A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

Body composition assessment of undernourished older subjects by dual-energy x-ray absorptiometry and bioelectric impedance analysis

The prevention and treatment of diseases related to changes in body composition require accurate methods for the measurement of body composition. However, few studies have dealt specifically with the assessment of body composition of undernourished older subjects by different methodologies. To assess the body composition of undernourished older subjects by two different methods, dual energy x-ray absorptiometry (DXA) and bioelectric impedance (BIA), and to compare results with those of an eutrophic group. The study model was cross-sectional; the study was performed at the University Hospital of the School of Medicine of Ribeiro Preto, University of So Paulo, Brazil. Forty-one male volunteers aged 62 to 91 years. The groups were selected on the basis of anamnesis, physical examination and nutritional assessment according to the Mini Nutritional Assessment (MNA) score. Body composition was assessed by DXA and BIA. Body weight, arm and calf circumference, body mass index (BMI), fat free mass (FFM) and fat mass (FM) were significantly lower in the undernourished group as compared to the eutrophic group. There were no significant differences between FFM and FM mean values determined by DXA and BIA in both groups, but the agreement between methods in the undernourished group was less strong. Our results suggest caution when BIA is to be applied in studies including undernourished older subjects. This study does not support BIA as an accurate method for the individual assessment of body composition.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Anti-aversive effects of the atypical antipsychotic, aripiprazole, in animal models of anxiety

Aripiprazole is a unique antipsychotic that seems to act as a partial agonist at dopamine D2-receptors, contrasting with other drugs in this class, which are silent antagonists. Aripiprazole may also bind to serotonin receptors. Both neurotransmitters may play major roles in aversion-, anxiety-and panic-related behaviours. Thus, the present work tested the hypothesis that this antipsychotic could also have anti-aversive properties. Male Wistar rats received injections of aripiprazole (0.1-10 mg/kg) and were tested in the open field, in the elevated plus and T mazes (EPM and ETM, respectively) and in a contextual fear conditioning paradigm. Aripiprazole (1mg/kg) increased the percentage of entries onto the open arms of the EPM and attenuated escape responses in the ETM. In the latter model, the dose of 0.1 mg/kg also decreased the latency to leave the enclosed arm, suggesting anxiolytic- and panicolytic-like properties. This dose also decreased the time spent in freezing in a contextual fear conditioning. No significant motor effects were observed at these doses. The present data support the hypothesis that aripiprazole could inhibit anxiety-related responses. Acting as a partial agonist at dopamine receptors, this drug could effectively treat schizophrenia and, in contrast with most antipsychotic drugs, alleviate aversive states.

Nutrition Therapy in a Pediatric Intensive Care Unit: Indications, Monitoring, and Complications

Background: Nutrition therapy (NT) is essential for the care of critically ill children. Inadequate feeding leads to malnutrition and may increase the patient`s risk of morbidity and mortality. The aim of this study was to describe the NT used in a tertiary pediatric intensive care unit (PICU). Methods: The authors evaluated NT administered to 90 consecutive patients who were hospitalized for 7 days in the PICU of Instituto da Crianca, Hospital das Clinicas, Universidade de Sao Paulo, Brazil. NT was established according to the protocol provided by the institution`s NT team. NT provided a balance of fluids and nutrients and was monitored with a weekly anthropometric nutrition assessment and an evaluation of complications. Results: NT was initiated, on average, within 72 hours of hospitalization. Most children (80%) received enteral nutrition (EN) therapy; of these, 35% were fed orally and the rest via nasogastric or postpyloric tube. There were gastrointestinal complications in patients (5%) who needed a postpyloric tube. Parenteral nutrition (PN) was used in only 10% of the cases, and the remaining 10% received mixed NT (EN + PN). The average calorie and protein intake was 82 kcal/kg and 2.7 g/kg per day. Arm circumference and triceps skinfold thickness decreased. Conclusions: The use of EN was prevalent in the tertiary PICU, and few clinical complications occurred. There was no statistically significant change in most anthropometric indicators evaluated during hospitalization, which suggests that NT probably helped patients maintain their nutrition status. (JPEN J Parenter Enteral Nutr. 2011;35:523-529)

The public's knowledge of and support for conservation of Australia's Tree-Kangaroos

After providing some brief background on Dendrolagus species in Australia, two consecutive surveys of Brisbane’s residents are used to assess public knowledge of tree-kangaroos and the stated degree of support for their conservation in Australia. The responses of participants in Survey I are based on their pre-survey knowledge of wildlife. The same additional set of participants completed Survey II after being provided with information on all the wildlife species mentioned in Survey I. Changes in the attitudes of respondents and their degree of support for the protection and conservation of Australia’s tree-kangaroos are measured, including changes in their contingent valuations and stated willingness to provide financial support for such conservation. Reasons for wanting to protect tree-kangaroos are specified and analyzed. Furthermore, changes that occur in the relative importance of these reasons with increased knowledge are also examined. Support for the conservation of tree-kangaroos is found to increase with the additional knowledge supplied. Furthermore, support for the conservation of Australia’s less well-known tropical mammals is shown to increase relative to better known mammals (icons) present in temperate areas, such as koalas and red kangaroos with this increased knowledge. Possible implications of the results for government conservation policies in Australia are examined.

Clear cell odontogenic carcinoma: case report with immunohistochemical findings adding support to the challenging diagnosis

Clear cell odontogenic carcinoma (CCOC) is a rare odontogenic tumor associated with aggressive clinical behavior, metastasis, and low survival. We report a case of CCOC affecting the mandible of a 39-year-old man. The tumor presented a biphasic pattern composed of clear cell nests intermingled with eosinophilic cells and separated by collagenous stroma. Immunoreactivity to cytokeratin (CK), specifically AE1/AE3 and CK 8, 14, 18, and 19 was found, as well as to epithelial membrane antigen (EMA). The tumor cells were negative for S100 protein, CK 13, vimentin, smooth muscle actin, laminin and type IV collagen. Low labeling indices for the proliferation markers Ki-67 and proliferating cell nuclear antigen and to p53 protein might predict a favorable prognosis for the lesion. A surgical resection was performed, followed by adjuvant radiotherapy. A 2-year follow-up has shown no signs of recurrence. The significance of histochemical and immunohistochemical resources in the correct diagnosis of CCOC is analyzed.