received care at an urban facility. The variables which conferred the highest odds of developing GI dysmotility included presence of hepatic comorbidities (OR 2.35), digestive comorbidities (OR 6.8), muscular dystrophy (OR 569.2), and Raynaud (OR 1.98). In univariable analysis and multivariable regression with 95% CI; 4 variables were predictive for GI dysmotility, and none were protective against GI dysmotility. Conclusions In this longitudinal national database study of patient with diagnosed SSc - hepatic, digestive comorbidities, muscular dystrophy, and Raynaud were noted to be associated with high risk of developing GI dysmotility. Careful evaluation and follow up is advised for SSc patients. Supported by None

78 Classification and Regression Tree Model for Predicting Satisfaction with Life Scale Scores After Burn Injury

IntroductionCurrent early burn care prognostication models predict in-hospital mortality (e.g., revised Baux Score). However, patients, families and clinicians need more holistic tools in the hours and days after injury to identify specific factors that might affect their quality of life and indicate a need for more intensive services. This project aims to predict Satisfaction with Life (SWL) in survivors of burn injury using patient, injury, and care factors available within 24 hours of admission.MethodsTwo hundred and fourteen participants were identified from a multicenter national longitudinal database and merged with clinical data from a single institution's trauma registry. Patients were randomized into a training dataset (80%) and a testing dataset (20%). A CART algorithm was used to examine the relative contributions of individual predictor variables in classifying low SWL at six-month follow up (SWL ≤ 20). Seventeen covariables obtained within 24 hours of index hospital admission were analyzed from five domains: demographics, comorbidities, injury, care, and host response to injury. Lab values were those closest to but not greater than 24 hours after index hospital admission.ResultsMultiple covariables contributed to the SWL score. CART analysis selected a pre-injury SWL score < 31 as the first node and strongest indicator of low SWL. CART then selected the following subgroups at risk for SWL ≤ 20 at 6 months: (1) hematocrit >55%; (2) lactate >4 mmol/L, age > 59; (3) total body surface area (TBSA) burned >30%, presence of a hand, neck, and/or face burn. The cross-validated predictive accuracy of the CART model was 69.4% with a cross-validated relative error of 0.379. In the validation data set, sensitivity and specificity were 62.5% and 72.0%, respectively.ConclusionsThe findings demonstrate the potential feasibility of creating a model that can predict a clinically meaningful quality of life outcome using covariables gathered within hours of hospital admission after burn injury. Predictive measures suggest that while some of the included covariables may be associated with SWL, they are not consistently and reliably predictive of low SWL alone. With more data and additional refined inputs, a similar model could be used to identify those in need of more intensive services earlier on in the hospitalization.

27 Pain Medication Use at Follow up Is Associated with Long-term Outcomes

IntroductionUse of prescription pain medication after burn injury is commonly required. However, little is known about long-term pain medication use and its association with outcomes. Therefore, the purpose of this study is to assess patterns of prescription pain medication use after discharge and the association between these medications and quality of life outcomes.MethodsData from the Burn Model System National Longitudinal Database (2015-2021) were analyzed. Pain medication use was assessed at pre-injury (recall at discharge), discharge (medical record) and follow-up (self-report at 6, 12, and 24 months after injury). Outcome measures included: VR-12 Physical and Mental Component Summary scores (PCS and MCS), Community Integration Questionnaire (CIQ), Posttraumatic Stress Disorder Checklist (PCL), Satisfaction with Life Scale (SWLS), and NeuroQOL Stigma. The population was divided into two groups, those taking and not taking prescription pain medications at one year. Regression analyses examined associations between prescription pain medication use and outcomes at 12 months, controlling for age, gender, race, ethnicity and burn size.ResultsOf the 645 participants, 15% reported prescription pain medication use prior to their burn. At discharge, 81% reported use of an opioid and 46% reported use of a neuropathic pain medication. At 12 months, 32% of individuals indicated prescription pain medication use. The pain medication group exhibited larger burn size (24.0% vs 15.2%) and longer hospital stays (40.4 vs 25.0 days) than the non-pain medication group (p< 0.0001 for all). Additionally, 25% of individuals who reported pre-injury pain medication use also reported use at 12 months. Regression analyses demonstrated that pain medication use was associated with worse physical health (PCS: coefficient 8.69, p< 0.0001) mental health (MCS: 6.31, p< 0.0001), stigma (NeuroQOL Stigma: 3.91, p< 0.0001), and satisfaction with life (SWLS: -3.66, p< 0.0001) at one year. Additionally, pain medication use was associated with 45% decreased odds of being employed (coefficient 0.55, p=0.029) and approximately 3 times greater odds of having post-traumatic stress disorder at 12 months (coefficient 3.25, p< 0.0001).ConclusionsThere are significant associations between prescription pain medication use and worse physical, mental and employment outcomes at twelve months. This information may be used to trigger screening and manage long-term recovery outcomes.

