A clinical prediction model to identify patients at high risk of death in the emergency department.

PURPOSE Rapid assessment and intervention is important for the prognosis of acutely ill patients admitted to the emergency department (ED). The aim of this study was to prospectively develop and validate a model predicting the risk of in-hospital death based on all available information available at the time of ED admission and to compare its discriminative performance with a non-systematic risk estimate by the triaging first health-care provider. METHODS Prospective cohort analysis based on a multivariable logistic regression for the probability of death. RESULTS A total of 8,607 consecutive admissions of 7,680 patients admitted to the ED of a tertiary care hospital were analysed. Most frequent APACHE II diagnostic categories at the time of admission were neurological (2,052, 24 %), trauma (1,522, 18 %), infection categories [1,328, 15 %; including sepsis (357, 4.1 %), severe sepsis (249, 2.9 %), septic shock (27, 0.3 %)], cardiovascular (1,022, 12 %), gastrointestinal (848, 10 %) and respiratory (449, 5 %). The predictors of the final model were age, prolonged capillary refill time, blood pressure, mechanical ventilation, oxygen saturation index, Glasgow coma score and APACHE II diagnostic category. The model showed good discriminative ability, with an area under the receiver operating characteristic curve of 0.92 and good internal validity. The model performed significantly better than non-systematic triaging of the patient. CONCLUSIONS The use of the prediction model can facilitate the identification of ED patients with higher mortality risk. The model performs better than a non-systematic assessment and may facilitate more rapid identification and commencement of treatment of patients at risk of an unfavourable outcome.

Reliable prediction of clinical outcome in patients with chronic HCV infection and compensated advanced hepatic fibrosis: a validated model using objective and readily available clinical parameters.

OBJECTIVE Reliable tools to predict long-term outcome among patients with well compensated advanced liver disease due to chronic HCV infection are lacking. DESIGN Risk scores for mortality and for cirrhosis-related complications were constructed with Cox regression analysis in a derivation cohort and evaluated in a validation cohort, both including patients with chronic HCV infection and advanced fibrosis. RESULTS In the derivation cohort, 100/405 patients died during a median 8.1 (IQR 5.7-11.1) years of follow-up. Multivariate Cox analyses showed age (HR=1.06, 95% CI 1.04 to 1.09, p<0.001), male sex (HR=1.91, 95% CI 1.10 to 3.29, p=0.021), platelet count (HR=0.91, 95% CI 0.87 to 0.95, p<0.001) and log10 aspartate aminotransferase/alanine aminotransferase ratio (HR=1.30, 95% CI 1.12 to 1.51, p=0.001) were independently associated with mortality (C statistic=0.78, 95% CI 0.72 to 0.83). In the validation cohort, 58/296 patients with cirrhosis died during a median of 6.6 (IQR 4.4-9.0) years. Among patients with estimated 5-year mortality risks <5%, 5-10% and >10%, the observed 5-year mortality rates in the derivation cohort and validation cohort were 0.9% (95% CI 0.0 to 2.7) and 2.6% (95% CI 0.0 to 6.1), 8.1% (95% CI 1.8 to 14.4) and 8.0% (95% CI 1.3 to 14.7), 21.8% (95% CI 13.2 to 30.4) and 20.9% (95% CI 13.6 to 28.1), respectively (C statistic in validation cohort = 0.76, 95% CI 0.69 to 0.83). The risk score for cirrhosis-related complications also incorporated HCV genotype (C statistic = 0.80, 95% CI 0.76 to 0.83 in the derivation cohort; and 0.74, 95% CI 0.68 to 0.79 in the validation cohort). CONCLUSIONS Prognosis of patients with chronic HCV infection and compensated advanced liver disease can be accurately assessed with risk scores including readily available objective clinical parameters.

