917 resultados para linear mixed model
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Objective: Minimizing resection and preserving leaflet tissue has been previously shown to be beneficial for mitral valve function and leaflet kinematics after repair of acute posterior leaflet prolapse in porcine valves. We examined the effects of different additional methods of mitral valve repair (neochordoplasty, ring annuloplasty, edge-to-edge repair and triangular resection) on hemodynamics at different heart rates in an experimental model. Methods: Severe acute P2 prolapse was created in eight porcine mitral valves by resecting the posterior marginal chordae. Valve hemodynamics was quantified under pulsatile conditions in an in vitro heart simulator before and after surgical manipulation. Mitral regurgitation was corrected using four different methods of repair on the same valve: neochordoplasty with expanded polytetrafluoroethylene sutures alone and together with ring annuloplasty, edge-to-edge repair and triangular resection, both with non-restrictive annuloplasty. Residual mitral valve leak, trans-valvular pressure gradients, flow and cardiac output were measured at 60 and 80 beats/min. A validated statistical linear mixed model was used to analyze the effect of treatment. The p values were calculated using a two-sided Wald test. Results: Only neochordoplasty with expanded polytetrafluoroethylene sutures but without ring annuloplasty achieved similar hemodynamics compared to those of the native mitral valve (p range 0.071-0.901). Trans-valvular diastolic pressure gradients were within a physiologic range but significantly higher than those of the native valve following neochordoplasty with ring annuloplasty (p=0.000), triangular resection (p=0.000) and edge-to-edge repair (p=0.000). Neochordoplasty alone was significantly better in terms of hemodynamic than neochordoplasty with a ring annuloplasty (p=0.000). These values were stable regardless of heart rate or ring size. Conclusions: Neochordoplasty without ring annuloplasty is the only repair technique able to achieve almost native physiological hemodynamics after correction of leaflet prolapse in a porcine experimental model of acute chordal rupture.
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OBJECTIVE To determine the biomechanical effect of an intervertebral spacer on construct stiffness in a PVC model and cadaveric canine cervical vertebral columns stabilized with monocortical screws/polymethylmethacrylate (PMMA). STUDY DESIGN Biomechanical study. SAMPLE POPULATION PVC pipe; cadaveric canine vertebral columns. METHODS PVC model-PVC pipe was used to create a gap model mimicking vertebral endplate orientation and disk space width of large-breed canine cervical vertebrae; 6 models had a 4-mm gap with no spacer (PVC group 1); 6 had a PVC pipe ring spacer filling the gap (PCV group 2). Animals-large breed cadaveric canine cervical vertebral columns (C2-C7) from skeletally mature dogs without (cadaveric group 1, n = 6, historical data) and with an intervertebral disk spacer (cadaveric group 2, n = 6) were used. All PVC models and cadaver specimens were instrumented with monocortical titanium screws/PMMA. Stiffness of the 2 PVC groups was compared in extension, flexion, and lateral bending using non-destructive 4-point bend testing. Stiffness testing in all 3 directions was performed of the unaltered C4-C5 vertebral motion unit in cadaveric spines and repeated after placement of an intervertebral cortical allograft ring and instrumentation. Data were compared using a linear mixed model approach that also incorporated data from previously tested spines with the same screw/PMMA construct but without disk spacer (cadaveric group 1). RESULTS Addition of a spacer increased construct stiffness in both the PVC model (P < .001) and cadaveric vertebral columns (P < .001) compared to fixation without a spacer. CONCLUSIONS Addition of an intervertebral spacer significantly increased construct stiffness of monocortical screw/PMMA fixation.
