Long-term safety and efficacy of percutaneous coronary intervention with stenting and coronary artery bypass surgery for multivessel coronary artery disease - A meta-analysis with 5-year patient-level data from the ARTS, ERACI-II, MASS-II, and SoS trials

Background-Randomized trials that studied clinical outcomes after percutaneous coronary intervention (PCI) with bare metal stenting versus coronary artery bypass grafting (CABG) are underpowered to properly assess safety end points like death, stroke, and myocardial infarction. Pooling data from randomized controlled trials increases the statistical power and allows better assessment of the treatment effect in high-risk subgroups. Methods and Results-We performed a pooled analysis of 3051 patients in 4 randomized trials evaluating the relative safety and efficacy of PCI with stenting and CABG at 5 years for the treatment of multivessel coronary artery disease. The primary end point was the composite end point of death, stroke, or myocardial infarction. The secondary end point was the occurrence of major adverse cardiac and cerebrovascular accidents, death, stroke, myocardial infarction, and repeat revascularization. We tested for heterogeneities in treatment effect in patient subgroups. At 5 years, the cumulative incidence of death, myocardial infarction, and stroke was similar in patients randomized to PCI with stenting versus CABG (16.7% versus 16.9%, respectively; hazard ratio, 1.04, 95% confidence interval, 0.86 to 1.27; P = 0.69). Repeat revascularization, however, occurred significantly more frequently after PCI than CABG (29.0% versus 7.9%, respectively; hazard ratio, 0.23; 95% confidence interval, 0.18 to 0.29; P<0.001). Major adverse cardiac and cerebrovascular events were significantly higher in the PCI than the CABG group (39.2% versus 23.0%, respectively; hazard ratio, 0.53; 95% confidence interval, 0.45 to 0.61; P<0.001). No heterogeneity of treatment effect was found in the subgroups, including diabetic patients and those presenting with 3-vessel disease. Conclusions-In this pooled analysis of 4 randomized trials, PCI with stenting was associated with a long-term safety profile similar to that of CABG. However, as a result of persistently lower repeat revascularization rates in the CABG patients, overall major adverse cardiac and cerebrovascular event rates were significantly lower in the CABG group at 5 years.

Gene expression profiling of papillary thyroid carcinoma identifies transcripts correlated with BRAF mutational status and lymph node metastasis

Purpose: To identify papillary thyroid carcinoma (PTC)-associated transcripts, we compared the gene expression profiles of three Serial Analysis of Gene Expression libraries generated from thyroid tumors and a normal thyroid tissue. Experimental Design: Selected transcripts were validated in a panel of 57 thyroid tumors using quantitative PCR (qPCR). An independent set of 71 paraffin-embedded sections was used for validation using immunohistochemical analysis. To determine if PTC-associated gene expression could predict lymph node involvement, a separate cohort of 130 primary PTC (54 metastatic and 76 nonmetastatic) was investigated. The BRAF(V600E) mutational status was compared with qPCR data to identify genes that might be regulated by abnormal BRAF/MEK/extracellular signal-regulated kinase signaling. Results: We identified and validated new PTC-associated transcripts. Three genes (CST6, CXCL14, and DHRS3) are strongly associated with PTC. Immunohistochemical analysis of CXCL14 confirmed the qPCR data and showed protein expression in PTC epithelial cells. We also observed that CST6, CXCL14, DHRS3, and SPP1 were associated with PTC lymph node metastasis, with CST6, CXCL14, and SPP1 being positively correlated with metastasis and DHRS3 being negatively correlated. Finally, we found a strong correlation between CST6 and CXCL14 expression and BRAF(V600E) mutational status, suggesting that these genes may be induced subsequently to BRAF activation and therefore may be downstream in the BRAF/MEK/extracellular signal-regulated kinase signaling pathway. Conclusion: CST6, CXCL14, DHRS3, and SPP1 may play a role in PTC pathogenesis and progression and are possible molecular targets for FTC therapy.

