41 resultados para Random field model
Resumo:
Background: Since the cognitive revolution of the early 1950s, cognitions have been discussed as central components in the understanding and treatment of mental illnesses. Even though there is an extensive literature on the association between therapy-related cognitions such as irrational beliefs and psychological distress over the past 60 years, there is little meta-analytical knowledge about the nature of this association. Methods: The relationship between irrational beliefs and distress was examined based on a systematic review that included 100 independent samples, gathered in 83 primary studies, using a random-effect model. The overall effects as well as potential moderators were examined: (a) distress measure, (b) irrational belief measure, (c) irrational belief type, (d) method of assessment of distress, (e) nature of irrational beliefs, (f) time lag between irrational beliefs and distress assessment, (g) nature of stressful events, (h) sample characteristics (i.e. age, gender, income, and educational, marital, occupational and clinical status), (i) developer/validator status of the author(s), and (k) publication year and country. Results: Overall, irrational beliefs were positively associated with various types of distress, such as general distress, anxiety, depression, anger, and guilt (omnibus: r = 0.38). The following variables were significant moderators of the relationship between the intensity of irrational beliefs and the level of distress: irrational belief measure and type, stressful event, age, educational and clinical status, and developer/validator status of the author. Conclusions: Irrational beliefs and distress are moderately connected to each other; this relationship remains significant even after controlling for several potential covariates.
Resumo:
Importance In treatment-resistant schizophrenia, clozapine is considered the standard treatment. However, clozapine use has restrictions owing to its many adverse effects. Moreover, an increasing number of randomized clinical trials (RCTs) of other antipsychotics have been published. Objective To integrate all the randomized evidence from the available antipsychotics used for treatment-resistant schizophrenia by performing a network meta-analysis. Data Sources MEDLINE, EMBASE, Biosis, PsycINFO, PubMed, Cochrane Central Register of Controlled Trials, World Health Organization International Trial Registry, and clinicaltrials.gov were searched up to June 30, 2014. Study Selection At least 2 independent reviewers selected published and unpublished single- and double-blind RCTs in treatment-resistant schizophrenia (any study-defined criterion) that compared any antipsychotic (at any dose and in any form of administration) with another antipsychotic or placebo. Data Extraction and Synthesis At least 2 independent reviewers extracted all data into standard forms and assessed the quality of all included trials with the Cochrane Collaboration's risk-of-bias tool. Data were pooled using a random-effects model in a Bayesian setting. Main Outcomes and Measures The primary outcome was efficacy as measured by overall change in symptoms of schizophrenia. Secondary outcomes included change in positive and negative symptoms of schizophrenia, categorical response to treatment, dropouts for any reason and for inefficacy of treatment, and important adverse events. Results Forty blinded RCTs with 5172 unique participants (71.5% men; mean [SD] age, 38.8 [3.7] years) were included in the analysis. Few significant differences were found in all outcomes. In the primary outcome (reported as standardized mean difference; 95% credible interval), olanzapine was more effective than quetiapine (-0.29; -0.56 to -0.02), haloperidol (-0. 29; -0.44 to -0.13), and sertindole (-0.46; -0.80 to -0.06); clozapine was more effective than haloperidol (-0.22; -0.38 to -0.07) and sertindole (-0.40; -0.74 to -0.04); and risperidone was more effective than sertindole (-0.32; -0.63 to -0.01). A pattern of superiority for olanzapine, clozapine, and risperidone was seen in other efficacy outcomes, but results were not consistent and effect sizes were usually small. In addition, relatively few RCTs were available for antipsychotics other than clozapine, haloperidol, olanzapine, and risperidone. The most surprising finding was that clozapine was not significantly better than most other drugs. Conclusions and Relevance Insufficient evidence exists on which antipsychotic is more efficacious for patients with treatment-resistant schizophrenia, and blinded RCTs-in contrast to unblinded, randomized effectiveness studies-provide little evidence of the superiority of clozapine compared with other second-generation antipsychotics. Future clozapine studies with high doses and patients with extremely treatment-refractory schizophrenia might be most promising to change the current evidence.
Resumo:
Immunoassays are essential in the workup of patients with suspected heparin-induced thrombocytopenia. However, the diagnostic accuracy is uncertain with regard to different classes of assays, antibody specificities, thresholds, test variations, and manufacturers. We aimed to assess diagnostic accuracy measures of available immunoassays and to explore sources of heterogeneity. We performed comprehensive literature searches and applied strict inclusion criteria. Finally, 49 publications comprising 128 test evaluations in 15 199 patients were included in the analysis. Methodological quality according to the revised tool for quality assessment of diagnostic accuracy studies was moderate. Diagnostic accuracy measures were calculated with the unified model (comprising a bivariate random-effects model and a hierarchical summary receiver operating characteristics model). Important differences were observed between classes of immunoassays, type of antibody specificity, thresholds, application of confirmation step, and manufacturers. Combination of high sensitivity (>95%) and high specificity (>90%) was found in 5 tests only: polyspecific enzyme-linked immunosorbent assay (ELISA) with intermediate threshold (Genetic Testing Institute, Asserachrom), particle gel immunoassay, lateral flow immunoassay, polyspecific chemiluminescent immunoassay (CLIA) with a high threshold, and immunoglobulin G (IgG)-specific CLIA with low threshold. Borderline results (sensitivity, 99.6%; specificity, 89.9%) were observed for IgG-specific Genetic Testing Institute-ELISA with low threshold. Diagnostic accuracy appears to be inadequate in tests with high thresholds (ELISA; IgG-specific CLIA), combination of IgG specificity and intermediate thresholds (ELISA, CLIA), high-dose heparin confirmation step (ELISA), and particle immunofiltration assay. When making treatment decisions, clinicians should be a aware of diagnostic characteristics of the tests used and it is recommended they estimate posttest probabilities according to likelihood ratios as well as pretest probabilities using clinical scoring tools.
