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56 Chronic Musculoskeletal Pain, Biobehavioral and Psychosocial Resilience Index, and Brain Age Gap
- Udell Holmes III, Jared Tanner, Brittany Addison, Kenia Rangel, Angela M Mickle, Cynthia S Garvan, Emily J Bartley, Amber K Brooks, Lai Song, Roland Staud, Burel Goodin, Roger B Fillingim, Catherine C Price, Kimberly T Sibille
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, p. 465
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Objective:
Chronic musculoskeletal pain is associated with neurobiological, physiological, and cellular measures. Importantly, we have previously demonstrated that a biobehavioral and psychosocial resilience index appears to have a protective relationship on the same biomarkers. Less is known regarding the relationships between chronic musculoskeletal pain, protective factors, and brain aging. This study investigates the relationships between clinical pain, a resilience index, and brain age. We hypothesized that higher reported chronic pain would correlate with older appearing brains, and the resilience index will attenuate the strength of the relationship between chronic pain and brain age.
Participants and Methods:Participants were drawn from an ongoing observational multisite study and included adults with chronic pain who also reported knee pain (N = 135; age = 58.3 ± 8.1; 64% female; 49% non-Hispanic Black, 51% non-Hispanic White; education Mdn = some college; income level Mdn = $30,000 - $40,000; MoCA M = 24.27 ± 3.49). Measures included the Graded Chronic Pain Scale (GCPS), characteristic pain intensity (CPI) and disability, total pain body sites; and a cognitive screening (MoCA). The resilience index consisted of validated biobehavioral (e.g., smoking, waist/hip ratio, and active coping) and psychosocial measures (e.g., optimism, positive affect, negative affect, perceived stress, and social support). T1-weighted MRI data were obtained. Surface area metrics were calculated in FreeSurfer using the Human Connectome Project's multi-modal cortical parcellation scheme. We calculated brain age in R using previously validated and trained machine learning models. Chronological age was subtracted from predicted brain age to generate a brain age gap (BAG). With higher scores of BAG indicating predicated age is older than chronological age. Three parallel hierarchical regression models (each containing one of three pain measures) with three blocks were performed to assess the relationships between chronic pain and the resilience index in relation to BAG, adjusting for covariates. For each model, Block 1 entered the covariates, Block 2 entered a pain score, and Block 3 entered the resilience index.
Results:GCPS CPI (R2 change = .033, p = .027) and GCPS disability (R2 change = 0.038, p = 0.017) significantly predicted BAG beyond the effects of the covariates, but total pain sites (p = 0.865) did not. The resilience index was negatively correlated and a significant predictor of BAG in all three models (p < .05). With the resilience index added in Block 3, both GCPS CPI (p = .067) and GCPS disability (p = .066) measures were no longer significant in their respective models. Additionally, higher education/income (p = 0.016) and study site (p = 0.031) were also significant predictors of BAG.
Conclusions:In this sample, higher reported chronic pain correlated with older appearing brains, and higher resilience attenuated this relationship. The biobehavioral and psychosocial resilience index was associated with younger appearing brains. While our data is cross-sectional, findings are encouraging that interventions targeting both chronic pain and biobehavioral and psychosocial factors (e.g., coping strategies, positive and negative affect, smoking, and social support) might buffer brain aging. Future directions include assessing if chronic pain and resilience factors can predict brain aging over time.
73662 Racial Disparities in Septic Shock Mortality: Results from the OneFlorida Data Trust Cohort
- Lauren Page Black, Charlotte Hopson, Elizabeth DeVos, Michael Puskarich, Rosemarie Fernandez, Faheem Guirgis, Cynthia Garvan
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- Journal:
- Journal of Clinical and Translational Science / Volume 5 / Issue s1 / March 2021
- Published online by Cambridge University Press:
- 30 March 2021, pp. 117-118
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ABSTRACT IMPACT: Identifying racial disparities in septic shock mortality, a common and lethal condition, can inform future research and policy efforts aimed at understanding the drivers these disparities and addressing the underlying factors in order to reduce disparities and improve health. OBJECTIVES/GOALS: Septic shock is a major public health problem with significant mortality. Existing data indicate racial disparities in sepsis incidence, but evidence is limited on differences in septic shock outcomes. Our objective was to determine the association between race and septic shock mortality in a statewide cohort while controlling for clinical factors. METHODS/STUDY POPULATION: This was a retrospective analysis of septic shock patients in the One Florida Data Trust between 2012-18. Data was collected regarding age, sex, race, insurance status, and selected comorbid conditions [liver disease, hypertension, chronic obstructive pulmonary disease (COPD), congestive heart failure (CHF), end-stage renal disease (ESRD), and human immunodeficiency virus infection (HIV)]. To account for severity of illness, we assigned Sequential Organ Failure Assessment scores for components based on laboratory values (labSOFA), and collected data on mechanical ventilation use and initial lactate.
