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131 citation(s) found for "St Sauver, Jennifer L".

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

Mayo Clinic

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

10.1212/wnl.0000000000001492 | PMID 25832668 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

Mayo Clinic

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

10.1136/bmjopen-2014-006681 | PMID 25735301 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.
Effect of Multiple Chronic Diseases on Health Care Expenditures in Childhood
Zhong, Wenjun , Finnie, Dawn M., Shah, Nilay D. , Wagie, Amy E., Sauver, Jennifer L. St. , Jacobson, Debra J., Naessens, James M. , St Sauver, Jennifer L, St Sauver, Jennifer L

Mayo Clinic

Journal of Primary Care & Community Health | July 8, 2014 | Volume: 6 | Issue: 1 | Pages: 2-9

10.1177/2150131914540916 | PMID 25001922 Get It

Objectives: To examine multiple chronic conditions and related health care expenditures in children. Methods: Retrospective cohort study of all dependents of Mayo Clinic employees aged 0-17 on Jan 1, 2004 with continuous health benefits coverage for 4 years (N=14,727). Chronic conditions, health care utilization, and associated expenditures were obtained from medical and pharmacy claims. Results: The most prevalent chronic conditions were asthma/chronic obstructive pulmonary disease (12%), allergic rhinitis (11%), and behavior problems (9%). The most costly conditions were congenital anomalies, asthma/chronic obstructive pulmonary disease, and behavior problems ($9602, $4335, and $5378 annual cost per child, respectively). Annual health care expenditures increased substantially with the number of chronic conditions, and a small proportion of children with multiple chronic conditions accounted for a large proportion of health care costs. In addition, those with multiple chronic conditions were more likely to persist in the top 10th percentile spender group in year-to-year spending. Conclusion: Children with multiple chronic conditions accounted for a large proportion of health care expenditures. These children were also likely to persist as high spenders in the 4-year time frame. Further research into effective ways to manage the health care delivery for children with multiple chronic conditions is needed.
The incidence of cerebrovascular accidents and second brain tumors in patients with pituitary adenoma: a population-based study
Brown, Paul D. , Blanchard, M.J., Flemming, Kelly D. , Brown, Cerise A., Kline, Robert W., Jacobson, Debra J., Sauver, Jennifer L. St. , Pollock, Bruce E. , Garces, Yolanda I. , Stafford, Scott L., Link, Michael J. , Erickson, Dana , Foote, Robert L. , Blanchard, Miran, Jethwa, Krishan, St Sauver, Jennifer, Laack, Nadia N I, Jethwa, Krishan R. , Laack, Nadia N. , St Sauver, Jennifer L , Flemming, Kelly D

Mayo Clinic

Neuro-Oncology Practice | May 3, 2014 | Volume: 1 | Issue: 1 | Pages: 22-28

10.1093/nop/npt001 | PMID 26034611 Get It

AbstractBackgroundTo assess the risk of cerebrovascular accidents (CVAs) and second brain tumors (SBTs) in patients with pituitary adenoma after surgery or radiotherapy.MethodsA cohort of 143 people from Olmsted County, who were diagnosed with pituitary adenoma between 1933 and 2000, was studied. Only patients from Olmsted County were included because of the unique nature of medical care in Olmsted County, which allows the ascertainment of virtually all cases of pituitary adenoma for this community's residents and comparisons to the general population in the county. Surgical resection was performed in 76 patients, 29 patients underwent radiotherapy (with 21 undergoing both surgery and radiotherapy), 5 patients were reirradiated, and 59 patients were managed conservatively and observed.ResultsMedian follow-up was 15.5 years. There was no difference in CVA-free survival between treatment groups. On univariate analysis age > 60 years (hazard ratio [HR], 11.93; 95% CI, 6.26–23.03; P < .001); male sex (HR, 3.67; 95% CI, 2.03–6.84; P < .001), and reirradiation (HR, 3.41; 95% CI, 1.05–9.68; P = .04) were associated with worse CVA-free survival. In multivariate analysis, only age > 60 years was associated with worse CVA-free survival. Compared with the general population, there was a 4-fold increase in the rate of CVAs in pituitary adenoma patients (HR, 4.2; 95% CI, 2.8–6.1). Two patients developed SBT (an irradiated patient and a surgically managed patient).ConclusionCVA is a significant risk for patients with pituitary tumors, but treatment does not seem to impact the risk. Even with long-term follow-up, SBTs are a rare event regardless of treatment modality.
TheFramingham risk score and heart disease in nonalcoholic fatty liver disease
Treeprasertsuk, Sombat , Leverage, Scott, Adams, Leon A. , Lindor, Keith D. , Sauver, Jennifer L. St. , Angulo, Paul, St Sauver, Jennifer L

