Tag: pubmed

PLoS One. 2021 Feb 25;16(2):e0246674. doi: 10.1371/journal.pone.0246674. eCollection 2021.

ABSTRACT

OBJECTIVES: The European Randomized Study of Screening for Prostate Cancer found that prostate-specific antigen (PSA) screening reduced prostate cancer mortality, however the costs and harms from screening may outweigh any mortality reduction. Compared with screening using the PSA test alone, using the Stockholm3 Model (S3M) as a reflex test for PSA ≥ 1 ng/mL has the same sensitivity for Gleason score ≥ 7 cancers while the relative positive fractions for Gleason score 6 cancers and no cancer were 0.83 and 0.56, respectively. The cost-effectiveness of the S3M test has not previously been assessed.

METHODS: We undertook a cost-effectiveness analysis from a lifetime societal perspective. Using a microsimulation model, we simulated for: (i) no prostate cancer screening; (ii) screening using the PSA test; and (iii) screening using the S3M test as a reflex test for PSA values ≥ 1, 1.5 and 2 ng/mL. Screening strategies included quadrennial re-testing for ages 55-69 years performed by a general practitioner. Discounted costs, quality-adjusted life-years (QALYs) and incremental cost-effectiveness ratios (ICERs) were calculated.

RESULTS: Comparing S3M with a reflex threshold of 2 ng/mL with screening using the PSA test, S3M had increased effectiveness, reduced lifetime biopsies by 30%, and increased societal costs by 0.4%. Relative to the PSA test, the S3M reflex thresholds of 1, 1.5 and 2 ng/mL had ICERs of 170,000, 60,000 and 6,000 EUR/QALY, respectively. The S3M test was more cost-effective at higher biopsy costs.

CONCLUSIONS: Prostate cancer screening using the S3M test for men with an initial PSA ≥ 2.0 ng/mL was cost-effective compared with screening using the PSA test alone.

PMID:33630863 | DOI:10.1371/journal.pone.0246674

PLoS One. 2021 Feb 25;16(2):e0246790. doi: 10.1371/journal.pone.0246790. eCollection 2021.

ABSTRACT

Falling in Parkinsonian syndromes (PS) is associated with postural instability and consists a common cause of disability among PS patients. Current posturographic practices record the body’s center-of-pressure displacement (statokinesigram) while the patient stands on a force platform. Statokinesigrams, after appropriate processing, can offer numerous posturographic features. This fact, although beneficial, challenges the efforts for valid statistics via standard univariate approaches. In this work, 123 PS patients were classified into fallers (PSF) or non-faller (PSNF) based on the clinical assessment, and underwent simple Romberg Test (eyes open/eyes closed). We developed a non-parametric multivariate two-sample test (ts-AUC) based on machine learning, in order to examine statokinesigrams’ differences between PSF and PSNF. We analyzed posturographic features using both multiple testing with p-value adjustment and ts-AUC. While ts-AUC showed significant difference between groups (p-value = 0.01), multiple testing did not agree with this result (eyes open). PSF showed significantly increased antero-posterior movements as well as increased posturographic area compared to PSNF. Our study highlights the superiority of ts-AUC compared to standard statistical tools in distinguishing PSF and PSNF in multidimensional space. Machine learning-based statistical tests can be seen as a natural extension of classical statistics and should be considered, especially when dealing with multifactorial assessments.

PMID:33630865 | DOI:10.1371/journal.pone.0246790

PLoS One. 2021 Feb 25;16(2):e0245579. doi: 10.1371/journal.pone.0245579. eCollection 2021.

ABSTRACT

Achieving biologically interpretable neural-biomarkers and features from neuroimaging datasets is a challenging task in an MRI-based dyslexia study. This challenge becomes more pronounced when the needed MRI datasets are collected from multiple heterogeneous sources with inconsistent scanner settings. This study presents a method of improving the biological interpretation of dyslexia’s neural-biomarkers from MRI datasets sourced from publicly available open databases. The proposed system utilized a modified histogram normalization (MHN) method to improve dyslexia neural-biomarker interpretations by mapping the pixels’ intensities of low-quality input neuroimages to range between the low-intensity region of interest (ROIlow) and high-intensity region of interest (ROIhigh) of the high-quality image. This was achieved after initial image smoothing using the Gaussian filter method with an isotropic kernel of size 4mm. The performance of the proposed smoothing and normalization methods was evaluated based on three image post-processing experiments: ROI segmentation, gray matter (GM) tissues volume estimations, and deep learning (DL) classifications using Computational Anatomy Toolbox (CAT12) and pre-trained models in a MATLAB working environment. The three experiments were preceded by some pre-processing tasks such as image resizing, labelling, patching, and non-rigid registration. Our results showed that the best smoothing was achieved at a scale value, σ = 1.25 with a 0.9% increment in the peak-signal-to-noise ratio (PSNR). Results from the three image post-processing experiments confirmed the efficacy of the proposed methods. Evidence emanating from our analysis showed that using the proposed MHN and Gaussian smoothing methods can improve comparability of image features and neural-biomarkers of dyslexia with a statistically significantly high disc similarity coefficient (DSC) index, low mean square error (MSE), and improved tissue volume estimations. After 10 repeated 10-fold cross-validation, the highest accuracy achieved by DL models is 94.7% at a 95% confidence interval (CI) level. Finally, our finding confirmed that the proposed MHN method significantly outperformed the normalization method of the state-of-the-art histogram matching.

