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.

Coping by relatives of critical care patients

OBJECTIVE: To describe the coping strategies used by the relatives of patients hospitalized in an intensive care unit. METHODS: This is a descriptive study that uses a convenience sample and both qualitative and quantitative methods. The study was conducted at a tertiary university hospital in Brazil. Participants included 41 relatives who were selected during the first 96 hours of patient hospitalization in the intensive care unit. RESULTS: The participants reported that they more frequently used Coping Strategies Based on the Stressor, followed by Religiosity/Fantasy Thinking and Seeking for Social Support. There was a statistically significant relationship (P <.01) between the use of the strategy Seeking for Social Support and elevated Acute Physiology, Age, and Chronic Health Evaluation 11 scores. Qualitative analysis allowed a clearer understanding of the relation between the patient`s condition and changes in the coping strategies used by the patient`s relatives. CONCLUSION: This study describes the coping strategies used by patients` relatives during the early hospitalization period. This investigation allowed for a better understanding of the relatives` psychologic aspects and their relation with the patient`s clinical condition. The results shall assist the design of specific interventions directed at facilitating positive coping responses on the part of relatives. (Heart Lung (R) 200 38:217-227.)

The A61 G EGF polymorphism is associated with development of extraaxial nervous system tumors but not with overall survival

Epidermal growth factor can activate several signaling pathways, leading to proliferation, differentiation, and tumorigenesis of epithelial tissues by binding with its receptor. The EGF protein is involved in nervous system development, and polymorphisms in the EGF gene on chromosome band 4q25 are associated with brain cancers. The purpose of this study was to investigate the association between the single-nucleotide polymorphism of EGF + 61 G/A and extraaxial brain tumors in a population of the southeast of Brazil. We analyzed the genotype distribution of this polymorphism in 90 patients and 100 healthy subjects, using the polymerase chain reaction restriction fragment length polymorphism technique. Comparison of genotype distribution revealed a significant difference between patients and control subjects (P < 0.001). The variant genotypes of A/G and G/G were associated with a significant increase of the risk of tumor development, compared with the homozygote A/A (P < 0.0001). When the analyses were stratified, we observed that the genotype GIG was more frequent in female patients (P = 0.021). The same genotype was observed more frequently in patients with low-grade tumors (P = 0.001). Overall survival rates did not show statistically significant differences. Our data suggest that the EGF A61 G polymorphism can be associated with susceptibility to development of these tumors. (C) 2010 Elsevier Inc. All rights reserved.

Temporal distribution of trauma deaths: Quality of trauma care in a developing country

Background: Examination of the epidemiology and timing of trauma deaths has been deemed a useful method to evaluate the quality of trauma care. Objective: The purpose of this study was to evaluate the quality of trauma care in a regional trauma system and in a university hospital in Brazil by comparing the timing of deaths in the studied prehospital and in-hospital settings to those published for trauma systems in other areas. Methods: We analyzed the National Health Minister`s System of Deaths Information for the prehospital mortality and we retrospectively collected the demographics, timelines, and trauma severity scores of all in-hospital patients who died after admission through the Emergency Unit of Hospital das Clinicas de Ribeirao Preto between 2000 and 2001. Results. During the study period, there were 787 trauma fatalities in the city: 448 (56.9%) died in the prehospital setting and 339 (43.1%) died after being admitted to a medical facility. In 2 years, 238 trauma deaths occurred in the studied hospital, and we found a complete clinical set of data for 224 of these patients. The majority of deaths in the prehospital setting were caused by penetrating injuries (66.7%), whereas in-hospital mortality was mainly because of blunt traumas (59.1%). The largest number of in-hospital deaths occurred beyond 72 hours of stay (107 patients-47%). Conclusions: The region studied showed some deficiencies in prehospital and in-hospitals settings, in particular in the critical care and short-term follow-up of trauma patients when compared with the literature. Particularly, the late mortality may be related to training and human resources deficiency. Based on the timeline of trauma deaths, we can suggest that the studied region needs improvements in the prehospital trauma system and in hospital critical care.

Tuberculosis among health care workers in a Brazilian tertiary hospital emergency unit

The Brazilian emergency system is being reorganized as a hierarchy in the region of Ribeirao Preto, state of Sao Paulo. We found increased occupational risk for tuberculosis in this region tertiary reference center-a nurse technician (Incidence rate [IR] 526.3/100000 inhabitants) had a risk of tuberculosis 12.6 (95% confidence interval [CI], 2.57-37.23) greater than the city population (41.8/100000 inhabitants). The system reorganization will have to make the centers adequate to deal with this problem. (C) 2008 Elsevier Inc. All rights reserved.