Efficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis.

Randomized, controlled trials have demonstrated efficacy for second-generation antipsychotics in the treatment of acute mania in bipolar disorder. Despite depression being considered the hallmark of bipolar disorder, there are no published systematic reviews or meta-analyses to evaluate the efficacy of modern atypical antipsychotics in bipolar depression. We systematically reviewed published or registered randomized, double-blind, placebo-controlled trials (RCTs) of modern antipsychotics in adult bipolar I and/or II depressive patients (DSM-IV criteria). Efficacy outcomes were assessed based on changes in the Montgomery-Asberg Depression Rating Scale (MADRS) during an 8-wk period. Data were combined through meta-analysis using risk ratio as an effect size with a 95% confidence interval (95% CI) and with a level of statistical significance of 5% (p<0.05). We identified five RCTs; four involved antipsychotic monotherapy and one addressed both monotherapy and combination with an antidepressant. The two quetiapine trials analysed the safety and efficacy of two doses: 300 and 600 mg/d. The only olanzapine trial assessed olanzapine monotherapy within a range of 5-20 mg/d and olanzapine-fluoxetine combination within a range of 5-20 mg/d and 6-12 mg/d, respectively. The two aripiprazole placebo-controlled trials assessed doses of 5-30 mg/d. Quetiapine and olanzapine trials (3/5, 60%) demonstrated superiority over placebo (p<0.001). Only 2/5 (40%) (both aripiprazole trials) failed in the primary efficacy measure after the first 6 wk. Some modern antipsychotics (quetiapine and olanzapine) have demonstrated efficacy in bipolar depressive patients from week 1 onwards. Rapid onset of action seems to be a common feature of atypical antipsychotics in bipolar depression. Comment in The following popper user interface control may not be accessible. Tab to the next button to revert the control to an accessible version.Destroy user interface controlEfficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis--results to be interpreted with caution.

Efficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis.

Randomized, controlled trials have demonstrated efficacy for second-generation antipsychotics in the treatment of acute mania in bipolar disorder. Despite depression being considered the hallmark of bipolar disorder, there are no published systematic reviews or meta-analyses to evaluate the efficacy of modern atypical antipsychotics in bipolar depression. We systematically reviewed published or registered randomized, double-blind, placebo-controlled trials (RCTs) of modern antipsychotics in adult bipolar I and/or II depressive patients (DSM-IV criteria). Efficacy outcomes were assessed based on changes in the Montgomery-Asberg Depression Rating Scale (MADRS) during an 8-wk period. Data were combined through meta-analysis using risk ratio as an effect size with a 95% confidence interval (95% CI) and with a level of statistical significance of 5% (p<0.05). We identified five RCTs; four involved antipsychotic monotherapy and one addressed both monotherapy and combination with an antidepressant. The two quetiapine trials analysed the safety and efficacy of two doses: 300 and 600 mg/d. The only olanzapine trial assessed olanzapine monotherapy within a range of 5-20 mg/d and olanzapine-fluoxetine combination within a range of 5-20 mg/d and 6-12 mg/d, respectively. The two aripiprazole placebo-controlled trials assessed doses of 5-30 mg/d. Quetiapine and olanzapine trials (3/5, 60%) demonstrated superiority over placebo (p<0.001). Only 2/5 (40%) (both aripiprazole trials) failed in the primary efficacy measure after the first 6 wk. Some modern antipsychotics (quetiapine and olanzapine) have demonstrated efficacy in bipolar depressive patients from week 1 onwards. Rapid onset of action seems to be a common feature of atypical antipsychotics in bipolar depression. Comment in The following popper user interface control may not be accessible. Tab to the next button to revert the control to an accessible version.Destroy user interface controlEfficacy of modern antipsychotics in placebo-controlled trials in bipolar depression: a meta-analysis--results to be interpreted with caution.

Convex linear combination processes for compositions

Aitchison and Bacon-Shone (1999) considered convex linear combinations ofcompositions. In other words, they investigated compositions of compositions, wherethe mixing composition follows a logistic Normal distribution (or a perturbationprocess) and the compositions being mixed follow a logistic Normal distribution. Inthis paper, I investigate the extension to situations where the mixing compositionvaries with a number of dimensions. Examples would be where the mixingproportions vary with time or distance or a combination of the two. Practicalsituations include a river where the mixing proportions vary along the river, or acrossa lake and possibly with a time trend. This is illustrated with a dataset similar to thatused in the Aitchison and Bacon-Shone paper, which looked at how pollution in aloch depended on the pollution in the three rivers that feed the loch. Here, I explicitlymodel the variation in the linear combination across the loch, assuming that the meanof the logistic Normal distribution depends on the river flows and relative distancefrom the source origins

To select or to weigh: a comparative study of linear combination schemes for superparent-one-dependence estimators

We conduct a large-scale comparative study on linearly combining superparent-one-dependence estimators (SPODEs), a popular family of seminaive Bayesian classifiers. Altogether, 16 model selection and weighing schemes, 58 benchmark data sets, and various statistical tests are employed. This paper's main contributions are threefold. First, it formally presents each scheme's definition, rationale, and time complexity and hence can serve as a comprehensive reference for researchers interested in ensemble learning. Second, it offers bias-variance analysis for each scheme's classification error performance. Third, it identifies effective schemes that meet various needs in practice. This leads to accurate and fast classification algorithms which have an immediate and significant impact on real-world applications. Another important feature of our study is using a variety of statistical tests to evaluate multiple learning methods across multiple data sets.