Psychosocial pathways to inconsistent condom use among male sex workers: personality, drug misuse and criminality

Background: This research compared street male sex workers in Santo Andre, Brazil, that reported consistent condom use with those that revealed inconsistent condom use with their clients, concerning personality aspects, impulsiveness, alcohol and drug consumption, depressive symptoms, sociodemographic data and criminal involvement. Methods: Eighty-six male sex workers were evaluated in face-to-face interviews at their place of work. A `snowball` sampling procedure was used to access this hard-to-reach population. Findings: Male sex workers with inconsistent condom use showed greater involvement with criminal activities, higher reward dependence level and more frequent self-report of being HIV-positive. Conclusions: Conceptualisation of male sex workers` psychological characteristics may be required where HIV risk is not only attributed to sex work per se, but to other aspects such as personality-related factors and negative identity.

Smart Alerts: Development of Software to Optimize Data Monitoring

Dherte PM, Negrao MPG, Mori Neto S, Holzhacker R, Shimada V, Taberner P, Carmona MJC - Smart Alerts: Development of a Software to Optimize Data Monitoring. Background and objectives: Monitoring is useful for vital follow-ups and prevention, diagnosis, and treatment of several events in anesthesia. Although alarms can be useful in monitoring they can cause dangerous user`s desensitization. The objective of this study was to describe the development of specific software to integrate intraoperative monitoring parameters generating ""smart alerts"" that can help decision making, besides indicating possible diagnosis and treatment. Methods: A system that allowed flexibility in the definition of alerts, combining individual alarms of the parameters monitored to generate a more elaborated alert system was designed. After investigating a set of smart alerts, considered relevant in the surgical environment, a prototype was designed and evaluated, and additional suggestions were implemented in the final product. To verify the occurrence of smart alerts, the system underwent testing with data previously obtained during intraoperative monitoring of 64 patients. The system allows continuous analysis of monitored parameters, verifying the occurrence of smart alerts defined in the user interface. Results: With this system a potential 92% reduction in alarms was observed. We observed that in most situations that did not generate alerts individual alarms did not represent risk to the patient. Conclusions: Implementation of software can allow integration of the data monitored and generate information, such as possible diagnosis or interventions. An expressive potential reduction in the amount of alarms during surgery was observed. Information displayed by the system can be oftentimes more useful than analysis of isolated parameters.

Is PHEEM a multi-dimensional instrument? An international perspective

Aim: To look at the characteristics of Postgraduate Hospital Educational Environment Measure (PHEEM) using data from the UK, Brazil, Chile and the Netherlands, and to examine the reliability and characteristics of PHEEM, especially how the three PHEEM subscales fitted with factors derived statistically from the data sets. Methods: Statistical analysis of PHEEM scores from 1563 sets of data, using reliability analysis, exploratory factor analysis and correlations of factors derived with the three defined PHEEM subscales. Results: PHEEM was very reliable with an overall Cronbach`s alpha of 0.928. Three factors were derived by exploratory factor analysis. Factor One correlated most strongly with the teaching subscale (R=0.802), Factor Two correlated most strongly with the role autonomy subscale (R=0.623) and Factor Three correlated most strongly with the social support subscale (R=0.538). Conclusions: PHEEM is a multi-dimensional instrument. Overall, it is very reliable. There is a good fit of the three defined subscales, derived by qualitative methods, with the three principal factors derived from the data by exploratory factor analysis.

Evaluation of serum trace element, biochemical and hematological data of a healthy elderly group residing in So Paulo city, Brazil

In this study, blood serum trace elements, biochemical and hematological parameters were obtained to assess the health status of an elderly population residing in So Paulo city, SP, Brazil. Results obtained showed that more than 93% of the studied individuals presented most of the serum trace element concentrations and of the hematological and biochemical data within the reference values used in clinical laboratories. However, the percentage of elderly presenting recommended low density lipoprotein (LDL) cholesterol concentrations was low (70%). The study indicated positive correlation between the concentrations of Zn and LDL-cholesterol (p < 0.06).

