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Background The extensive and continuous reuse of sensitive health data could enhance the role of population health research on public decisions. This paper describes the design principles and the different building blocks that have supported the implementation and deployment of Population Health Information Research Infrastructure (PHIRI), the strengths and challenges of the approach and some future developments. Methods The design and implementation of PHIRI have been developed upon: (i) the data visiting principle—data does not move but code moves; (ii) the orchestration of the research question throughout a workflow that ensured legal, organizational, semantic and technological interoperability and (iii) a 'master–worker' federated computational architecture that supported the development of four uses cases. Results Nine participants nodes and 28 Euro-Peristat members completed the deployment of the infrastructure according to the expected outputs. As a consequence, each use case produced and published their own common data model, the analytical pipeline and the corresponding research outputs. All the digital objects were developed and published according to Open Science and FAIR principles. Conclusion PHIRI has successfully supported the development of four use cases in a federated manner, overcoming limitations for the reuse of sensitive health data and providing a methodology to achieve interoperability in multiple research nodes. [ABSTRACT FROM AUTHOR]

UV light is a potent mutagen that induces bulky DNA damage in the form of cyclobutane pyrimidine dimers (CPDs). Photodamage and other bulky lesions occurring in nuclear genomes can be repaired through nucleotide excision repair (NER), where incisions on both sides of a damaged site precede the removal of a single-stranded oligonucleotide containing the damage. Mitochondrial genomes (mtDNAs) are also susceptible to damage from UV light, but current evidence suggests that the only way to eliminate bulky mtDNA damage is through mtDNA degradation. Damage-containing oligonucleotides excised during NER can be captured with antidamage antibodies and sequenced (XR-seq) to produce high-resolution maps of active repair locations following UV exposure. We analyzed previously published datasets from Arabidopsis thaliana, Saccharomyces cerevisiae , and Drosophila melanogaster to identify reads originating from the mtDNA (and plastid genome in A. thaliana). In A. thaliana and S. cerevisiae , the mtDNA-mapping reads have unique length distributions compared to the nuclear-mapping reads. The dominant fragment size was 26 nt in S. cerevisiae and 28 nt in A. thaliana with distinct secondary peaks occurring in regular intervals. These reads also show a nonrandom distribution of di-pyrimidines (the substrate for CPD formation) with TT enrichment at positions 7–8 of the reads. Therefore, UV damage to mtDNA appears to result in production of DNA fragments of characteristic lengths and positions relative to the damaged location. The mechanisms producing these fragments are unclear, but we hypothesize that they result from a previously uncharacterized DNA degradation pathway or repair mechanism in mitochondria. [ABSTRACT FROM AUTHOR]

Background Blockchain technology has made great strides in many industries but has yet to impact the world of public health. Population health issues such as outbreak surveillance and controlled substance tracking during emergencies all require a secure, easily accessible database. While the healthcare industry is typically slow to adapt to change, blockchain technology lends itself well to many healthcare issues. Methods We utilized a 3D framework using difficulty, novelty and necessity to examine the adoption of blockchain technology in population health, based on the 2D framework of difficulty and novelty as driving factors for the development of foundational technologies in the world of business by Iansiti and Lakhani in The Harvard Business Review. Results We find that by implementing the third dimension of necessity into an evaluation framework, we can better predict the adoption of technology. We found how different areas of population health fit into the evaluation framework and how necessity can eliminate barriers from implementing novel technologies. Conclusion The byproduct of this paper will be the extension of the Iansiti and Lakhani framework. We will show that blockchain, in all of these domains, shows promise to improve population health as we move past COVID-19 and into the future of healthcare. [ABSTRACT FROM AUTHOR]

Researchers often face the problem of how to address missing data. Multiple imputation is a popular approach, with multiple imputation by chained equations (MICE) being among the most common and flexible methods for execution. MICE iteratively fits a predictive model for each variable with missing values, conditional on other variables in the data. In theory, any imputation model can be used to predict the missing values. However, if the predictive models are incorrectly specified, they may produce biased estimates of the imputed data, yielding inconsistent parameter estimates and invalid inference. Given the set of modeling choices that must be made in conducting multiple imputation, in this paper we propose a data-adaptive approach to model selection. Specifically, we adapt MICE to incorporate an ensemble algorithm, Super Learner, to predict the conditional mean for each missing value, and we also incorporate a local kernel-based estimate of variance. We present a set of simulations indicating that this approach produces final parameter estimates with lower bias and better coverage than other commonly used imputation methods. These results suggest that using a flexible machine learning imputation approach can be useful in settings where data are missing at random, especially when the relationships among the variables are complex. [ABSTRACT FROM AUTHOR]

