A meta-analysis of the feed intake and growth performance of broiler chickens challenged by bacteria

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

The use of artificial neural networks in analysing the nutritional ecology of Chrysomya megacephala (F.) (Diptera: Calliphoridae), compared with a statistical model

Artificial neural networks (ANNs) have been widely applied to the resolution of complex biological problems. An important feature of neural models is that their implementation is not precluded by the theoretical distribution shape of the data used. Frequently, the performance of ANNs over linear or non-linear regression-based statistical methods is deemed to be significantly superior if suitable sample sizes are provided, especially in multidimensional and non-linear processes. The current work was aimed at utilising three well-known neural network methods in order to evaluate whether these models would be able to provide more accurate outcomes in relation to a conventional regression method in pupal weight predictions of Chrysomya megacephala, a species of blowfly (Diptera: Calliphoridae), using larval density (i.e. the initial number of larvae), amount of available food and pupal size as input data. It was possible to notice that the neural networks yielded more accurate performances in comparison with the statistical model (multiple regression). Assessing the three types of networks utilised (Multi-layer Perceptron, Radial Basis Function and Generalised Regression Neural Network), no considerable differences between these models were detected. The superiority of these neural models over a classical statistical method represents an important fact, because more accurate models may clarify several intricate aspects concerning the nutritional ecology of blowflies.

Avaliação do comportamento da mecânica respiratória e dos testes de exercício cardiopulmonar no pré e pós-operatório de pacientes submetidos à toracotomia para tratamento de doenças malignas e benignas, sua relação com as complicações pós-operatórias e com a qualidade de vida

Pós-graduação em Bases Gerais da Cirurgia - FMB

Referee Assignment Problem Case: Italian Volleyball Championships

This thesis addresses the formulation of a referee assignment problem for the Italian Volleyball Serie A Championships. The problem has particular constraints such as a referee must be assigned to different teams in a given period of times, and the minimal/maximal level of workload for each referee is obtained by considering cost and profit in the objective function. The problem has been solved through an exact method by using an integer linear programming formulation and a clique based decomposition for improving the computing time. Extensive computational experiments on real-world instances have been performed to determine the effectiveness of the proposed approach.

Changes in the use of broad-spectrum antibiotics after cefepime shortage: a time series analysis

The original cefepime product was withdrawn from the Swiss market in January 2007 and replaced by a generic 10 months later. The goals of the study were to assess the impact of this cefepime shortage on the use and costs of alternative broad-spectrum antibiotics, on antibiotic policy, and on resistance of Pseudomonas aeruginosa toward carbapenems, ceftazidime, and piperacillin-tazobactam. A generalized regression-based interrupted time series model assessed how much the shortage changed the monthly use and costs of cefepime and of selected alternative broad-spectrum antibiotics (ceftazidime, imipenem-cilastatin, meropenem, piperacillin-tazobactam) in 15 Swiss acute care hospitals from January 2005 to December 2008. Resistance of P. aeruginosa was compared before and after the cefepime shortage. There was a statistically significant increase in the consumption of piperacillin-tazobactam in hospitals with definitive interruption of cefepime supply and of meropenem in hospitals with transient interruption of cefepime supply. Consumption of each alternative antibiotic tended to increase during the cefepime shortage and to decrease when the cefepime generic was released. These shifts were associated with significantly higher overall costs. There was no significant change in hospitals with uninterrupted cefepime supply. The alternative antibiotics for which an increase in consumption showed the strongest association with a progression of resistance were the carbapenems. The use of alternative antibiotics after cefepime withdrawal was associated with a significant increase in piperacillin-tazobactam and meropenem use and in overall costs and with a decrease in susceptibility of P. aeruginosa in hospitals. This warrants caution with regard to shortages and withdrawals of antibiotics.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

Perceived Influence and Friendship as Antecedents of Cooperation in Top Management Teams: A Network Approach

Using the relational dyad as unit of analysis this study examines the effects of perceived influence and friendship ties on the formation and maintenance of cooperative relationships between corporate top executives. Specifically, it is argued that perceived influence as well as friendship ties between any two managers will enhance the likelihood that these managers collaborate with each other. Additionally, a negative interaction effect between perceived influence and friendship on cooperation is proposed. The empirical analyses draw on network data that have been collected among all members of the top two organizational levels for the strategy-making process in two multinational firms headquartered in Germany. Applying logistic regression based on QAP the empirical results support our hypotheses on the direct effects between perceived influence, friendship ties, and cooperative relationships in both companies. In addition, we find at least partial support for our assumption that perceived influence and friendship interact negatively with respect to their effect on cooperation. Seemingly, perceived influence is partially substituted by managerial friendship ties.

