The value of diastolic function parameters in the prediction of left atrial appendage thrombus in patients with nonvalvular atrial fibrillation

BACKGROUND: Left ventricular diastolic impairment and consequently elevated filling pressure may contribute to stasis leading to left atrial appendage thrombus (LAAT) in nonvalvular atrial fibrillation (AF). We investigated whether transthoracic echocardiographic parameters can predict LAAT independent of traditional clinical predictors. METHODS: We conducted a retrospective cohort study of 297 consecutive nonvalvular AF patients who underwent transthoracic echocardiogram followed by a transesophageal echocardiogram within one year. Multivariate logistic regression analysis models were used to determine factors independently associated with LAAT. RESULTS: Nineteen subjects (6.4%) were demonstrated to have LAAT by transesophageal echocardiography. These patients had higher mean CHADS(2) scores [2.6 ± 1.2 vs. 1.9 ± 1.3, P = 0.009], higher E:e’ ratios [16.6 ± 6.1 vs. 12.0 ± 5.4, P = 0.001], and lower mean e’ velocities [6.5 ± 2.1 cm/sec vs. 9.1 ± 3.2 cm/sec, P = 0.001]. Both E:e’ and e’ velocity were associated with LAAT formation independent of the CHADS(2) score, warfarin therapy, left ventricular ejection fraction (LVEF), and left atrial volume index (LAVI) [E:e’ odds-ratio = 1.14 (95% confidence interval = 1.03 – 1.3), P = 0.009; e’ velocity odds-ratio = 0.68 (95% confidence interval = 0.5 – 0.9), P = 0.007]. Similarly, diastolic function parameters were independently associated with spontaneous echo contrast. CONCLUSION: The diastolic function indices E:e’ and e’ velocity are independently associated with LAAT in nonvalvular AF patients and may help identify patients at risk for LAAT

Developing Interactive Learning for Continuous Glucose Monitoring

This research project investigates the development of aninteractive visual learning tool for patients utilizingcontinuous glucose monitoring. A beta product of thisinteractive learning tool was developed to run real-lifescenarios that visualize how meal choices and medicationaffect glucose trajectories in both healthy patients andpatients with type 2 diabetes. This learning tool isintended to be used by the clinician to engage thepatient in an educational discussion about continuousglucose monitoring. The tool may enhance a patient’sunderstanding of graphic glucose trajectories so that theymay discover how their body reacts to different lifestylechoices and learn to make better real-time decisions withtheir own CGM data. The effectiveness of this betaproduct was evaluated by 17 health professionals

The Association between Self-Reported Energy Intake and Intra-Abdominal Adipose Tissue in Perimenopausal Women

We have previously shown that physical activity predicts intra-abdominal adipose tissue (IAT), but it is unknown whether energy intake predicts IAT independently of physical activity in a community-based, naturalistic environment. The association of energy intake with IAT was explored cross-sectionally in women, recruited between 2002 and 2005 for a study of fat patterning in midlife. IAT at L4-L5 vertebral interspace was assessed by computed tomography, energy intake by the Block Food Frequency Questionnaire, and physical activity by the Kaiser Physical Activity Survey. Linear regression models were used for the principal analyses. Among the 257 women, 48% were African American and 52% were Caucasian. Women were 52±3 years old, and 49% were postmenopausal. Every 500 kcal increase in energy intake was associated with a 6% higher IAT (P=0.02), independent of physical activity (P=0.02), after adjustment for ethnicity, menopausal status, age, smoking, income, and DXA-assessed percent body fat. Energy intake had a significant interaction with ethnicity (P=0.02), but not with physical activity. Models using the IAT to subcutaneous abdominal adipose tissue ratio as an outcome had similar associations. In conclusion, self-reported EI was associated with preferential IAT accumulation in midlife women, independent of physical activity. This association was significantly stronger in Caucasian than African American women. Future longitudinal studies are needed to explore lifestyle predictors of IAT accumulation during the menopausal transition

Meal preparation and cleanup time and cardiometabolic risk over 14years in the Study of Women's Health Across the Nation (SWAN)

