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St Sauver, Jennifer L

0000-0002-9789-8544

Mayo Clinic

Division of Epidemiology, Department of Quantitative Health Sciences

Citations 58

Electronic Medical Record‐Integrated Pharmacogenomics and Related Clinical Decision Support Concepts
Caraballo, PJ, Bielinski, Suzette J. , Sauver, JL St., Weinshilboum, RM, Sauver, Jennifer L. St. , Caraballo, Pedro J. , St Sauver, Jennifer L , Bielinski, Suzette

Clinical Pharmacology & Therapeutics | April 8, 2017 | Volume: 102 | Issue: 2 | Pages: 254-264

10.1002/cpt.707 Get It

Advances in pharmacogenomics (PGx) have the potential to transform healthcare by allowing precision medicine to become a reality. However, PGx knowledge is new, complex, and evolving, and relying on the cognition of clinicians alone is insufficient for clinical implementation. Integrating clinical decision support (CDS) tools in the electronic health record (EHR) is critical for translating PGx into clinical practice. Herein, we review current strategies to implement PGx using EHR‐CDS functionalities.
A Population-Based Study of Sociodemographic and Geographic Variation in HPV Vaccination
Wilson, Patrick M. , Jacobson, Debra J., Agunwamba, Amenah A. , Breitkopf, Carmen Radecki , Sauver, Jennifer L. St. , Finney Rutten, Lila J, Radecki Breitkopf, Carmen, Jacobson, Robert M. , St Sauver, Jennifer L, Rutten, Lila J. Finney , St Sauver, Jennifer L

Cancer Epidemiology, Biomarkers & Prevention | February 14, 2017 | Volume: 26 | Issue: 4 | Pages: 533-540

10.1158/1055-9965.epi-16-0877 Get It

Abstract Background: Human papillomavirus (HPV) vaccination rates in the United States remain low and lag behind other recommended adolescent vaccines. Studies evaluating the association of geographic and area-level characteristics with HPV vaccination rates provide a valuable resource for public health planning. Method: We used the Rochester Epidemiology Project data linkage system to ascertain HPV vaccination rates between 2010 and 2015 in a 7-county region of southern Minnesota. Geocoded individual patient data were spatially linked to socioeconomic data from the American Community Survey at the census block group level. Bayesian hierarchical logistic regression was used to model incident vaccination rates, adjusting for individual- and area-level sociodemographic characteristics, and geolocation. Geolocation was modeled as an approximated Gaussian field using a Stochastic Partial Differential Equations approach. All models were estimated using Integrated Nested Laplace Approximations. Results: In adjusted models, increasing age and female sex were associated with increased HPV vaccination. Lower socioeconomic status was associated with decreased rates of initiation [adjusted odds ratio (AOR); 95% confidence interval = 0.90 (0.86–0.95)], completion of the second dose [AOR = 0.88 (0.83–0.93)], and completion of the third dose [AOR = 0.85 (0.80–0.92)]. Geographic spatial analysis demonstrated increased odds of vaccination for the eastern region and in the greater Rochester metropolitan area, showing significant spatial variation not explained by individual level characteristics and ACS block group-level data. Conclusions: HPV vaccination rates varied geographically and by individual and geographically indexed sociodemographic characteristics. Impact: Identifying geographic regions with low HPV vaccination rates can help target clinical and community efforts to improve vaccination rates. Cancer Epidemiol Biomarkers Prev; 26(4); 533–40. ©2017 AACR. See all the articles in this CEBP Focus section, “Geospatial Approaches to Cancer Control and Population Sciences.”
Incidence Rate of Prediabetes Progression to Diabetes: Modeling an Optimum Target Group for Intervention
DeJesus, Ramona S. , Breitkopf, Carmen Radecki , Jacobson, Debra J., Wilson, Patrick M. , Sauver, Jennifer L. St. , Rutten, Lila J, Rutten, Lila J. Finney , St Sauver, Jennifer L

Population Health Management | September 30, 2016 | Volume: 20 | Issue: 3 | Pages: 216-223