Bilateral uterine vessel ligation as a model of intrauterine growth restriction in mice

BACKGROUND Intrauterine growth restriction (IUGR) occurs in up to 10% of pregnancies and is considered as a major risk to develop various diseases in adulthood, such as cardiovascular diseases, insulin resistance, hypertension or end stage kidney disease. Several IUGR models have been developed in order to understand the biological processes linked to fetal growth retardation, most of them being rat or mouse models and nutritional models. In order to reproduce altered placental flow, surgical models have also been developed, and among them bilateral uterine ligation has been frequently used. Nevertheless, this model has never been developed in the mouse, although murine tools display multiple advantages for biological research. The aim of this work was therefore to develop a mouse model of bilateral uterine ligation as a surgical model of IUGR. RESULTS In this report, we describe the set up and experimental data obtained from three different protocols (P1, P2, P3) of bilateral uterine vessel ligation in the mouse. Ligation was either performed at the cervical end of each uterine horn (P1) or at the central part of each uterine horn (P2 and P3). Time of surgery was E16 (P1), E17 (P2) or E16.5 (P3). Mortality, maternal weight and abortion parameters were recorded, as well as placentas weights, fetal resorption, viability, fetal weight and size. Results showed that P1 in test animals led to IUGR but was also accompanied with high mortality rate of mothers (50%), low viability of fetuses (8%) and high resorption rate (25%). P2 and P3 improved most of these parameters (decreased mortality and improved pregnancy outcomes; improved fetal viability to 90% and 27%, respectively) nevertheless P2 was not associated to IUGR contrary to P3. Thus P3 experimental conditions enable IUGR with better pregnancy and fetuses outcomes parameters that allow its use in experimental studies. CONCLUSIONS Our results show that bilateral uterine artery ligation according to the protocol we have developed and validated can be used as a surgical mouse model of IUGR.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

Articulated Statistical Shape Model-Based 2D-3D Reconstruction of a Hip Joint

In this paper, reconstruction of three-dimensional (3D) patient-specific models of a hip joint from two-dimensional (2D) calibrated X-ray images is addressed. Existing 2D-3D reconstruction techniques usually reconstruct a patient-specific model of a single anatomical structure without considering the relationship to its neighboring structures. Thus, when those techniques would be applied to reconstruction of patient-specific models of a hip joint, the reconstructed models may penetrate each other due to narrowness of the hip joint space and hence do not represent a true hip joint of the patient. To address this problem we propose a novel 2D-3D reconstruction framework using an articulated statistical shape model (aSSM). Different from previous work on constructing an aSSM, where the joint posture is modeled as articulation in a training set via statistical analysis, here it is modeled as a parametrized rotation of the femur around the joint center. The exact rotation of the hip joint as well as the patient-specific models of the joint structures, i.e., the proximal femur and the pelvis, are then estimated by optimally fitting the aSSM to a limited number of calibrated X-ray images. Taking models segmented from CT data as the ground truth, we conducted validation experiments on both plastic and cadaveric bones. Qualitatively, the experimental results demonstrated that the proposed 2D-3D reconstruction framework preserved the hip joint structure and no model penetration was found. Quantitatively, average reconstruction errors of 1.9 mm and 1.1 mm were found for the pelvis and the proximal femur, respectively.

Is the acetabular cup orientation after total hip arthroplasty on a two dimension or three dimension model accurate?

Purpose Malposition of the acetabular component in total hip arthroplasty (THA) is a common surgical problem that can lead to hip dislocation, reduced range of motion and may result in early loosening. The aim of this study is to validate the accuracy and reproducibility of a single x-ray image based 2D/3D reconstruction technique in determining cup inclination and anteversion against two different computer tomography (CT)-based measurement techniques. Methods Cup anteversion and inclination of 20 patients after cementless primary THA was measured on standard anteroposterior (AP) radiographs with the help of the single x-ray 2D/3D reconstruction program and compared with two different 3D CT-based analyses [Ground Truth (GT) and MeVis (MV) reconstruction model]. Results The measurements from the single x-ray 2D/3D reconstruction technique were strongly correlated with both types of CT image-processing protocols for both cup inclination [R²=0.69 (GT); R²=0.59 (MV)] and anteversion [R²=0.89 (GT); R²=0.80 (MV)]. Conclusions The single x-ray image based 2D/3D reconstruction technique is a feasible method to assess cup position on postoperative x-rays. CTscans remain the golden standard for a more complex biomechanical evaluation when a lower tolerance limit (+/-2 degrees) is required.

Investigation of retinal morphology alterations using spectral domain optical coherence tomography in a mouse model of retinal branch and central retinal vein occlusion.

