Additional file 1: of The feasibility and efficacy of implementing a focused cardiac ultrasound course into a medical school curriculum

Appendix A. (DOCX 92 kb

Mortality rates stratified by the score.

<p>For each abnormal result in admission laboratory test (urea≥43 mg/dL, sodium<136 meq/L and albumin<3.5 g/dL) one point was assigned. Patient population was stratified by the total combined score. Mortality rates presented for derivation cohort (3 hospitals, 3,941 subjects) and validation cohort (4 hospitals, 4,305 subjects).</p

Odds ratios of laboratory values for 30-day all cause mortality.

<p>Five categorized laboratory tests found to be significant in the multivariable analysis as continuous variables are presented.</p

Calibration plot for 30-days and 1-year mortality.

<p>Model included laboratory tests, demographics and comorbidities.</p

Kaplan-Meier curves for one-year mortality according to risk points.

<p>For each abnormal result in admission laboratory test (urea≥43 mg/dL, sodium<136 meq/L and albumin<3.5 g/dL) one point was assigned. Patient population was stratified by the total combined score. Log-rank test, p<0.001.</p

Calibration and Discrimination of the logistic regression models.

<p>*-adjusted for pre-hospitalization use of angiotensin-converting enzyme inhibitors, angiotensin receptors blockers, β-blockers, statins, spironolactone, digoxin and diuretics.</p><p>Laboratory tests include albumin, urea, sodium, uric acid and WBC.</p

Odds ratios of laboratory values for one-year all cause mortality.

<p>Five categorized laboratory tests found to be significant in the multivariable analysis as continuous variables are presented.</p

Baseline characteristics of the patient population.

<p>Baseline characteristics of the patient population.</p

On the significance of high spatial resolution to capture all relevant scales in the turbulent flow over periodic hills

Due to the complex nature of turbulence, the simulation of turbulent flows is still challenging and numerical models have to be further improved. For the validation of these numerical flow simulation methods reliable experimental data is essential as the simulation can only be more precise than the validation data but never be more accurate. However, for the correct numerical prediction of flows, the accuracy is the essential quantity. A typical test case is the flow over periodic hills. The numerical prediction is difficult, since flow separation and reattachment are not fixed in space and time due to the smooth geometry [10, 2]. Furthermore, the separated and fully three-dimensional flow from the previous hill impinges on the next hill, which will result in very complex turbulent flow features as shown in Fig. 1 on the left side. With the increasing computer performance available, it becomes possible to examine larger Reynolds numbers with DNS and LES. Typical grid sizes are in the order of several (3-10) Kolmogorov length scales h for LES and approach h for DNS [1]. The resolution of currently available measurements is in the order of 30 h (Re = 8,000) and above which is not sufficient to resolve the large gradients in the shear layer at the hill crest for instance. Even more severe, the contribution of the small eddies is averaged over a region associated with the measurement resolution. Thus an important part of the turbulent energy cannot be measured at all and is lost for the validation of turbulence models. Since these models are supposed to simulate the contribution of these small eddies it is of inherent interest to increase the resolution in the experiment. The aim of the current measurement campaign was therefore to increase the spatial resolution in order to study the resolution effect systematically and to provide an additional data set for the validation of numerical tools

Clinical outcomes (n = 7265).

<p>LOS length of stay; ICU intensive care unit.</p