PMID:33630876 | DOI:10.1371/journal.pone.0245579

PLoS One. 2021 Feb 25;16(2):e0246485. doi: 10.1371/journal.pone.0246485. eCollection 2021.

ABSTRACT

q-Rung orthopair fuzzy set (qROFS) and m-polar fuzzy set (mPFS) are rudimentary concepts in the computational intelligence, which have diverse applications in fuzzy modeling and decision making under uncertainty. The aim of this paper is to introduce the hybrid concept of q-rung orthopair m-polar fuzzy set (qROmPFS) as a hybrid model of q-rung orthopair fuzzy set and m-polar fuzzy set. A qROmPFS has the ability to deal with real life situations when decision experts are interested to deal with multi-polarity as well as membership and non-membership grades to the alternatives in an extended domain with q-ROF environment. Certain operations on qROmPFSs and several new notions like support, core, height, concentration, dilation, α-cut and (α, β)-cut of qROmPFS are defined. Additionally, grey relational analysis (GRA) and choice value method (CVM) are presented under qROmPFSs for multi-criteria decision making (MCDM) in robotic agri-farming. The proposed methods are suitable to find out an appropriate mode of farming among several kinds of agri-farming. The applications of proposed MCDM approaches are illustrated by respective numerical examples. To justify the feasibility, superiority and reliability of proposed techniques, the comparison analysis of the final ranking in the robotic agri-farming computed by the proposed techniques with some existing MCDM methods is also given.

PMID:33630877 | DOI:10.1371/journal.pone.0246485

PLoS One. 2021 Feb 25;16(2):e0247069. doi: 10.1371/journal.pone.0247069. eCollection 2021.

ABSTRACT

INTRODUCTION: The prevalence of oral hygiene behaviors (OHB) is very low among school children in Ethiopia. However, the determinants of student’s readiness/intention to perform those behaviors have been remained unstudied.

OBJECTIVE: This study aimed to identify the determinants of oral hygiene behavioral intention (OHBI) among preparatory school students based on the theory of planned behavior (TPB).

METHODS AND MATERIALS: An institution-based cross-sectional study was conducted among 393 students. A 98-item self-administered questionnaire was used to evaluate oral hygiene knowledge (OHK), oral hygiene behavior (OHB), and OHBI based on TPB variables [attitude (ATT), subjective norms (SN) and perceived behavioral control (PBC)]. Descriptive statistics and structural equation modeling analysis (SEM) were employed to confirm relationships and associations among study variables. A p-value of less than 0.05 and a 95% confidence interval were used to declare statistical significance.

RESULTS: A total of 393 students were participated with a response rate of 97.5%. The mean age of the participants (54% females) was 18 (± 1.3) with an age range of 16 to 24. The TPB model was well fitted to the data and explained 66% of the variance in intention. ATT (β = 0.38; 95% CI, (0.21, 0.64)), SN (β = 0.33; 95% CI, (0.05, 0.83)) and PBC (β = 0.29; 95% CI, (0.13, 0.64)) were significant predictors of OHBI, where ATT was the strongest predictor of OHBI.

CONCLUSION: The TPB model explained a large variance in the intention of students to improve their OHB. All TPB variables were significantly and positively linked to stronger intent, as the theory suggests. Furthermore, these results suggest that the model could provide a framework for oral hygiene promotion interventions in the study area. Indeed, these interventions should focus on changing the attitudes of students towards OHB, creation of positive social pressure, and enabling students to control over OHB barriers.

PMID:33630853 | DOI:10.1371/journal.pone.0247069

PLoS Genet. 2021 Feb 25;17(2):e1009269. doi: 10.1371/journal.pgen.1009269. eCollection 2021 Feb.

