Signal propagation in Bayesian networks and its relationship with intrinsically multivariate predictive variables

A set of predictor variables is said to be intrinsically multivariate predictive (IMP) for a target variable if all properly contained subsets of the predictor set are poor predictors of the. target but the full set predicts the target with great accuracy. In a previous article, the main properties of IMP Boolean variables have been analytically described, including the introduction of the IMP score, a metric based on the coefficient of determination (CoD) as a measure of predictiveness with respect to the target variable. It was shown that the IMP score depends on four main properties: logic of connection, predictive power, covariance between predictors and marginal predictor probabilities (biases). This paper extends that work to a broader context, in an attempt to characterize properties of discrete Bayesian networks that contribute to the presence of variables (network nodes) with high IMP scores. We have found that there is a relationship between the IMP score of a node and its territory size, i.e., its position along a pathway with one source: nodes far from the source display larger IMP scores than those closer to the source, and longer pathways display larger maximum IMP scores. This appears to be a consequence of the fact that nodes with small territory have larger probability of having highly covariate predictors, which leads to smaller IMP scores. In addition, a larger number of XOR and NXOR predictive logic relationships has positive influence over the maximum IMP score found in the pathway. This work presents analytical results based on a simple structure network and an analysis involving random networks constructed by computational simulations. Finally, results from a real Bayesian network application are provided. (C) 2012 Elsevier Inc. All rights reserved.

Clinical trial design in non-invasive brain stimulation psychiatric research

Major depressive disorder (MDD) trials - investigating either non-pharmacological or pharmacological interventions - have shown mixed results. Many reasons explain this heterogeneity, but one that stands out is the trial design due to specific challenges in the field. We aimed therefore to review the methodology of non-invasive brain stimulation (NIBS) trials and provide a framework to improve clinical trial design. We performed a systematic review for randomized, controlled MDD trials whose intervention was transcranial magnetic stimulation (rTMS) or transcranial direct current stimulation (tDCS) in MEDLINE and other databases from April 2002 to April 2008. We created an unstructured checklist based on CONSORT guidelines to extract items such as power analysis, sham method, blinding assessment, allocation concealment, operational criteria used for MDD, definition of refractory depression and primary study hypotheses. Thirty-one studies were included. We found that the main methodological issues can be divided in to three groups: (1) issues related to phase II/small trials, (2) issues related to MDD trials and, (3) specific issues of NIBS studies. Taken together, they can threaten study validity and lead to inconclusive results. Feasible solutions include: estimating the sample size a priori; measuring the degree of refractoriness of the subjects; specifying the primary hypothesis and statistical tests; controlling predictor variables through stratification randomization methods or using strict eligibility criteria; adjusting the study design to the target population; using adaptive designs and exploring NIBS efficacy employing biological markers. In conclusion, our study summarizes the main methodological issues of NIBS trials and proposes a number of alternatives to manage them. Copyright (C) 2011 John Wiley & Sons, Ltd.

Extraoral Implants in the Rehabilitation of Craniofacial Defects: Implant and Prosthesis Survival Rates and Peri-Implant Soft Tissue Evaluation

Purpose: Few reports have evaluated cumulative survival rates of extraoral rehabilitation and peri-implant soft tissue reaction at long-term follow-up. The objective of this study was to evaluate implant and prosthesis survival rates and the soft tissue reactions around the extraoral implants used to support craniofacial prostheses. Materials and Methods: A retrospective study was performed of patients who received implants for craniofacial rehabilitation from 2003 to 2010. Two outcome variables were considered: implant and prosthetic success. The following predictor variables were recorded: gender, age, implant placement location, number and size of implants, irradiation status in the treated field, date of prosthesis delivery, soft tissue response, and date of last follow-up. A statistical model was used to estimate survival rates and associated confidence intervals. We randomly selected 1 implant per patient for analysis. Data were analyzed using the Kaplan-Meier method and log-rank test to compare survival curves. Results: A total of 150 titanium implants were placed in 56 patients. The 2-year overall implant survival rates were 94.1% for auricular implants, 90.9% for nasal implants, 100% for orbital implants, and 100% for complex midfacial implants (P = .585). The implant survival rates were 100% for implants placed in irradiated patients and 94.4% for those placed in nonirradiated patients (P = .324). The 2-year overall prosthesis survival rates were 100% for auricular implants, 90.0% for nasal implants, 92.3% for orbital implants, and 100% for complex midfacial implants (P = .363). The evaluation of the peri-implant soft tissue response showed that 15 patients (26.7%) had a grade 0 soft tissue reaction, 30 (53.5%) had grade 1, 6 (10.7%) had grade 2, and 5 (8.9%) had grade 3. Conclusions: From this study, it was concluded that craniofacial rehabilitation with extraoral implants is a safe, reliable, and predictable method to restore the patient's normal appearance. (C) 2012 American Association of Oral and Maxillofacial Surgeons J Oral Maxillofac Surg 70:1551-1557, 2012