Increasing frailty is associated with higher prevalence and reduced recognition of delirium in older hospitalised inpatients: results of a multi-centre study

Purpose Delirium is a neuropsychiatric disorder delineated by an acute change in cognition, attention, and consciousness. It is common, particularly in older adults, but poorly recognised. Frailty is the accumulation of deficits conferring an increased risk of adverse outcomes. We set out to determine how severity of frailty, as measured using the CFS, affected delirium rates, and recognition in hospitalised older people in the United Kingdom. Methods Adults over 65 years were included in an observational multi-centre audit across UK hospitals, two prospective rounds, and one retrospective note review. Clinical Frailty Scale (CFS), delirium status, and 30-day outcomes were recorded. Results The overall prevalence of delirium was 16.3% (483). Patients with delirium were more frail than patients without delirium (median CFS 6 vs 4). The risk of delirium was greater with increasing frailty [OR 2.9 (1.8–4.6) in CFS 4 vs 1–3; OR 12.4 (6.2–24.5) in CFS 8 vs 1–3]. Higher CFS was associated with reduced recognition of delirium (OR of 0.7 (0.3–1.9) in CFS 4 compared to 0.2 (0.1–0.7) in CFS 8). These risks were both independent of age and dementia. Conclusion We have demonstrated an incremental increase in risk of delirium with increasing frailty. This has important clinical implications, suggesting that frailty may provide a more nuanced measure of vulnerability to delirium and poor outcomes. However, the most frail patients are least likely to have their delirium diagnosed and there is a significant lack of research into the underlying pathophysiology of both of these common geriatric syndromes

Application of global regression method for calibration of wind tunnel balances

Aerodynamic forces and moments on scaled models are measured in wind tunnels by multi-component strain gauge balances whose performance and accuracy are characterized by careful calibrations. It is well recognized that calibration loads that are representative of the combined loads experienced by the balance/model in wind tunnel test conditions lead to high accuracy of the measured loads. But, in the traditional method the calibration loads are restricted to single-component and two component loads that are unrepresentative of model loads. A recently developed method called Global Regression Method (GRM)places no such restrictions and therefore, permits application of multi-component calibration loads similar to model loads, leading to improved accuracy of measured loads. In addition, with use of GRM it is possible to substantially reduce the number of calibration loads and hence, the calibration effort by optimization of load schedule. The GRM was recently implemented and a MATLAB software developed for balance calibration data analysis at NAL. In order to illustrate the application of GRM and use of the computer program calibrations of a 6-component internal balance were carried out with different types and number of calibration loads that included combined loads similar to model loads and the data were analyzed using GRM. The balance accuracy was assessed for a set of check loads consisting primarily of combined loads. Results showed that the accuracy when the calibration loads were similar to model loads was significantly better than that obtained using single- and two–component calibration loads. It was also found that improved accuracy could be obtained with substantially reduced number of loadings. The paper presents an overview of the GRM and brief details of application of the GRM to calibration of multicomponent balances. A description of the above calibrations and discussions of the results are included

Statistical Analysis of Repeat Test Results for Assessment of Wind Tunnel Data Quality

A methodology for quantifying wind tunnel data quality from repeat tests is described. The methodology largely adopts the measurement uncertainty concepts and statistical analysis techniques recommended by AIAA Standards. Repeatability quality of measurements is quantified in terms of three statistical parameters viz., precision limit (or random uncertainty), tolerance interval and precision interval. A description of the methods used for determining these statistical parameters is given. A computer program developed to facilitate routine application of the above analysis to repeat test data obtained in the NAL 1.2m and 0.6m wind tunnels is described. To illustrate the application of the above methodology and use of the computer program an analysis of longitudinal aerodynamic data obtained from repeat tests on a typical fighter aircraft model in the 1.2m tunnel has been made. Results of this analysis along with a discussion of the same, and a comparison with similar results obtained on a commercial transport airplane configuration in the NASA 2.5m cryogenic tunnel are included in the report

Wind tunnel simulation of multibooster separation trajectories of a launch vehicle13;

Wind tunnel investigations were undertaken to study the separation characteristics of four strap-on boosters simultaneously separating from the core of a launch vehicle. Tests were conducted in the NAL 1.2-m trisonic blowdown wind tunnel at a freestream Mach number of 3.1 and a test Reynolds number of 30.5amp;times. Force data from all the four boosters were obtained for a range of pitch angles between -3 and 3 deg. Data corresponding to the highest value of the pitch angle in flight were utilized for the trajectory computation

Analysis of unsteady pressure measurements on a supercritical airfoil with a harmonically oscillating trailing edge flap at subsonic and transonic speeds

With 35 figs., 2 tabs. and 13 refs.Copy held by FIZ Karlsruhe; available from UB/TIB Hannover / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEDEGerman