2 resultados para Objective spirit

em DigitalCommons@The Texas Medical Center


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Critically ill and injured patients require pain relief and sedation to reduce the body's stress response and to facilitate painful diagnostic and therapeutic procedures. Presently, the level of sedation and analgesia is guided by the use of clinical scores which can be unreliable. There is therefore, a need for an objective measure of sedation and analgesia. The Bispectral Index (BIS) and Patient State Index (PSI) were recently introduced into clinical practice as objective measures of the depth of analgesia and sedation. ^ Aim. To compare the different measures of sedation and analgesia (BIS and PSI) to the standard and commonly used modified Ramsay Score (MRS) and determine if the monitors can be used interchangeably. ^ Methods. MRS, BIS and PSI values were obtained in 50 postoperative cardiac surgery patients requiring analgesia and sedation from June to December 2004. The MRS, BIS and PSI values were assessed hourly for up to 6-h by a single observer. ^ The relationship between BIS and PSI values were explored using scatter plots and correlation between MRS, BIS and PSI was determined using Spearman's correlation coefficient. Intra-class correlation (ICC) was used to determine the inter-rater reliability of MRS, BIS and PSI. Kappa statistics was used to further evaluate the agreement between BIS and PSI at light, moderate and deep levels of sedation. ^ Results. There was a positive correlation between BIS and PSI values (Rho = 0.731, p<0.001). Intra-class correlation between BIS and PSI was 0.58, MRS and BIS 0.43 and MRS and PSI 0.27. Using Kappa statistics, agreement between MRS and BIS was 0.35 (95% CI: 0.27–0.43) and for MRS and PSI was 0.21 (95% CI: 0.15–0.28). The kappa statistic for BIS and PSI was 0.45 (95% CI: 0.37–0.52). Receiver operating characteristics (ROC) curves constructed to detect undersedation indicated an area under the curve (AUC) of 0.91 (95% CI = 0.87 to 0.94) for the BIS and 0.84 (95% CI = 0.79 to 0.88) for the PSI. For detection of oversedation, AUC for the BIS was 0.89 (95% CI = 0.84 to 0.92) and 0.80 (95% CI = 0.75 to 0.85) for the PSI. ^ Conclusions. There is a statistically significant positive correlation between the BIS and PSI but poor correlation and poor test agreement between the MRS and BIS as well as MRS and PSI. Both the BIS and PSI demonstrated a high level of prediction for undersedation and oversedation; however, the BIS and PSI can not be considered interchangeable monitors of sedation. ^

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The role of physical activity in the promotion of individual and population health has been well documented in research and policy publications. Significant research activities have produced compelling evidence for the support of the positive association between physical activity and improved health. Despite the knowledge about these public health benefits of physical activity, over half of US adults do not engage in physical activity at levels consistent with public health recommendations. Just as physical inactivity is of significant public health concern in the US, the prevalence of obesity (and its attendant co-morbidities) is also increasing among US adults.^ Research suggests racial and ethnic disparities relevant to physical inactivity and obesity in the US. Various studies have shown more favorable outcomes among non-Hispanic whites when compared to other minority groups as far as physical activity and obesity are concerned. The health disparity issue is especially important because Mexican-Americans who are the fastest growing segment of the US population are disproportionately affected by physical inactivity and obesity by a significant margin (when compared to non-Hispanic whites), so addressing the physical inactivity and obesity issues in this group is of significant public health concern. ^ Although the evidence for health benefits of physical activity is substantial, various research questions remain on the potential motivators for engaging in physical activity. One area of emerging interest is the potential role that the built environment may play in facilitating or inhibiting physical activity.^ In this study, based on an ongoing research project of the Department of Epidemiology at the University of Texas M. D. Anderson Cancer Center, we examined the built environment, measured objectively through the use of geographical information systems (GIS), and its association with physical activity and obesity among a cohort of Mexican- Americans living in Harris County, Texas. The overall study hypothesis was that residing in dense and highly connected neighborhoods with mixed land-use is associated with residents’ increased participation in physical activity and lowered prevalence of obesity. We completed the following specific aims: (1) to generate a land-use profile of the study area and create a “walkability index” measure for each block group within the study area; (2) to compare the level of engagement in physical activity between study participants that reside in high walkability index block groups and those from low walkability block groups; (3) to compare the prevalence of obesity between study participants that reside in high walkability index block groups and those from low walkability block groups. ^ We successfully created the walkability index as a form of objective measure of the built environment for portions of Harris County, Texas. We used a variety of spatial and non-spatial dataset to generate the so called walkability index. We are not aware of previous scholastic work of this kind (construction of walkability index) in the Houston area. Our findings from the assessment of relationships among walkability index, physical activity and obesity suggest the following, that: (1) that attempts to convert people to being walkers through health promotion activities may be much easier in high-walkability neighborhoods, and very hard in low-walkability neighborhoods. Therefore, health promotion activities to get people to be active may require supportive environment, walkable in this case, and may not succeed otherwise; and (2) Overall, among individuals with less education, those in the high walkability index areas may be less obese (extreme) than those in the low walkability area. To the extent that this association can be substantiated, we – public health practitioners, urban designers, and policy experts – we may need to start thinking about ways to “retrofit” existing urban forms to conform to more walkable neighborhoods. Also, in this population especially, there may be the need to focus special attention on those with lower educational attainment.^