The article discusses various papers published in the Practice of Epidemiology section of this journal, including one by Brookhart et al. on the use of propensity scores in simulation studies, one by Benowitz et al. on the National Health and Nutrition Examination Survey and one by Stuart et al. on the application of multiple imputation to account for missing data.

Sequences of treatments that adapt to a patient's changing condition over time are often needed for the management of chronic diseases. An adaptive treatment strategy (ATS) consists of personalized treatment rules to be applied through the course of a disease that input the patient's characteristics at the time of decision-making and output a recommended treatment. An optimal ATS is the sequence of tailored treatments that yields the best clinical outcome for patients sharing similar characteristics. Methods for estimating optimal adaptive treatment strategies, which must disentangle short- and long-term treatment effects, can be theoretically involved and hard to explain to clinicians, especially when the outcome to be optimized is a survival time subject to right-censoring. In this paper, we describe dynamic weighted survival modeling, a method for estimating an optimal ATS with survival outcomes. Using data from the Clinical Practice Research Datalink, a large primary-care database, we illustrate how it can answer an important clinical question about the treatment of type 2 diabetes. We identify an ATS pertaining to which drug add-ons to recommend when metformin in monotherapy does not achieve the therapeutic goals. [ABSTRACT FROM AUTHOR]

Background: Study-based registers facilitate systematic reviews through shortening the process for review team and reducing considerable waste during the review process. Such a register also provides new insights about trends of trials in a sub-specialty. This paper reports development and content analysis of Cochrane Schizophrenia Group's Study-Based Register. Methods: The randomized controlled trials were collected through systematic searches of major information sources. Data points were extracted, curated and classified in the register. We report trends using regression analyses in Microsoft Excel and we used GIS mapping (GunnMap 2) to visualize the geographical distribution of the origin of schizophrenia trials. Results: Although only 17% of trials were registered, the number of reports form registered trials is steadily increasing and registered trials produce more reports. Clinical trial registers are main source of trial reports followed by sub-specialty journals. Schizophrenia trials have been published in 23 languages from 90 countries while 105 nations do not have any reported schizophrenia trials. Only 9.7% of trials were included in at least one Cochrane review. Pharmacotherapy is the main target of trials while trials targeting psychotherapy are increasing in a continuous rate. The number of people randomized in trials is on average 114 with 60 being the most frequent sample size. Conclusions: Curated datasets within the register uncover new patterns in data that have implications for research, policy, and practice for testing new interventions in trials or systematic reviews. [ABSTRACT FROM AUTHOR]

Background Health systems in the European Union (EU) are being questioned over their effectiveness and sustainability. In pursuing both goals, they have to conciliate coexisting, not always aligned, realities. Methods This paper originated from a workshop entitled 'Health systems for the future' held at the European Parliament. Experts and decision makers were asked to discuss measures that may increase the effectiveness and sustainability of health systems, namely: (i) increasing citizens' participation; (ii) the importance of primary care in providing integrated services; (iii) improving the governance and (iv) fostering better data collection and information channels to support the decision making process. Results In the parliamentary debate, was discussed the concept that, in the near future, health systems' effectiveness and sustainability will very much depend on effective access to integrated services where primary care is pivotal, a clearer shift from care-oriented systems to health promotion and prevention, a profound commitment to good governance, particularly to stakeholders participation, and a systematic reuse of data meant to build health data-driven learning systems. Conclusions Many health issues, such as future health systems in the EU, are potentially transformative and hence an intense political issue. It is policy-making leadership that will mostly determine how well EU health systems are prepared to face future challenges. [ABSTRACT FROM AUTHOR]