ABSTRACT

Malaria remains a major public health problem in many countries. Unlike influenza and HIV, where diversity in immunodominant surface antigens is understood geographically to inform disease surveillance, relatively little is known about the global population structure of PfEMP1, the major variant surface antigen of the malaria parasite Plasmodium falciparum. The complexity of the var multigene family that encodes PfEMP1 and that diversifies by recombination, has so far precluded its use in malaria surveillance. Recent studies have demonstrated that cost-effective deep sequencing of the region of var genes encoding the PfEMP1 DBLα domain and subsequent classification of within host sequences at 96% identity to define unique DBLα types, can reveal structure and strain dynamics within countries. However, to date there has not been a comprehensive comparison of these DBLα types between countries. By leveraging a bioinformatic approach (jumping hidden Markov model) designed specifically for the analysis of recombination within var genes and applying it to a dataset of DBLα types from 10 countries, we are able to describe population structure of DBLα types at the global scale. The sensitivity of the approach allows for the comparison of the global dataset to ape samples of Plasmodium Laverania species. Our analyses show that the evolution of the parasite population emerging out of Africa underlies current patterns of DBLα type diversity. Most importantly, we can distinguish geographic population structure within Africa between Gabon and Ghana in West Africa and Uganda in East Africa. Our evolutionary findings have translational implications in the context of globalization. Firstly, DBLα type diversity can provide a simple diagnostic framework for geographic surveillance of the rapidly evolving transmission dynamics of P. falciparum. It can also inform efforts to understand the presence or absence of global, regional and local population immunity to major surface antigen variants. Additionally, we identify a number of highly conserved DBLα types that are present globally that may be of biological significance and warrant further characterization.

PMID:33630855 | DOI:10.1371/journal.pgen.1009269

PLoS One. 2021 Feb 25;16(2):e0246823. doi: 10.1371/journal.pone.0246823. eCollection 2021.

ABSTRACT

This two-part study examined the perceptions of talented Swiss soccer players about their talent development environment. The first study presented the translation and validation of the Talent Development Environment Questionnaire (TDEQ) into French using a recommended methodology for translating and culturally adapting questionnaires. Two hundred and three Swiss athletes (M = 16.99 years old) responded to the 25 items of the TDEQ-5. One item was excluded due to low factor loadings, and the descriptive statistics showed that the re-specified TDEQ-5 instrument had acceptable global model fit according to the thresholds in the literature (χ2 (df = 17) = 484.62, p<0.001, CFI = 0.91, TLI = 0.90, RMSEA = 0.07, SRMR = 0.06). This adaptation is thus valid for assessing the effectiveness of talent development processes. For the second study, a holistic design was used to examine the perceptions of a set of players embedded in a top-level Swiss soccer academy (i.e., 64 elite soccer players from 14 to 18 years old) by using the TDEQ-5. The results showed some relative strengths (i.e., F1-Long-Term Focus for the M15 and M16 age-groups) and weaknesses (i.e., F2-Alignment of Expectations for the M17 and M18 age -groups and F3-Communication for M17). They also highlighted that the talent pathways of these Swiss soccer players could not be summarized by a single type of transition toward a professional team. Rather, there were context-specific requirements, such as the critical period between the M15-M16 and M17-M18 age-groups, suggesting that when the players first entered their TDE they experienced a set of affordances to develop and flourish, which thereafter were perceived as less rich and/or abundant. These results offer a starting point for optimizing talent pathways.

PMID:33630856 | DOI:10.1371/journal.pone.0246823

Health Technol Assess. 2021 Feb;25(9):1-378. doi: 10.3310/hta25090.

ABSTRACT

BACKGROUND: Cognitive-behavioural therapy aims to increase quality of life by changing cognitive and behavioural factors that maintain problematic symptoms. A previous overview of cognitive-behavioural therapy systematic reviews suggested that cognitive-behavioural therapy was effective for many conditions. However, few of the included reviews synthesised randomised controlled trials.

OBJECTIVES: This project was undertaken to map the quality and gaps in the cognitive-behavioural therapy systematic review of randomised controlled trial evidence base. Panoramic meta-analyses were also conducted to identify any across-condition general effects of cognitive-behavioural therapy.

DATA SOURCES: The overview was designed with cognitive-behavioural therapy patients, clinicians and researchers. The Cochrane Library, MEDLINE, EMBASE, PsycINFO, Cumulative Index to Nursing and Allied Health Literature, Child Development & Adolescent Studies, Database of Abstracts of Reviews of Effects and OpenGrey databases were searched from 1992 to January 2019.

REVIEW METHODS: Study inclusion criteria were as follows: (1) fulfil the Centre for Reviews and Dissemination criteria; (2) intervention reported as cognitive-behavioural therapy or including one cognitive and one behavioural element; (3) include a synthesis of cognitive-behavioural therapy trials; (4) include either health-related quality of life, depression, anxiety or pain outcome; and (5) available in English. Review quality was assessed with A MeaSurement Tool to Assess systematic Reviews (AMSTAR)-2. Reviews were quality assessed and data were extracted in duplicate by two independent researchers, and then mapped according to condition, population, context and quality. The effects from high-quality reviews were pooled within condition groups, using a random-effect panoramic meta-analysis. If the across-condition heterogeneity was I ² < 75%, we pooled across conditions. Subgroup analyses were conducted for age, delivery format, comparator type and length of follow-up, and a sensitivity analysis was performed for quality.

