Cluster randomized clinical trials in orthodontics: design, analysis and reporting issues

Cluster randomized trials (CRTs) use as the unit of randomization clusters, which are usually defined as a collection of individuals sharing some common characteristics. Common examples of clusters include entire dental practices, hospitals, schools, school classes, villages, and towns. Additionally, several measurements (repeated measurements) taken on the same individual at different time points are also considered to be clusters. In dentistry, CRTs are applicable as patients may be treated as clusters containing several individual teeth. CRTs require certain methodological procedures during sample calculation, randomization, data analysis, and reporting, which are often ignored in dental research publications. In general, due to similarity of the observations within clusters, each individual within a cluster provides less information compared with an individual in a non-clustered trial. Therefore, clustered designs require larger sample sizes compared with non-clustered randomized designs, and special statistical analyses that account for the fact that observations within clusters are correlated. It is the purpose of this article to highlight with relevant examples the important methodological characteristics of cluster randomized designs as they may be applied in orthodontics and to explain the problems that may arise if clustered observations are erroneously treated and analysed as independent (non-clustered).

Morphological ripening of fluid inclusions and coupled zone-refining in quartz crystals revealed by cathodoluminescence imaging: Implications for CL-petrography, fluid inclusion analysis and trace-element geothermometry

Cathodoluminescence (CL) studies have previously shown that some secondary fluid inclusions in luminescent quartz are surrounded by dark, non-luminescent patches, resulting from fracture-sealing by late, trace-element-poor quartz. This finding has led to the tacit generalization that all dark CL patches indicate influx of low temperature, late-stage fluids. In this study we have examined natural and synthetic hydrothermal quartz crystals using CL imaging supplemented by in-situ elemental analysis. The results lead us to propose that all natural, liquid-water-bearing inclusions in quartz, whether trapped on former crystal growth surfaces (i.e., of primary origin) or in healed fractures (i.e., of pseudosecondary or secondary origin), are surrounded by three-dimensional, non-luminescent patches. Cross-cutting relations show that the patches form after entrapment of the fluid inclusions and therefore they are not diagnostic of the timing of fluid entrapment. Instead, the dark patches reveal the mechanism by which fluid inclusions spontaneously approach morphological equilibrium and purify their host quartz over geological time. Fluid inclusions that contain solvent water perpetually dissolve and reprecipitate their walls, gradually adopting low-energy euhedral and equant shapes. Defects in the host quartz constitute solubility gradients that drive physical migration of the inclusions over distances of tens of μm (commonly) up to several mm (rarely). Inclusions thus sequester from their walls any trace elements (e.g., Li, Al, Na, Ti) present in excess of equilibrium concentrations, thereby chemically purifying their host crystals in a process analogous to industrial zone refining. Non-luminescent patches of quartz are left in their wake. Fluid inclusions that contain no liquid water as solvent (e.g., inclusions of low-density H2O vapor or other non-aqueous volatiles) do not undergo this process and therefore do not migrate, do not modify their shapes with time, and are not associated with dark-CL zone-refined patches. This new understanding has implications for the interpretation of solids within fluid inclusions (e.g., Ti- and Al-minerals) and for the elemental analysis of hydrothermal and metamorphic quartz and its fluid inclusions by microbeam methods such as LA-ICPMS and SIMS. As Ti is a common trace element in quartz, its sequestration by fluid inclusions and its depletion in zone-refined patches impacts on applications of the Ti-in-quartz geothermometer.

