A comparative analysis of predictive models of morbidity in intensive care unit after cardiac surgery – Part I: model planning

<p>Abstract</p> <p>Background</p> <p>Different methods have recently been proposed for predicting morbidity in intensive care units (ICU). The aim of the present study was to critically review a number of approaches for developing models capable of estimating the probability of morbidity in ICU after heart surgery. The study is divided into two parts. In this first part, popular models used to estimate the probability of class membership are grouped into distinct categories according to their underlying mathematical principles. Modelling techniques and intrinsic strengths and weaknesses of each model are analysed and discussed from a theoretical point of view, in consideration of clinical applications.</p> <p>Methods</p> <p>Models based on Bayes rule, <it>k-</it>nearest neighbour algorithm, logistic regression, scoring systems and artificial neural networks are investigated. Key issues for model design are described. The mathematical treatment of some aspects of model structure is also included for readers interested in developing models, though a full understanding of mathematical relationships is not necessary if the reader is only interested in perceiving the practical meaning of model assumptions, weaknesses and strengths from a user point of view.</p> <p>Results</p> <p>Scoring systems are very attractive due to their simplicity of use, although this may undermine their predictive capacity. Logistic regression models are trustworthy tools, although they suffer from the principal limitations of most regression procedures. Bayesian models seem to be a good compromise between complexity and predictive performance, but model recalibration is generally necessary. <it>k</it>-nearest neighbour may be a valid non parametric technique, though computational cost and the need for large data storage are major weaknesses of this approach. Artificial neural networks have intrinsic advantages with respect to common statistical models, though the training process may be problematical.</p> <p>Conclusion</p> <p>Knowledge of model assumptions and the theoretical strengths and weaknesses of different approaches are fundamental for designing models for estimating the probability of morbidity after heart surgery. However, a rational choice also requires evaluation and comparison of actual performances of locally-developed competitive models in the clinical scenario to obtain satisfactory agreement between local needs and model response. In the second part of this study the above predictive models will therefore be tested on real data acquired in a specialized ICU.</p

Reporting bias in medical research - a narrative review

Reporting bias represents a major problem in the assessment of health care interventions. Several prominent cases have been described in the literature, for example, in the reporting of trials of antidepressants, Class I anti-arrhythmic drugs, and selective COX-2 inhibitors. The aim of this narrative review is to gain an overview of reporting bias in the medical literature, focussing on publication bias and selective outcome reporting. We explore whether these types of bias have been shown in areas beyond the well-known cases noted above, in order to gain an impression of how widespread the problem is. For this purpose, we screened relevant articles on reporting bias that had previously been obtained by the German Institute for Quality and Efficiency in Health Care in the context of its health technology assessment reports and other research work, together with the reference lists of these articles

Complex partial seizures and aphasia as initial manifestations of non-ketotic hyperglycemia: case report Crises parciais complexas e afasia como manifestações iniciais de hiperglicemia não cetótica: relato de caso

We describe a case of non-ketotic hyperglycemia (NKH), heralded by complex partial seizures and aphasia of epileptic origin, besides versive and partial motor seizures. This clinical picture was accompanied by left fronto-temporal spikes in the EEG. The seizures were controlled by carbamazepine only after the control of the diabetes. A month later, carbamazepine was discontinued. The patient remained without seizures, with normal language, using only glybenclamide. Complex partial seizures, opposed to simple partial seizures, are rarely described in association to NKH. Epileptic activity localized over language regions can manifest as aphasia.<br>Descrevemos um caso de hiperglicemia não-cetótica (HNC) cujas manifestações iniciais foram crises parciais complexas e afasia de origem epiléptica, além de crises versivas e parcias motoras. Este quadro clínico foi acompanhado por atividade epileptiforme na região fronto-temporal esquerda ao eletrencefalograma. As crises epilépticas foram controladas com carbamazepina (CBZ) apenas após o controle do diabetes mellitus. Após um mês, a CBZ foi suspensa, permanecendo a paciente com linguagem normal, sem novas crises epilépticas, em uso apenas de glibenclamida. Crises parciais complexas, ao contrário de crises parciais simples, são raramente descritas como manifestação de HNC. Atividade epileptiforme nas regiões relacionadas a linguagem podem manifestar-se como afasia

Automated Genome Annotation And Metabolic Model Reconstruction In The SEED And Model SEED

Over the past decade, genome-scale metabolic models have proven to be a crucial resource for predicting organism phenotypes from genotypes. These models provide a means of rapidly translating detailed knowledge of thousands of enzymatic processes into quantitative predictions of whole-cell behavior. Until recently, the pace of new metabolic model development was eclipsed by the pace at which new genomes were being sequenced. To address this problem, the RAST and the Model SEED framework were developed as a means of automatically producing annotations and draft genome-scale metabolic models. In this chapter, we describe the automated model reconstruction process in detail, starting from a new genome sequence and finishing on a functioning genome-scale metabolic model. We break down the model reconstruction process into eight steps: submitting a genome sequence to RAST, annotating the genome, curating the annotation, submitting the annotation to Model SEED, reconstructing the core model, generating the draft biomass reaction, auto-completing the model, and curating the model. Each of these eight steps is documented in detail

Evidence-based Practice for Mere Mortals: The Role of Informatics and Health Services Research

The poor translation of evidence into practice is a well-known problem. Hopes are high that information technology can help make evidence-based practice feasible for mere mortal physicians. In this paper, we draw upon the methods and perspectives of clinical practice, medical informatics, and health services research to analyze the gap between evidence and action, and to argue that computing systems for bridging this gap should incorporate both informatics and health services research expertise. We discuss 2 illustrative systems—trial banks and a web-based system to develop and disseminate evidence-based guidelines (alchemist)— and conclude with a research and training agenda

Encefalopatia induzida por cefepime: achados clínicos e eletroencefalográficos em sete pacientes Cefepime-induced encephalopathy: clinical and electroencephalographic features in seven patients

Cefepime, uma cefalosporina de quarta geração, com amplo espectro de ação, é um antibiótico largamente utilizado no tratamento de infecções graves em ambientes hospitalares. O registro de segurança deste fármaco é considerado favorável. Vários casos de encefalopatia grave, associada ao uso de cefepime, reversível, foram descritos recentemente. No presente artigo, descrevemos sete casos de encefalopatia induzida por cefepime, com achados eletroencefalográficos (EEG) característicos, que apresentaram reversão do quadro com a suspensão da droga. As relações do padrão EEG encontrado nestes pacientes com estado epiléptico não-convulsivo são consideradas, bem como a possibilidade de enquadrar os pacientes estudados na entidade "encefalopatia epileptiforme".<br>Cefepime, a fourth-generation cephalosporin, with large antibacterial spectrum, is a commonly used antibiotic for the treatment of serious hospitalar infections. Its security report is considered favourable. Recently, many cases of a severe and reversible cefepime-induced encephalopathy were described. In this paper, we report seven patients with reversible cefepime-induced encephalopathy, with a peculiar EEG pattern, characterized by semiperiodic diffuse triphasic waves. We discuss the EEG abnormalities found and their association with nonconvulsive status epilepticus