Jennifer E Stevenson

Johns Hopkins University, Baltimore, Maryland, United States

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Publications (5)18.75 Total impact

  • Journal of critical care. 09/2014;
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    ABSTRACT: Acute lung injury (ALI) is common in the intensive care unit (ICU), typically requiring life support ventilation. Survivors often experience anxiety after hospital discharge. We evaluated general anxiety symptoms 3months after ALI for: (1) associations with patient characteristics and ICU variables, and (2) cross-sectional associations with physical function and quality of life (QOL). General anxiety was assessed as part of a prospective cohort study recruiting patients from 13 ICUs at four hospitals in Baltimore, MD using the Hospital Anxiety and Depression Scale - Anxiety Subscale (HAD-A), with associations evaluated using multivariable linear and logistic regression models. Of 152 patients, 38% had a positive screening test for general anxiety (HAD-A≥8). Pre-ICU body mass index and psychiatric comorbidity were associated with general anxiety (OR, 95% confidence interval (CI): 1.06 (1.00, 1.13) and 3.59 (1.25, 10.30), respectively). No ICU-related variables were associated with general anxiety. General anxiety was associated with the number of instrumental ADL dependencies (Spearman's rho=0.22; p=0.004) and worse overall QOL as measured by EQ-5D visual analog scale (VAS) (rho=-0.34; p<0.001) and utility score (rho=-0.30; p<0.001), and by the SF-36 mental health domain (rho=-0.70; p<0.001) and Mental Component Summary score (rho=-0.73; p<0.001). Many patients have substantial general anxiety symptoms 3months after ALI. General anxiety was associated with patient characteristics and impaired physical function and quality of life. Early identification and treatment of general anxiety may enhance physical and emotional function in patients surviving critical illnesses.
    Journal of psychosomatic research 09/2013; 75(3):287-93. · 2.91 Impact Factor
  • Jennifer E Stevenson, David W Dowdy
    Critical care medicine 07/2012; 40(7):2231-2. · 6.37 Impact Factor
  • Jennifer E Stevenson, Bruce R Wright, Alan S Boydstun
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    ABSTRACT: The purpose of this research was to utilize a structural equation modeling (SEM) approach to simultaneously examine the relationship among the Metabolic Syndrome (MetSyn) and coronary artery calcification (CAC), a surrogate marker for sub-clinical atherosclerosis and coronary artery disease (CAD). Data were derived from the Spokane Heart Study (SHS), a prospective study designed to examine the role of traditional and non-traditional biological, psychological, and behavioral risk factors predictive of CAC. Study participants included 434 non-clinical healthy volunteers (54% female, 46% male; mean age of 56 years) who were asymptomatic for CAD at enrollment and had complete data for the primary variables of interest (MetSyn components and CAC) during the data collection period (i.e., 2002-2006). A confirmatory factor analysis (CFA) was conducted on the MetSyn factor with the following indicator variables: body mass index, fasting glucose, high-density lipoprotein cholesterol, fasting triglyceride levels, and systolic blood pressure. SEM was used to test the theoretical model that the MetSyn is associated with CAC. This study demonstrated that body mass index, fasting glucose, fasting triglyceride levels, HDL cholesterol, and blood pressure do cluster together under a single latent factor, and that this latent factor is associated with CAC. Our results highlight the possibility that there is a common pathophysiological pathway that could explain the relationship between the MetSyn and CAD. Future studies should examine these relationships in a prospective fashion for early detection and prevention of CAD and to identify ideal time points for clinical intervention.
    Metabolism: clinical and experimental 05/2012; 61(11):1582-8. · 3.10 Impact Factor
  • Dale M Needham, Biren B Kamdar, Jennifer E Stevenson
    Critical care medicine 04/2012; 40(4):1340-1. · 6.37 Impact Factor

Publication Stats

9 Citations
18.75 Total Impact Points


  • 2013
    • Johns Hopkins University
      Baltimore, Maryland, United States
  • 2012
    • Johns Hopkins Medicine
      Baltimore, Maryland, United States
    • Johns Hopkins Bloomberg School of Public Health
      • Department of Epidemiology
      Baltimore, Maryland, United States