bluuebunny/crossref_metadata_2025_split huggingface dataset:
Propensity Score Analysis for a Semi-Continuous Exposure Variable: A Study of Gestational Alcohol Exposure and Childhood Cognition
Authors: Akkaya Hocagil Tugba , Cook Richard J. , Jacobson Sandra W. , Jacobson Joseph L. , Ryan Louise M. 
Published: July 2021

AbstractPropensity score methodology has become increasingly popular in recent years as a tool for estimating causal effects in observational studies. Much of the related research has been directed at settings with binary or discrete exposure variables with more recent work involving continuous exposure variables. In environmental epidemiology, a substantial proportion of individuals is often completely unexposed while others may experience heavy exposure leading to an exposure distribution with a point mass at zero and a heavy right tail. We suggest a new approach to handle this type of exposure data by constructing a propensity score based on a two-part model and show how this model can be used to more reliably adjust for covariates of a semi-continuous exposure variable. We also consider the case when a misspecified propensity score is used in a regression adjustment and derive an explicit form of the bias. We show that the potential bias gets smaller as the estimated propensity score gets closer to the true expectation of the exposure variable given a set of observed covariates. While this result pertains to a more general setting, we use it to evaluate the potential bias in settings in which the true exposure has a semi-continuous structure. We also evaluate and compare the performance of our proposed method through simulation studies relative to a simpler linear regression-based propensity score for a continuous exposure variable as well as through direct covariate adjustment. Overall, we find that using a propensity score constructed via a two-part model significantly improves the regression estimate when the exposure variable is semi-continuous in nature. Specifically when the proportion of non-exposed subjects is high and the effects of covariates on exposure and outcome are strong, the proposed two-part propensity score method outperforms the more standard competing methods. We illustrate our method using data from the Detroit Longitudinal Cohort Study in which the exposure variable reflects gestational alcohol exposure featuring zero values and a long tail.
What factors affect patients’ ability to access healthcare? An overview of systematic reviews
Authors: Dawkins Bryony , Renwick Charlotte , Ensor Tim , Shinkins Bethany , Jayne David , Meads David 
Published: July 2021

AbstractOBJECTIVESThis overview aims to synthesise global evidence on factors affecting healthcare access, and variations across low‐ and middle‐income countries (LMICs) vs. high‐income countries (HICs); to develop understanding of where barriers to healthcare access lie, and in what context, to inform tailored policies aimed at improving access to healthcare for all who need it.METHODSAn overview of systematic reviews guided by a published protocol was conducted. Medline, Embase, Global Health and Cochrane Systematic Reviews databases were searched for published articles. Additional searches were conducted on the Gates Foundation, WHO and World Bank websites. Study characteristics and findings (barriers and facilitators to healthcare access) were documented and summarised. The methodological quality of included studies was assessed using an adapted version of the AMSTAR 2 tool.RESULTSFifty‐eight articles were included, 23 presenting findings from LMICs and 35 presenting findings from HICs. While many barriers to healthcare access occur in HICs as well as LMICs, the way they are experienced is quite different. In HICs, there is a much greater emphasis on patient experience; as compared to the physical absence of care in LMICs.CONCLUSIONSAs countries move towards universal healthcare access, evaluation methods that account for health system and wider cultural factors that impact capacity to provide care, healthcare finance systems and the socio‐cultural environment of the setting are required. Consequently, methods employed in HICs may not be appropriate in LMICs due to the stark differences in these areas.
Open chromatin in grapevine marks candidate CREs and with other chromatin features correlates with gene expression
Authors: Schwope Rachel , Magris Gabriele , Miculan Mara , Paparelli Eleonora , Celii Mirko , Tocci Aldo , Marroni Fabio , Fornasiero Alice , De Paoli Emanuele , Morgante Michele 
Published: July 2021

SummaryVitis vinifera is an economically important crop and a useful model in which to study chromatin dynamics. In contrast to the small and relatively simple genome of Arabidopsis thaliana, grapevine contains a complex genome of 487 Mb that exhibits extensive colonization by transposable elements. We used Hi‐C, ChIP‐seq and ATAC‐seq to measure how chromatin features correlate to the expression of 31 845 grapevine genes. ATAC‐seq revealed the presence of more than 16 000 open chromatin regions, of which we characterize nearly 5000 as possible distal enhancer candidates that occur in intergenic space > 2 kb from the nearest transcription start site (TSS). A motif search identified more than 480 transcription factor (TF) binding sites in these regions, with those for TCP family proteins in greatest abundance. These open chromatin regions are typically within 15 kb from their nearest promoter, and a gene ontology analysis indicated that their nearest genes are significantly enriched for TF activity. The presence of a candidate cis‐regulatory element (cCRE) > 2 kb upstream of the TSS, location in the active nuclear compartment as determined by Hi‐C, and the enrichment of H3K4me3, H3K4me1 and H3K27ac at the gene are correlated with gene expression. Taken together, these results suggest that regions of intergenic open chromatin identified by ATAC‐seq can be considered potential candidates for cis‐regulatory regions in V. vinifera. Our findings enhance the characterization of a valuable agricultural crop, and help to clarify the understanding of unique plant biology.
Epidemiology and risk factors of scrub typhus in Taiwan: A nationwide database study from 1996 to 2014
Authors: Chang Yi‐Chin , Sun Wu , Lin Jiun‐Nong , Chen Yen‐Hsu , Lai Chung‐Hsu , Lee Chen‐Hsiang 
Published: July 2021