10.1089/pop.2016.0067 Get It

Social and behavioural factors associated with frailty trajectories in a population-based cohort of older adults
Chamberlain, Alanna M. , Sauver, Jennifer L. St. , Jacobson, Debra J., Manemann, Sheila M., Fan, Chun , Roger, Véronique L. , Yawn, Barbara P. , St Sauver, Jennifer L, Finney Rutten, Lila J, Rutten, Lila J. Finney , St Sauver, Jennifer L , Chamberlain, Alanna M

BMJ Open | May 27, 2016 | Volume: 6 | Issue: 5 | Pages: e011410

10.1136/bmjopen-2016-011410 Get It

Objective The goal of this study was to identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an ageing population and to determine social and behavioural factors associated with frailty trajectories. Design Population-based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Primary outcome measure Changes in frailty over an 8-year period from 2005 to 2012, measured by constructing a yearly frailty index. Frailty trajectories by decade of age were determined using k-means cluster modelling for longitudinal data. Results After adjustment for age and sex, all social and behavioural factors (education, marital status, living arrangements, smoking status and alcohol use) were significantly associated with frailty trajectories in those aged 60–69 and 70–79 years. After further adjustment for baseline frailty, the likelihood of being in the high frailty trajectory was greatest among those reporting concerns from relatives/friends about alcohol consumption (OR (95% CI) 2.26 (1.19 to 4.29)) and those with less than a high school education (OR (95% CI) 1.98 (1.32 to 2.96)) in the 60–69 year olds. In the 70–79 year olds, the largest associations were observed among those with concerns from oneself about alcohol consumption (OR (95% CI) 1.92 (1.23 to 3.00)), those with less than a high school education (OR (95% CI) 1.57 (1.12 to 2.22)), and those living with family (vs spouse; OR (95% CI) 1.76 (1.05 to 2.94)). No factors remained associated with frailty trajectories in the 80–89 year olds after adjustment for baseline frailty. Conclusions Social and behavioural factors are associated with frailty, with stronger associations observed in younger ages. Recognition of social and behavioural factors associated with increasing frailty may inform interventions for individuals at risk of worsening frailty, specifically when targeted at younger individuals.
Frailty Trajectories in an Elderly Population‐Based Cohort
Chamberlain, Alanna M. , Manemann, Sheila M., Yawn, Barbara P. , Jacobson, Debra J., Fan, Chun , Grossardt, Brandon R. , Roger, Véronique L. , Sauver, Jennifer L. St. , Finney Rutten, Lila J, St Sauver, Jennifer L, Rutten, Lila J. Finney , St Sauver, Jennifer L , Chamberlain, Alanna M , Grossardt, Brandon R

Journal of the American Geriatrics Society | February 20, 2016 | Volume: 64 | Issue: 2 | Pages: 285-292

10.1111/jgs.13944 Get It

Objectives To identify distinct frailty trajectories (clusters of individuals following a similar progression of frailty over time) in an aging population and to estimate associations between frailty trajectories and emergency department visits, hospitalizations, and all‐cause mortality. Design Population‐based cohort study. Setting Olmsted County, Minnesota. Participants Olmsted County, Minnesota residents aged 60–89 in 2005. Measurements Longitudinal changes in frailty between 2005 and 2012 were measured by constructing a yearly Rockwood frailty index incorporating body mass index, 17 comorbidities, and 14 activities of daily living. The frailty index measures variation in health status as the proportion of deficits present of the 32 considered (range 0–1). Results Of the 16,443 Olmsted County residents aged 60–89 in 2005, 12,270 (74.6%) had at least 3 years of frailty index measures and were retained for analysis. The median baseline frailty index increased with age (0.11 for 60–69, 0.14 for 70–79, 0.19 for 80–89). Three distinct frailty trajectories were identified in individuals aged 60–69 at baseline and two trajectories in those aged 70–79 and 80–89. Within each decade of age, increasing frailty trajectories were associated with greater risks of emergency department visits, hospitalization, and all‐cause mortality, even after adjustment for baseline frailty index. Conclusion The number of frailty trajectories differed according to age. Within each age group, those in the highest frailty trajectory had greater healthcare use and worse survival. Frailty trajectories may offer a way to target aging individuals at high risk of hospitalization or death for therapeutic or preventive interventions.
Epidemiology of aquaporin‐4 autoimmunity and neuromyelitis optica spectrum
Flanagan, Eoin P. , Cabre, Philippe, Weinshenker, Brian G. , Sauver, Jennifer L. St. , Jacobson, Debra J., Majed, Masoud , Lennon, Vanda A. , Lucchinetti, Claudia F. , McKeon, Andrew , Matiello, Marcelo , Kale, Nilifur, Wingerchuk, Dean M. , Mandrekar, Jay , Sagen, Jessica, Fryer, James P., Robinson, Angala Borders, Pittock, Sean J. , Sagen, Jessica A., Pittock, S J , Flanagan, E P , Weinshenker, Brian G , St Sauver, Jennifer L , McKeon, Andrew