The primary outcome was 90-day mortality. The Least Absolute Shrinkage and Selection Operator (LASSO) method was used for variable selection for the multivariable regression model. RESULTS/ANTICIPATED RESULTS: There were 13,932 septic shock patients with a mean (SD) age of 61(16) years. Of these, 68% identified as white, 28% as black, 2.1% as Hispanic, and 2.0% as other races. 90-day mortality was 32% (n=4,437) and 59% required mechanical ventilation. Significant independent predictors of mortality in the regression model were age (OR 1.04; p<0.01), black race (1.72; p<0.01), lactate (1.10; p<0.01), mechanical ventilation (3.62; p<0.01), labSOFA (1.18; p<0.01), history of liver disease (1.75; p<0.01), hypertension (0.70; p<0.01), COPD (0.87; p<0.01), CHF (1.18; p<0.01), HIV (1.30; p=0.05), and the interaction between age and black race. Black patients had 1.72 times the odds of mortality compared to white patients. For every one-year decrease in age, black patients had a 1% increased odds of mortality (OR 1.01; p < 0.01). DISCUSSION/SIGNIFICANCE OF FINDINGS: Black patients have increased odds of dying from septic shock compared to white patients after controlling for age, selected comorbid conditions, and markers of illness severity. Future work is needed to move beyond demonstrating septic shock disparities and towards understanding the underlying factors.
4332 Septic Shock Epidemiology and Sociodemographic Predictors of Mortality: Results from One Florida Data Trust Cohort
- Lauren Page Black, Charlotte Hopson, Elizabeth DeVos, Rosemarie Fernandez, Faheem Guirgis, Cynthia Garvan
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- Journal:
- Journal of Clinical and Translational Science / Volume 4 / Issue s1 / June 2020
- Published online by Cambridge University Press:
- 29 July 2020, pp. 36-37
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OBJECTIVES/GOALS: Septic shock is a lethal condition. Research suggests that overall sepsis mortality varies by race, but less is known about demographic differences in septic shock mortality. Our objectives were to describe the septic shock population using a large, state-wide data repository and identify demographic predictors of septic shock mortality. METHODS/STUDY POPULATION: This was a retrospective review of patients with septic shock in the One Florida Data Trust from 2012-2018. Patients were classified as having septic shock if they received vasopressors and had either 1) an ICD-9 or 10 code for septic shock or 2) an ICD-9 or 10 code for infection and an ICD-9 or 10 code for organ dysfunction. Demographic data and place of residence prior to admission was collected. The primary outcome was 90 day mortality. T-test and chi-square tests were used to test association of individual predictors and mortality. Multiple logistic regression was used to identify predictors of mortality after adjustment for other variables. Level of significance was set at 0.05. SAS v9.4 (Cary, NC) was used for analyses. RESULTS/ANTICIPATED RESULTS: There were 11,790 patients with septic shock. The mean(SD) age was 61(16) years. With regard to race/ethnicity 66% identified as white, 27% as black, 3.7% as Hispanic, and 3.5% as other races (non-white, non-black, non-Hispanic). Most came from home (57%). Overall, 39% died. Mortality varied by race (p<0.01): white 39%, black 39%, Hispanic 31%, other races 51%. In the logistic regression model, age, race, and residence were significant predictors of mortality, after adjustment for other variables. Each additional year of age had a 2.7% increased odds of mortality (OR 1.03; 95% CI 1.02-1.03; p<0.01). Compared to white patients, odds of death were 1.6 times higher for other races (95% CI 1.3-2.0; p <0.01) and non-significantly higher for black patients (OR 1.1; 95% CI 1.0-1.2; p = 0.05). Compared to those from home, odds of death were highest for those from a skilled nursing facility (OR 1.5; p<0.01). DISCUSSION/SIGNIFICANCE OF IMPACT: Patients who identified as other races had increased mortality from septic shock compared to white patients after adjusting for other variables. Septic shock mortality also increased with age and varied by residence. Further analyses are needed to examine racial disparities and control for comorbidities, severity of illness, and aspects of resuscitation. CONFLICT OF INTEREST DESCRIPTION: The authors report no conflicts of interest, except for Dr. Fernandez, who reports personal payment from Physio-Control, Inc. for speaker fees.