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Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^
New methods for quantification and analysis of quantitative real-time polymerase chain reaction data
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Quantitative real-time polymerase chain reaction (qPCR) is a sensitive gene quantitation method that has been widely used in the biological and biomedical fields. The currently used methods for PCR data analysis, including the threshold cycle (CT) method, linear and non-linear model fitting methods, all require subtracting background fluorescence. However, the removal of background fluorescence is usually inaccurate, and therefore can distort results. Here, we propose a new method, the taking-difference linear regression method, to overcome this limitation. Briefly, for each two consecutive PCR cycles, we subtracted the fluorescence in the former cycle from that in the later cycle, transforming the n cycle raw data into n-1 cycle data. Then linear regression was applied to the natural logarithm of the transformed data. Finally, amplification efficiencies and the initial DNA molecular numbers were calculated for each PCR run. To evaluate this new method, we compared it in terms of accuracy and precision with the original linear regression method with three background corrections, being the mean of cycles 1-3, the mean of cycles 3-7, and the minimum. Three criteria, including threshold identification, max R2, and max slope, were employed to search for target data points. Considering that PCR data are time series data, we also applied linear mixed models. Collectively, when the threshold identification criterion was applied and when the linear mixed model was adopted, the taking-difference linear regression method was superior as it gave an accurate estimation of initial DNA amount and a reasonable estimation of PCR amplification efficiencies. When the criteria of max R2 and max slope were used, the original linear regression method gave an accurate estimation of initial DNA amount. Overall, the taking-difference linear regression method avoids the error in subtracting an unknown background and thus it is theoretically more accurate and reliable. This method is easy to perform and the taking-difference strategy can be extended to all current methods for qPCR data analysis.^
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La mosca blanca del fresno, Siphoninus phillyreae (Haliday) , es una especie polífaga invasiva que causa graves daños en sus hospedadores, entre ellos el olivo (Olea europaea L.). El uso del hospedador por parte de S. phillyreae fue observado en tres cultivares de olivo (Arauco, Arbequina y Aloreña) en el norte de la provincia de La Rioja (Argentina) durante 2007 y 2008. De cada cultivar se muestrearon seis plantas infestadas y de cada planta se tomaron ocho hojas. De cada hoja se registró la abundancia de adultos y estados inmaduros de la mosca blanca que fueron comparadas entre los cultivares mediante modelos lineales generales y mixtos. Los resultados obtenidos mostraron diferencias significativas entre las densidades de adultos y ninfas de S. phillyreae en los distintos cultivares de olivo analizados. Dichos resultados indican que este insecto realiza un uso diferente de los cultivares de olivo, siendo Arauco y Arbequina las variedades hospedadoras más utilizadas en la zona de estudio.
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The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.
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The feeding rate of a parasitic gnathiid isopod on fish was examined. Individual fish, Hemigymnus melapterus, were exposed to gnathiid larvae and sampled after 5, 10, 30, 60, and 240 min. I recorded whether larvae had an engorged gut, an engorged gut containing red material, or had dropped off the fish after having completed engorgement; variation among sampling times and larval stages was analyzed using generalized linear mixed model analyses. The likelihood that larvae had an engorged gut increased with time and varied with larval stage. First stage (1.45 mm) larvae. After 30 min, however, most (>93%) larvae had an engorged gut regardless of their larval stage. The likelihood of red material in the gut of third stage larvae increased over time (46% after 30 min, 70% after 60 min, and 86% after 240 min) while that of first and second stage larvae remained relatively low (
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Passive tilting increases ventilation in healthy subjects; however, controversy surrounds the proposed mechanism. This study is aimed to evaluate the possible mechanism for changes to ventilation following passive head-up tilt (HUT) and active standing by comparison of a range of ventilatory, metabolic and mechanical parameters. Ventilatory parameters (V (T), V (E), V (E)/VO2, V (E)/VCO2, f and PetCO(2)), functional residual capacity (FRC), respiratory mechanics with impulse oscillometry; oxygen consumption (VO2) and carbon dioxide production (VCO2) were measured in 20 healthy male subjects whilst supine, following HUT to 70 degrees and unsupported standing. Data were analysed using a linear mixed model. HUT to 70 degrees from supine increased minute ventilation (V (E)) (P < 0.001), tidal volume (V (T)) (P=0.001), ventilatory equivalent for O-2 (V (E)/VO2) (P=0.020) and the ventilatory equivalent for CO2 (V (E)/VCO2) (P < 0.001) with no change in f (P=0.488). HUT also increased FRC (P < 0.001) and respiratory system reactance (X5Hz) (P < 0.001) with reduced respiratory system resistance (R5Hz) (P=0.004) and end-tidal carbon dioxide (PetCO(2)) (P < 0.001) compared to supine. Standing increased V (E) (P < 0.001), V (T) (P < 0.001) and V (E)/VCO2 (P=0.020) with no change in respiratory rate (f) (P=0.065), V (E)/VO2 (P=0.543). Similar changes in FRC (P < 0.001), R5Hz (P=0.013), X5Hz (P < 0.001) and PetCO(2) (P < 0.001) compared to HUT were found. In contrast to HUT, standing increased VO2 (P=0.002) and VCO2 (P=0.048). The greater increase in V (E) in standing compared to HUT appears to be related to increased VO2 and VCO2 associated with increased muscle activity in the unsupported standing position. This has implications for exercise prescription and rehabilitation of critically ill patients who have reduced cardiovascular and respiratory reserve.