73 Associations Between Pre-burn Occupation Type and Employment Outcomes at One Year

IntroductionReintegration into the workforce after burn injury is an important issue for survivors. In a 2012 systematic review, 28% of burn survivors never returned to any form of employment. Although pre-burn employment status is strongly associated with post-burn employment, there are little data on the role of pre-injury occupation type on workplace reintegration. The aim of this project was to assess the impact of occupation type on employment outcomes after burn injury.MethodsData from the National Institute on Disability, Independent Living, and Rehabilitation Research Burn Model System National Longitudinal Database from 2015 to 2021 were used to investigate the association between occupation type and employment outcomes. Occupation type was classified into two groups, Labor and Non-labor, using the U.S. Bureau of Labor Statistics Standard Occupational Classification System. Demographic and clinical data were compared between groups. Mixed regression analyses examined associations between pre-burn occupation type and post-burn employment outcomes (employment at 1 year, days to return to work), controlling for age, gender, race, ethnicity, pre-injury employment, and burn size.ResultsOf the 600 patients who were employed pre-injury, 247 (41%) identified with a non-labor occupation and 353 (59%) with labor occupations. The Labor group was more male (82% vs. 61%) and Hispanic (23% vs. 6%), younger (mean age 42.1 vs. 48.3 years), less educated (high school or less, 25% vs. 11%) and more likely to have been injured at work (28% vs. 14%) compared to the Non-labor group (p< 0.001 for all comparisons). Changes in occupation were seen from pre-injury to post-injury; 16% of working survivors changed from Non-labor to Labor and 13% from Labor to Non-labor occupation types. For those who did return to work after injury, the average time to return to work was greater for Labor compared to the Non-labor group (150 vs 100 days; p=0.003). Additionally, those in the pre-injury Labor group were less likely to be employed at 12 months compared to the Non-labor group (odds ratio = 0.41; p=0.009).ConclusionsPre-injury occupation type is associated with employment outcomes after injury. Therefore, occupation type can be used to inform vocational reintegration resources, such as vocational rehabilitation programs, to optimize survivor outcomes.

755 Does Military Service History Make a Difference in Outcomes after Burn Injury?

IntroductionThere is little published research on the long-term outcomes of military service members with burn injuries. Military service members are often exposed to extraordinary challenges and adverse experiences that might influence their recovery from a burn injury. Therefore, to better understand the outcomes of service members with burn injuries, this study compares characteristics and health outcomes between burn survivors who have and do not have a history of military service.MethodsData from the Burn Injury Model System National Longitudinal Database (2015-2021) were analyzed. Military and civilian groups were identified by the following question administered at hospital discharge: “have you ever served in the military?”. The database does not identify if military service members were active duty at time of injury. Demographic and clinical characteristics as well as outcome measures at one year after injury were compared between groups. Patient reported outcome measures included: Veterans Rand 12-Item Health Survey (VR-12) physical and mental health, Satisfaction with Life Scale (SWL), 4-D Itch, Post Traumatic Stress Disorder (PTSD) Check List, self-reported PTSD diagnosis, and employment status. Multivariate regression analyses examined associations between outcome measures and military service status, controlling for age, gender, burn size, race, and ethnicity.ResultsThe study population included 672 burn survivors, 105 with and 567 without military service history, respectively. Participants with military service history were more likely to be male (93% vs. 65%, p < 0.001), older (55 vs. 45 years, p < 0.001) and have Medicare/Medicaid insurance (46.6% vs. 37.2%, p< 0.01) than those without military service history. Race, ethnicity, education, marital status, injury etiology, burn size, length of stay, burns to critical areas, amputation, and number of surgeries were not significantly different between groups. Regression analyses also demonstrated that none of the outcome measures examined (VR-12, SWL, 4-D Itch, PTSD Check List, self-reported PTSD, employment) were significantly different between groups at one-year after injury (p >0.05).ConclusionsNo significant differences in outcomes were found in the BMS Database between burn survivors with and without a history of military service. Harmonization of these data with other military service datasets will help us better understand long-term outcomes of this population.

Are burns a chronic condition? Examining patient reported outcomes up to 20 years after burn injury-A Burn Model System National Database investigation.