RESULTS: A total of 494 reviews were mapped, representing 68% (27/40) of the categories of the International Classification of Diseases, Eleventh Revision, Mortality and Morbidity Statistics. Most reviews (71%, 351/494) were of lower quality. Research on older adults, using cognitive-behavioural therapy preventatively, ethnic minorities and people living outside Europe, North America or Australasia was limited. Out of 494 reviews, 71 were included in the primary panoramic meta-analyses. A modest effect was found in favour of cognitive-behavioural therapy for health-related quality of life (standardised mean difference 0.23, 95% confidence interval 0.05 to 0.41, prediction interval -0.05 to 0.50, I ² = 32%), anxiety (standardised mean difference 0.30, 95% confidence interval 0.18 to 0.43, prediction interval -0.28 to 0.88, I ² = 62%) and pain (standardised mean difference 0.23, 95% confidence interval 0.05 to 0.41, prediction interval -0.28 to 0.74, I ² = 64%) outcomes. All condition, subgroup and sensitivity effect estimates remained consistent with the general effect. A statistically significant interaction effect was evident between the active and non-active comparator groups for the health-related quality-of-life outcome. A general effect for depression outcomes was not produced as a result of considerable heterogeneity across reviews and conditions.

LIMITATIONS: Data extraction and analysis were conducted at the review level, rather than returning to the individual trial data. This meant that the risk of bias of the individual trials could not be accounted for, but only the quality of the systematic reviews that synthesised them.

CONCLUSION: Owing to the consistency and homogeneity of the highest-quality evidence, it is proposed that cognitive-behavioural therapy can produce a modest general, across-condition benefit in health-related quality-of-life, anxiety and pain outcomes.

FUTURE WORK: Future research should focus on how the modest effect sizes seen with cognitive-behavioural therapy can be increased, for example identifying alternative delivery formats to increase adherence and reduce dropout, and pursuing novel methods to assess intervention fidelity and quality.

STUDY REGISTRATION: This study is registered as PROSPERO CRD42017078690.

FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 25, No. 9. See the NIHR Journals Library website for further project information.

PMID:33629950 | DOI:10.3310/hta25090

Int J Occup Saf Ergon. 2021 Feb 25:1-29. doi: 10.1080/10803548.2021.1888019. Online ahead of print.

ABSTRACT

Background: Professional drivers drive for many hours without rest. This factor, in addition to the characteristics of the job, the vehicle, the environment and the driver, causes driver fatigue. Fatigue is one of the most common risk factors when driving because it causes drowsiness, decreases their attention, and may make them fall asleep at the wheel. In this paper we propose a predictive model for professional drivers using the following variables: age, number of children, time spent at work, Time spent inside the vehicle, Personality (OPERAS), Job characteristics (JDS), Job content (JCQ) and Burnout.Method: Participants were 509 professional drivers from various transport sectors recruited by non-probabilistic sampling. SPSS version 25.0 was used for statistical analysis.Results: The predictive capacity of variables that cause driver fatigue was determined. Exhaustion best predicts fatigue positively, while Openness to Experience best predicts it negatively. Burnout and certain personality characteristics are good predictors, whereas other variables, such as JCQ and JDS, are weak predictors.Conclusions: This study extends our knowledge of the factors that cause fatigue in professional drivers and underlines the importance of designing interventions aimed at reducing the incidence of fatigue, promoting greater driver well-being, and lowering the incidence of accidents.

PMID:33629925 | DOI:10.1080/10803548.2021.1888019

Glob Chang Biol. 2021 Feb 25. doi: 10.1111/gcb.15539. Online ahead of print.

ABSTRACT

Globally, collapse of ecosystems-potentially irreversible change to ecosystem structure, composition and function-imperils biodiversity, human health and well-being. We examine the current state and recent trajectories of 19 ecosystems, spanning 58° of latitude across 7.7 M km² , from Australia’s coral reefs to terrestrial Antarctica. Pressures from global climate change and regional human impacts, occurring as chronic ‘presses’ and/or acute ‘pulses’, drive ecosystem collapse. Ecosystem responses to 5-17 pressures were categorised as four collapse profiles-abrupt, smooth, stepped and fluctuating. The manifestation of widespread ecosystem collapse is a stark warning of the necessity to take action. We present a three-step assessment and management framework (3As Pathway Awareness, Anticipation and Action) to aid strategic and effective mitigation to alleviate further degradation to help secure our future.

PMID:33629799 | DOI:10.1111/gcb.15539