Adequate Statistical Tools Research Articles

A prospective study to assess clinicopathological correlation of head and neck masses

Background: One of the most frequent clinical manifestations in the field of otorhinolaryngology is a mass in the head and neck area. A thorough history and good clinical examination including the findings of inspection and palpation are key factors for near accurate provisional diagnosis but histopathological is the gold standard for confirmation. FNAC is an easy, efficient, and affordable way to sample superficial neck masses. Methods: The present research has been performed on 100 patients presenting with clinically palpable head and neck masses in the ENT OPD of Rajindra Hospital, Patiala for duration of 2 years (2021-2023). Clinical diagnosis was correlated with cytology and histopathology findings. The data was compiled and evaluated using adequate statistical tools. Results: In this research, 100 cases of head and neck swellings were examined. Out of 100 swellings, 39 patients had lymph node swellings, 31 presented with thyroid swelling, 20 had salivary gland swelling and 10 were miscellaneous. In this study, most of the swellings found to be inflammatory in nature. Women were far more likely to be involved than men. Clinical and cytological diagnoses were made in all cases. Conclusions: When compared to a biopsy, the procedure of fine needle aspiration cytology for head and neck swellings is not only less invasive but also more cost-effective, and causes far less pain. It is possible to execute the procedure successfully on elderly people and children without the need for anesthesia.

CO-CLUSTERING OF SPATIALLY RESOLVED TRANSCRIPTOMIC DATA.

Spatial transcriptomics is a groundbreaking technology that allows the measurement of the activity of thousands of genes in a tissue sample and maps where the activity occurs. This technology has enabled the study of the spatial variation of the genes across the tissue. Comprehending gene functions and interactions in different areas of the tissue is of great scientific interest, as it might lead to a deeper understanding of several key biological mechanisms, such as cell-cell communication or tumor-microenvironment interaction. To do so, one can group cells of the same type and genes that exhibit similar expression patterns. However, adequate statistical tools that exploit the previously unavailable spatial information to more coherently group cells and genes are still lacking. In this work, we introduce SpaRTaCo, a new statistical model that clusters the spatial expression profiles of the genes according to a partition of the tissue. This is accomplished by performing a co-clustering, i.e., inferring the latent block structure of the data and inducing two types of clustering: of the genes, using their expression across the tissue, and of the image areas, using the gene expression in the spots where the RNA is collected. Our proposed methodology is validated with a series of simulation experiments and its usefulness in responding to specific biological questions is illustrated with an application to a human brain tissue sample processed with the 10X-Visium protocol.

Five-year follow-up of mitral valve repair versus replacement: a propensity score analysis

BackgroundMitral valve repair (MVRe) is considered to have a superior outcome compared to replacement (MVRp) in patients with mitral valve regurgitation (MVR). It was the aim of the study to analyse the clinical results and identify risk factors for short and long-term mortality.MethodsIn a retrospective single-center analysis, patients undergoing an isolated mitral valve procedure from June 2010 to December 2016 were identified. These were subsequently homogenized using 10 baseline characteristics for propensity-score matching. Comparative analyses were performed for early and long-term results, using adequate statistical tools, and identifying risk factors for the investigated endpoints, primary end-point: all-cause mortality within 5 years and secondary end-points: recurrent MVR, reoperation, endocarditis and/or mortality with 30 days, 1, 3 and 5 years.Results241 patients were identified in the entire patient cohort. After matching, patients were divided into 2 groups of 64 each respectively. The median age was similar in the two groups. There was a significant interaction between early mortality risk of MV in patients with coronary artery disease (CAD) (OR 11.94, 95% CI 1.49–285.92, p = 0.04) and late mortality in patients with higher EuroSCORE II (HR 1.14, 95% CI 1.06–1.23, p < 0.001). The primary end-point showed 5-year survival rate was significantly higher in MVRe versus MVRp (90.06% vs. 79.54% respectively, p = 0.04). The secondary end-point demonstrated recurrent MVR not to be statistically significant between the 2 groups (p = 0.09) as well as reoperation (p = 0.28). Endocarditis was observed in one patient after MVRp.ConclusionsWe concluded MVRe to be associated with lower operative and 5-year mortality and good postoperative outcomes compared to patients undergoing MVRp. Concomitant CAD was identified as one of the risk factors for increasing the in-hospital mortality rate. There was no significant difference in rehospitalisation over the follow-up period. MVRe should be the treatment of choice for severe MVR and should remain a central aspect in valve centers' treatment algorithms and quality measures.