Retinal vein occlusion is a leading cause of visual impairment. Experimental models of this condition based on laser photocoagulation of retinal veins have been described and extensively exploited in mammals and larger rodents such as the rat. However, few reports exist on the use of this paradigm in the mouse. The objective of this study was to investigate a model of branch and central retinal vein occlusion in the mouse and characterize in vivo longitudinal retinal morphology alterations using spectral domain optical coherence tomography. Retinal veins were experimentally occluded using laser photocoagulation after intravenous application of Rose Bengal, a photo-activator dye enhancing thrombus formation. Depending on the number of veins occluded, variable amounts of capillary dropout were seen on fluorescein angiography. Vascular endothelial growth factor levels were markedly elevated early and peaked at day one. Retinal thickness measurements with spectral domain optical coherence tomography showed significant swelling (p<0.001) compared to baseline, followed by gradual thinning plateauing two weeks after the experimental intervention (p<0.001). Histological findings at day seven correlated with spectral domain optical coherence tomography imaging. The inner layers were predominantly affected by degeneration with the outer nuclear layer and the photoreceptor outer segments largely preserved. The application of this retinal vein occlusion model in the mouse carries several advantages over its use in other larger species, such as access to a vast range of genetically modified animals. Retinal changes after experimental retinal vein occlusion in this mouse model can be non-invasively quantified by spectral domain optical coherence tomography, and may be used to monitor effects of potential therapeutic interventions.

Multi-Model Data Fusion to Improve an Early Warning System for Hypo-/Hyperglycemic Events

Correct predictions of future blood glucose levels in individuals with Type 1 Diabetes (T1D) can be used to provide early warning of upcoming hypo-/hyperglycemic events and thus to improve the patient's safety. To increase prediction accuracy and efficiency, various approaches have been proposed which combine multiple predictors to produce superior results compared to single predictors. Three methods for model fusion are presented and comparatively assessed. Data from 23 T1D subjects under sensor-augmented pump (SAP) therapy were used in two adaptive data-driven models (an autoregressive model with output correction - cARX, and a recurrent neural network - RNN). Data fusion techniques based on i) Dempster-Shafer Evidential Theory (DST), ii) Genetic Algorithms (GA), and iii) Genetic Programming (GP) were used to merge the complimentary performances of the prediction models. The fused output is used in a warning algorithm to issue alarms of upcoming hypo-/hyperglycemic events. The fusion schemes showed improved performance with lower root mean square errors, lower time lags, and higher correlation. In the warning algorithm, median daily false alarms (DFA) of 0.25%, and 100% correct alarms (CA) were obtained for both event types. The detection times (DT) before occurrence of events were 13.0 and 12.1 min respectively for hypo-/hyperglycemic events. Compared to the cARX and RNN models, and a linear fusion of the two, the proposed fusion schemes represents a significant improvement.

Hemodynamic Performance of Edwards Intuity Valve in a Compliant Aortic Root Model

Numerous designs of bioprosthetic valves exist. The sutureless surgical valve is a newer design concept which combines elements of the transcatheter valve technology with surgical valves. This design aims at shorter and easier implantation. It was the aim of this study to perform hemodynamic and kinematic measurements for this type of valves to serve as a baseline for following studies which investigate the effect of the aortic root on the valve performance. To this end, the Edwards Intuity aortic valve was investigated in a new in vitro flow loop mimicking the left heart. The valve was implanted in a transparent, compliant aortic root model, and the valve kinematics was investigated using a high speed camera together with synchronized hemodynamic measurements of pressures and flows. The valve closure was asynchronous (one by one leaflet), and the valve started to close before the deceleration of the fluid. The aortic root model showed a dilation of the sinuses which was different to the ascending aorta, and the annulus was found to move towards the left ventricle during diastole and towards the aorta during systole.

No sports – no mental health? Analysis of longitudinal effects in SHP data.