Resumo:
BACKGROUND Evidence suggests that EMS-physician-guided cardiopulmonary resuscitation (CPR) in out-of-hospital cardiac arrest (OOHCA) may be associated with improved outcomes, yet randomized controlled trials are not available. The goal of this meta-analysis was to determine the association between EMS-physician- versus paramedic-guided CPR and survival after OOHCA. METHODS AND RESULTS Studies that compared EMS-physician- versus paramedic-guided CPR in OOHCA published until June 2014 were systematically searched in MEDLINE, EMBASE and Cochrane databases. All studies were required to contain survival data. Data on study characteristics, methods, and as well as survival outcomes were extracted. A random-effects model was used for the meta-analysis due to a high degree of heterogeneity among the studies (I (2) = 44 %). Return of spontaneous circulation [ROSC], survival to hospital admission, and survival to hospital discharge were the outcome measures. Out of 3,385 potentially eligible studies, 14 met the inclusion criteria. In the pooled analysis (n = 126,829), EMS-physician-guided CPR was associated with significantly improved outcomes compared to paramedic-guided CPR: ROSC 36.2 % (95 % confidence interval [CI] 31.0 - 41.7 %) vs. 23.4 % (95 % CI 18.5 - 29.2 %) (pooled odds ratio [OR] 1.89, 95 % CI 1.36 - 2.63, p < 0.001); survival to hospital admission 30.1 % (95 % CI 24.2 - 36.7 %) vs. 19.2 % (95 % CI 12.7 - 28.1 %) (pooled OR 1.78, 95 % CI 0.97 - 3.28, p = 0.06); and survival to discharge 15.1 % (95 % CI 14.6 - 15.7 %) vs. 8.4 % (95 % CI 8.2 - 8.5 %) (pooled OR 2.03, 95 % CI 1.48 - 2.79, p < 0.001). CONCLUSIONS This systematic review suggests that EMS-physician-guided CPR in out-of-hospital cardiac arrest is associated with improved survival outcomes.
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State of the art methods for disparity estimation achieve good results for single stereo frames, but temporal coherence in stereo videos is often neglected. In this paper we present a method to compute temporally coherent disparity maps. We define an energy over whole stereo sequences and optimize their Conditional Random Field (CRF) distributions using mean-field approximation. We introduce novel terms for smoothness and consistency between the left and right views, and perform CRF optimization by fast, iterative spatio-temporal filtering with linear complexity in the total number of pixels. Our results rank among the state of the art while having significantly less flickering artifacts in stereo sequences.
Resumo:
We present a geospatial model to predict the radiofrequency electromagnetic field from fixed site transmitters for use in epidemiological exposure assessment. The proposed model extends an existing model toward the prediction of indoor exposure, that is, at the homes of potential study participants. The model is based on accurate operation parameters of all stationary transmitters of mobile communication base stations, and radio broadcast and television transmitters for an extended urban and suburban region in the Basel area (Switzerland). The model was evaluated by calculating Spearman rank correlations and weighted Cohen's kappa (kappa) statistics between the model predictions and measurements obtained at street level, in the homes of volunteers, and in front of the windows of these homes. The correlation coefficients of the numerical predictions with street level measurements were 0.64, with indoor measurements 0.66, and with window measurements 0.67. The kappa coefficients were 0.48 (95%-confidence interval: 0.35-0.61) for street level measurements, 0.44 (95%-CI: 0.32-0.57) for indoor measurements, and 0.53 (95%-CI: 0.42-0.65) for window measurements. Although the modeling of shielding effects by walls and roofs requires considerable simplifications of a complex environment, we found a comparable accuracy of the model for indoor and outdoor points.
Resumo:
Radio frequency electromagnetic fields (RF-EMF) in our daily life are caused by numerous sources such as fixed site transmitters (e.g. mobile phone base stations) or indoor devices (e.g. cordless phones). The objective of this study was to develop a prediction model which can be used to predict mean RF-EMF exposure from different sources for a large study population in epidemiological research. We collected personal RF-EMF exposure measurements of 166 volunteers from Basel, Switzerland, by means of portable exposure meters, which were carried during one week. For a validation study we repeated exposure measurements of 31 study participants 21 weeks after the measurements of the first week on average. These second measurements were not used for the model development. We used two data sources as exposure predictors: 1) a questionnaire on potentially exposure relevant characteristics and behaviors and 2) modeled RF-EMF from fixed site transmitters (mobile phone base stations, broadcast transmitters) at the participants' place of residence using a geospatial propagation model. Relevant exposure predictors, which were identified by means of multiple regression analysis, were the modeled RF-EMF at the participants' home from the propagation model, housing characteristics, ownership of communication devices (wireless LAN, mobile and cordless phones) and behavioral aspects such as amount of time spent in public transports. The proportion of variance explained (R2) by the final model was 0.52. The analysis of the agreement between calculated and measured RF-EMF showed a sensitivity of 0.56 and a specificity of 0.95 (cut-off: 90th percentile). In the validation study, the sensitivity and specificity of the model were 0.67 and 0.96, respectively. We could demonstrate that it is feasible to model personal RF-EMF exposure. Most importantly, our validation study suggests that the model can be used to assess average exposure over several months.