Application of a Selected Pseudorandom Number Generator for the Reliability of Farm Tractors

Knowledge of the use-to-failure periods of process equipment, including agricultural vehicles, is essential for the determination of their durability and reliability. Obtaining any empirical data on this issue is difficult and sometimes impossible. Experimental studies are costly and time-consuming. Manufacturers are usually reluctant to share such data, claiming that the information is classified for the sake of their companies. The purpose of this study was to compare empirical data with data generated using adequate statistical tools. The newly generated and very similar in value pseudorandom numbers were obtained by simulations using the Monte Carlo, Latin hypercube sampling and Iman-Conover methods. Reliability function graphs obtained from the generated time-series (use-to-failure periods) with matching Weibull distribution had very similar shape and scale parameters. They were are also comparable to parameters from experimental data extracted from a Polish Zetor agricultural tractor service station. The validation of the applied methods was limited as it was carried out only on the basis of the available data. Analysis of line graphs of cumulative deviations of the values of use-to-failure periods (times-to-fail) generated against empirical times-to-fail indicated that the best method in the studied case was the Monte Carlo method.

Poor Response Inhibition and Symptoms of Inattentiveness Are Core Characteristics of Lifetime Illicit Substance Use among Young Adults in the General Norwegian Population: The HUNT Study

Background Impairments in neurocognitive functioning are associated with substance use behavior. Previous studies in neurocognitive predictors of substance use typically use self-report measures rather than neuropsychological performance measures and suffer from low sample sizes and use of clinical diagnostic cut offs. Methods Crossectional data from the HUNT4 Study (Helseundersøkelsen i Trøndelag) was used to study executive neuropsychological performance and self-reported measures of neurocognitive function associated with a history of illicit substance use in a general population sample of young adults in Norway. We performed both between group comparisons and logistic regression modeling and controlled for mental health symptomatology. Results Subjects in our cohort with a self-reported use of illicit substances had significantly higher self-reported mental health and neurocognitive symptom load. A logistic regression model with substance use as response included sex, commission errors and self-reported inattentiveness and anxiety as significant predictors. After 10-fold cross-validation this model achieved a moderate area under the receiver-operator curve of 0.64. To handle the class imbalance typically found in such population data, we also calculated balanced accuracy with a optimal model cut off of 0.234 with a sensitivity of 0.50 and specificity of 0.76 as well as precision recall—area under the curve of 0.28. Conclusions Subtle cognitive dysfunction differentiates subjects with and without a history of illicit substance use. Neurocognitive factors outperformed the effects of depressive symptoms on substance use behavior in this cohort. We highlight the need for using adequate statistical tools for evaluating the performance of models in unbalanced datasets.

Development of the Multi-Criteria Model for the Quality of Life Assessment in Local Governments

Abstract The perception of satisfaction with the quality of life by an individual in urban and rural areas includes a number of objective and subjective indicators, based on the analysis that could be performed. Measuring the preferences of individuals living in different environments, in terms of life goals, needs, moods, expectations, as well as personal satisfaction with the quality of life, requires more criteria to be included for its evaluation. The research was conducted on the basis of twenty indicators for measuring the quality of life in local governments depending on the preferences of individuals, and of different age, gender, education, social status, and satisfaction motives. The subject of this paper is the selection of criteria in a multi-criteria model for assessing the quality of life in local governments, using adequate statistical tools. In addition to descriptive statistics and testing the significance of differences, the authors of the paper used a modified PROMETHEE multi-criteria method for ranking local governments.

When Bigger Is Better: 3D RNA Profiling of the Developing Head in the Catshark Scyliorhinus canicula.