Fully Automatic CT Segmentation for Computer-Assisted Pre-operative Planning of Hip Arthroscopy

Extraction of both pelvic and femoral surface models of a hip joint from CT data for computer-assisted pre-operative planning of hip arthroscopy is addressed. We present a method for a fully automatic image segmentation of a hip joint. Our method works by combining fast random forest (RF) regression based landmark detection, atlas-based segmentation, with articulated statistical shape model (aSSM) based hip joint reconstruction. The two fundamental contributions of our method are: (1) An improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the atlas-based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Validation on 30 hip CT images show that our method achieves high performance in segmenting pelvis, left proximal femur, and right proximal femur surfaces with an average accuracy of 0.59 mm, 0.62 mm, and 0.58 mm, respectively.

FACTS: Fully Automatic CT Segmentation of a Hip Joint

Extraction of surface models of a hip joint from CT data is a pre-requisite step for computer assisted diagnosis and planning (CADP) of periacetabular osteotomy (PAO). Most of existing CADP systems are based on manual segmentation, which is time-consuming and hard to achieve reproducible results. In this paper, we present a Fully Automatic CT Segmentation (FACTS) approach to simultaneously extract both pelvic and femoral models. Our approach works by combining fast random forest (RF) regression based landmark detection, multi-atlas based segmentation, with articulated statistical shape model (aSSM) based fitting. The two fundamental contributions of our approach are: (1) an improved fast Gaussian transform (IFGT) is used within the RF regression framework for a fast and accurate landmark detection, which then allows for a fully automatic initialization of the multi-atlas based segmentation; and (2) aSSM based fitting is used to preserve hip joint structure and to avoid penetration between the pelvic and femoral models. Taking manual segmentation as the ground truth, we evaluated the present approach on 30 hip CT images (60 hips) with a 6-fold cross validation. When the present approach was compared to manual segmentation, a mean segmentation accuracy of 0.40, 0.36, and 0.36 mm was found for the pelvis, the left proximal femur, and the right proximal femur, respectively. When the models derived from both segmentations were used to compute the PAO diagnosis parameters, a difference of 2.0 ± 1.5°, 2.1 ± 1.6°, and 3.5 ± 2.3% were found for anteversion, inclination, and acetabular coverage, respectively. The achieved accuracy is regarded as clinically accurate enough for our target applications.

INTEGRATIVE BIOMARKER IDENTIFICATION AND CLASSIFICATION USING HIGH THROUGHPUT ASSAYS

It is well accepted that tumorigenesis is a multi-step procedure involving aberrant functioning of genes regulating cell proliferation, differentiation, apoptosis, genome stability, angiogenesis and motility. To obtain a full understanding of tumorigenesis, it is necessary to collect information on all aspects of cell activity. Recent advances in high throughput technologies allow biologists to generate massive amounts of data, more than might have been imagined decades ago. These advances have made it possible to launch comprehensive projects such as (TCGA) and (ICGC) which systematically characterize the molecular fingerprints of cancer cells using gene expression, methylation, copy number, microRNA and SNP microarrays as well as next generation sequencing assays interrogating somatic mutation, insertion, deletion, translocation and structural rearrangements. Given the massive amount of data, a major challenge is to integrate information from multiple sources and formulate testable hypotheses. This thesis focuses on developing methodologies for integrative analyses of genomic assays profiled on the same set of samples. We have developed several novel methods for integrative biomarker identification and cancer classification. We introduce a regression-based approach to identify biomarkers predictive to therapy response or survival by integrating multiple assays including gene expression, methylation and copy number data through penalized regression. To identify key cancer-specific genes accounting for multiple mechanisms of regulation, we have developed the integIRTy software that provides robust and reliable inferences about gene alteration by automatically adjusting for sample heterogeneity as well as technical artifacts using Item Response Theory. To cope with the increasing need for accurate cancer diagnosis and individualized therapy, we have developed a robust and powerful algorithm called SIBER to systematically identify bimodally expressed genes using next generation RNAseq data. We have shown that prediction models built from these bimodal genes have the same accuracy as models built from all genes. Further, prediction models with dichotomized gene expression measurements based on their bimodal shapes still perform well. The effectiveness of outcome prediction using discretized signals paves the road for more accurate and interpretable cancer classification by integrating signals from multiple sources.

