The purpose of this study was to evaluate the effect of Reiki as an alternative and complementary approach to treating community-dwelling older adults who experience pain, depression, and/or anxiety. Participants (N = 20) were randomly assigned to either an experimental or wait list control group. The pre- and posttest measures included the Hamilton Anxiety Scale, Geriatric Depression Scale-Short Form, Faces Pain Scale, and heart rate and blood pressure. The research design included an experimental component to examine changes in these measures and a descriptive component (semi-structured interview) to elicit information about the experience of having Reiki treatments. Significant differences were observed between the experimental and treatment groups on measures of pain, depression, and anxiety; no changes in heart rate and blood pressure were noted. Content analysis of treatment notes and interviews revealed five broad categories of responses: Relaxation; Improved Physical Symptoms, Mood, and Well-Being; Curiosity and a Desire to Learn More; Enhanced Self-Care; and Sensory and Cognitive Responses to Reiki.
Aims Almost half of African American (AA) men and women have cardiovascular disease (CVD). Detection of prevalent CVD in community settings would facilitate secondary prevention of CVD. We sought to develop a tool for automated CVD detection. Methods and Results Participants from the Jackson Heart Study (JHS) with analyzable ECGs (n = 3,679; age, 62±12 years; 36% men) were included. Vectorcardiographic (VCG) metrics QRS, T, and spatial ventricular gradient (SVG) vectors’ magnitude and direction, and traditional ECG metrics were measured on 12-lead ECG. Random forests, convolutional neural network (CNN), lasso, adaptive lasso, plugin lasso, elastic net, ridge, and logistic regression models were developed in 80% and validated in 20% samples. We compared models with demographic, clinical, and VCG input (43 predictors) and those after the addition of ECG metrics (695 predictors). Prevalent CVD was diagnosed in 411 out of 3,679 participants (11.2%). Machine-learning models detected CVD with ROC AUC 0.69-0.74. There was no difference in CVD detection accuracy between models with VCG and VCG+ECG input. Models with VCG input were better calibrated than models with ECG input. Plugin-based lasso model consisting of only two predictors (age and peak QRS-T angle) detected CVD with AUC 0.687 (95%CI 0.625-0.749), which was similar (P = 0.394) to the CNN (0.660; 95%CI 0.597-0.722) and better (P < 0.0001) than random forests (0.512; 95% CI 0.493-0.530). Conclusions Simple model (age and QRS-T angle) can be used for prevalent CVD detection in limited-resources community settings, which opens an avenue for secondary prevention of CVD in underserved communities.
Most of the world's phosphate deposits can be grouped into six type*2 1) igneous apatite deposits| 2) marine phosphorites; 3) residual phosphorites j 4) river pebble deposits; 5) phosphatized rock2 and 6) guano. The igneous apatites and marine phosphorites form deposits measurable in millions or billions of tons; the residual deposits are measurable in thousands or millions 5 and the other types generally only in thousands of
ObjectivesWe hypothesised that (1) the prevalent cardiovascular disease (CVD) is associated with global electrical heterogeneity (GEH) after adjustment for demographic, anthropometric, socioeconomic and traditional cardiovascular risk factors, (2) there are sex differences in GEH and (3) sex modifies an association of prevalent CVD with GEH.DesignCross-sectional, cohort study.SettingProspective African-American The Jackson Heart Study (JHS) with a nested family cohort in 2000–2004 enrolled residents of the Jackson, Mississippi metropolitan area.ParticipantsParticipants from the JHS with analysable ECGs recorded in 2009–2013 (n=3679; 62±12 y; 36% men; 863 family units). QRS, T and spatial ventricular gradient (SVG) vectors’ magnitude and direction, spatial QRS-T angle and sum absolute QRST integral (SAI QRST) were measured.OutcomePrevalent CVD was defined as the history of (1) coronary heart disease defined as diagnosed/silent myocardial infarction, or (2) revascularisation procedure defined as prior coronary/peripheral arterial revascularisation, or (3) carotid angioplasty/carotid endarterectomy, or (4) stroke.ResultsIn adjusted mixed linear models, women had a smaller spatial QRS-T angle (−12.2 (95% CI −19.4 to -5.1)°; p=0.001) and SAI QRST (−29.8 (−39.3 to −20.3) mV*ms; p<0.0001) than men, but larger SVG azimuth (+16.2(10.5–21.9)°; p<0.0001), with a significant random effect between families (+20.8 (8.2–33.5)°; p=0.001). SAI QRST was larger in women with CVD as compared with CVD-free women or men (+15.1 (3.8–26.4) mV*ms; p=0.009). Men with CVD had a smaller T area (by 5.1 (95% CI 1.2 to 9.0) mV*ms) and T peak magnitude (by 44 (95%CI 16 to 71) µV) than CVD-free men. T vectors pointed more posteriorly in women as compared with men (peak T azimuth + 17.2(8.9–25.6)°; p<0.0001), with larger sex differences in T azimuth in some families by +26.3(7.4–45.3)°; p=0.006.ConclusionsThere are sex differences in the electrical signature of CVD in African-American men and women. There is a significant effect of unmeasured genetic and environmental factors on cardiac repolarisation.
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