We report the adaptation of RNA tomography, a technique allowing spatially resolved, genome-wide expression profiling, to a species occupying a key phylogenetic position in gnathostomes, the catshark Scyliorhinus canicula. We focused analysis on head explants at an embryonic stage, shortly following neural tube closure and of interest for a number of developmental processes, including early brain patterning, placode specification or the establishment of epithalamic asymmetry. As described in the zebrafish, we have sequenced RNAs extracted from serial sections along transverse, horizontal and sagittal planes, mapped the data onto a gene reference taking advantage of the high continuity genome recently released in the catshark, and projected read counts onto a digital model of the head obtained by confocal microscopy. This results in the generation of a genome-wide 3D atlas, containing expression data for most protein-coding genes in a digital model of the embryonic head. The digital profiles obtained for candidate forebrain regional markers along antero-posterior, dorso-ventral and left-right axes reproduce those obtained by in situ hybridization (ISH), with expected relative organizations. We also use spatial autocorrelation and correlation as measures to analyze these data and show that they provide adequate statistical tools to extract novel expression information from the model. These data and tools allow exhaustive searches of genes exhibiting any predefined expression characteristic, such a restriction to a territory of interest, thus providing a reference for comparative analyses across gnathostomes. This methodology appears best suited to species endowed with large embryo or organ sizes and opens novel perspectives to a wide range of evo-devo model organisms, traditionally counter-selected on size criterion.

Management Strategies of Service Providers and Post-Travel Opinion of Bus Passengers’ (with Reference to Government and Private Omni Bus Operating Enterprises and its Services from Chennai)

The present research study primarily focuses on the post-travel Opinion of the bus passengers' who availed the service provider of SETC, TNSTC, and Private Omnibuses. An effort was made to detect, ascertain and to know commuters by bus opinions after their travel which is the primary reason for their level of satisfaction. A short analysis report is made on services, service delivery systems, how far the passengers satisfied with the facilities and frequency of service towards the service provider. In addition, the present study connects with behavior, brand loyalty towards the service provider. The reviews were properly taken into consideration for finding the gap between earlier and present study. The adequate statistical tools such as t-test, chi-square test, ANOVA, multi-regression analysis were used to test hypotheses related to the current topic. The variables connect with post-travel experience, the grouping of variables, factor analysis, adequate statistical tools was used. Objective-based findings, suggestions, and conclusions are given at an appropriate level to carry out further research.

Statistical tools used for analyses of frequent users of emergency department: a scoping review

ObjectiveFrequent users represent a small proportion of emergency department users, but they account for a disproportionately large number of visits. Their use of emergency departments is often considered suboptimal. It...

Gamma-Ray Astrophysics in the Time Domain

The last few years have seen gamma-ray astronomy maturing and advancing in the field of time-domain astronomy, utilizing source variability on timescales over many orders of magnitudes, from a decade down to a few minutes and shorter, depending on the source. This review focuses on some of the key science issues and conceptual developments concerning the timing characteristics of active galactic nuclei (AGN) at gamma-ray energies. It highlights the relevance of adequate statistical tools and illustrates that the developments in the gamma-ray domain bear the potential to fundamentally deepen our understanding of the nature of the emitting source and the link between accretion dynamics, black hole physics, and jet ejection.

Six-minute walk test as a determinant of the functional capacity of children and adolescents with cystic fibrosis: A systematic review.

Cystic Fibrosis (CF) is a multisystem disorder. The involvement of the respiratory system is frequent and culminates in dyspnea and exercise intolerance. Functional capacity is an important diagnostic tool, because it reflects the cardiorespiratory status, quality of life and prognosis. This systematic review aims to assess the reproducibility and validity of the six minute walk test (6MWT) to reflect the functional capacity of children and adolescents with cystic fibrosis, and also the correlation between 6MWT and lung function. Searches for articles were performed in eight databases using MeSH/DeCS keywords. A total of 695 articles were found and, after verifying all eligibility criteria, six articles were included for analysis and scoring regarding the methodological quality according to the QUADAS scale (Quality Assessment of Diagnostic Accuracy Studies). All articles had good methodology (QUADAS between 9 and 11 points). The 6MWT is not correlated with lung function. There is a strong indication that the 6MWT is a reproducible test to assess the functional capacity of children and adolescents with CF. The validity assessment could not be reached because the studies included in this systematic review did not use adequate statistical tools to carry out such an evaluation.