Developing the follow-up schedules for women with breast cancer

Background: The follow-up care for women with breast cancer requires an understanding of disease recurrence patterns and the follow-up visit schedule should be determined according to the times when the recurrence are most likely to occur, so that preventive measure can be taken to avoid or minimize the recurrence. Objective: To model breast cancer recurrence through stochastic process with an aim to generate a hazard function for determining a follow-up schedule. Methods: We modeled the process of disease progression as the time transformed Weiner process and the first-hitting-time was used as an approximation of the true failure time. The women's "recurrence-free survival time" or a "not having the recurrence event" is modeled by the time it takes Weiner process to cross a threshold value which represents a woman experiences breast cancer recurrence event. We explored threshold regression model which takes account of covariates that contributed to the prognosis of breast cancer following development of the first-hitting time model. Using real data from SEER-Medicare, we proposed models of follow-up visits schedule on the basis of constant probability of disease recurrence between consecutive visits. Results: We demonstrated that the threshold regression based on first-hitting-time modeling approach can provide useful predictive information about breast cancer recurrence. Our results suggest the surveillance and follow-up schedule can be determined for women based on their prognostic factors such as tumor stage and others. Women with early stage of disease may be seen less frequently for follow-up visits than those women with locally advanced stages. Our results from SEER-Medicare data support the idea of risk-controlled follow-up strategies for groups of women. Conclusion: The methodology we proposed in this study allows one to determine individual follow-up scheduling based on a parametric hazard function that incorporates known prognostic factors.^

User Experience in Human-Technology Interaction. Communication, context and evaluation methodology