Forensic Sci Res. 2022; 7. 2 Miamoto P, Uehara C. Personal identification and missing persons initiatives in Santa Catarina state, Brazil: forensic perspectives from 2019 to 2021. Invited authors were forensic anthropology practitioners in Brazil representing the main cities in which practice is being pursued. What is the current state of Forensic Anthropology in Brazil and where do we stand when identification is concerned?. [Extracted from the article]

Background: the worldwide population is ageing. One expected consequence of this is an increase in morbidity and an associated increased demand for long-term care. Physical rehabilitation is beneficial in older people, but relatively little is known about effects in residents of long-term care facilities.Objective: to examine the effects of physical rehabilitation on activities of daily living (ADL) in elderly residents of long-term care facilities.Methods: systematic review with meta-analysis of randomised controlled trials. We included studies that compared the effect of a physical rehabilitation intervention on independence in ADL with either no intervention or an alternative intervention in older people (over 60 years) living in long-term care facilities. We searched 19 databases including the Cochrane Central Register of Controlled Trials, MEDLINE, EMBASE, CINAHL, AMED, Web of Knowledge and Google Scholar. Two researchers independently screened papers and extracted data. Outcomes of included studies were combined in a standardised mean difference random-effects meta-analysis.Results: thirteen of 14 studies identified were included in the meta-analysis. Independence in ADL was improved by 0.24 standard units (95% CI: 0.11–0.38; P = 0.0005). This is equivalent to 1.3 points on the Barthel Index (0–20 scale). No significant differences in effect were found based on participant or intervention characteristics. Larger sample size and low attrition were associated with smaller estimates of effect. All studies were assessed to be at risk of bias.Conclusions: physical rehabilitation may improve independence for elderly long-term care facility residents, but mean effects are small. It is unclear which interventions are most appropriate. [ABSTRACT FROM AUTHOR]

There are more than 1.2 billion biological specimens in the world's museums and herbaria. These objects are particularly important forms of biological sample and observation. They underpin biological taxonomy but the data they contain have many other uses in the biological and environmental sciences. Nevertheless, from their conception they are almost entirely documented on paper, either as labels attached to the specimens or in catalogues linked with catalogue numbers. In order to make the best use of these data and to improve the findability of these specimens, these data must be transcribed digitally and made to conform to standards, so that these data are also interoperable and reusable. Through various digitization projects, the authors have experimented with transcription by volunteers, expert technicians, scientists, commercial transcription services and automated systems. We have also been consumers of specimen data for taxonomical, biogeographical and ecological research. In this paper, we draw from our experiences to make specific recommendations to improve transcription data. The paper is split into two sections. We first address issues related to database implementation with relevance to data transcription, namely versioning, annotation, unknown and incomplete data and issues related to language. We then focus on particular data types that are relevant to biological collection specimens, namely nomenclature, dates, geography, collector numbers and uniquely identifying people. We make recommendations to standards organizations, software developers, data scientists and transcribers to improve these data with the specific aim of improving interoperability between collection datasets. [ABSTRACT FROM AUTHOR]

Background. To date, there has been no attempt to describe or compare physical therapy as practiced globally, nor any evidence that an international data set exists to support this effort. It is known that research evidence can be used in strategic and tactical ways, especially within the highly politicized context of the policy arena. The International Private Practitioners Association recognized the potential value a global evidence base could have in influencing policy and supporting professional development in a number of countries, yet it lacked a mechanism to achieve these aims. Objectives. The purposes of this study were: (1) to identify and test an international data set, definitions, and means of data collection and (2) to establish views in relation to the value of international collaborations. Design. A mixed, prospective design was used in the study. Method. Phase 1 (2006-2007) involved the development of a data set, definitions, and Web-based and paper-based data collection options involving 98 physical therapists from 68 physical therapy practices in 7 countries. Phase 2 (2008-2009) involved testing of the data set in 34 practices involving 3,195 patient episodes and included physical therapist feedback of experience, local relevance of the data set, and value of international collaborations. Results. Testing confirmed the relevance and reliability of the data set and definitions and a preference for Web-based data collection (74.0%). Physical therapist feedback supported these findings. Most respondents (60.0%-100.0%) reported the value of further international collaborations for their profession nationally or internationally. Limitations. Although a true international collaboration, the limited sample size should be recognized. Conclusions. It is possible to develop an agreed-upon international data set and means of data collection. Testing appears to support its acceptability and relevance for use in practice. Participants highly valued the opportunity to undertake international collaborations that may benefit their profession nationally and internationally. Further testing and use of the data set are advocated before final validation is sought. [ABSTRACT FROM AUTHOR]