Fused Estimation of Sparse Connectivity Patterns From Rest fMRI-Application to Comparison of Children and Adult Brains.

In this paper, we consider the problem of estimating multiple sparse, co-activated brain regions from functional magnetic resonance imaging (fMRI) observations belonging to different classes. More precisely, we propose a method to analyze similarities and differences in functional connectivity between children and young adults. Often, analysis is conducted on each class separately, and differences across classes are identified with an additional postprocessing step using adequate statistical tools. Here, we propose to rely on a generalized fused Lasso penalty, which allows us to make use of the entire data set in order to estimate connectivity patterns that are either shared across classes, or specific to a given group. By using the entire population during the estimation, we hope to increase the power of our analysis. The proposed model falls in the category of population-wise matrix decomposition, and a simple and efficient alternating direction method of multipliers algorithm is introduced to solve the associated optimization problem. After validating our approach on simulated data, experiments are performed on resting-state fMRI imaging from the Philadelphia neurodevelopmental cohort data set, comprised of normally developing children from ages 8 to 21. Developmental differences were observed in various brain regions, as a total of three class-specific resting-state components were identified. Statistical analysis of the estimated subject-specific features, as well as classification results (based on age groups, up to 81% accuracy, samples) related to these components demonstrate that the proposed method is able to properly extract meaningful shared and class-specific sub-networks.

Determination of Expert Group Preferences in the Multi-Criteria Model for the Analysis of Local Economic Environment

Abstract Local economic environment is characterised by a range of economic, social, political and demographic parameters, based on which we can perform its analysis. Heterogeneity of relevant characteristics of the local economic environment imposes multiple criteria analysis as one of the suitable tools for the evaluation. Assessment of local economic environment often falls within the scope of group decision-making, as it is usually performed on the basis of an analysis of preferences of economic subjects or relevant experts on the issue of the economic environment at the local level. Regardless of whether it is based on economic subjects or expert group, in order to form a multi-criteria model, it is necessary to generate preferences of individuals into a single weight coefficient, which shows groups’ preference on the importance of each criterion. The subject of this paper is determination of weight coefficients in the multi-criteria model for the analysis of local economic development based on the preferences from a group of experts, by applying adequate statistical tools, and then by ranking local governments according to the quality of business environment perceived by the expert group.In addition to descriptive statistics and testing the significance of differences, in the paper is applied multi-criteria method Simple Additive Weights - SAW.

Quantitative speculations about lost incunabula and cinquecentine, wether editions or copies

The editions of incunabula currently held by Italian libraries appear to be roughly 11,000 for a total of 100,000 copies so far identified. Without adequate statistical calculation tools, but according to the data from the Indice Generale degli Incunaboli (IGI), The Author speculates the number of lost editions and books through the centuries.

Foreword.