Analysis of Phenotypic Variation in Childhood Wheezing Disorders

Recurrent wheezing or asthma is a common problem in children that has increased considerably in prevalence in the past few decades. The causes and underlying mechanisms are poorly understood and it is thought that a numb er of distinct diseases causing similar symptoms are involved. Due to the lack of a biologically founded classification system, children are classified according to their observed disease related features (symptoms, signs, measurements) into phenotypes. The objectives of this PhD project were a) to develop tools for analysing phenotypic variation of a disease, and b) to examine phenotypic variability of wheezing among children by applying these tools to existing epidemiological data. A combination of graphical methods (multivariate co rrespondence analysis) and statistical models (latent variables models) was used. In a first phase, a model for discrete variability (latent class model) was applied to data on symptoms and measurements from an epidemiological study to identify distinct phenotypes of wheezing. In a second phase, the modelling framework was expanded to include continuous variability (e.g. along a severity gradient) and combinations of discrete and continuo us variability (factor models and factor mixture models). The third phase focused on validating the methods using simulation studies. The main body of this thesis consists of 5 articles (3 published, 1 submitted and 1 to be submitted) including applications, methodological contributions and a review. The main findings and contributions were: 1) The application of a latent class model to epidemiological data (symptoms and physiological measurements) yielded plausible pheno types of wheezing with distinguishing characteristics that have previously been used as phenotype defining characteristics. 2) A method was proposed for including responses to conditional questions (e.g. questions on severity or triggers of wheezing are asked only to children with wheeze) in multivariate modelling.ii 3) A panel of clinicians was set up to agree on a plausible model for wheezing diseases. The model can be used to generate datasets for testing the modelling approach. 4) A critical review of methods for defining and validating phenotypes of wheeze in children was conducted. 5) The simulation studies showed that a parsimonious parameterisation of the models is required to identify the true underlying structure of the data. The developed approach can deal with some challenges of real-life cohort data such as variables of mixed mode (continuous and categorical), missing data and conditional questions. If carefully applied, the approach can be used to identify whether the underlying phenotypic variation is discrete (classes), continuous (factors) or a combination of these. These methods could help improve precision of research into causes and mechanisms and contribute to the development of a new classification of wheezing disorders in children and other diseases which are difficult to classify.

Combining qualitative and quantitative methods to analyze serious games outcomes: A pilot study for a new cognitive screening tool

Computer games for a serious purpose - so called serious games can provide additional information for the screening and diagnosis of cognitive impairment. Moreover, they have the advantage of being an ecological tool by involving daily living tasks. However, there is a need for better comprehensive designs regarding the acceptance of this technology, as the target population is older adults that are not used to interact with novel technologies. Moreover given the complexity of the diagnosis and the need for precise assessment, an evaluation of the best approach to analyze the performance data is required. The present study examines the usability of a new screening tool and proposes several new outlines for data analysis.

Fast Prediction of Femoral Biomechanics Using Supervised Machine Learning and Statistical Shape Modeling

Finite element (FE) analysis is an important computational tool in biomechanics. However, its adoption into clinical practice has been hampered by its computational complexity and required high technical competences for clinicians. In this paper we propose a supervised learning approach to predict the outcome of the FE analysis. We demonstrate our approach on clinical CT and X-ray femur images for FE predictions ( FEP), with features extracted, respectively, from a statistical shape model and from 2D-based morphometric and density information. Using leave-one-out experiments and sensitivity analysis, comprising a database of 89 clinical cases, our method is capable of predicting the distribution of stress values for a walking loading condition with an average correlation coefficient of 0.984 and 0.976, for CT and X-ray images, respectively. These findings suggest that supervised learning approaches have the potential to leverage the clinical integration of mechanical simulations for the treatment of musculoskeletal conditions.

Revealing Assembly of a Pore-Forming Complex Using Single-Cell Kinetic Analysis and Modeling

Many biological processes depend on the sequential assembly of protein complexes. However, studying the kinetics of such processes by direct methods is often not feasible. As an important class of such protein complexes, pore-forming toxins start their journey as soluble monomeric proteins, and oligomerize into transmembrane complexes to eventually form pores in the target cell membrane. Here, we monitored pore formation kinetics for the well-characterized bacterial pore-forming toxin aerolysin in single cells in real time to determine the lag times leading to the formation of the first functional pores per cell. Probabilistic modeling of these lag times revealed that one slow and seven equally fast rate-limiting reactions best explain the overall pore formation kinetics. The model predicted that monomer activation is the rate-limiting step for the entire pore formation process. We hypothesized that this could be through release of a propeptide and indeed found that peptide removal abolished these steps. This study illustrates how stochasticity in the kinetics of a complex process can be exploited to identify rate-limiting mechanisms underlying multistep biomolecular assembly pathways.

Input Aggregation in Models of Data Envelopment Analysis: A Statistical Test with an Application to Indian Manufacturing

A problem frequently encountered in Data Envelopment Analysis (DEA) is that the total number of inputs and outputs included tend to be too many relative to the sample size. One way to counter this problem is to combine several inputs (or outputs) into (meaningful) aggregate variables reducing thereby the dimension of the input (or output) vector. A direct effect of input aggregation is to reduce the number of constraints. This, in its turn, alters the optimal value of the objective function. In this paper, we show how a statistical test proposed by Banker (1993) may be applied to test the validity of a specific way of aggregating several inputs. An empirical application using data from Indian manufacturing for the year 2002-03 is included as an example of the proposed test.

