949 resultados para public decision
Resumo:
Objective. The objective of this study was to conduct a cost-effectiveness analysis of a universal rotavirus vaccination program among children : 5 years of age in Brazil. Methods. Considering a hypothetical annual cohort of approximately 3 300 000 newborns followed over 5 years, a decision-tree model was constructed to examine the possible clinical and economic effects of rotavirus infection with and without routine vaccination of children. Probabilities and unit costs were derived from published research and national administrative data. The impact of different estimates for key parameters was studied using sensitivity analysis. The analysis was conducted from both healthcare system and societal perspectives. Results. The vaccination program was estimated to prevent approximately 1735 351 (54%) of the 3 210 361 cases of rotavirus gastroenteritis and 703 (75%) of 933 rotavirus-associated deaths during the 5-year period. At a vaccine price of 18.6 Brazilian reais (R$) per dose, this program would cost R$121 673 966 and would save R$38 536 514 in direct costs to the public healthcare system and R$71 778 377 in direct and indirect costs to society. The program was estimated to cost R$1 028 and R$1 713 per life-years saved (LYS)from the societal and healthcare system perspectives, respectively. Conclusions. Universal rotavirus vaccination was a cost-effective strategy for both perspectives. However, these findings are highly sensitive to diarrhea incidence rate, proportion of severe cases, vaccine coverage, and vaccine price.
Resumo:
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.
Resumo:
Generalized Social Anxiety Disorder (SAD) is one of the most common anxiety conditions with impairment in social life. Cannabidiol (CBD), one major non-psychotomimetic compound of the cannabis sativa plant, has shown anxiolytic effects both in humans and in animals. This preliminary study aimed to compare the effects of a simulation public speaking test (SPST) on healthy control (HC) patients and treatment-naive SAD patients who received a single dose of CBD or placebo. A total of 24 never-treated patients with SAD were allocated to receive either CBD (600 mg; n = 12) or placebo (placebo; n = 12) in a double-blind randomized design 1 h and a half before the test. The same number of HC (n = 12) performed the SPST without receiving any medication. Each volunteer participated in only one experimental session in a double-blind procedure. Subjective ratings on the Visual Analogue Mood Scale (VAMS) and Negative Self-Statement scale (SSPS-N) and physiological measures (blood pressure, heart rate, and skin conductance) were measured at six different time points during the SPST. The results were submitted to a repeated-measures analysis of variance. Pretreatment with CBD significantly reduced anxiety, cognitive impairment and discomfort in their speech performance, and significantly decreased alert in their anticipatory speech. The placebo group presented higher anxiety, cognitive impairment, discomfort, and alert levels when compared with the control group as assessed with the VAMS. The SSPS-N scores evidenced significant increases during the testing of placebo group that was almost abolished in the CBD group. No significant differences were observed between CBD and HC in SSPS-N scores or in the cognitive impairment, discomfort, and alert factors of VAMS. The increase in anxiety induced by the SPST on subjects with SAD was reduced with the use of CBD, resulting in a similar response as the HC. Neuropsychopharmacology (2011) 36, 1219-1226; doi: 10.1038/npp.2011.6; published online 9 February 2011
Resumo:
Simulated public speaking (SPS) test is sensitive to drugs that interfere with serotonin-mediated neurotransmission and is supposed to recruit neural systems involved in panic disorder. The study was aimed at evaluating the effects of escitalopram, the most selective serotonin-selective reuptake inhibitor available, in SPS. Healthy males received, in a double-blind, randomized design, placebo (n = 12), 10 (n = 17) or 20 (n = 14) mg of escitalopram 2 hours before the test. Behavioural, autonomic and neuroendocrine measures were assessed. Both doses of escitalopram did not produce any effect before or during the speech but prolonged the fear induced by SPS. The test itself did not significantly change cortisol and prolactin levels but under the higher dose of escitalopram, cortisol and prolactin increased immediately after SPS. This fear-enhancing effect of escitalopram agrees with previously reported results with less selective serotonin reuptake inhibitors and the receptor antagonist ritanserin, indicating that serotonin inhibits the fear of speaking in public.