Nevin Manimala

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

Chem Rev. 2021 Feb 25. doi: 10.1021/acs.chemrev.1c00103. Online ahead of print.

NO ABSTRACT

PMID:33629840 | DOI:10.1021/acs.chemrev.1c00103

Pol Arch Intern Med. 2021 Feb 25. doi: 10.20452/pamw.15848. Online ahead of print.

ABSTRACT

INTRODUCTION: Chronic rhinosinusitis (CRS) is one of the most widespread chronic diseases in the world, whereas stroke is a leading cause of death and disability. There are numerous reports emphasizing the relationship between chronic inflammatory diseases and cardio-cerebro-vascular diseases (CCVDs).

OBJECTIVES: The aim of the study was to assess whether sinus inflammatory changes can be a risk factor for stroke similar to other known risk factors such as arterial hypertension, atrial fibrillation, arteriosclerosis, diabetes mellitus or smoking.

PATIENTS AND METHODS: The authors of the study analysed the results of sinus computed tomography (CT) performed in 163 ischemic stroke patients (79 men), mean (SD) age 68.5 (12.7) years, qualified for mechanical thrombectomy. The control group consisted of 75 patients (31 men) with neurological diseases of non-vascular origin.

RESULTS: In the group of stroke patients, sinus inflammatory changes were found in 95 subjects (58.3%), with a frequency comparable to the occurrence of atrial fibrillation (77; 47.2%). CRS was statistically more frequent than diabetes mellitus (33; 20.2%, P < 0.001), self-reported nicotinism (18; 11.0%, P <0.001), less frequent than arterial hypertension and generalized arteriosclerosis (124; 76.1%, P < 0.001 and 116; 71.2%, P = 0.02, respectively). Sinus inflammatory changes of moderate or severe intensity were observed more frequently in the group of stroke patients than in the control group and they involved mainly the ethmoid sinuses.

CONCLUSION: Moderate to severe inflammatory changes indicating chronic rhinosinusitis are common in stroke patients, which suggests the role of local inflammation in inducing acute cerebral ischemia.

PMID:33629827 | DOI:10.20452/pamw.15848

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

J Magn Reson Imaging. 2021 Feb 25. doi: 10.1002/jmri.27578. Online ahead of print.

ABSTRACT

BACKGROUND: Although contrast agents would be beneficial, they are seldom used in four-dimensional (4D) flow magnetic resonance imaging (MRI) due to potential side effects and contraindications.

PURPOSE: To develop and evaluate a deep learning architecture to generate high blood-tissue contrast in noncontrast 4D flow MRI by emulating the use of an external contrast agent.

STUDY TYPE: Retrospective.

SUBJECTS: Of 222 data sets, 141 were used for neural network (NN) training (69 with and 72 without contrast agent). Evaluation was performed on the remaining 81 noncontrast data sets.

FIELD STRENGTH/SEQUENCES: Gradient echo or echo-planar 4D flow MRI at 1.5 T and 3 T.

ASSESSMENT: A cyclic generative adversarial NN was trained to perform image translation between noncontrast and contrast data. Evaluation was performed quantitatively using contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), structural similarity index (SSIM), mean squared error (MSE) of edges, and Dice coefficient of segmentations. Three observers performed a qualitative assessment of blood-tissue contrast, noise, presence of artifacts, and image structure visualization.

STATISTICAL TESTS: The Wilcoxon rank-sum test evaluated statistical significance. Kendall’s concordance coefficient assessed interobserver agreement.

RESULTS: Contrast in the regions of interest (ROIs) in the NN enhanced images increased by 88%, CNR increased by 63%, and SNR improved by 48% (all P < 0.001). The SSIM was 0.82 ± 0.01, and the MSE of edges was 0.09 ± 0.01 (range [0,1]). Segmentations based on the generated images resulted in a Dice similarity increase of 15.25%. The observers managed to differentiate between contrast MR images and our results; however, they preferred the NN enhanced images in 76.7% of cases. This percentage increased to 93.3% for phase-contrast MR angiograms created from the NN enhanced data. Visual grading scores were blood-tissue contrast = 4.30 ± 0.74, noise = 3.12 ± 0.98, and presence of artifacts = 3.63 ± 0.76. Image structures within and without the ROIs resulted in scores of 3.42 ± 0.59 and 3.07 ± 0.71, respectively (P < 0.001).

DATA CONCLUSION: The proposed approach improves blood-tissue contrast in MR images and could be used to improve data quality, visualization, and postprocessing of cardiovascular 4D flow data. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 1.

PMID:33629795 | DOI:10.1002/jmri.27578

Biom J. 2021 Feb 25. doi: 10.1002/bimj.202000227. Online ahead of print.