Evaluation of the association between cryptosporidiosis outbreaks and two interactive water fountain parks: Epidemiologic analysis and implications for public health

Background. A community-wide outbreak of cryptosporidiosis occurred in Dallas County during the summer of 2008. A subset of cases occurring with onset of illness within a 2 week interval was epidemiologically linked to 2 neighborhood interactive water fountain parks. ^ Methods. A case control study was conducted to evaluate risk factors associated with developing illness with cryptosporidiosis from the fountain parks. Cases were selected from a line list from the epidemiological study. The selection for the controls was either healthy family members or a daycare center nearby. Cases and controls were not matched. ^ Results. Interviews were completed for 44 fountain park attendees who met case definition and 54 community controls. Twenty-seven percent (27.3%) of the cases and 13.0% of the controls were between the ages of 0–4 years. Thirty-nine percent (38.6%) of the cases and 24.1% of the controls were between the ages of 5–13 years. Fourteen percent (13.6%) of the cases and 33.3% of the controls were between the ages of 14–31 years. Twenty percent (20.5%) of the cases and 29.6% of the controls were between the ages of 32–63 years. 47.7% of the cases and 42.6% of the controls were males. Fountain park attendees who reported having been splashed in the face with water were 10 times more likely to become ill than controls (OR = 10.0, 95% CI = 2.8–35.1). Persons who reported having swallowed water from the interactive fountains were 34 times more likely to become ill than controls (OR = 34.3, 95%CI = 9.3–125.7). ^ Conclusion. Prompt reporting of cases, identification of outbreak sources, and immediate implementation of remediation measures were critical in curtailing further transmission from these particular sites through the remainder of the season. This investigation underscores the potential for cryptosporidiosis outbreaks to occur in interactive fountain parks, and the need for enhanced preventive measures in these settings. Education of the public regarding avoidance of behaviors such as drinking water from interactive fountains is also an important component of public health prevention efforts. ^

Performance recovery from exercise: A review from a statistical point of view

Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^

Statistical Methods for Differential Expressions of Genes Detected in Multiple-Condition Experiment of Microarray

Most studies of differential gene-expressions have been conducted between two given conditions. The two-condition experimental (TCE) approach is simple in that all genes detected display a common differential expression pattern responsive to a common two-condition difference. Therefore, the genes that are differentially expressed under the other conditions other than the given two conditions are undetectable with the TCE approach. In order to address the problem, we propose a new approach called multiple-condition experiment (MCE) without replication and develop corresponding statistical methods including inference of pairs of conditions for genes, new t-statistics, and a generalized multiple-testing method for any multiple-testing procedure via a control parameter C. We applied these statistical methods to analyze our real MCE data from breast cancer cell lines and found that 85 percent of gene-expression variations were caused by genotypic effects and genotype-ANAX1 overexpression interactions, which agrees well with our expected results. We also applied our methods to the adenoma dataset of Notterman et al. and identified 93 differentially expressed genes that could not be found in TCE. The MCE approach is a conceptual breakthrough in many aspects: (a) many conditions of interests can be conducted simultaneously; (b) study of association between differential expressions of genes and conditions becomes easy; (c) it can provide more precise information for molecular classification and diagnosis of tumors; (d) it can save lot of experimental resources and time for investigators.^

SOCIO-ENVIRONMENTAL FACTORS ASSOCIATED WITH THE DISTRIBUTION OF DRACUNCULUS MEDINENSIS (GUINEA WORM DISEASE) AND SUGGESTED METHODS FOR CONTROL, IBARAPA, NIGERIA, 1982 (AFRICA)