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Background: Written material is often inaccessible fro people with aphasia. The format of written material needs to be adapted to enable people with aphasia to read with understanding. Aims: This study aimed to further explore some issues raised in Rose, Worrall, and MacKenna (2003) concerning the effects of aphasia-friendly formats on the reading comprehension of people with aphasia. It was hypothesised that people with aphasia would comprehend significantly more paragraphs that were formatted in an aphasia-friendly manner than control paragraphs. This study also aimed to investigate if each single aspect of aphasia-friendly formatting (i.e., simplified vocabulary and syntax, large print, increased white spacem and pictures) used in isolation would result in increased comprehension compared to control paragraphs. Other aims were to compare the effect of aphasia-friendly fromatting with the effects of each single adaptation, and to investigate if the effects of aphasia-friendly formates were related to aphasia severity. Methods & Procedures: Participants with mild to moderately severe aphasia (N = 9) read a battery of 90 paragraphs and selected the best word of phrase from a choice of four to complete each paragraph. A linear mixed model (p < .05) was used to analyse the differences in reading comprehension with each paragraph fromat across three reading grade levels. Outcomes & Results: People with aphasia comprehended significantly more aphasia-friendly paragraphs than control paragraphs. They also comprehended significantly more paragraphs with each of the following single adaptations: simplified vocabulary and syntax, large ptint, and increased white spaces. Although people with aphasia tended to comprehend more paragraphs with pictures added than control paragraphs, this difference was not significant. No significant correlation between aphasia severity and the effect of aphasia-friendly formatting was found. Conclusion: This study supports the idea that aphasia-friendly formats increase the reading comprehension of people with aphasia. It suggests that adding pictures, particularly Clip Art pictures, may not significantly improve the reading the reading comprehension of people with aphasia. These findings have implications for all written communication with people with aphasia, both in the clinical setting and in the wider community. Applying these findings may enable people with aphasia to have equal access to written information and to participate in society.
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Context: Subclinical hypothyroidism (SCH) and cognitive dysfunction are both common in the elderly and have been linked. It is important to determine whether T4 replacement therapy in SCH confers cognitive benefit. Objective: Our objective was to determine whether administration of T4 replacement to achieve biochemical euthyroidism in subjects with SCH improves cognitive function. Design and Setting: We conducted a double-blind placebo-controlled randomized controlled trial in the context of United Kingdom primary care. Patients: Ninety-four subjects aged 65 yr and over (57 females, 37 males) with SCH were recruited from a population of 147 identified by screening. Intervention: T4 or placebo was given at an initial dosage of one tablet of either placebo or 25 µg T4 per day for 12 months. Thyroid function tests were performed at 8-weekly intervals with dosage adjusted in one-tablet increments to achieve TSH within the reference range for subjects in treatment arm. Fifty-two subjects received T4 (31 females, 21 males; mean age 73.5 yr, range 65–94 yr); 42 subjects received placebo (26 females, 16 males; mean age 74.2 yr, 66–84 yr). Main Outcome Measures: Mini-Mental State Examination, Middlesex Elderly Assessment of Mental State (covering orientation, learning, memory, numeracy, perception, attention, and language skills), and Trail-Making A and B were administered. Results: Eighty-two percent and 84% in the T4 group achieved euthyroidism at 6- and 12-month intervals, respectively. Cognitive function scores at baseline and 6 and 12 months were as follows: Mini-Mental State Examination T4 group, 28.26, 28.9, and 28.28, and placebo group, 28.17, 27.82, and 28.25 [not significant (NS)]; Middlesex Elderly Assessment of Mental State T4 group, 11.72, 11.67, and 11.78, and placebo group, 11.21, 11.47, and 11.44 (NS); Trail-Making A T4 group, 45.72, 47.65, and 44.52, and placebo group, 50.29, 49.00, and 46.97 (NS); and Trail-Making B T4 group, 110.57, 106.61, and 96.67, and placebo group, 131.46, 119.13, and 108.38 (NS). Linear mixed-model analysis demonstrated no significant changes in any of the measures of cognitive function over time and no between-group difference in cognitive scores at 6 and 12 months. Conclusions: This RCT provides no evidence for treating elderly subjects with SCH with T4 replacement therapy to improve cognitive function.
