A Stratified Model for Psychosis Prediction in Clinical Practice

Objective: Impaired cognition is an important dimension in psychosis and its at-risk states. Research on the value of impaired cognition for psychosis prediction in at-risk samples, however, mainly relies on study-specific sample means of neurocognitive tests, which unlike widely available general test norms are difficult to translate into clinical practice. The aim of this study was to explore the combined predictive value of at-risk criteria and neurocognitive deficits according to test norms with a risk stratification approach. Method: Potential predictors of psychosis (neurocognitive deficits and at-risk criteria) over 24 months were investigated in 97 at-risk patients. Results: The final prediction model included (1) at-risk criteria (attenuated psychotic symptoms plus subjective cognitive disturbances) and (2) a processing speed deficit (digit symbol test). The model was stratified into 4 risk classes with hazard rates between 0.0 (both predictors absent) and 1.29 (both predictors present). Conclusions: The combination of a processing speed deficit and at-risk criteria provides an optimized stratified risk assessment. Based on neurocognitive test norms, the validity of our proposed 3 risk classes could easily be examined in independent at-risk samples and, pending positive validation results, our approach could easily be applied in clinical practice in the future.

Science to practice: Can diffusion-weighted MR imaging findings be used as biomarkers to monitor the progression of renal fibrosis?

In an experimental murine model of unilateral ureteral obstruction, Togao et al demonstrated that diffusion-weighted (DW) magnetic resonance (MR) imaging can depict and enable monitoring of abnormal changes in the progression of renal fibrosis; because these microstructural changes are complex and multifactorial, future studies focused on their specificity should be performed before they are applied in clinical trials.

Functional Imaging of Pheochromocytoma with Ga-DOTATOC and C-HED in a Genetically Defined Rat Model of Multiple Endocrine Neoplasia

Rats affected by the MENX multitumor syndrome develop pheochromocytoma (100%). Pheochromocytomas are uncommon tumors and animal models are scarce, hence the interest in MENX rats to identify and preclinically evaluate novel targeted therapies. A prerequisite for such studies is a sensitive and noninvasive detection of MENXassociated pheochromocytoma. We performed positron emission tomography (PET) to determine whether rat pheochromocytomas are detected by tracers used in clinical practice, such as 68Ga-DOTATOC (somatostatin analogue) or (11)C-Hydroxyephedrine (HED), a norepinephrine analogue. We analyzed four affected and three unaffected rats. The PET scan findings were correlated to histopathology and immunophenotype of the tumors, their proliferative index, and the expression of genes coding for somatostatin receptors or the norepinephrine transporter. We observed that mean 68Ga-DOTATOC standard uptake value (SUV) in adrenals of affected animals was 23.3 ± 3.9, significantly higher than in control rats (15.4 ± 7.9; P = .03). The increase in mean tumor-to-liver ratio of (11)C-HED in the MENX-affected animals (1.6 ± 0.5) compared to controls (0.7 ± 0.1) was even more significant (P = .0016). In a unique animal model, functional imaging depicting two pathways important in pheochromocytoma biology discriminated affected animals from controls, thus providing the basis for future preclinical work with MENX rats.

The SURTAVI model: proposal for a pragmatic risk stratification for patients with severe aortic stenosis

Transcatheter aortic valve implantation (TAVI) is a less invasive alternative to surgical aortic valve replacement (SAVR) for patients with symptomatic severe aortic stenosis (AS) and a high operative risk. Risk stratification plays a decisive role in the optimal selection of therapeutic strategies for AS patients. The accuracy of contemporary surgical risk algorithms for AS patients has spurred considerable debate especially in the higher risk patient population. Future trials will explore TAVI in patients at intermediate operative risk. During the design of the SURgical replacement and Transcatheter Aortic Valve Implantation (SURTAVI) trial, a novel concept of risk stratification was proposed based upon age in combination with a fixed number of predefined risk factors, which are relatively prevalent, easy to capture and with a reasonable impact on operative mortality. Retrospective application of this algorithm to a contemporary academic practice dealing with clinically significant AS patients allocates about one-fourth of these patients as being at intermediate operative risk. Further testing is required for validation of this new paradigm in risk stratification. Finally, the Heart Team, consisting of at least an interventional cardiologist and cardiothoracic surgeon, should have the decisive role in determining whether a patient could be treated with TAVI or SAVR.

