A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Minimally Invasive Computer-Assisted Stereotactic Fenestration of an Aqueductal Cyst: Case Report

Introduction: Current advances in frame modeling and computer software allow stereotactic procedures to be performed with great accuracy and minimal risk of neural tissue or vascular injury. Case Report: In this report we associate a previously described minimally invasive stereotactic technique with state-of-the-art 3D computer guidance technology to successfully treat a 55-year-old patient with an arachnoidal cyst obstructing the aqueduct of Sylvius. We provide 1 detailed technical information and discuss how this technique deals with previous limitations for stereotactic manipulation of the aqueductal region. We further discuss current advances in neuroendoscopy for treating obstructive hydrocephalus and make comparisons with our proposed technique. Conclusion: We advocate that this technique is not only capable of treating this pathology but it also has the advantages to enable reestablishment of physiological CSF flow thus preventing future brainstem compression by cyst enlargement.

A randomized controlled trial comparing a computer-assisted insulin infusion protocol with a strict and a conventional protocol for glucose control in critically ill patients

Purpose: The objective of this study is to evaluate blood glucose (BG) control efficacy and safety of 3 insulin protocols in medical intensive care unit (MICU) patients. Methods: This was a multicenter randomized controlled trial involving 167 MICU patients with at least one BG measurement +/- 150 mg/dL and one or more of the following: mechanical ventilation, systemic inflammatory response syndrome, trauma, or burns. The interventions were computer-assisted insulin protocol (CAIP), with insulin infusion maintaining BG between 100 and 130 mg/dL; Leuven protocol, with insulin maintaining BG between 80 and 110 mg/dL; or conventional treatment-subcutaneous insulin if glucose > 150 mg/dL. The main efficacy outcome was the mean of patients` median BG, and the safety outcome was the incidence of hypoglycemia (<= 40 mg/dL). Results: The mean of patients` median BG was 125.0, 127.1, and 158.5 mg/dL for CAIP, Leuven, and conventional treatment, respectively (P = .34, CAIP vs Leuven; P < .001, CAIP vs conventional). In CAIP, 12 patients (21.4%) had at least one episode of hypoglycemia vs 24 (41.4%) in Leuven and 2 (3.8%) in conventional treatment (P = .02, CAIP vs Leuven; P = .006, CAIP vs conventional). Conclusions: The CAIP is safer than and as effective as the standard strict protocol for controlling glucose in MICU patients. Hypoglycemia was rare under conventional treatment. However, BG levels were higher than with IV insulin protocols. (C) 2009 Elsevier Inc. All rights reserved.