The usefulness of collaborative work between cerebral palsy (CP) registers is little recognized and is important to highlight. With the exciting presentation of data from the Australian CP registers, we can see the breadth of research possible through these efforts. Collaboration between CP registers affords an improvement in power provided by pooling data from different CP registers, which is of particular benefit in certain situations, for example analyzing trends in prevalence rates of CP among very tiny babies, quantifying the higher risk of CP among those born from multiple pregnancies, or studying the association between specific congenital anomalies and CP. It is important, of course, to have some caution when pooling data from different CP registers. It is necessary to have common descriptions of CP1, 2 and to ensure that the data points are sufficiently harmonized to allow accurate pooling. Decisions about the level of harmonization are a great challenge indeed, and can be addressed using repeated reliability studies between registers.3 Further, trends observed from different CP registers also generate new questions that require new investigations. And it is important as well to have some caution when analyzing these data, for example to use adequate statistical tools for multi-centric data to ensure accurate analysis. For example, what does it mean if trends in CP rates are decreasing in some geographical regions and not in others (all areas being population-based registers)? Are these true differences? Either in a single region, country, or continent, either from a single CP register or from a network of CP registers, we need to remember how powerful these data from CP registers can be when correctly analyzed. These data can be used for monitoring and surveillance of course, but are also an excellent resource for clinical epidemiological research in the CP field. Health professionals, policymakers, and persons with CP themselves should be aware of this and the potential benefits available through the excellent data resource that CP registers can provide. Professor Christine Cans Special Issue Associate Editor In the past few years there has been an increase both in the number and in the type of registries in medicine. Registries can be used to identify the medical needs and outcomes for people with specific diseases or conditions, can monitor newly registered medications for side effects, and evaluate the success of new treatments. In addition, the collection of such information, particularly if comprehensive, provides an invaluable resource for various types of research from health systems, health behaviour, and epidemiology, as well as providing baseline data for the design of clinical trials to improve treatment outcomes. This issue of papers uses data from the Australian Cerebral Palsy Register and demonstrates the wide range of research that is possible using population datasets. Some findings are clinically related, and concern correlations between prenatal conditions and birth outcomes, trends in congenital abnormalities over time, the variety of impairments across cohorts, and the social implications of specific impairments, and the possibilities for prevention. In addition, this issue contains three articles examining social–demographic findings from the registry, and policy-specific implications, including an article on the Australian National Disability Insurance Scheme. The supplement reports findings both from the long-standing cerebral palsy registries from Western Australia, Victoria, and South Australia and from data from the relatively new cerebral palsy registries from the remaining states and territories. Since the Australian Cerebral Palsy Register's inception in 2008, the Australian Cerebral Palsy Register Group have worked together to support the work of individual CP registers and to develop a minimum dataset to allow collaboration between them. This work has increased both the volume and the value of the data held, widening the possibility for conducting research to improve the quality of life of those with CP. This is clearly borne out in the following collection of papers and holds out the promise that this systematic collection of data will increase both our understanding of what it is like to live with CP and what can be done to improve the lives of those who do. Dr Nicole Gerrand Consumer Manager, Research Support and Development, Hunter New England Local Health District, Newcastle, Australia

Development of a Rapid and Sensitive Routine Method of Analyses for Organochlorine Compounds in Fish: A Metrological Approach

The determination of organochlorine compounds in biological samples is very important, since these compounds are lipophilic and persistent in the environment and tend to accumulate in living organisms. However, considering the importance to apply adequate statistical tools to develop and evaluate analytical methods, this paper has as objective the optimization, validation and uncertainty evaluation of a rapid and sensitive routine method for analyses of organochlorine compounds in fish. For optimization of the method, statistical tools such as design of experiments were used, while guidance from SANCO 12571 and Eurachem/Citac Guide were used for the validation of the method and uncertainty estimation of the results respectively. Finally, the method was evaluated using a certified reference material (CRM) in an accredited laboratory that is in accordance with ISO/IEC 17025:2005, completing a suitable metrological approach ensuring that the method is fit for purpose.

Multimarker Testing With ST2 in Chronic Heart Failure

Despite important progress in recent decades, mortality remains high for patients with chronic heart failure. Risk stratification may be refined by the use of biomarkers for different pathophysiological processes that established mortality risk factors do not directly reflect. Biomarkers that are currently available can provide information about at least 7 pathobiological processes operative in HF, help to identify the specific processes involved in individual patients, and aid in constructing management plans. However, the additional prognostic information gained by any biomarker over a clinical risk model plus other biomarkers needs to be determined with adequate statistical tools. A major problem in selecting a biomarker profile is the proportional increase in economic burden; thus, the addition of any biomarker to a profile should be justified by adequate discrimination, calibration, reclassification, and likelihood analyses. Three studies that implemented such rigorous analyses have assessed a multimarker panel in chronic heart failure that incorporated the biomarker ST2: the Penn HF Study, the Barcelona Study, and the ProBNP Outpatient Tailored Chronic Heart Failure (PROTECT) biomarker substudy. In all 3 studies, a multimarker panel appeared to provide significant information over conventional risk stratification. The latter 2 reports proposed that ST2 might be superior to natriuretic peptides. The Barcelona Bio-HF calculator (www.bcnbiohfcalculator.cat) is a novel risk calculator that considers clinical variables, treatment, and biomarkers (i.e., N terminal pro-brain natriuretic peptide [NT-proBNP], ST2, and high sensitivity troponin T [hsTnT]). The optimal panel of markers, the change in these markers over time, and how these changes might help guide therapeutic interventions remain to be defined.