Pathology hinting as the combination of automatic segmentation with a statistical shape model

With improvements in acquisition speed and quality, the amount of medical image data to be screened by clinicians is starting to become challenging in the daily clinical practice. To quickly visualize and find abnormalities in medical images, we propose a new method combining segmentation algorithms with statistical shape models. A statistical shape model built from a healthy population will have a close fit in healthy regions. The model will however not fit to morphological abnormalities often present in the areas of pathologies. Using the residual fitting error of the statistical shape model, pathologies can be visualized very quickly. This idea is applied to finding drusen in the retinal pigment epithelium (RPE) of optical coherence tomography (OCT) volumes. A segmentation technique able to accurately segment drusen in patients with age-related macular degeneration (AMD) is applied. The segmentation is then analyzed with a statistical shape model to visualize potentially pathological areas. An extensive evaluation is performed to validate the segmentation algorithm, as well as the quality and sensitivity of the hinting system. Most of the drusen with a height of 85.5 microm were detected, and all drusen at least 93.6 microm high were detected.

The well-being model: a new drug interaction model for positive and negative effects

BACKGROUND: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. METHODS: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs. RESULTS: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. CONCLUSIONS: The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

Effectiveness, safety and cost-effectiveness of homeopathy in general practice - summarized health technology assessment

Introduction: The Health Technology Assessment report on effectiveness, cost-effectiveness and appropriateness of homeopathy was compiled on behalf of the Swiss Federal Office for Public Health (BAG) within the framework of the 'Program of Evaluation of Complementary Medicine (PEK)'. Materials and Methods: Databases accessible by Internet were systematically searched, complemented by manual search and contacts with experts, and evaluated according to internal and external validity criteria. Results: Many high-quality investigations of pre-clinical basic research proved homeopathic high-potencies inducing regulative and specific changes in cells or living organisms. 20 of 22 systematic reviews detected at least a trend in favor of homeopathy. In our estimation 5 studies yielded results indicating clear evidence for homeopathic therapy. The evaluation of 29 studies in the domain 'Upper Respiratory Tract Infections/Allergic Reactions' showed a positive overall result in favor of homeopathy. 6 out of 7 controlled studies were at least equivalent to conventional medical interventions. 8 out of 16 placebocontrolled studies were significant in favor of homeopathy. Swiss regulations grant a high degree of safety due to product and training requirements for homeopathic physicians. Applied properly, classical homeopathy has few side-effects and the use of high-potencies is free of toxic effects. A general health-economic statement about homeopathy cannot be made from the available data. Conclusion: Taking internal and external validity criteria into account, effectiveness of homeopathy can be supported by clinical evidence and professional and adequate application be regarded as safe. Reliable statements of cost-effectiveness are not available at the moment. External and model validity will have to be taken more strongly into consideration in future studies.

Drug-induced respiratory depression: an integrated model of drug effects on the hypercapnic and hypoxic drive

Drug-induced respiratory depression is a common side effect of the agents used in anesthesia practice to provide analgesia and sedation. Depression of the ventilatory drive in the spontaneously breathing patient can lead to severe cardiorespiratory events and it is considered a primary cause of morbidity. Reliable predictions of respiratory inhibition in the clinical setting would therefore provide a valuable means to improve the safety of drug delivery. Although multiple studies investigated the regulation of breathing in man both in the presence and absence of ventilatory depressant drugs, a unified description of respiratory pharmacodynamics is not available. This study proposes a mathematical model of human metabolism and cardiorespiratory regulation integrating several isolated physiological and pharmacological aspects of acute drug-induced ventilatory depression into a single theoretical framework. The description of respiratory regulation has a parsimonious yet comprehensive structure with substantial predictive capability. Simulations relative to the synergistic interaction of the hypercarbic and hypoxic respiratory drive and the global effect of drugs on the control of breathing are in good agreement with published experimental data. Besides providing clinically relevant predictions of respiratory depression, the model can also serve as a test bed to investigate issues of drug tolerability and dose finding/control under non-steady-state conditions.