A population-based cross-sectional survey of socio-environmental factors associated with the prevalence of Dracunculus medinensis (guinea worm disease) was conducted in Idere, a rural agricultural community in Ibarapa, Oyo state, Nigeria, during 1982.^ The epidemiologic data were collected by household interview of all 501 households. The environmental data were collected by analysis of water samples collected from all domestic water sources and rainfall records.^ The specific objectives of this research were to: (a) Describe the prevalence of guinea worm disease in Idere during 1982 by age, sex, area of residence, drinking water source, religion and weekly amount of money spent by the household to collect potable drinking water. (b) Compare the characteristics of cases with non-cases of guinea worm in order to identify factors associated with high risk of infection. (c) Investigate domestic water sources for the distribution of Cyclops. (d) Determine the extent of potable water shortage with a view to identifying factors responsible for such shortage in the community. (e) Describe the effects of guinea worm on school attendance during 1980/1982 school years by class and location of school from piped water supply.^ The findings of this research indicate that during 1982, 31.8 percent of Idere's 6,527 residents experienced guinea worm infection, with higher prevalence of infection recorded in males in their most productive years and females in their teenage years. The role of sex and age to risk of higher infection rate was explained in the context of water related exposure and water intake due to dehydration from physical occupational actitives of subgroups.^ Potable water available to residents was considerably below the minimum recommended by WHO for tropical climates, with sixty-eight percent of water needs of the residents coming from unprotected surface water which harbour Cyclops, the obligatory intermediate host of Dracunculus medinensis. An association was found between periods of relative high density of Cyclops in domestic water and rainfall.^ Impact of guinea worm infection on educational activities was considerable and its implications were discussed, including the implications of the research findings in relation to control of guinea worm disease in Ibarapa. ^

Grain-size analysis and geochemistry of sediment core GeoB13602-1

Grain-size, terrigenous element and rock magnetic remanence data of Quaternary marine sediments retrieved at the NW African continental margin off Gambia (gravity core GeoB 13602-1, 13°32.71' N, 17°50.96'W) were jointly analyzed by end-member (EM) unmixing methods to distinguish and budget past terrigenous fluxes. We compare and cross-validate the identified single-parameter EM systems and develop a numerical strategy to calculate associated multi-parameter EM properties. One aeolian and two fluvial EMs were found. The aeolian EM is much coarser than the fluvial EMs and is associated with a lower goethite/hematite ratio, a higher relative concentration of magnetite and lower Al/Si and Fe/K ratios. Accumulation rates and grain sizes of the fluvial sediment appear to be primarily constrained by shore distance (i.e., sea-level fluctuations) and to a lesser extent by changes in hinterland precipitation. High dust fluxes occurred during the Last Glacial Maximum (LGM) and during Heinrich Stadials (HS) while the fluvial input remained unchanged. Our approach reveals that the LGM dust fluxes were ~7 times higher than today's. However, by far the highest dust accumulation occurred during HS 1 (~300 g m**-2 yr** -1), when dust fluxes were ~80 fold higher than today. Such numbers have not yet been reported for NW Africa, and emphasize strikingly different environmental conditions during HSs. They suggest that deflation rate and areal extent of HSs dust sources were much larger due to retreating vegetation covers. Beyond its regional and temporal scope, this study develops new, in principle, generally applicable strategies for multi-method end-member interpretation, validation and flux budgeting calibration.

Results of bulk sediment X-ray diffraction analysis and quantification of mineral phases based on the RockJock and on the QUAX quantitative analysis

We have performed quantitative X-ray diffraction (qXRD) analysis of 157 grab or core-top samples from the western Nordic Seas between (WNS) ~57°-75°N and 5° to 45° W. The RockJock Vs6 analysis includes non-clay (20) and clay (10) mineral species in the <2 mm size fraction that sum to 100 weight %. The data matrix was reduced to 9 and 6 variables respectively by excluding minerals with low weight% and by grouping into larger groups, such as the alkali and plagioclase feldspars. Because of its potential dual origins calcite was placed outside of the sum. We initially hypothesized that a combination of regional bedrock outcrops and transport associated with drift-ice, meltwater plumes, and bottom currents would result in 6 clusters defined by "similar" mineral compositions. The hypothesis was tested by use of a fuzzy k-mean clustering algorithm and key minerals were identified by step-wise Discriminant Function Analysis. Key minerals in defining the clusters include quartz, pyroxene, muscovite, and amphibole. With 5 clusters, 87.5% of the observations are correctly classified. The geographic distributions of the five k-mean clusters compares reasonably well with the original hypothesis. The close spatial relationship between bedrock geology and discrete cluster membership stresses the importance of this variable at both the WNS-scale and at a more local scale in NE Greenland.