VALIDATION OF THE LONDON CHEST ACTIVITY OF DAILY LIVING SCALE IN PATIENTS WITH HEART FAILURE

Background: The Minnesota Living with Heart Failure Questionnaire (MLHFQ) is a well-validated, commonly-used tool to assess quality of life in patients with heart failure. However, it lacks specific information concerning breathlessness during daily activities. Objective: To determine the validity of the London Chest Activity of Daily Living (LCADL) scale for use in patients with heart failure. Methods: Forty-seven patients with heart failure (57% males, mean age 50 years (standard deviation 9), mean left ventricle ejection fraction 29% (SD 6), New York Heart Association (NYHA) functional class I-III) were included. All subjects first performed a cardiopulmonary exercise test and then responded to the LCADL and the MLHFQ, with guidance from the same investigator. The re-test for the LCADL was applied one week later. Results: LCADL was correlated with MLHFQ (r=0.88; p < 0.0001). LCADL and MLHFQ were also correlated with exercise capacity (r=-0.75 and r=-0.73, respectively; both p < 0.0001). The LCADL was shown to be reproducible (r(i)=0.98). There was a significant difference (p < 0.05) in the LCADL scores between NYHA functional classes I and II, as well as classes I and III, hut not between classes II and III. Conclusion: The LCADL was shown to be a valid measurement of dyspnoea during daily activities in patients with heart failure. This scale could be an additional useful tool for the assessment of patients` dyspnoea during activities of daily living.

Validation of a strategy to diagnose coronary artery disease and predict cardiac events in high-risk renal transplant candidates

Background We validated a strategy for diagnosis of coronary artery disease ( CAD) and prediction of cardiac events in high-risk renal transplant candidates ( at least one of the following: age >= 50 years, diabetes, cardiovascular disease). Methods A diagnosis and risk assessment strategy was used in 228 renal transplant candidates to validate an algorithm. Patients underwent dipyridamole myocardial stress testing and coronary angiography and were followed up until death, renal transplantation, or cardiac events. Results The prevalence of CAD was 47%. Stress testing did not detect significant CAD in 1/3 of patients. The sensitivity, specificity, and positive and negative predictive values of the stress test for detecting CAD were 70, 74, 69, and 71%, respectively. CAD, defined by angiography, was associated with increased probability of cardiac events [log-rank: 0.001; hazard ratio: 1.90, 95% confidence interval (CI): 1.29-2.92]. Diabetes (P=0.03; hazard ratio: 1.58, 95% CI: 1.06-2.45) and angiographically defined CAD (P=0.03; hazard ratio: 1.69, 95% CI: 1.08-2.78) were the independent predictors of events. Conclusion The results validate our observations in a smaller number of high-risk transplant candidates and indicate that stress testing is not appropriate for the diagnosis of CAD or prediction of cardiac events in this group of patients. Coronary angiography was correlated with events but, because less than 50% of patients had significant disease, it seems premature to recommend the test to all high-risk renal transplant candidates. The results suggest that angiography is necessary in many high-risk renal transplant candidates and that better noninvasive methods are still lacking to identify with precision patients who will benefit from invasive procedures. Coron Artery Dis 21: 164-167 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

A Dynamic Model of Hand-and-Foot Syndrome in Patients Receiving Capecitabine

For the purpose of developing a longitudinal model to predict hand-and-foot syndrome (HFS) dynamics in patients receiving capecitabine, data from two large phase III studies were used. Of 595 patients in the capecitabine arms, 400 patients were randomly selected to build the model, and the other 195 were assigned for model validation. A score for risk of developing HFS was modeled using the proportional odds model, a sigmoidal maximum effect model driven by capecitabine accumulation as estimated through a kinetic-pharmacodynamic model and a Markov process. The lower the calculated creatinine clearance value at inclusion, the higher was the risk of HFS. Model validation was performed by visual and statistical predictive checks. The predictive dynamic model of HFS in patients receiving capecitabine allows the prediction of toxicity risk based on cumulative capecitabine dose and previous HFS grade. This dose-toxicity model will be useful in developing Bayesian individual treatment adaptations and may be of use in the clinic.