Synergy between trovafloxacin and ceftriaxone against penicillin-resistant pneumococci in the rabbit meningitis model and in vitro

The bactericidal activities of monotherapy with trovafloxacin (-0.37 +/- 0.15 Delta log(10) CFU/ml. h), vancomycin (-0.32 +/- 0.12 Delta log(10) CFU/ml. h), and ceftriaxone (-0.36 +/- 0.19 Delta log(10) CFU/ml. h) for the treatment of experimental meningitis in rabbits due to a clinical penicillin-resistant pneumococcal strain (MIC, 4 mg/liter) were similar. The combination of ceftriaxone with trovafloxacin considerably improved the killing rates (-0.67 +/- 0.16 Delta log(10) CFU/ml. h) and was slightly superior to ceftriaxone with vancomycin (killing rate, -0.53 +/- 0. 22 Delta log(10) CFU/ml. h), the regimen most commonly used in clinical practice. In vitro, synergy was demonstrated between ceftriaxone and trovafloxacin by the checkerboard method (fractional inhibitory concentration index, 0.5) and by time-killing assays over 8 h.

A continuous-time MILP model for short-term scheduling of make-and-pack production processes

In process industries, make-and-pack production is used to produce food and beverages, chemicals, and metal products, among others. This type of production process allows the fabrication of a wide range of products in relatively small amounts using the same equipment. In this article, we consider a real-world production process (cf. Honkomp et al. 2000. The curse of reality – why process scheduling optimization problems are diffcult in practice. Computers & Chemical Engineering, 24, 323–328.) comprising sequence-dependent changeover times, multipurpose storage units with limited capacities, quarantine times, batch splitting, partial equipment connectivity, and transfer times. The planning problem consists of computing a production schedule such that a given demand of packed products is fulfilled, all technological constraints are satisfied, and the production makespan is minimised. None of the models in the literature covers all of the technological constraints that occur in such make-and-pack production processes. To close this gap, we develop an efficient mixed-integer linear programming model that is based on a continuous time domain and general-precedence variables. We propose novel types of symmetry-breaking constraints and a preprocessing procedure to improve the model performance. In an experimental analysis, we show that small- and moderate-sized instances can be solved to optimality within short CPU times.

From school to work: A comprehensive model of work-related motivation in the transition to working life.

Motivation is a core concept to understand work related outcomes and vocational pursuits. However, existing research mostly focused on specific aspects of motivation, such as goals or self-efficacy beliefs, while falling short of adequately addressing more complex and integrative notions of motivation. Advancing the current state of research, we draw from Motivational Systems Theory and a model of proactive motivation to propose a comprehensive model of work-related motivation. Specifically, we define motivation as a system of mutually related factors consisting of goals, emotions, and personal agency beliefs, comprised by capability beliefs and context evaluations. Adapting this model of motivation to the school-to-work transition, we postulate that this motivational system is affected by different social, personal, and environmental variables, for example social support, the presence of role-models, personality traits, and scholastic achievement. We further expect that students with more autonomous work-related goals, expectations of more positive emotional experiences in their future working life, fewer perceived barriers to their career development, and higher work-related self-efficacy beliefs would be more successful in their transition from school to work. We also propose that goal-directed engagement acts as a partial mediator in the relationship between motivation and a successful transition. Finally, we hypothesize that work-related motivation while in school will have meaningful effects on positive outcomes while in vocational training, as represented by more work engagement, higher career commitment, job satisfaction, and lower intentions to quit training. In sum, we advance the point that the adaptation of a broader concept of work-related motivation in the school-to-work transition would result in more powerful predictions of success in this transition and would enhance scientific research and interventions in career development and counselling practice.