Annals of Neurology | February 18, 2016 | Volume: 79 | Issue: 5 | Pages: 775-783

10.1002/ana.24617 Get It

ObjectiveNeuromyelitis optica (NMO) and its spectrum disorders (NMOSD) are inflammatory demyelinating diseases (IDDs) with a specific biomarker, aquaporin‐4–immunoglobulin G (AQP4‐IgG). Prior NMO/NMOSD epidemiological studies have been limited by lack of AQP4‐IgG seroprevalence assessment, absence of population‐based USA studies, and under‐representation of blacks. To overcome these limitations, we sought to compare NMO/NMOSD seroepidemiology across 2 ethnically divergent populations.MethodsWe performed a population‐based comparative study of the incidence (2003–2011) and prevalence (on December 31, 2011) of NMO/NMOSD and AQP4‐IgG seroincidence and seroprevalence (sera collected in 80–84% of IDD cases) among patients with IDD diagnosis in Olmsted County, Minnesota (82% white [Caucasian]) and Martinique (90% black [Afro‐Caribbean]). AQP4‐IgG was measured by M1 isoform fluorescence‐activated cell‐sorting assays.ResultsThe age‐ and sex‐adjusted incidence (7.3 vs 0.7/1,000,000 person‐years [p < 0.01]) and prevalence (10 vs 3.9/100,000 [p = 0.01]) in Martinique exceeded that in Olmsted County. The AQP4‐IgG age‐ and sex‐adjusted seroincidence (6.5 vs 0.7/1,000,000 person‐years [p < 0.01]) and seroprevalence (7.9 vs 3.3/100,000 [p = 0.04]) were also higher in Martinique than Olmsted County. The ethnicity‐specific prevalence was similar in Martinique and Olmsted County: 11.5 and 13/100,000 in blacks, and 6.1 and 4.0/100,000 in whites, respectively. NMO/NMOSD represented a higher proportion of IDD cases in Martinique than Olmsted County (16% vs 1.4%; p < 0.01). The onset age (median = 35–37 years) and female:male distribution (5–9:1) were similar across both populations; 60% of prevalent cases were either blind in 1 eye, dependent on a gait aid, or both.InterpretationThis study reports the highest prevalence of NMO/NMOSD in any population (10/100,000 in Martinique), estimates it affects 16,000 to 17,000 in the USA (higher than previous predictions), and demonstrates it disproportionately affects blacks. Ann Neurol 2016;79:775–783
The most effective and promising population health strategies to advance human papillomavirus vaccination
Agunwamba, Amenah A. , Sauver, Jennifer L. St. , Jacobson, Robert M. , St Sauver, Jennifer L, Finney Rutten, Lila J, Rutten, Lila J. Finney , St Sauver, Jennifer L

Expert Review of Vaccines | November 11, 2015 | Volume: 15 | Issue: 2 | Pages: 257-269

10.1586/14760584.2016.1116947 Get It

Multimorbidity and Risk of Mild Cognitive Impairment
Vassilaki, Maria , Aakre, Jeremiah A. , Cha, Ruth H., Kremers, Walter K. , Sauver, Jennifer L. St. , Mielke, Michelle M. , Geda, Yonas E. , Petersen, Ronald C. , Roberts, Rosebud O., St Sauver, Jennifer L, Cha, Ruth H., Machulda, Mary M. , Knopman, David S. , Mielke, Michelle M , St Sauver, Jennifer L , Geda, Yonas E , Kremers, Walter K