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This paper argues that, currently, significant change is taking place in economics because (1) technological changes in analytic and computing methods are opening up new avenues of study, and (2) the 'low hanging fruit' from previous approaches and methods have already been picked. It offers a vision of the future of economics that sees economists focusing less on the study of infinitely bright agents operating in information rich environments and more on the study of reasonably bright individuals operating in information-poor environments. Agent-based models and computer analysis of data will increase in importance, and deductive analytics will decrease in importance. [ABSTRACT FROM AUTHOR]

There are national and global moves to improve effective digital data design and application in healthcare. This New Horizons commentary describes the role of digital data in healthcare of the ageing population. We outline how health and social care professionals can engage in the proactive design of digital systems that appropriately serve people as they age, carers and the workforce that supports them. Key Points Healthcare improvements have resulted in increased population longevity and hence multimorbidity. Shared care records to improve communication and information continuity across care settings hold potential for older people. Data structure and coding are key considerations. A workforce with expertise in caring for older people with relevant knowledge and skills in digital healthcare is important. [ABSTRACT FROM AUTHOR]

SUMMARY This paper considers some of the problems of managing data on a computer, concentrating mainly on the storage and accessing requirements of basic data structures such as the data matrix. The similarity between scans of these structures for different purposes will be noted and common operations identified. The distinction between the detailed structure of the data and the structure as assumed by the scanning program will be clarified and examples of structure scans for different purposes will be described. Related problems of the maintenance of directories keeping track of structures, and the differences between the use of magnetic tape and disc will be included. The main purpose of the paper is to stress the advantages of establishing the requirements of access to the data, identifying the characteristics of a scan of a data structure, and identifying the basic operations that make up such scans. The advantages of a systematic approach to the problems of data management include (1) a clearer program organization, (2) a clearer division of responsibilities for programming and debugging, (3) changing of programs to meet new requirements or the writing of new parts is much easier, (4) duplication of programming effort both within one program and between programs is avoided, (5) time-consuming operations are better identified and defined and the chances of reducing the time they take are increased. [ABSTRACT FROM AUTHOR]

Currently, there are no generally applicable legal regulations in the field of digital succession in the majority of legal orders. However, such legal provisions are needed because digital assets are getting more and more significant in the contemporary world. Entry into force of legal regulations in this area should be preceded by creation of legal theory of digital succession. Therefore, it is necessary to consider fundamental principles of digital asset inheritance system. The author of this work reviews current theoretical and practical approaches to the matters of digital succession. Considerations included in this work lead to answer to the question how to create fundamental principles of digital succession system. Furthermore, there are separate recommendations for legislators, end-users, digital service providers and judiciary in this work. Hence, this article seems not only theoretical but also practical. [ABSTRACT FROM AUTHOR]

Background Systematic continuous thinking about the future helps organizations, professions and communities to both prepare for, and shape, the future. This becomes ever more critical given the accelerating rate at which new data emerge, and in some cases uncertainties around their reliability and interpretation. Businesses with the capability to filter and analyse vast volumes of data to create knowledge and insights requiring action have a competitive advantage. Similarly Government and the public sector, including public health can be more effective and efficient through the early identification of emerging issues (both threats and opportunities). Methods Horizon scanning approaches, and the use of resulting intelligence related to health protection and improvement were reviewed. Results Public health horizon scanning systems have to date focussed on health technologies and infectious diseases. While these have been successful there is a major gap in terms of non-infectious hazards and health improvement. Conclusion Any system to meet this need must recognize the changed environment for delivering front line public health services and the critical role of local authorities and the local democratic process. This presents opportunities and challenges and this paper explores those dynamics describing an existing environment and health horizon scanning system which could readily and rapidly be re-engineered to provide a national service. [ABSTRACT FROM AUTHOR]

