Linear versus nonlinear methods of sire evaluation for categorical traits: a simulation study

Linear (BLUP) and nonlinear (GFCAT) methods of sire evaluation for categorical data were compared using Monte Carlo techniques. Binary and ordered tetrachotomous responses were generated from an underlying normal distribution via fixed thresholds, so as to model incidences in the population as a whole. Sires were sampled from a normal distribution and family structure consisted of half-sib groups of equal or unequal size; simulations were done at several levels of heritability (h2). When a one-way model was tenable or when responses were tetrachotomous, the differences between the 2 methods were negligible. However, when responses were binary, the layout was highly unbalanced and a mixed model was appropriate to describe the underlying variate, GFCAT elicited significantly larger responses to truncation selection than BLUP at h2.20 or.50 and when the incidence in the = population was below 25 p. 100. The largest observed difference in selection efficiency between the 2 methods was 12 p. 100

Data-aware conformance checking with SMT

Conformance checking is a key process mining task to confront the normative behavior imposed by a process model with the actual behavior recorded in a log. While this problem has been extensively studied for pure control-flow processes, data-aware conformance checking has received comparatively little attention. In this paper, we tackle the conformance checking problem for the challenging scenario of processes that combine data and control-flow dimensions. Concretely, we adopt the formalism of data Petri nets (DPNs) and show how solid, well-established automated reasoning techniques from the area of Satisfiability Modulo Theories (SMT) can be effectively harnessed to compute conformance metrics and optimal data-aware alignments. To this end, we introduce the CoCoMoT (Computing Conformance Modulo Theories) framework, with a fourfold contribution. First, we show how SMT allows to leverage SAT-based encodings for the pure control-flow setting to the data-aware case. Second, we introduce a novel preprocessing technique based on a notion of property-preserving clustering, to speed up the computation of conformance checking outputs. Third, we show how our approach extends seamlessly to the more comprehensive conformance checking artifacts of multi- and anti-alignments. Fourth, we describe a proof-of-concept implementation based on state-of-the-art SMT solvers, and report on experiments. Finally, we discuss how CoCoMoT directly lends itself to further process mining tasks like log analysis by clustering and model repair, and the use of SMT facilitates the support of even richer multi-perspective models, where, for example, more expressive DPN guards languages are considered or generic datatypes (other than integers or reals) are employed

Comparison of classification methods for detecting associations between SNPs and chick mortality

Multi-category classification methods were used to detect SNP-mortality associations in broilers. The objective was to select a subset of whole genome SNPs associated with chick mortality. This was done by categorizing mortality rates and using a filter-wrapper feature selection procedure in each of the classification methods evaluated. Different numbers of categories (2, 3, 4, 5 and 10) and three classification algorithms (naïve Bayes classifiers, Bayesian networks and neural networks) were compared, using early and late chick mortality rates in low and high hygiene environments. Evaluation of SNPs selected by each classification method was done by predicted residual sum of squares and a significance test-related metric. A naïve Bayes classifier, coupled with discretization into two or three categories generated the SNP subset with greatest predictive ability. Further, an alternative categorization scheme, which used only two extreme portions of the empirical distribution of mortality rates, was considered. This scheme selected SNPs with greater predictive ability than those chosen by the methods described previously. Use of extreme samples seems to enhance the ability of feature selection procedures to select influential SNPs in genetic association studies

Perceptions and Experiences of Individuals With Neck Pain: A Systematic Critical Review of Qualitative Studies With Meta-Summary and Meta-Synthesis

This study aimed at exploring the perspectives and experiences of individuals with neck pain by synthesizing all available qualitative studies

Prevalence and incidence of low back pain among runners: A systematic review

Background: Running is one of the most popular sports worldwide. Despite low back pain (LBP) represents the most common musculoskeletal disorder in population and in sports, there is currently sparse evidence about prevalence, incidence and risk factors for LBP among runners. The aims of this systematic review were to investigate among runners: prevalence and incidence of LBP and specific risk factors for the onset of LBP. Methods: A systematic review has been conducted according to the guidelines of the PRISMA statement. The research was conducted in the following databases from their inception to 31st of July 2019: PubMed; CINAHL; Google Scholar; Ovid; PsycINFO; PSYNDEX; Embase; SPORTDiscus; Scientific Electronic Library Online; Cochrane Library and Web of Science. The checklists of The Joanna Briggs Institute Critical Appraisal tools were used to investigate the risk of bias of the included studies. Results: Nineteen studies were included and the interrater agreement for full-text selection was good (K = 0.78; 0.61-0.80 IC 95%). Overall, low values of prevalence (0.7-20.2%) and incidence (0.3-22%) of LBP among runners were reported. Most reported risk factors were: running for more than 6 years; body mass index > 24; higher physical height; not performing traditional aerobics activity weekly; restricted range of motion of hip flexion; difference between leg-length; poor hamstrings and back flexibility. Conclusions: Prevalence and incidence of LBP among runners are low compared to the others running related injuries and to general, or specific population of athletes. View the low level of incidence and prevalence of LBP, running could be interpreted as a protective factor against the onset of LBP. Systematic review registration: PROSPERO CRD42018102001