Mayo Clinic

Liver International | February 2, 2012 | Volume: 32 | Issue: 6 | Pages: 945-950

10.1111/j.1478-3231.2011.02753.x | PMID 22299674 Get It

AbstractThe accuracy of theFramingham risk score (FRS) in identifying patients with nonalcoholic fatty liver disease (NAFLD) at higher 10‐year coronary heart disease (CHD) risk remains unknown. We aimed at evaluating both the baseline probability ofCHDas predicted by theFRSand the actual long‐term occurrence ofCHDinNAFLDpatients. This was a longitudinal study of a community‐based cohort. A total of 309NAFLDpatients were followed up for 11.5 ± 4.1 years (total 3554 person‐years). The overall calculated 10‐yearCHDrisk was significantly higher in theNAFLDcohort than the absoluteCHDrisk predicted by theFRSfor persons of the same age and gender (10.9 ± 9.3% vs. 9.9 ± 5.9%, respectively,P < 0.0001), and higher in men than women (12.6 ± 10.3% vs. 9.6 ± 8.1%, respectively,P = 0.006). New onsetCHDoccurred in 34 patients (11% vs. 10.9% predicted at baseline,P = NS), whereas 279 (89%) patients did not developCHD. Using multivariable analysis, theFRSwas the only variable significantly associated with new onsetCHD(OR = 1.13, 95%CI = 1.05–1.21;P = 0.001). AFRScut‐point of 11 in women, and 6 in men had a sensitivity of 80% and 74%, respectively, and a negative predictive value of 97% and 93% respectively.NAFLDpatients have a higher 10‐yearCHDrisk than the general population of the same age and gender. TheFRSaccurately predicts the higher 10‐yearCHDrisk inNAFLDpatients, and helps identify those patients expected to derive the most benefit from early intervention to preventCHDevents.
Distribution and Associations of [−2]Proenzyme-Prostate Specific Antigen in Community Dwelling Black and White Men
Rhodes, Thomas , Jacobson, Debra J., McGree, Michaela E. , Sauver, Jennifer L. St. , Sarma, Aruna V. , Lieber, Michael M., Klee, George G., Demissie, Kitaw , Jacobsen, Steven J. , Girman, Cynthia J. , St Sauver, Jennifer L

Mayo Clinic

Journal of Urology | November 17, 2011 | Volume: 187 | Issue: 1 | Pages: 92-96

10.1016/j.juro.2011.09.060 | PMID 22093189 Get It

Benign Prostate Specific Antigen Distribution and Associations With Urological Outcomes in Community Dwelling Black and White Men
Rhodes, Thomas , Jacobson, Debra J., McGree, Michaela E. , Sauver, Jennifer L. St. , Sarma, Aruna V. , Lieber, Michael M., Klee, George G., Demissie, Kitaw , Jacobsen, Steven J. , Girman, Cynthia J. , St Sauver, Jennifer L

Mayo Clinic

Journal of Urology | November 17, 2011 | Volume: 187 | Issue: 1 | Pages: 87-91

10.1016/j.juro.2011.09.061 | PMID 22093190 Get It

1722 ASSOCIATIONS BETWEEN MODEST WEIGHT LOSS AND ONSET AND PROGRESSION OF LOWER URINARY TRACT SYMPTOMS
Sarma, Aruna V. , Hollingsworth, John M. , Jacobson, Debra J., McGree, Michaela E. , Dunn, Rodney L. , Lieber, Michael M., Jacobsen, Steven J. , Sauver, Jennifer L. St.

Mayo Clinic

Journal of Urology | May 20, 2011 | Volume: 185 | Issue: 4S | Pages: No page available

10.1016/j.juro.2011.02.1993 Get It

Re: Ultrasound Estimated Bladder Weight and Measurement of Bladder Wall Thickness—Useful Noninvasive Methods for Assessing the Lower Urinary Tract?
Jacobson, Debra J., Sauver, Jennifer L. St. , Jacobsen, Steven J. , Rule, Andrew D. , St Sauver, Jennifer L

Mayo Clinic

Journal of Urology | April 24, 2011 | Volume: 185 | Issue: 6 | Pages: 2435-2435

10.1016/j.juro.2011.02.031 | PMID 21513957 Get It

The Effects of Body Mass Index on Changes in Prostate-Specific Antigen Levels and Prostate Volume Over 15 Years of Follow-up: Implications for Prostate Cancer Detection
Wallner, Lauren P. , Morgenstern, Hal, McGree, Michaela E. , Jacobson, Debra J., Sauver, Jennifer L. St. , Jacobsen, Steven J. , Sarma, Aruna V. , St Sauver, Jennifer L

Mayo Clinic

Cancer Epidemiology, Biomarkers & Prevention | March 8, 2011 | Volume: 20 | Issue: 3 | Pages: 501-508

10.1158/1055-9965.epi-10-1006 | PMID 21242331 Get It

Abstract Objective: To investigate the association of body mass index (BMI) and BMI change with change in prostate-specific antigen (PSA) level and to assess the possible roles of PSA hemodilution and prostate volume in explaining the obesity and PSA association. Methods: In 1990, a randomly selected cohort of Caucasian men, aged 40 to 79 years, from Olmsted County, Minnesota, completed questionnaires ascertaining demographic characteristics, current medical conditions, and medications biennially, with a subset undergoing blood draws and clinical examinations. Linear mixed models were used to predict annual changes and intercepts of individual changes in BMI, PSA, prostate volume, plasma volume, and PSA mass, adjusting for age in 545 men with at least 2 serial PSA, BMI, and prostate volume measurements. Results: Baseline BMI was inversely associated with the annual percent change in PSA, adjusting for age, baseline PSA, and prostate volume and for the rates of change in BMI and prostate volume (β = −0.003, 95% CI: −0.006 to −0.0003). Baseline obesity was positively associated with mean baseline levels and the rate of change in prostate volume (P = 0.002) and plasma volume (both P &lt; 0.001) but was not associated with either the mean baseline values or the rate of change in PSA mass. Conclusions: Baseline obesity was associated with baseline PSA and prostate volume and with the rate of change in PSA over 15 years of follow-up. Impact: The inverse association of obesity with prostate cancer diagnosis may be at least partly due to detection bias, which is due to larger prostate volumes and PSA hemodilution in obese men. Cancer Epidemiol Biomarkers Prev; 20(3); 501–8. ©2011 AACR.