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.

Dietary trends: Estimates from food supply and survey data

Objective: To illustrate methodological issues involved in estimating dietary trends in populations using data obtained from various sources in Australia in the 1980s and 1990s. Methods: Estimates of absolute and relative change in consumption of selected food items were calculated using national data published annually on the national food supply for 1982-83 to 1992-93 and responses to food frequency questions in two population based risk factor surveys in 1983 and 1994 in the Hunter Region of New South Wales, Australia. The validity of estimated food quantities obtained from these inexpensive sources at the beginning of the period was assessed by comparison with data from a national dietary survey conducted in 1983 using 24 h recall. Results: Trend estimates from the food supply data and risk factor survey data were in good agreement for increases in consumption of fresh fruit, vegetables and breakfast food and decreases in butter, margarine, sugar and alcohol. Estimates for trends in milk, eggs and bread consumption, however, were inconsistent. Conclusions: Both data sources can be used for monitoring progress towards national nutrition goals based on selected food items provided that some limitations are recognized. While data collection methods should be consistent over time they also need to allow for changes in the food supply (for example the introduction of new varieties such as low-fat dairy products). From time to time the trends derived from these inexpensive data sources should be compared with data derived from more detailed and quantitative estimates of dietary intake.

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).

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.

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.

Estimating correlations from epidemiological data in the presence of measurement error

Analysis of a major multi-site epidemiologic study of heart disease has required estimation of the pairwise correlation of several measurements across sub-populations. Because the measurements from each sub-population were subject to sampling variability, the Pearson product moment estimator of these correlations produces biased estimates. This paper proposes a model that takes into account within and between sub-population variation, provides algorithms for obtaining maximum likelihood estimates of these correlations and discusses several approaches for obtaining interval estimates. (C) 1997 by John Wiley & Sons, Ltd.

The GHEP-EMPOP collaboration on mtDNA population data-A new resource for forensic casework

Mitochondrial DNA (mtDNA) population data for forensic purposes are still scarce for some populations, which may limit the evaluation of forensic evidence especially when the rarity of a haplotype needs to be determined in a database search. In order to improve the collection of mtDNA lineages from the Iberian and South American subcontinents, we here report the results of a collaborative study involving nine laboratories from the Spanish and Portuguese Speaking Working Group of the International Society for Forensic Genetics (GHEP-ISFG) and EMPOP. The individual laboratories contributed population data that were generated throughout the past 10 years, but in the majority of cases have not been made available to the scientific community. A total of 1019 haplotypes from Iberia (Basque Country, 2 general Spanish populations, 2 North and 1 Central Portugal populations), and Latin America (3 populations from Sao Paulo) were collected, reviewed and harmonized according to defined EMPOP criteria. The majority of data ambiguities that were found during the reviewing process (41 in total) were transcription errors confirming that the documentation process is still the most error-prone stage in reporting mtDNA population data, especially when performed manually. This GHEP-EMPOP collaboration has significantly improved the quality of the individual mtDNA datasets and adds mtDNA population data as valuable resource to the EMPOP database (www.empop.org). (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Identification of FAM46D as a novel cancer/testis antigen using EST data and serological analysis

Cancer/testis Antigens (CTAs) are immunogenic proteins with a restricted expression pattern in normal tissues and aberrant expression in different types of tumors being considered promising candidates for immunotherapy. We used the alignment between EST sequences and the human genome sequence to identify novel CT genes. By examining the EST tissue composition of known CT clusters we defined parameters for the selection of 1184 EST clusters corresponding to putative CT genes. The expression pattern of 70 CT gene candidates was evaluated by RT-PCR in 21 normal tissues, 17 tumor cell lines and 160 primary tumors. We were able to identify 4 CT genes expressed in different types of tumors. The presence of antibodies against the protein encoded by 1 of these 4 CT genes (FAM46D) was exclusively detected in plasma samples from cancer patients. Due to its restricted expression pattern and immunogenicity FAM46D represents a novel target for cancer immunotherapy. (c) 2009 Elsevier Inc. All rights reserved.