System identification using a linear combination of cumulant slices

In this paper we develop a new linear approach to identify the parameters of a moving average (MA) model from the statistics of the output. First, we show that, under some constraints, the impulse response of the system can be expressed as a linear combination of cumulant slices. Then, thisresult is used to obtain a new well-conditioned linear methodto estimate the MA parameters of a non-Gaussian process. Theproposed method presents several important differences withexisting linear approaches. The linear combination of slices usedto compute the MA parameters can be constructed from dif-ferent sets of cumulants of different orders, providing a generalframework where all the statistics can be combined. Further-more, it is not necessary to use second-order statistics (the autocorrelation slice), and therefore the proposed algorithm stillprovides consistent estimates in the presence of colored Gaussian noise. Another advantage of the method is that while mostlinear methods developed so far give totally erroneous estimates if the order is overestimated, the proposed approach doesnot require a previous estimation of the filter order. The simulation results confirm the good numerical conditioning of thealgorithm and the improvement in performance with respect to existing methods.

Experimental study of clinafloxacin alone and in combination in the treatment of ciprofloxacin-susceptible and -resistant pneumococcal meningitis

The increasing incidence of ciprofloxacin resistance in Streptococcus pneumoniae may limit the efficacy of the new quinolones in difficult-to-treat infections such as meningitis. The aim of the present study was to determine the efficacy of clinafloxacin alone and in combination with teicoplanin and rifampin in the therapy of ciprofloxacin-susceptible and ciprofloxacin-resistant pneumococcal meningitis in rabbits. When used against a penicillin-resistant ciprofloxacin-susceptible strain (Clinafloxacin MIC 0.12 μg/ml), clinafloxacin at a dose of 20 mg/kg per day b.i.d. decreased bacterial concentration by -5.10 log cfu/ml at 24 hr. Combinations did not improve activity. The same clinafloxacin schedule against a penicillin- and ciprofloxacin-resistant strain (Clinafloxacin MIC 0.5 μg/ml) was totally ineffective. Our data suggest that a moderate decrease in quinolone susceptibility, as indicated by the detection of any degree of ciprofloxacin resistance, may render these antibiotics unsuitable for the management of pneumococcal meningitis

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Combination of diffusion tensor and functional magnetic resonance imaging during recovery from the vegetative state

Background: The rate of recovery from the vegetative state (VS) is low. Currently, little is known of the mechanisms and cerebral changes that accompany those relatively rare cases of good recovery. Here, we combined functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) to study the evolution of one VS patient at one month post-ictus and again twelve months later when he had recovered consciousness. Methods fMRI was used to investigate cortical responses to passive language stimulation as well as task-induced deactivations related to the default-mode network. DTI was used to assess the integrity of the global white matter and the arcuate fasciculus. We also performed a neuropsychological assessment at the time of the second MRI examination in order to characterize the profile of cognitive deficits. Results: fMRI analysis revealed anatomically appropriate activation to speech in both the first and the second scans but a reduced pattern of task-induced deactivations in the first scan. In the second scan, following the recovery of consciousness, this pattern became more similar to that classically described for the default-mode network. DTI analysis revealed relative preservation of the arcuate fasciculus and of the global normal-appearing white matter at both time points. The neuropsychological assessment revealed recovery of receptive linguistic functioning by 12-months post-ictus. Conclusions: These results suggest that the combination of different structural and functional imaging modalities may provide a powerful means for assessing the mechanisms involved in the recovery from the VS.

Classifier combination for in vivo magnetic resonance spectra of brain tumours

Peer-reviewed

Classifier combination for in vivo magnetic resonance spectra of brain tumours

In this paper we present a multi-stage classifier for magnetic resonance spectra of human brain tumours which is being developed as part of a decision support system for radiologists. The basic idea is to decompose a complex classification scheme into a sequence of classifiers, each specialising in different classes of tumours and trying to reproducepart of the WHO classification hierarchy. Each stage uses a particular set of classification features, which are selected using a combination of classical statistical analysis, splitting performance and previous knowledge.Classifiers with different behaviour are combined using a simple voting scheme in order to extract different error patterns: LDA, decision trees and the k-NN classifier. A special label named "unknown¿ is used when the outcomes of the different classifiers disagree. Cascading is alsoused to incorporate class distances computed using LDA into decision trees. Both cascading and voting are effective tools to improve classification accuracy. Experiments also show that it is possible to extract useful information from the classification process itself in order to helpusers (clinicians and radiologists) to make more accurate predictions and reduce the number of possible classification mistakes.