En esta Tesis se presentan dos líneas de investigación relacionadas y que contribuyen a las áreas de Interacción Hombre-Tecnología (o Máquina; siglas en inglés: HTI o HMI), lingüística computacional y evaluación de la experiencia del usuario. Las dos líneas en cuestión son el diseño y la evaluación centrada en el usuario de sistemas de Interacción Hombre-Máquina avanzados. En la primera parte de la Tesis (Capítulos 2 a 4) se abordan cuestiones fundamentales del diseño de sistemas HMI avanzados. El Capítulo 2 presenta una panorámica del estado del arte de la investigación en el ámbito de los sistemas conversacionales multimodales, con la que se enmarca el trabajo de investigación presentado en el resto de la Tesis. Los Capítulos 3 y 4 se centran en dos grandes aspectos del diseño de sistemas HMI: un gestor del diálogo generalizado para tratar la Interacción Hombre-Máquina multimodal y sensible al contexto, y el uso de agentes animados personificados (ECAs) para mejorar la robustez del diálogo, respectivamente. El Capítulo 3, sobre gestión del diálogo, aborda el tratamiento de la heterogeneidad de la información proveniente de las modalidades comunicativas y de los sensores externos. En este capítulo se propone, en un nivel de abstracción alto, una arquitectura para la gestión del diálogo con influjos heterogéneos de información, apoyándose en el uso de State Chart XML. En el Capítulo 4 se presenta una contribución a la representación interna de intenciones comunicativas, y su traducción a secuencias de gestos a ejecutar por parte de un ECA, diseñados específicamente para mejorar la robustez en situaciones de diálogo críticas que pueden surgir, por ejemplo, cuando se producen errores de entendimiento en la comunicación entre el usuario humano y la máquina. Se propone, en estas páginas, una extensión del Functional Mark-up Language definido en el marco conceptual SAIBA. Esta extensión permite representar actos comunicativos que realizan intenciones del emisor (la máquina) que no se pretende sean captadas conscientemente por el receptor (el usuario humano), pero con las que se pretende influirle a éste e influir el curso del diálogo. Esto se consigue mediante un objeto llamado Base de Intenciones Comunicativas (en inglés, Communication Intention Base, o CIB). La representación en el CIB de intenciones “no claradas” además de las explícitas permite la construcción de actos comunicativos que realizan simultáneamente varias intenciones comunicativas. En el Capítulo 4 también se describe un sistema experimental para el control remoto (simulado) de un asistente domótico, con autenticación de locutor para dar acceso, y con un ECA en el interfaz de cada una de estas tareas. Se incluye una descripción de las secuencias de comportamiento verbal y no verbal de los ECAs, que fueron diseñados específicamente para determinadas situaciones con objeto de mejorar la robustez del diálogo. Los Capítulos 5 a 7 conforman la parte de la Tesis dedicada a la evaluación. El Capítulo 5 repasa antecedentes relevantes en la literatura de tecnologías de la información en general, y de sistemas de interacción hablada en particular. Los principales antecedentes en el ámbito de la evaluación de la interacción sobre los cuales se ha desarrollado el trabajo presentado en esta Tesis son el Technology Acceptance Model (TAM), la herramienta Subjective Assessment of Speech System Interfaces (SASSI), y la Recomendación P.851 de la ITU-T. En el Capítulo 6 se describen un marco y una metodología de evaluación aplicados a la experiencia del usuario con sistemas HMI multimodales. Se desarrolló con este propósito un novedoso marco de evaluación subjetiva de la calidad de la experiencia del usuario y su relación con la aceptación por parte del mismo de la tecnología HMI (el nombre dado en inglés a este marco es Subjective Quality Evaluation Framework). En este marco se articula una estructura de clases de factores subjetivos relacionados con la satisfacción y aceptación por parte del usuario de la tecnología HMI propuesta. Esta estructura, tal y como se propone en la presente tesis, tiene dos dimensiones ortogonales. Primero se identifican tres grandes clases de parámetros relacionados con la aceptación por parte del usuario: “agradabilidad ” (likeability: aquellos que tienen que ver con la experiencia de uso, sin entrar en valoraciones de utilidad), rechazo (los cuales sólo pueden tener una valencia negativa) y percepción de utilidad. En segundo lugar, este conjunto clases se reproduce para distintos “niveles, o focos, percepción del usuario”. Éstos incluyen, como mínimo, un nivel de valoración global del sistema, niveles correspondientes a las tareas a realizar y objetivos a alcanzar, y un nivel de interfaz (en los casos propuestos en esta tesis, el interfaz es un sistema de diálogo con o sin un ECA). En el Capítulo 7 se presenta una evaluación empírica del sistema descrito en el Capítulo 4. El estudio se apoya en los mencionados antecedentes en la literatura, ampliados con parámetros para el estudio específico de los agentes animados (los ECAs), la auto-evaluación de las emociones de los usuarios, así como determinados factores de rechazo (concretamente, la preocupación por la privacidad y la seguridad). También se evalúa el marco de evaluación subjetiva de la calidad propuesto en el capítulo anterior. Los análisis de factores efectuados revelan una estructura de parámetros muy cercana conceptualmente a la división de clases en utilidad-agradabilidad-rechazo propuesta en dicho marco, resultado que da cierta validez empírica al marco. Análisis basados en regresiones lineales revelan estructuras de dependencias e interrelación entre los parámetros subjetivos y objetivos considerados. El efecto central de mediación, descrito en el Technology Acceptance Model, de la utilidad percibida sobre la relación de dependencia entre la intención de uso y la facilidad de uso percibida, se confirma en el estudio presentado en la presente Tesis. Además, se ha encontrado que esta estructura de relaciones se fortalece, en el estudio concreto presentado en estas páginas, si las variables consideradas se generalizan para cubrir más ampliamente las categorías de agradabilidad y utilidad contempladas en el marco de evaluación subjetiva de calidad. Se ha observado, asimismo, que los factores de rechazo aparecen como un componente propio en los análisis de factores, y además se distinguen por su comportamiento: moderan la relación entre la intención de uso (que es el principal indicador de la aceptación del usuario) y su predictor más fuerte, la utilidad percibida. Se presentan también resultados de menor importancia referentes a los efectos de los ECAs sobre los interfaces de los sistemas de diálogo y sobre los parámetros de percepción y las valoraciones de los usuarios que juegan un papel en conformar su aceptación de la tecnología. A pesar de que se observa un rendimiento de la interacción dialogada ligeramente mejor con ECAs, las opiniones subjetivas son muy similares entre los dos grupos experimentales (uno interactuando con un sistema de diálogo con ECA, y el otro sin ECA). Entre las pequeñas diferencias encontradas entre los dos grupos destacan las siguientes: en el grupo experimental sin ECA (es decir, con