AbstractBackgroundScrub typhus (ST) is one of the most underdiagnosed, potentially fatal febrile diseases in the Asia‐Pacific region. We conducted a comprehensive review of the risk factors of ST over 19 years using data from a nationwide database.MethodsWe used data on ST from the nationwide database of the Taiwan Centers for Disease Control from 1996 to 2014 to analyse the incidence rates and relative risks of ST according to different regions. The trends of incidence rates over the study period were also evaluated. The distribution of confirmed ST cases was mapped using geographic information system software. The characteristics of confirmed ST cases and non‐ST cases (cases with suspected ST but negative test findings) were compared.ResultsAmong the 38,127 reported cases, there were 6,791 (17.8%) confirmed ST cases. The overall incidence rate of ST in Taiwan was 1.49 per 100,000 residents per year. The trend of incidence rates increased over time. The Island region had the highest incidence rate (56.55 per 100,000 residents per year), followed by the Eastern region (15.13 per 100,000 residents per year). More confirmed ST cases were distributed in mountainous areas of Taiwan Main Island and Island region. Compared to non‐ST cases, individuals with confirmed ST were younger (median [interquartile range] age: 44 [26–57] years versus 45 [30–60] years,p < .001) and more likely to engage in at‐risk occupations (29.4% versus 13.3%,p < .001), including farming and animal husbandry (16.6% versus 9.0%,p < .001) and the armed forces (12.3% versus 3.5%,p < .001); however, they had a lower rate of animal contact (12.8% versus 20.1%,p < .001).ConclusionsST is an endemic disease in Taiwan, particularly in the Island region, Eastern region and mountainous areas. Patients engaged in at‐risk occupations and presenting with acute febrile diseases should undergo investigations for ST.
Modeling Fracture in Rate-Dependent Polymer Networks: A Quasicontinuum Approach
Authors: Ghareeb Ahmed , Elbanna Ahmed 
Published: July 2021

Abstract
Soft materials, such as rubber and gels, exhibit rate-dependent response where the stiffness, strength, and fracture patterns depend largely on loading rates. Thus, accurate modeling of the mechanical behavior requires accounting for different sources of rate dependence such as the intrinsic viscoelastic behavior of the polymer chains and the dynamic bond breakage and formation mechanism. In this chapter, we extend the QC approach presented in Ghareeb and Elbanna (2020, An Adaptive Quasi-Continuum Approach for Modeling Fracture in Networked Materials: Application to Modeling of Polymer Networks, J. Mech. Phys. Solids, 137, p. 103819) to include rate-dependent behavior of polymer networks. We propose a homogenization rule for the viscous forces in the polymer chains and update the adaptive mesh refinement algorithm to account for dynamic bond breakage. Then, we use nonlinear finite element framework with predictor–corrector scheme to solve for the nodal displacements and velocities. We demonstrate the accuracy of the method by verifying it against fully discrete simulations for different examples of network structures and loading conditions. We further use the method to investigate the effects of the loading rates on the fracture characteristics of networks with different rate-dependent parameters. Finally, We discuss the implications of the extended method for multiscale analysis of fracture in rate-dependent polymer networks.
Predicting the Rock Sonic Logs While Drilling by Random Forest and Decision Tree-Based Algorithms
Authors: Gamal Hany , Alsaihati Ahmed , Elkatatny Salaheldin 
Published: July 2021