Simulation study for analysis of binary responses in the presence of extreme case problems

<p>Abstract</p> <p>Background</p> <p>Estimates of variance components for binary responses in presence of extreme case problems tend to be biased due to an under-identified likelihood. The bias persists even when a normal prior is used for the fixed effects.</p> <p>Methods</p> <p>A simulation study was carried out to investigate methods for the analysis of binary responses with extreme case problems. A linear mixed model that included a fixed effect and random effects of sire and residual on the liability scale was used to generate binary data. Five simulation scenarios were conducted based on varying percentages of extreme case problems, with true values of heritability equal to 0.07 and 0.17. Five replicates of each dataset were generated and analyzed with a generalized prior (<b>g-prior</b>) of varying weight.</p> <p>Results</p> <p>Point estimates of sire variance using a normal prior were severely biased when the percentage of extreme case problems was greater than 30%. Depending on the percentage of extreme case problems, the sire variance was overestimated when a normal prior was used by 36 to 102% and 25 to 105% for a heritability of 0.17 and 0.07, respectively. When a g-prior was used, the bias was reduced and even eliminated, depending on the percentage of extreme case problems and the weight assigned to the g-prior. The lowest Pearson correlations between true and estimated fixed effects were obtained when a normal prior was used. When a 15% g-prior was used instead of a normal prior with a heritability equal to 0.17, Pearson correlations between true and fixed effects increased by 11, 20, 23, 27, and 60% for 5, 10, 20, 30 and 75% of extreme case problems, respectively. Conversely, Pearson correlations between true and estimated fixed effects were similar, within datasets of varying percentages of extreme case problems, when a 5, 10, or 15% g-prior was included. Therefore this indicates that a model with a g-prior provides a more adequate estimation of fixed effects.</p> <p>Conclusions</p> <p>The results suggest that when analyzing binary data with extreme case problems, bias in the estimation of variance components could be eliminated, or at least significantly reduced by using a g-prior.</p

Comparative effectiveness of conservative and pharmacological interventions for chronic non-specific neck pain : Protocol of a systematic review and network meta-analysis

BACKGROUND: Neck Pain (NP) has been ranked as one of the top chronic pain conditions in terms of prevalence and years lived with disability in the latest Global Burden of Disease. NP has remarkable socio-economic consequences however, research efforts are limited. Discrepancies among guidelines recommendations on management of chronic neck pain exist. The purpose of this study protocol is to provide the methods for a review with network meta-analysis to identify the most effective interventions for chronic neck pain. METHODS: The following databases will be searched from their inception to February 2019: Cochrane Controlled Trials Register (CENTRAL), PubMed, CINAHL, Scopus, ISI Web of Science and PEDro.Randomized controlled trials (RCTs) on pharmacological and not pharmacological interventions will be included and their risk of bias will be evaluated using the Cochrane Risk of bias tool. Primary outcomes will be reduction in pain and disability. A network meta-analysis will be carried out and pairwise meta-analysis will be conducted using Stata 15 software. Grading of recommendations assessment, development, and evaluation (GRADE) will be applied to assess quality of the body of the evidence. RESULTS: The results of this review will be submitted to a peer-review journal for publication. CONCLUSION: This network meta-analysis will provide a comprehensive review on the most effective treatments for the management of chronic neck pain providing key evidence-based information to patients, clinicians and other relevant stakeholders. Registration: PROSPERO (registration number CRD42019124501)

Towards a New System for the Assessment of the Quality in Care Pathways: An Overview of Systematic Reviews

Clinical or care pathways are developed by a multidisciplinary team of healthcare practitioners, based on clinical evidence, and standardized processes. The evaluation of their framework/content quality is unclear. The aim of this study was to describe which tools and domains are able to critically evaluate the quality of clinical/care pathways. An overview of systematic reviews was conducted, according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses, using Medline, Embase, Science Citation Index, PsychInfo, CINAHL, and Cochrane Library, from 2015 to 2020, and with snowballing methods. The quality of the reviews was assessed with Assessment the Methodology of Systematic Review (AMSTAR-2) and categorized with The Leuven Clinical Pathway Compass for the definition of the five domains: processes, service, clinical, team, and financial. We found nine reviews. Three achieved a high level of quality with AMSTAR-2. The areas classified according to The Leuven Clinical Pathway Compass were: 9.7% team multidisciplinary involvement, 13.2% clinical (morbidity/mortality), 44.3% process (continuity-clinical integration, transitional), 5.6% financial (length of stay), and 27.0% service (patient-/family-centered care). Overall, none of the 300 instruments retrieved could be considered a gold standard mainly because they did not cover all the critical pathway domains outlined by Leuven and Health Technology Assessment. This overview shows important insights for the definition of a multiprinciple framework of core domains for assessing the quality of pathways. The core domains should consider general critical aspects common to all pathways, but it is necessary to define specific domains for specific diseases, fast pathways, and adapting the tool to the cultural and organizational characteristics of the health system of each country