People living with burn injury often face long-term physical and psychological sequelae associated with their injuries. Few studies have examined the impacts of burn injuries on long-term health and function, life satisfaction, and community integration beyond 5 years postinjury. The purpose of this study was to examine these outcomes up to 20 years after burn injury. Data from the Burn Model System National Longitudinal Database (1993-2020) were analyzed. Patient-reported outcome measures were collected at discharge (preinjury status recall) and 5 years, 10 years, 15 years, and 20 years after injury. Outcomes examined were the SF-12/VR-12 Physical Component Summary and Mental Component Summary, Satisfaction with Life Scale, and Community Integration Questionnaire. Trajectories were developed using linear mixed models with repeated measures of outcome scores over time, controlling for demographic and clinical variables. The study population included 421 adult burn survivors with a mean age of 42.4 years. Lower Physical Component Summary scores (worse health) were associated with longer length of hospital stay, older age at injury and greater time since injury. Similarly, lower Mental Component Summary scores were associated with longer length of hospital stay, female sex, and greater time since injury. Satisfaction with Life Scale scores decrease negatively over time. Lower Community Integration Questionnaire scores were associated with burn size and Hispanic/Latino ethnicity. Burn survivors' physical and mental health and satisfaction with life worsened over time up to 20 years after injury. Results strongly suggest that future studies should focus on long-term follow-up where clinical interventions may be necessary. Prognostic and Epidemiologic; Level III.

RISK FACTORS FOR DEVELOPMENT OF PROSTATE CANCER IN PATIENT WITH INFLAMMATORY BOWEL DISEASE (IBD)

Abstract BACKGROUND Prostate cancer (PC) is a 2nd leading cause of cancer death in the USA among men. We aim to investigate incidence, characteristics, and risk factors for PC in patients diagnosed with Inflammatory bowel disease (IBD) using Cerner Health Facts, a national longitudinal database representing approximately 69 million patients. METHODS All male patients over 40 years of age with IBD were included in our analysis. Our primary endpoint was development of PC, specified by ICD coding. Patient characteristics were evaluated as potential risk factors for development of PC using multivariable regression built using all variables with p&amp;lt;0.1 on univariable analysis. RESULTS Overall, 2.23% patients with IBD developed prostate cancer (992/44,551). Mean age was 59.7±12.7 years and 9.65% (04,297/44,551) of patients were obese. In terms of race, 82.9% (36,929/44,551) were white and 7.8% (3,470/44,551) were African American. 94.9% (41829/44,551) received care at an acute care facility and 83.7% (37,266/44,551) received care at an urban facility. On multivariable regression, the risk factors associated with higher risk of prostate cancer include diabetes (odds ratio OR 1.20), obesity (OR 1.22), age (OR 1.07), family history of prostate cancer (OR 6.04), African American race (OR 2.00), and married status (OR 1.43). Factors that decreased risk of pancreatic cancer include other race (OR 0.70; 95% CI 0.53-0.92), and presentation at acute facility (OR 0.59; 95% CI 0.46-0.76). Factors not found to be associated with high risk of PC in our study includes sexually transmitted disease, alcohol use disorder, smoking, presentation at teaching facility, and facility size/type (Table 1). The most protective variable against PC was presentation at acute facility (OR 0.59), other-race (OR 0.70). Table 1 contains our univariable analysis and multivariable regression model with 95% confidence intervals; 6 variables were predictive for PC and 2 variables were protective against PC. CONCLUSION We describe risk factors for development of PC from IBD. In this longitudinal national database study of patient with diagnosed IBD – age, diabetes, obesity, married status, family history of prostate cancer, and African American race were noted to be associated with high risk of developing prostate cancer. Careful evaluation and follow up is advised for IBD patients.

RISK FACTORS FOR DEVELOPMENT OF PROSTATE CANCER IN PATIENT WITH INFLAMMATORY BOWEL DISEASE (IBD)

Prostate cancer (PC) is a 2nd leading cause of cancer death in the USA among men. We aim to investigate incidence, characteristics, and risk factors for PC in patients diagnosed with Inflammatory bowel disease (IBD) using Cerner Health Facts, a national longitudinal database representing approximately 69 million patients.

Synthetic Longitudinal Education Database: Linking National Datasets for K-16 Education and College Readiness

&lt;p style="text-align: justify;"&gt;What are missing in the U.S. education policy of “college for all” are supporting data and indicators on K-16 education pathways, i.e, how well all students get ready and stay on track from kindergarten through college. This study creates synthetic national longitudinal education database that helps track and support students’ educational pathways by combining two nationally-representative U.S. sample datasets: Early Childhood Longitudinal Study- Kindergarten (ECLS-K; Kindergarten through 8th grade) and National Education Longitudinal Study (NELS; 8th grade through age 25). The merge of these national datasets, linked together via statistical matching and imputation techniques, can help bridge the gap between elementary and secondary/postsecondary education data/research silos. Using this synthetic K-16 education longitudinal database, this study applies machine learning data analytics in search of college readiness early indicators among kindergarten students. It shows the utilities and limitations of linking preexisting national datasets to impute education pathways and assess college readiness. It discusses implications for developing more holistic and equitable educational assessment system in support of K-16 education longitudinal database.&lt;/p&gt;