Results from the Zurich study have shown lasting associations between sport practice and mental health. The effects are pronounced in people with pre-exising mental health problems. This analysis aims to replicate these results with the large Swiss Household Panel data set and to provide more differentiated results. The analysis covered the interviews 1999-2003 and included 3891 stayers, i.e., participants who were interviewed in all years. The outcome variables are depression / blues / anxiety, weakness / weariness, sleeping problems, energy / optimism. Confounding variables include sex, age, education level, citizenship. The analyses were carried out with mixed models (depression, optimism) and GEE models (weakness, sleep). About 60% of the SHP participants practise weekly or daily an individual or a team sport. A similar proportion enjoys a frequent physical activity (for half an hour minimum) which makes oneself slightly breathless. There are slight age-specific differences but also noteworthy regional differences. Practice of sport is clearly interrelated with self-reported depressive symptoms, optimism and weakness. This applies even though some relevant confounders – sex, educational level and citizenship – were introduced into the model. However, no relevant interaction effects with time could be shown. Moreover, direct interrelations commonly led to better fits than models with lagged variables, thus indicating that delayed effects of sport practice on the self-reported psychological complaints are less important. Model variants resulted for specific subgroups, for example, participants with a high vs. low initial activity level. Lack of sport practice is an interesting marker for serious psychological symptoms and mental disorders. The background of this association may differ in different subgroups, and should stimulate further investigations in this area.

Estimating the prevalence of comorbid conditions and their effect on health care costs in patients with diabetes mellitus in Switzerland.

BACKGROUND Estimating the prevalence of comorbidities and their associated costs in patients with diabetes is fundamental to optimizing health care management. This study assesses the prevalence and health care costs of comorbid conditions among patients with diabetes compared with patients without diabetes. Distinguishing potentially diabetes- and nondiabetes-related comorbidities in patients with diabetes, we also determined the most frequent chronic conditions and estimated their effect on costs across different health care settings in Switzerland. METHODS Using health care claims data from 2011, we calculated the prevalence and average health care costs of comorbidities among patients with and without diabetes in inpatient and outpatient settings. Patients with diabetes and comorbid conditions were identified using pharmacy-based cost groups. Generalized linear models with negative binomial distribution were used to analyze the effect of comorbidities on health care costs. RESULTS A total of 932,612 persons, including 50,751 patients with diabetes, were enrolled. The most frequent potentially diabetes- and nondiabetes-related comorbidities in patients older than 64 years were cardiovascular diseases (91%), rheumatologic conditions (55%), and hyperlipidemia (53%). The mean total health care costs for diabetes patients varied substantially by comorbidity status (US$3,203-$14,223). Patients with diabetes and more than two comorbidities incurred US$10,584 higher total costs than patients without comorbidity. Costs were significantly higher in patients with diabetes and comorbid cardiovascular disease (US$4,788), hyperlipidemia (US$2,163), hyperacidity disorders (US$8,753), and pain (US$8,324) compared with in those without the given disease. CONCLUSION Comorbidities in patients with diabetes are highly prevalent and have substantial consequences for medical expenditures. Interestingly, hyperacidity disorders and pain were the most costly conditions. Our findings highlight the importance of developing strategies that meet the needs of patients with diabetes and comorbidities. Integrated diabetes care such as used in the Chronic Care Model may represent a useful strategy.

In vitro-ex vivo model systems for nanosafety assessment

Engineered nanomaterials have unique and novel properties enabling wide-ranging new applications in nearly all fields of research. As these new properties have raised concerns about potential adverse effects for the environment and human health, extensive efforts are underway to define reliable, cost- and time-effective, as well as mechanistic-based testing strategies to replace the current method of animal testing, which is still the most prevalent model used for the risk assessment of chemicals. Current approaches for nanomaterials follow this line. The aim of this review is to explore and qualify the relevance of new in vitro and ex vivo models in (nano)material safety assessment, a crucial prerequisite for translation into applications.

Fluid-structure interaction of an elastic pipe immersed inside a coaxial rigid pipe: a model for the Tullio phenomenon

An axisymmetric, elastic pipe is filled with an incompressible fluid and is immersed in a second, coaxial rigid pipe which contains the same fluid. A pressure pulse in the outer fluid annulus deforms the elastic pipe which invokes a fluid motion in the fluid core. It is the aim of this study to investigate streaming phenomena in the core which may originate from such a fluid-structure interaction. This work presents a numerical solver for such a configuration. It was developed in the OpenFOAM software environment and is based on the Arbitrary Lagrangian Eulerian (ALE) approach for moving meshes. The solver features a monolithic integration of the one-dimensional, coupled system between the elastic structure and the outer fluid annulus into a dynamic boundary condition for the moving surface of the fluid core. Results indicate that our configuration may serve as a mechanical model of the Tullio Phenomenon (sound-induced vertigo).