AbstractThe sonic data provide significant rock properties that are commonly used for designing the operational programs for drilling, rock fracturing, and development operations. The conventional methods for acquiring the rock sonic data in terms of compressional and shear slowness (ΔTc and ΔTs) are considered costly and time-consuming operations. The target of this paper is to propose machine learning models for predicting the sonic logs from the drilling data in real-time. Decision tree (DT) and random forest (RF) were employed as train-based algorithms for building the sonic prediction models for drilling complex lithology rocks that have limestone, sandstone, shale, and carbonate formations. The input data for the models include the surface drilling parameters to predict the shear and compressional slowness. The study employed data set of 2888 data points for building and testing the model, while another collected 2863 data set was utilized for further validation of the sonic models. Sensitivity investigations were performed for DT and RF models to confirm optimal accuracy. The correlation of coefficient (R) and average absolute percentage error (AAPE) were used to check the models’ accuracy between the actual values and models’ outputs, in addition to the sonic log profiles. The results indicated that the developed sonic models have a high capability for the sonic prediction from the drilling data as the DT model recorded R higher than 0.967 and AAPE less than 2.76% for ΔTc and ΔTs models, while RF showed R higher than 0.991 with AAPE less than 1.07%. The further validation process for the developed models indicated the great results for the sonic prediction and the RF model outperformed DT models as RF showed R higher than 0.986 with AAPE less than 1.12% while DT prediction recorded R greater than 0.93 with AAPE less than 1.95%. The sonic prediction through the developed models will save the cost and time for acquiring the sonic data through the conventional methods and will provide real-time estimation from the drilling parameters.
Management of social isolation and loneliness in community-dwelling older adults: protocol for a network meta-analysis of randomised controlled trials
Authors: Lee Ahreum , McArthur Caitlin , Veroniki Areti Angeliki , Kastner Monika , Ioannidis George , Griffith Lauren E , Thabane Lehana , Adachi Jonathan D , Papaioannou Alexandra 
Published: July 2021

IntroductionSocial isolation and loneliness in older adults are significant public health issues. Various interventions such as exercise programmes or social activities are used in the management of social isolation and loneliness in older adults. Network meta-analysis (NMA) provides effect estimates for all comparisons by considering the relative efficacy of multiple intervention alternatives. Therefore, this study will determine the comparative efficacy of intervention to alleviate social isolation and loneliness of older adults in community dwelling by comparing direct and indirect interventions through systematic review and NMA.Methods and analysisWe will include all relevant randomised controlled trials for interventions of social isolation and loneliness in older adults written in English without any limitation of publication date through electronic databases: MEDLINE via OVID, EMBASE, Cochrane Central Registry of Controlled Trials (CENTRAL), PsycINFO and CINAHL. Independent teams of reviewers will screen trial eligibility, collect data, identify duplication and assess risk of bias, by using the Cochrane revised risk of bias tool. The interventions for the management of social isolation and loneliness will be included. The primary outcome is social isolation. The secondary outcomes are loneliness and health-related quality of life. We will conduct an NMA through a Bayesian hierarchical model, by testing assumption (ie, transitivity) for NMA. We will also estimate the ranking probabilities for all interventions at each possible rank for each intervention. For estimation of each intervention efficacy, we will assess the certainty and credibility using the Grading of Recommendations Assessment, Development and Evaluation approach.Ethics and disseminationEthics approval will not be obtained for this systematic review as it will be conducted with published papers. The review results will be presented at a field-specific conference and published in a relevant peer-reviewed journal.PROSPERO registration numberCRD42020155789.
Patterns of peritoneal dissemination and response to systemic chemotherapy in common and rare peritoneal tumours treated by cytoreductive surgery: study protocol of a prospective, multicentre, observational study
Authors: Bhatt Aditi , Rousset Pascal , Baratti Dario , Biacchi Daniele , Benzerdjeb Nazim , H J T de Hingh Ignace , Deraco Marcello , Gushchin Vadim , Kammar Praveen , Labow Daniel , Levine Edward , Moran Brendan , Mohamed Faheez , Morris David , Mehta Sanket , Nissan Aviram , Alyami Mohammad , Adileh Mohammad , Barat Shoma , Ben Yacov Almog , Campbell Kurtis , Cummins-Perry Kathleen , Cortes-Guiral Delia , Cohen Noah , Parikh Loma , Alammari Samer , Bashanfer Galal , Alshukami Anwar , Kundalia Kaushal , Goswami Gaurav , de Vlasakker Vincent van , Sittig Michelle , Sammartino Paolo , Sardi Armando , Villeneuve Laurent , Turaga Kiran , Yonemura Yutaka , Glehen Olivier 
Published: July 2021