Validation of plasma clearance of (51)Cr-EDTA in adult renal transplant recipients: comparison with inulin renal clearance

Plasma clearance of (51)Cr-EDTA ((51)Cr-EDTA-Cl) is an alternative method to evaluate glomerular filtration rate (GFR). This study aimed to investigate the concordance between (51)Cr-EDTA-Cl and renal inulin clearance (In-Cl) in renal transplant recipients as well to determine the repeatability of (51)Cr-EDTA-Cl in kidney donors. Forty four kidney recipients and 22 kidney donors were enrolled. Simultaneous measurements of (51)Cr-EDTA-Cl and In-Cl were performed. A single dose of 3.7MBq of (51)Cr-EDTA was injected and the plasma disappearance curve was created by taking blood samples at 2, 4, 6 and 8 h after injection. Bland and Altman statistical approach was used to quantify the agreement between In-Cl and (51)Cr-EDTA-Cl and to determine the better concordance between all possibilities of measure for the (51)Cr-EDTA-Cl. The mean of In-Cl was 44.5 +/- 17.9 ml/min/1.73 m(2). There was a positive correlation between In-Cl and all possible measurements of (51)Cr-EDTA-Cl. (51)Cr-EDTA-Cl with two samples taken at 4 and 8 h or at 4 and 6 h presenting the narrow limits of agreement and a difference (bias) of 2.8 and 2.7 ml/min, respectively. Two plasma sampling for (51)Cr-EDTA-Cl was a reliable method to measure GFR compared with In-Cl and comprises a suitable method to be used in kidney transplanted patients.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

Validation of ASHA FACS-Functional Assessment of Communication Skills for Alzheimer Disease Population

This study vas aimed to validate the American Speech-Language-Hearing Association Functional Assessment Of Communication Skills (ASHA FACS) for a Brazilian population. The scale was translated and adapted into Portuguese. Thirty-two patients with mild Alzheimer disease (AD). 25 patients with moderate AD. and 51 elderly without dementia were examined with Mini Mental State Examination, Geriatric Depression Scale. and Alzheimer Disease Assessment Scale-Cognitive subscale (ADAS-cog). The ASHA FACS was answered by their relative/caregiver. The scale`s internal consistency. its inter-examiner and intra-examiner`s reproducibility. and scale`s criterion validity were researched by correlation with ADAS-cog,. The sensitivity and specificity Were also researched. Statistical analyses indicated that the ASHA FACS has excellent internal consistency (Cronbach alpha = 0.955), test-retest reliability (interclass correlation coefficient = 0.995; P < 0.001). and inter-examiners (interclass correlation coefficient = 0.998: P < 0.001). It showed excellent criterion validity when correlated with ADAS-cog,. The ASHA FACS scale showed good sensitivity (75.0%) and specificity (82.4%) values once it is an ecologic and broad evaluation. The ASHA FACS Portuguese version is a valid and reliable instrument to verify communication alterations in AD patients and fills an important gap of efficiency indicators for speech language therapy in our country.

New body fat prediction equations for severely obese patients

Background & aims: Severe obesity imposes physical limitations to body composition assessment. Our aim was to compare body fat (BF) estimations of severely obese patients obtained by bioelectrical impedance (BIA) and air displacement plethysmography (ADP) for development of new equations for BF prediction. Methods: Severely obese subjects (83 female/36 mate, mean age = 41.6 +/- 11.6 years) had BF estimated by BIA and ADP. The agreement of the data was evaluated using Bland-Altman`s graphic and concordance correlation coefficient (CCC). A multivariate regression analysis was performed to develop and validate new predictive equations. Results: BF estimations from BIA (64.8 +/- 15 kg) and ADP (65.6 +/- 16.4 kg) did not differ (p > 0.05, with good accuracy, precision, and CCC), but the Bland- Altman graphic showed a wide Limit of agreement (- 10.4; 8.8). The standard BIA equation overestimated BF in women (-1.3 kg) and underestimated BF in men (5.6 kg; p < 0.05). Two BF new predictive equations were generated after BIA measurement, which predicted BF with higher accuracy, precision, CCC, and limits of agreement than the standard BIA equation. Conclusions: Standard BIA equations were inadequate for estimating BF in severely obese patients. Equations developed especially for this population provide more accurate BF assessment. (C) 2008 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.