Photograph of a scene during the pecan harvest, in Eastern Oklahoma

Cardiovascular risk and midlife cognitive decline in the Study of Women's Health Across the Nation

IntroductionCardiovascular risk factors in midlife have been linked to late life risk for Alzheimer's disease and related dementias (ADRD). The relation of vascular risk factors on cognitive decline within midlife has been less studied.MethodsUsing data from the Study of Women's Health Across the Nation, we examined associations of midlife hypertension, elevated lipid levels, diabetes, fasting glucose, central adiposity, and Framingham heart age with rates of cognitive decline in women who completed multiple cognitive assessments of processing speed, and working and verbal memory during midlife.ResultsDiabetes, elevated fasting glucose, central obesity, and heart age greater than chronological age were associated with rate of decline in processing speed during midlife. Vascular risk factors were not related to rate of decline in working or verbal memory.DiscussionMidlife may be a critical period for intervening on cardiovascular risk factors to prevent or delay later life cognitive impairment and ADRD

Birthweight, mediating biomarkers and the development of type 2 diabetes later in life: a prospective study of multi-ethnic women

Aims/hypothesisThe aim of this work was to investigate the prospective relationship between low birthweight (LBW) and type 2 diabetes risk later in life and the mediation effects of type 2 diabetes biomarkers linking LBW to type 2 diabetes risk.MethodsWe measured baseline plasma concentrations of various type 2 diabetes biomarkers in 1,259 incident type 2 diabetes cases and 1,790 controls in the Women's Health Initiative-Observational Study. Self-report birthweights of the participants were recorded. The total effect of LBW on type 2 diabetes risk was partitioned into effects that were mediated by a specific biomarker and effects that were not mediated by this biomarker, using counterfactual model-based mediation analysis.ResultsLBW was significantly associated with increased risk of type 2 diabetes. Compared with women with birthweight 3.63-4.54 kg, women with LBW (<2.72 kg) had a multivariable-adjusted OR of 2.15 (95% CI, 1.54, 3.00). Insulin resistance (indicated by HOMA-IR) mediated 47% of the total effect. Decreased sex hormone-binding globulin (SHBG) concentration accounted for 24%, elevated E-selectin concentration accounted for 25% and increased systolic blood pressure accounted for 8% of the total effect of LBW on type 2 diabetes risk. (Due to interactions among different mediators, the sum of each individual mediator's contribution could exceed 100%, without an upper limit.)Conclusions/interpretationLBW is directly predictive of higher risk of type 2 diabetes later in life. The effect of LBW on type 2 diabetes risk seems mainly mediated by insulin resistance, which is further explained by circulating levels of SHBG and E-selectin and systolic blood pressure. The study provides potential risk stratification in a population at greater risk of developing type 2 diabetes

Does Season of Reported Dietary Intake Influence Diet Quality? Analysis From the Women's Health Initiative

We evaluated the role of seasonality in self-reported diet quality among postmenopausal women participating in the Women's Health Initiative (WHI). A total of 156,911 women completed a food frequency questionnaire (FFQ) at enrollment (1993-1998). FFQ responses reflected intake over the prior 3-month period, and seasons were defined as spring (March-May), summer (June-August), fall (September-November), and winter (December-February). FFQ data were used to calculate the Alternate Healthy Eating Index (AHEI), a measure of diet quality that has a score range of 2.5-87.5, with higher scores representing better diet quality. In multivariable linear regression models using winter as the reference season, AHEI scores were higher in spring, summer, and fall (all P values < 0.05); although significant, the variance was minimal (mean AHEI score: winter, 41.7 (standard deviation, 11.3); summer, 42.2 (standard deviation, 11.3)). Applying these findings to hypothesis-driven association analysis of diet quality and its relationship with chronic disease risk (cardiovascular disease) showed that controlling for season had no effect on the estimated hazard ratios. Although significant differences in diet quality across seasons can be detected in this population of US postmenopausal women, these differences are not substantial enough to warrant consideration in association studies of diet quality