IntroductionDespite optimal patient selection and surgical effort, recurrence is seen in over 70% of patients undergoing cytoreductive surgery (CRS) for peritoneal metastases (PM). Apart from the Peritoneal Cancer Index (PCI), completeness of cytoreduction and tumour grade, there are other factors like disease distribution in the peritoneal cavity, pathological response to systemic chemotherapy (SC), lymph node metastases and morphology of PM which may have prognostic value. One reason for the underutilisation of these factors is that they are known only after surgery. Identifying clinical predictors, specifically radiological predictors, could lead to better utilisation of these factors in clinical decision making and the extent of peritoneal resection performed for different tumours. This study aims to study these factors, their impact on survival and identify clinical and radiological predictors.Methods and analysisThere is no therapeutic intervention in the study. All patients with biopsy-proven PM from colorectal, appendiceal, gastric and ovarian cancer and peritoneal mesothelioma undergoing CRS will be included. The demographic, clinical, radiological, surgical and pathological details will be collected according to a prespecified format that includes details regarding distribution of disease, morphology of PM, regional node involvement and pathological response to SC. In addition to the absolute value of PCI, the structures bearing the largest tumour nodules and a description of the morphology in each region will be recorded. A correlation between the surgical, radiological and pathological findings will be performed and the impact of these potential prognostic factors on progression-free and overall survival determined. The practices pertaining to radiological and pathological reporting at different centres will be studied.Ethics and disseminationThe study protocol has been approved by the Zydus Hospital ethics committee (27 July, 2020) and Lyon-Sud ethics committee (A15-128).Trial registration numberCTRI/2020/09/027709; Pre-results.
Incentive preferences for community health volunteers in Kenya: findings from a discrete choice experiment
Authors: Abuya Timothy , Mwanga Daniel , Obadha Melvin , Ndwiga Charity , Odwe George , Kavoo Daniel , Wanyugu John , Warren Charlotte , Agarwal Smisha 
Published: July 2021

BackgroundCommunity health volunteers (CHVs) play crucial roles in enabling access to healthcare at the community levels. Although CHVs are considered volunteers, programmes provide financial and non-financial incentives. However, there is limited evidence on which bundle of financial and non-financial incentives are most effective for their improved performance.MethodsWe used a discrete choice experiment (DCE) to understand incentive preferences of CHVs with the aim to improve their motivation, performance and retention. Relevant incentive attributes were identified through qualitative interviews with CHVs and with their supervisors. We then deployed a nominal group technique to generate and rank preferred attributes among CHVs. We developed a DCE based on the five attributes and administered it to 211 CHVs in Kilifi and Bungoma counties in Kenya. We used mixed multinomial logit models to estimate the utility of each incentive attribute and calculated the trade-offs the CHWs were willing to make for a change in stipend.ResultsTransport was considered the incentive attribute with most relative importance followed by tools of trade then monthly stipend. CHVs preferred job incentives that offered higher monthly stipends even though it was not the most important. They had negative preference for job incentives that provided award mechanisms for the best performing CHVs as compared with jobs that provided recognition at the community level and preferred job incentives that provided more tools of trade compared with those that provided limited tools.ConclusionA bundled incentive of both financial and non-financial packages is necessary to provide a conducive working environment for CHVs. The menu of options relevant for CHVs in Kenya include transport, tools of trade and monthly stipend. Policy decisions should be contextualised to include these attributes to facilitate CHW satisfaction and performance.
Costing interventions in the field: preliminary cost estimates and lessons learned from an evaluation of community-wide mass drug administration for elimination of soil-transmitted helminths in the DeWorm3 trial
Authors: Galactionova Katya , Sahu Maitreyi , Gideon Samuel Paul , Puthupalayam Kaliappan Saravanakumar , Morozoff Chloe , Ajjampur Sitara Swarna Rao , Walson Judd , Rubin Means Arianna , Tediosi Fabrizio 
Published: July 2021

ObjectiveTo present a costing study integrated within the DeWorm3 multi-country field trial of community-wide mass drug administration (cMDA) for elimination of soil-transmitted helminths.DesignTailored data collection instruments covering resource use, expenditure and operational details were developed for each site. These were populated alongside field activities by on-site staff. Data quality control and validation processes were established. Programmed routines were used to clean, standardise and analyse data to derive costs of cMDA and supportive activities.SettingField site and collaborating research institutions.Primary and secondary outcome measuresA strategy for costing interventions in parallel with field activities was discussed. Interim estimates of cMDA costs obtained with the strategy were presented for one of the trial sites.ResultsThe study demonstrated that it was both feasible and advantageous to collect data alongside field activities. Practical decisions on implementing the strategy and the trade-offs involved varied by site; trialists and local partners were key to tailoring data collection to the technical and operational realities in the field. The strategy capitalised on the established processes for routine financial reporting at sites, benefitted from high recall and gathered operational insight that facilitated interpretation of the estimates derived. The methodology produced granular costs that aligned with the literature and allowed exploration of relevant scenarios. In the first year of the trial, net of drugs, the incremental financial cost of extending deworming of school-aged children to the whole community in India site averaged US$1.14 (USD, 2018) per person per round. A hypothesised at-scale routine implementation scenario yielded a much lower estimate of US$0.11 per person treated per round.ConclusionsWe showed that costing interventions alongside field activities offers unique opportunities for collecting rich data to inform policy toward optimising health interventions and for facilitating transfer of economic evidence from the field to the programme.Trial registration numberNCT03014167; Pre-results.