Journal of the American Geriatrics Society | August 27, 2015 | Volume: 63 | Issue: 9 | Pages: 1783-1790

10.1111/jgs.13612 Get It

Objectives To determine the association between multiple chronic conditions and risk of incident mild cognitive impairment ( MCI ) and dementia. Design Prospective cohort study. Setting Olmsted County, Minnesota. Participants Cognitively normal individuals (N = 2,176) enrolled in the Mayo Clinic Study of Aging ( MCSA ). Measurements Participants were randomly selected from the community, evaluated by a physician, and underwent neuropsychometric testing at baseline and at 15‐month intervals to assess diagnoses of MCI and dementia. Information on International Classification of Diseases, Ninth Revision codes for chronic conditions in the 5 years before enrollment was electronically captured using the Rochester Epidemiology Project medical records linkage system. Multimorbidity was defined as having two or more chronic conditions, and the association between multimorbidity and MCI and dementia was examined using Cox proportional hazards models. Results Of 2,176 cognitively normal participants (mean age ± standard deviation 78.5 ± 5.2; 50.6% male), 1,884 (86.6%) had multimorbidity. The risk of MCI or dementia was higher in persons with multimorbidity (hazard ratio ( HR ) = 1.38, 95% confidence interval ( CI ) = 1.05–1.82) than in those with one or no chronic condition. The HR was of greater magnitude in persons with four or more conditions ( HR = 1.61, 95% CI = 1.21–2.13) than in those with two or three conditions ( HR = 1.03, 95% CI = 0.76–1.39) and for men with multimorbidity( HR = 1.53, 95% CI = 1.01–2.31) than for women with multimorbidity ( HR = 1.20, 95% CI = 0.83–1.74), compared to those with one or no chronic condition. Conclusion In older adults, having multiple chronic conditions is associated with greater risk of MCI and dementia. This is consistent with the hypothesis that multiple etiologies may contribute to MCI and late‐life dementia. Preventing chronic diseases may be beneficial in delaying or preventing MCI and dementia.
Impairments and comorbidities of polyneuropathy revealed by population-based analyses
Hoffman, E. Matthew , Staff, Nathan P. , Robb, Jared M., Sauver, Jennifer L. St. , Dyck, P. James B. , Klein, Christopher J. , St Sauver, Jennifer L, Staff, Nathan P , Klein, Christopher J , St Sauver, Jennifer L

Neurology | April 2, 2015 | Volume: 84 | Issue: 16 | Pages: 1644-1651

10.1212/wnl.0000000000001492 Get It

A cross-sectional assessment of the prevalence of multiple chronic conditions and medication use in a sample of community-dwelling adults with fibromyalgia in Olmsted County, Minnesota
Vincent, Ann, Whipple, Mary O. , McAllister, Samantha J., Aleman, Katherine M, Sauver, Jennifer L. St. , St Sauver, Jennifer L, St Sauver, Jennifer L , Whipple, Mary

BMJ Open | March 3, 2015 | Volume: 5 | Issue: 3 | Pages: e006681

10.1136/bmjopen-2014-006681 Get It

Objectives The objective of this study was to evaluate the problem of multiple chronic conditions and polypharmacy in patients with fibromyalgia. Design Retrospective medical record review. Setting Olmsted County, Minnesota. Participants 1111 adults with fibromyalgia. Primary and secondary outcome measures Number and type of chronic medical and psychiatric conditions, medication use. Results Medical record review demonstrated that greater than 50% of the sample had seven or more chronic conditions. Chronic joint pain/degenerative arthritis was the most frequent comorbidity (88.7%), followed by depression (75.1%), migraines/chronic headaches (62.4%) and anxiety (56.5%). Approximately, 40% of patients were taking three or more medications for symptoms of fibromyalgia. Sleep aids were the most commonly prescribed medications in our sample (33.3%) followed by selective serotonin reuptake inhibitors (28.7%), opioids (22.4%) and serotonin norepinephrine reuptake inhibitors (21.0%). Conclusions The results of our study highlight the problem of multiple chronic conditions and high prevalence of polypharmacy in fibromyalgia. Clinicians who care for patients with fibromyalgia should take into consideration the presence of multiple chronic conditions when recommending medications.