ABSTRACT

Shrinkage estimation in a meta-analysis framework may be used to facilitate dynamical borrowing of information. This framework might be used to analyze a new study in the light of previous data, which might differ in their design (e.g., a randomized controlled trial and a clinical registry). We show how the common study weights arise in effect and shrinkage estimation, and how these may be generalized to the case of Bayesian meta-analysis. Next we develop simple ways to compute bounds on the weights, so that the contribution of the external evidence may be assessed a priori. These considerations are illustrated and discussed using numerical examples, including applications in the treatment of Creutzfeldt-Jakob disease and in fetal monitoring to prevent the occurrence of metabolic acidosis. The target study’s contribution to the resulting estimate is shown to be bounded below. Therefore, concerns of evidence being easily overwhelmed by external data are largely unwarranted.

PMID:33629749 | DOI:10.1002/bimj.202000227

Br J Math Stat Psychol. 2021 Feb 25. doi: 10.1111/bmsp.12238. Online ahead of print.

ABSTRACT

Principal covariate regression (PCOVR) is a method for regressing a set of criterion variables with respect to a set of predictor variables when the latter are many in number and/or collinear. This is done by extracting a limited number of components that simultaneously synthesize the predictor variables and predict the criterion ones. So far, no procedure has been offered for estimating statistical uncertainties of the obtained PCOVR parameter estimates. The present paper shows how this goal can be achieved, conditionally on the model specification, by means of the bootstrap approach. Four strategies for estimating bootstrap confidence intervals are derived and their statistical behaviour in terms of coverage is assessed by means of a simulation experiment. Such strategies are distinguished by the use of the varimax and quartimin procedures and by the use of Procrustes rotations of bootstrap solutions towards the sample solution. In general, the four strategies showed appropriate statistical behaviour, with coverage tending to the desired level for increasing sample sizes. The main exception involved strategies based on the quartimin procedure in cases characterized by complex underlying structures of the components. The appropriateness of the statistical behaviour was higher when the proper number of components were extracted.

PMID:33629738 | DOI:10.1111/bmsp.12238

Cereb Cortex. 2021 Feb 25:bhab029. doi: 10.1093/cercor/bhab029. Online ahead of print.

ABSTRACT

The posterior superior temporal sulcus (pSTS) is a brain region characterized by perceptual representations of human body actions that promote the understanding of observed behavior. Increasingly, action observation is recognized as being strongly shaped by the expectations of the observer (Kilner 2011; Koster-Hale and Saxe 2013; Patel et al. 2019). Therefore, to characterize top-down influences on action observation, we evaluated the statistical structure of multivariate activation patterns from the action observation network (AON) while observers attended to the different dimensions of action vignettes (the action kinematics, goal, or identity of avatars jumping or crouching). Decoding accuracy varied as a function of attention instruction in the right pSTS and left inferior frontal cortex (IFC), with the right pSTS classifying actions most accurately when observers attended to the action kinematics and the left IFC classifying most accurately when observed attended to the actor’s goal. Functional connectivity also increased between the right pSTS and right IFC when observers attended to the actions portrayed in the vignettes. Our findings are evidence that the attentive state of the viewer modulates sensory representations in the pSTS, consistent with proposals that the pSTS occupies an interstitial zone mediating top-down context and bottom-up perceptual cues during action observation.

PMID:33629729 | DOI:10.1093/cercor/bhab029

Mil Med. 2021 Feb 25:usab085. doi: 10.1093/milmed/usab085. Online ahead of print.

ABSTRACT

INTRODUCTION: Weight status perception (WSP) is the subjective assessment of one’s own body weight. It is not correlated with the body mass index (BMI). People practicing sports, including overweight people, tend to perceive themselves as normal weight. The military is in a paradoxical position between the need to gain muscle mass for professional purposes while respecting BMI standards. Using body composition might be more advantageous than using BMI as part of an individual approach in making a decision about fitness to serve. However, measuring body composition is not easy in current practice, and a bridge between WSP and body composition would make it possible to develop a simple assessment tool.

MATERIALS AND METHODS: This was a prospective, descriptive, cross-sectional study. We collected sociodemographic data, anthropometric data, and WSP.

RESULTS: Thirty-eight subjects were included. Among them, 71.1% were male. Mean age was 31.2 years (SD 8.9). The BMI was greater than 25 for 15 (39.5%) subjects. Twenty-four (63.2%) defined themselves as being overweight. Thirteen were overweight according to fat percentage (Fat%). A significant association (P = .008) was found between WSP and Fat%.

CONCLUSION: We were able to show a statistically significant association between WSP and Fat%. Such an association may be of great interest because the measurement of the Fat%, whatever the method used, is not easy in current practice. A replication of the study in the general population would be of great interest, especially since Fat% is closely associated with the incidence of cardiovascular diseases and many cancers.

PMID:33629720 | DOI:10.1093/milmed/usab085