Complete-case analyses can be biased if missing data are not missing completely at random. We propose simple sensitivity analyses that apply to complete-case estimates of treatment effects; these analyses use only simple summary data and obviate specifying the precise mechanism of missingness and making distributional assumptions. Bias arises when treatment effects differ between retained and nonretained participants or, among retained participants, the estimate is biased because conditioning on retention has induced a noncausal path between the treatment and outcome. We thus bound the overall treatment effect on the difference scale by specifying: 1) the unobserved treatment effect among nonretained participants; and 2) the strengths of association that unobserved variables have with the exposure and with the outcome among retained participants ("induced confounding associations"). Working with the former sensitivity parameter subsumes certain existing methods of worst-case imputation while also accommodating less-conservative assumptions (e.g. that the treatment is not detrimental on average even among nonretained participants). As an analog to the E-value for confounding, we propose the M-value, which represents, for a specified treatment effect among nonretained participants, the strength of induced confounding associations required to reduce the treatment effect to the null or to any other value. These methods could help characterize the robustness of complete-case analyses to potential bias due to missing data. [ABSTRACT FROM AUTHOR]

This article presents the latest developments in neuroscience information dissemination through the SenseLab suite of databases: NeuronDB, CellPropDB, ORDB, OdorDB, OdorMapDB, ModelDB and Brain Pharm. These databases include information related to: (i) neuronal membrane properties and neuronal models, and (ii) genetics, genomics, proteomics and imaging studies of the olfactory system. We describe here: the new features for each database, the evolution of SenseLab's unifying database architecture and instances of SenseLab database interoperation with other neuroscience online resources. [ABSTRACT FROM AUTHOR]

Objectives In this tutorial, we examine methods for exploring missingness in a dataset in ways that can help to identify the sources and extent of missingness, as well as clarify gaps in evidence. Methods Using raw data from a meta-analysis of substance abuse interventions, we demonstrate the use of exploratory missingness analysis (EMA) including techniques for numerical summaries and visual displays of missing data. Results These techniques examine the patterns of missing covariates in meta-analysis data and the relationships among variables with missing data and observed variables including the effect size. The case study shows complex relationships among missingness and other potential covariates in meta-regression, highlighting gaps in the evidence base. Conclusion Meta-analysts could often benefit by employing some form of EMA as they encounter missing data. [ABSTRACT FROM AUTHOR]

The traditional approach to relational database design is based on the logical organization of data into a number of related normalized tables. One assumption is that the nature and structure of the data is known at the design stage. In the case of designing a relational database to store historical dental epidemiological data from individual clinical surveys, the structure of the data is not known until the data is presented for inclusion into the database. This paper addresses the issues concerned with the theoretical design of a clinical dynamic database capable of adapting the internal table structure to accommodate clinical survey data, and presents a prototype database application capable of processing, displaying, and querying the dental data. [ABSTRACT FROM AUTHOR]

Genotype-phenotype association studies often combine phenotype data from multiple studies to increase statistical power. Harmonization of the data usually requires substantial effort due to heterogeneity in phenotype definitions, study design, data collection procedures, and data-set organization. Here we describe a centralized system for phenotype harmonization that includes input from phenotype domain and study experts, quality control, documentation, reproducible results, and data-sharing mechanisms. This system was developed for the National Heart, Lung, and Blood Institute's Trans-Omics for Precision Medicine (TOPMed) program, which is generating genomic and other -omics data for more than 80 studies with extensive phenotype data. To date, 63 phenotypes have been harmonized across thousands of participants (recruited in 1948–2012) from up to 17 studies per phenotype. Here we discuss challenges in this undertaking and how they were addressed. The harmonized phenotype data and associated documentation have been submitted to National Institutes of Health data repositories for controlled access by the scientific community. We also provide materials to facilitate future harmonization efforts by the community, which include 1) the software code used to generate the 63 harmonized phenotypes, enabling others to reproduce, modify, or extend these harmonizations to additional studies, and 2) the results of labeling thousands of phenotype variables with controlled vocabulary terms. [ABSTRACT FROM AUTHOR]