interfaz sólo de voz) se observó un efecto más directo de los problemas de diálogo (por ejemplo, errores de reconocimiento) sobre la percepción de robustez, mientras que el grupo con ECA tuvo una respuesta emocional más positiva cuando se producían problemas. Los ECAs parecen generar inicialmente expectativas más elevadas en cuanto a las capacidades del sistema, y los usuarios de este grupo se declaran más seguros de sí mismos en su interacción. Por último, se observan algunos indicios de efectos sociales de los ECAs: la “amigabilidad ” percibida los ECAs estaba correlada con un incremento la preocupación por la seguridad. Asimismo, los usuarios del sistema con ECAs tendían más a culparse a sí mismos, en lugar de culpar al sistema, de los problemas de diálogo que pudieran surgir, mientras que se observó una ligera tendencia opuesta en el caso de los usuarios del sistema con interacción sólo de voz. ABSTRACT This Thesis presents two related lines of research work contributing to the general fields of Human-Technology (or Machine) Interaction (HTI, or HMI), computational linguistics, and user experience evaluation. These two lines are the design and user-focused evaluation of advanced Human-Machine (or Technology) Interaction systems. The first part of the Thesis (Chapters 2 to 4) is centred on advanced HMI system design. Chapter 2 provides a background overview of the state of research in multimodal conversational systems. This sets the stage for the research work presented in the rest of the Thesis. Chapers 3 and 4 focus on two major aspects of HMI design in detail: a generalised dialogue manager for context-aware multimodal HMI, and embodied conversational agents (ECAs, or animated agents) to improve dialogue robustness, respectively. Chapter 3, on dialogue management, deals with how to handle information heterogeneity, both from the communication modalities or from external sensors. A highly abstracted architectural contribution based on State Chart XML is proposed. Chapter 4 presents a contribution for the internal representation of communication intentions and their translation into gestural sequences for an ECA, especially designed to improve robustness in critical dialogue situations such as when miscommunication occurs. We propose an extension of the functionality of Functional Mark-up Language, as envisaged in much of the work in the SAIBA framework. Our extension allows the representation of communication acts that carry intentions that are not for the interlocutor to know of, but which are made to influence him or her as well as the flow of the dialogue itself. This is achieved through a design element we have called the Communication Intention Base. Such r pr s ntation of “non- clar ” int ntions allows th construction of communication acts that carry several communication intentions simultaneously. Also in Chapter 4, an experimental system is described which allows (simulated) remote control to a home automation assistant, with biometric (speaker) authentication to grant access, featuring embodied conversation agents for each of the tasks. The discussion includes a description of the behavioural sequences for the ECAs, which were designed for specific dialogue situations with particular attention given to the objective of improving dialogue robustness. Chapters 5 to 7 form the evaluation part of the Thesis. Chapter 5 reviews evaluation approaches in the literature for information technologies, as well as in particular for speech-based interaction systems, that are useful precedents to the contributions of the present Thesis. The main evaluation precedents on which the work in this Thesis has built are the Technology Acceptance Model (TAM), the Subjective Assessment of Speech System Interfaces (SASSI) tool, and ITU-T Recommendation P.851. Chapter 6 presents the author’s work in establishing an valuation framework and methodology applied to the users’ experience with multimodal HMI systems. A novel user-acceptance Subjective Quality Evaluation Framework was developed by the author specifically for this purpose. A class structure arises from two orthogonal sets of dimensions. First we identify three broad classes of parameters related with user acceptance: likeability factors (those that have to do with the experience of using the system), rejection factors (which can only have a negative valence) and perception of usefulness. Secondly, the class structure is further broken down into several “user perception levels”; at the very least: an overall system-assessment level, task and goal-related levels, and an interface level (e.g., a dialogue system with or without an ECA). An empirical evaluation of the system described in Chapter 4 is presented in Chapter 7. The study was based on the abovementioned precedents in the literature, expanded with categories covering the inclusion of an ECA, the users’ s lf-assessed emotions, and particular rejection factors (privacy and security concerns). The Subjective Quality Evaluation Framework proposed in the previous chapter was also scrutinised. Factor analyses revealed an item structure very much related conceptually to the usefulness-likeability-rejection class division introduced above, thus giving it some empirical weight. Regression-based analysis revealed structures of dependencies, paths of interrelations, between the subjective and objective parameters considered. The central mediation effect, in the Technology Acceptance Model, of perceived usefulness on the dependency relationship of intention-to-use with perceived ease of use was confirmed in this study. Furthermore, the pattern of relationships was stronger for variables covering more broadly the likeability and usefulness categories in the Subjective Quality Evaluation Framework. Rejection factors were found to have a distinct presence as components in factor analyses, as well as distinct behaviour: they were found to moderate the relationship between intention-to-use (the main measure of user acceptance) and its strongest predictor, perceived usefulness. Insights of secondary importance are also given regarding the effect of ECAs on the interface of spoken dialogue systems and the dimensions of user perception and judgement attitude that may have a role in determining user acceptance of the technology. Despite observing slightly better performance values in the case of the system with the ECA, subjective opinions regarding both systems were, overall, very similar. Minor differences between two experimental groups (one interacting with an ECA, the other only through speech) include a more direct effect of dialogue problems (e.g., non-understandings) on perceived dialogue robustness for the voice-only interface test group, and a more positive emotional response for the ECA test group. Our findings further suggest that the ECA generates higher initial expectations, and users seem slightly more confident in their interaction with the ECA than do those without it. Finally, mild evidence of social effects of ECAs was also found: the perceived friendliness of the ECA increased security concerns, and ECA users may tend to blame themselves rather than the system when dialogue problems are encountered, while the opposite may be true for voice-only users.

