Haemodynamic variables and functional outcome in hypothermic patients following out-of-hospital cardiac arrest

To evaluate the association between haemodynamic variables during the first 24h after intensive care unit (ICU) admission and neurological outcome in out-of-hospital cardiac arrest (OHCA) victims undergoing therapeutic hypothermia.

OUT-OF-STEP DETECTION BASED ON ZUBOV’S APPROXIMATION BOUNDARY METHOD

Disturbances in power systems may lead to electromagnetic transient oscillations due to mismatch of mechanical input power and electrical output power. Out-of-step conditions in power system are common after the disturbances where the continuous oscillations do not damp out and the system becomes unstable. Existing out-of-step detection methods are system specific as extensive off-line studies are required for setting of relays. Most of the existing algorithms also require network reduction techniques to apply in multi-machine power systems. To overcome these issues, this research applies Phasor Measurement Unit (PMU) data and Zubov’s approximation stability boundary method, which is a modification of Lyapunov’s direct method, to develop a novel out-of-step detection algorithm. The proposed out-of-step detection algorithm is tested in a Single Machine Infinite Bus system, IEEE 3-machine 9-bus, and IEEE 10-machine 39-bus systems. Simulation results show that the proposed algorithm is capable of detecting out-of-step conditions in multi-machine power systems without using network reduction techniques and a comparative study with an existing blinder method demonstrate that the decision times are faster. The simulation case studies also demonstrate that the proposed algorithm does not depend on power system parameters, hence it avoids the need of extensive off-line system studies as needed in other algorithms.

The Getting-Out-of-Bed (GoB) scale: a measure of motivation and life outlook in older adults with cancer

OBJECTIVE: To develop and evaluate the psychometric properties of a measure of motivation and life outlook (Getting-Out-of-Bed [GoB]). DESIGN: Secondary analysis of baseline and 6-month data from a longitudinal follow-up study of older breast cancer survivors. PARTICIPANTS: Women (N = 660) diagnosed with primary breast cancer stage I-IIIA disease, age >or=65 years, and permission to contact from an attending physician in four geographic regions in the United States (city-based Los Angeles, California; statewide in Minnesota, North Carolina, and Rhode Island). MEASUREMENT: Data were collected over 6-months of follow-up from consenting patients' medical records and telephone interviews with patients. Data collected included the 4-item GoB, health-related quality of life (HRQoL), breast cancer, sociodemographic, and health-related characteristics. RESULTS: Factor analysis produced, as hypothesized, one principal component with eigen values of 2.74(baseline) and 2.91(6-months) which explained 68.6%(baseline) and 72.7%(6-months) of total variance. In further psychometric analyses, GoB exhibited good construct validity (divergent: low nonstatistically significant correlations with unrelated constructs; convergent: moderate statistically significant correlations with related constructs; discriminant: distinguished high HRQoL groups with a high level of significance), excellent internal reliability (Cronbach's alpha 0.84(baseline), 0.87(6-months)), and produced stable measurements over 6-months. Women with GoB scores >or=50 at baseline were more likely at 6-months to have good HRQoL, good self-perceived health, and report regular exercise, indicating good predictive ability. CONCLUSION: GoB demonstrated overall good psychometric properties in this sample of older breast cancer survivors, suggestive of a promising tool for assessing motivation and life outlook in older adults. Nevertheless, because it was developed and initially evaluated in a select sample, using measures with similar but not exact content overlap further evaluation is needed before it can be recommended for widespread use.