Multiple biomarker strategies for risk stratification in heart failure

Biomarkers of cardiovascular diseases are indispensable tools for diagnosis and prognosis, and the use of biomarkers is now considered standard-of-care. New markers continue to be developed, but few prove to be substantially better than established markers. Heart failure (HF) risk stratification may be refined by the use of biomarkers for different pathobiological processes that established mortality risk factors do not directly reflect. Biomarkers that are currently available can provide information about at least seven pathobiological processes operative in HF, help to identify the specific processes involved in individual patients, and aid in constructing management plans. However, the additional prognostic information gained by any biomarker over a clinical risk model plus other biomarkers needs to be determined with adequate statistical tools. A major problem in selecting a biomarker profile is the proportional increase in economic burden; thus, the addition of any biomarker to a profile should be justified by adequate discrimination, calibration, reclassification, and likelihood analyses. This review assesses the value of multimarker strategies in both acutely decompensated (ADHF) and chronic HF. Most data on biomarkers have been derived from patient cohorts with chronic HF. However, risk prediction in patients admitted with ADHF remains a challenge. ADHF is not a single disease, it presents in various manners and different etiologies may underlie ADHF, which are reflected by different biomarkers. The optimal panel of markers, the change in these markers over time, and how these changes might help guide therapeutic interventions remain to be defined.

Effects of Airborne Birch Pollen Levels on Clinical Symptoms of Seasonal Allergic Rhinoconjunctivitis

Background: Most panel studies focusing on rhinitis and conjunctivitis symptoms and birch pollen have been performed on a linear basis and have not included air pollution and meteorological variables as potential confounders. The objective of this panel study was to assess the relationship between symptoms of seasonal allergic rhinoconjunctivitis and daily airborne birch pollen concentrations, checking with adequate statistical tools the shapes of concentration-response curves and controlling for confounders. Methods: The severity of rhinitis, conjunctivitis, and bronchial symptoms was recorded daily in March and April 2010 (3,311 person-days) in 61 seasonal allergic rhinoconjunctivitis patients sensitized to birch. Data were analyzed with generalized additive and generalized estimating equation models to quantify the effects of birch pollens. Results: The relationship between birch pollen and the percentage of patients with nasal, ocular and bronchial symptoms was linear until birch daily average concentrations of, respectively, 110, 70, and 70 grains/m³; it reached a plateau thereafter. For an increase of 10 grains/m³, the OR (95% CI) for nasal, ocular, and bronchial symptoms were, respectively, 1.07 (1.03-1.12), 1.17 (1.08-1.27), and 1.12 (1.03-1.21). At the beginning of the season, no nasal or ocular symptoms were observed below a threshold of 30 grains/m³. Conclusions: Adequate modeling regression shows that the clinical response to natural exposure to birch pollen in sensitized patients varies during Betula pollen season, with a threshold at the beginning of the season, while over the whole season the relationship is linear for nasal, ocular, and bronchial symptoms up to a saturation point, followed by a plateau.

Variance Calculations for Quantitative Real-Time PCR Experiments with Multiple Levels of Replication

Heap bioleaching is an established technology for recovering copper from low-grade sulphide ores. Recently, genetics-based approaches have been employed to characterize mineral-processing bacteria. In these approaches, data analysis is a key issue. Consequently, it is of fundamental importance to provide adequate mathematical models and statistical tools to draw reliable conclusions. The present work relates to current studies of the consortium of organisms inhabiting the bioleaching heap of the Escondida mine in Northern Chile. These studies aim to describe and understand the relationship between the dynamics of the community and the performance of the industrial process. Here, we consider a series of quantitative real-time polymerase chain reaction (PCR) experiments performed to quantify six different microorganisms at various stages of the bioleaching cycle. Establishing the reliability of the data obtained by real-time PCR requires the estimation of the error variance at several different levels. The results obtained show that the sampling component of the error variance is the dominant source of variability for most microorganisms. An estimate for the proportional reduction in residual standard deviation from the use of extraction and real-time PCR triplicates was found to range from 3% to 27% for the different organisms. This result suggests that triplicate assays would produce only a modest reduction in error variance compared to more frequent sampling from the heap.