Methods to Control for Bias in Observational Studies

Thesis (Master's)--University of Washington, 2016-06

Replicated linkage for eye color on 15q using comparative ratings of sibling pairs

The aim of the study was to perform a genetic linkage analysis for eye color, for comparative data. Similarity in eye color of mono- and dizygotic twins was rated by the twins' mother, their father and/or the twins themselves. For 4748 twin pairs the similarity in eye color was available on a three point scale (not at all alike-somewhat alike-completely alike), absolute eye color on individuals was not assessed. The probability that twins were alike for eye color was calculated as a weighted average of the different responses of all respondents on several different time points. The mean probability of being alike for eye color was 0.98 for MZ twins (2167 pairs), whereas the mean probability for DZ twins was 0.46 (2537 pairs), suggesting very high heritability for eye color. For 294 DZ twin pairs genome-wide marker data were available. The probability of being alike for eye color was regressed on the average amount of IBD sharing. We found a peak LOD-score of 2.9 at chromosome 15q, overlapping with the region recently implicated for absolute ratings of eye color in Australian twins [Zhu, G., Evans, D. M., Duffy, D. L., Montgomery, G. W., Medland, S. E., Gillespie, N. A., Ewen, K. R., Jewell, M., Liew, Y. W., Hayward, N. K., Sturm, R. A., Trent, J. M., and Martin, N. G. (2004). Twin Res. 7:197-210] and containing the OCA2 gene, which is the major candidate gene for eye color [Sturm, R. A. Teasdale, R. D, and Box, N. F. (2001). Gene 277:49-62]. Our results demonstrate that comparative measures on relatives can be used in genetic linkage analysis.

Assessment of statistical change criteria used to define significant change in neuropsychological test performance following cardiac surgery

Objective: This paper compares four techniques used to assess change in neuropsychological test scores before and after coronary artery bypass graft surgery (CABG), and includes a rationale for the classification of a patient as overall impaired. Methods: A total of 55 patients were tested before and after surgery on the MicroCog neuropsychological test battery. A matched control group underwent the same testing regime to generate test–retest reliabilities and practice effects. Two techniques designed to assess statistical change were used: the Reliable Change Index (RCI), modified for practice, and the Standardised Regression-based (SRB) technique. These were compared against two fixed cutoff techniques (standard deviation and 20% change methods). Results: The incidence of decline across test scores varied markedly depending on which technique was used to describe change. The SRB method identified more patients as declined on most measures. In comparison, the two fixed cutoff techniques displayed relatively reduced sensitivity in the detection of change. Conclusions: Overall change in an individual can be described provided the investigators choose a rational cutoff based on likely spread of scores due to chance. A cutoff value of ≥20% of test scores used provided acceptable probability based on the number of tests commonly encountered. Investigators must also choose a test battery that minimises shared variance among test scores.