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Purpose: Depression in older females is a significant and growing problem. Females who experience life stressors across the life span are at higher risk for developing problems with depression than their male counterparts. The primary aim of this study was (a) to examine gender-specific differences in the correlates of depression in older primary care patients based on baseline and longitudinal analyses; and (b) to examine the longitudinal effect of biopsychosocial risk factors on depression treatment outcomes in different models of behavioral healthcare (i.e., integrated care and enhanced referral). Method: This study used a quantitative secondary data analysis with longitudinal data from the Primary Care Research in Substance Abuse and Mental Health for Elderly (PRISM-E) study. A linear mixed model approach to hierarchical linear modeling was used for analysis using baseline assessment, and follow-up from three-month and six-month. Results: For participants diagnosed with major depressive disorder female gender was associated with increased depression severity at six-month compared to males at six-month. Further, the interaction between gender and life stressors found that females who reported loss of family and friends, family issues, money issues, medical illness was related to higher depression severity compared to males whereas lack of activities was related to lower depression severity among females compared to males. Conclusion: These findings suggest that gender moderated the relationship between specific life stressors and depression severity similar to how a protective factor can impact a person's response to a problem and reduce the negative impact of a risk factor on a problem outcome. Therefore, life stressors may be a reliable predictor of depression for both females and males in either behavioral health treatment model. This study concluded that life stressors influence males basic comfort, stability, and survival whereas life stressors influence females' development, personal growth, and happiness; therefore, life stressors may be a useful component to include in gender-based screening and assessment tools for depression. ^
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Robust joint modelling is an emerging field of research. Through the advancements in electronic patient healthcare records, the popularly of joint modelling approaches has grown rapidly in recent years providing simultaneous analysis of longitudinal and survival data. This research advances previous work through the development of a novel robust joint modelling methodology for one of the most common types of standard joint models, that which links a linear mixed model with a Cox proportional hazards model. Through t-distributional assumptions, longitudinal outliers are accommodated with their detrimental impact being down weighed and thus providing more efficient and reliable estimates. The robust joint modelling technique and its major benefits are showcased through the analysis of Northern Irish end stage renal disease patients. With an ageing population and growing prevalence of chronic kidney disease within the United Kingdom, there is a pressing demand to investigate the detrimental relationship between the changing haemoglobin levels of haemodialysis patients and their survival. As outliers within the NI renal data were found to have significantly worse survival, identification of outlying individuals through robust joint modelling may aid nephrologists to improve patient's survival. A simulation study was also undertaken to explore the difference between robust and standard joint models in the presence of increasing proportions and extremity of longitudinal outliers. More efficient and reliable estimates were obtained by robust joint models with increasing contrast between the robust and standard joint models when a greater proportion of more extreme outliers are present. Through illustration of the gains in efficiency and reliability of parameters when outliers exist, the potential of robust joint modelling is evident. The research presented in this thesis highlights the benefits and stresses the need to utilise a more robust approach to joint modelling in the presence of longitudinal outliers.
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1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.
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We analyze a real data set pertaining to reindeer fecal pellet-group counts obtained from a survey conducted in a forest area in northern Sweden. In the data set, over 70% of counts are zeros, and there is high spatial correlation. We use conditionally autoregressive random effects for modeling of spatial correlation in a Poisson generalized linear mixed model (GLMM), quasi-Poisson hierarchical generalized linear model (HGLM), zero-inflated Poisson (ZIP), and hurdle models. The quasi-Poisson HGLM allows for both under- and overdispersion with excessive zeros, while the ZIP and hurdle models allow only for overdispersion. In analyzing the real data set, we see that the quasi-Poisson HGLMs can perform better than the other commonly used models, for example, ordinary Poisson HGLMs, spatial ZIP, and spatial hurdle models, and that the underdispersed Poisson HGLMs with spatial correlation fit the reindeer data best. We develop R codes for fitting these models using a unified algorithm for the HGLMs. Spatial count response with an extremely high proportion of zeros, and underdispersion can be successfully modeled using the quasi-Poisson HGLM with spatial random effects.
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This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.