An examination of male and female odds ratios by BMI, cigarette smoking, and alcohol consumption for cancers of the oral cavity, pharynx, and larynx in pooled data from 15 case-control studies

Greater tobacco smoking and alcohol consumption and lower body mass index (BMI) increase odds ratios (OR) for oral cavity, oropharyngeal, hypopharyngeal, and laryngeal cancers; however, there are no comprehensive sex-specific comparisons of ORs for these factors. We analyzed 2,441 oral cavity (925 women and 1,516 men), 2,297 oropharynx (564 women and 1,733 men), 508 hypopharynx (96 women and 412 men), and 1,740 larynx (237 women and 1,503 men) cases from the INHANCE consortium of 15 head and neck cancer case-control studies. Controls numbered from 7,604 to 13,829 subjects, depending on analysis. Analyses fitted linear-exponential excess ORs models. ORs were increased in underweight (< 18.5 BMI) relative to normal weight (18.5-24.9) and reduced in overweight and obese categories (a parts per thousand yen25 BMI) for all sites and were homogeneous by sex. ORs by smoking and drinking in women compared with men were significantly greater for oropharyngeal cancer (p < 0.01 for both factors), suggestive for hypopharyngeal cancer (p = 0.05 and p = 0.06, respectively), but homogeneous for oral cavity (p = 0.56 and p = 0.64) and laryngeal (p = 0.18 and p = 0.72) cancers. The extent that OR modifications of smoking and drinking by sex for oropharyngeal and, possibly, hypopharyngeal cancers represent true associations, or derive from unmeasured confounders or unobserved sex-related disease subtypes (e.g., human papillomavirus-positive oropharyngeal cancer) remains to be clarified.

Prevalence of cannabis use in Brazil: Data from the I Brazilian National Alcohol Survey (BNAS)

Aims: To estimate the prevalence of cannabis use in the last 12 months in the Brazilian population and to examine its association with individual and geographic characteristics. Design: Cross-sectional survey with a national probabilistic sample. Participants: 3006 individuals aged 14 to 65 years. Measurements: Questionnaire based on well established instruments, adapted to the Brazilian population. Findings: The 12-month prevalence of cannabis use was 2.1% (95%Cl 1.3-2.9). Male gender, better educational level, unemployment and living in the regions South and Southeast were independently associated with higher 12-month prevalence of cannabis use. Conclusion: While the prevalence of cannabis use in Brazil is lower than in many countries, the profile of those who are more likely to have used it is similar. Educational and prevention policies should be focused on specific population groups. (C) 2009 Elsevier Ltd. All rights reserved.

Behavioral disturbances in Noonan Syndrome: Brazilian preliminary data

Different from other countries Of Europe and North American, studies about the behavioral profile of Noonan syndrome`s patients are inexistent. The objective of this study was to report the profiles of behavioral functions of 10 participants (4 females and 6 males), with mutations in the PTPN11 gene. For this assessment it was used the Inventory of Behaviors of Children and Adolescents from 6 to 18 years (CBCL/6-18) and the Inventory of Auto-Evaluation for Adults from 18 to 59 years (ASR). The main results point that in Adaptive Functioning Scale all the participants were in the normality range. In the Syndrome Scale the adult participants were in normality range and the children were in clinical range to the sub-scales anxious/depressed, somatic complaints and aggressive behavior. In the DSM-Oriented Scale, 25% of the adult patients were in the borderline clinical range and clinical range, respectively, for Avoidant Personality Problems and Antisocial Personality Problems. About the both children in this scale were in the clinical range of Affective Problems and Anxiety Problems. This relatively homogenous sample, regarding the PTPN11 gene, shows a normal adult behavioral profile, on the average. However, the individual children anti adult profiles show diverse internalizing and externalizing behavioral disturbances.