Objective To determine the prevalence, profile and predictors of infections in an Indian cohort with idiopathic inflammatory myopathies (IIM). Methods We reviewed the records of a retrospective cohort with IIM enrolled from consecutive patients being followed up in the clinic, and these constituted the observation cohort. A newly diagnosed inception cohort with IIM were followed prospectively as the validation cohort for confirmation of observations and comparison with the observation cohort. Results Among the 68 patients in the observation cohort (average age 33.4 years, female:male 4.2:1), 37 (54.4%) experienced 54 infections between them; of these 54 infections, 21 (38.8%) were major and recurrent infections and they occurred in 11 patients (16.17%) over 3.08 years. Tuberculosis was the most common infection (12, 22.2%), with a predominance of extrapulmonary forms. Serum protein [odds ratio (OR) 0.44], platelets (0.44) at disease onset and daily steroid dose (1.04) predicted major infections on multivariate analysis. A higher daily dose of steroids at first infection correlated with number of recurrent infections. The infection-free 1-year survival was 73.8%. Of the 70 patients in the validation cohort (average age 35.7 years, female:male 3.7:1), 3 had myositis attributed to an infection. A similar proportion of the cohort experienced infections (22, 33.3%) with similar number of major (10, 45.4%) and recurrent (4, 18%) infections being recorded. The most common infection was community-acquired pneumonia, followed by tuberculosis, with serum albumin (OR 0.25) at disease onset being the only predictor. The one-year infection-free survival rate was 64.7%. Those who had a major infection had increased mortality at 1 year, with a survival rate of 60%, compared with 89.09% in those without. In both cohorts, a daily prednisone dose >6.25 mg predisposed to major infections. Conclusion Major and recurrent infections are common in Indian IIM patients and confer higher risk for future infections and lower survival. Respiratory and atypical bacterial infections such as tuberculosis occur throughout the disease course. [ABSTRACT FROM AUTHOR]

Background Variable consent rates threaten the validity of linked datasets. One modifiable element is the interviewer–respondent relationship. We examine interviewer attitudes to consent to linkage and the effect on respondent consent. Methods Subjects were 27 380 respondents from the Wave 1 Understanding Society (US) survey in Great Britain and 449 interviewers who completed the US Interviewer Survey. Two types of consent were considered: (i) whether the interviewer would hypothetically agree to having their data linked if he/she was an US respondent and (ii) whether the respondent consented to have their data linked. Factors influencing the interviewer's propensity to link data were examined using logistic regression. The association between interviewer consent and respondent consent to health record linkage was assessed using multi-level logistic regression models. Results The interviewer's propensity to consent to data linkage was strongly positively associated with its perceived usefulness: those that found it somewhat useful were 57% less likely to consent [adjusted odds ratio (AOR) 0.43, 95% CI: 0.22–0.82] compared to those who thought it was very useful. Positive beliefs about data security and their ability to understand the data linkage information were also associated. Respondents were 17% less likely to consent when interviewed by an interviewer who would not consent to record linkage (AOR 0.83, 95% CI: 0.71–0.97). Conclusions The interviewer's propensity to consent was influenced by their beliefs about data linkage, which in turn influenced respondent consent. We recommend using interviewer training to emphasize the usefulness of data linkage and the measures around data security. [ABSTRACT FROM AUTHOR]

When estimating causal effects, careful handling of missing data is needed to avoid bias. Complete-case analysis is commonly used in epidemiologic analyses. Previous work has shown that covariate-stratified effect estimates from complete-case analysis are unbiased when missingness is independent of the outcome conditional on the exposure and covariates. Here, we assess the bias of complete-case analysis for adjusted marginal effects when confounding is present under various causal structures of missing data. We show that estimation of the marginal risk difference requires an unbiased estimate of the unconditional joint distribution of confounders and any other covariates required for conditional independence of missingness and outcome. The dependence of missing data on these covariates must be considered to obtain a valid estimate of the covariate distribution. If none of these covariates are effect-measure modifiers on the absolute scale, however, the marginal risk difference will equal the stratified risk differences and the complete-case analysis will be unbiased when the stratified effect estimates are unbiased. Estimation of unbiased marginal effects in complete-case analysis therefore requires close consideration of causal structure and effect-measure modification. [ABSTRACT FROM AUTHOR]

Objectives Data collected during routine clinic visits are key to driving successful quality improvement in clinical services and enabling integration of research into routine care. The purpose of this study was to develop a standardized core dataset for juvenile idiopathic arthritis (JIA) (termed CAPTURE-JIA), enabling routine clinical collection of research-quality patient data useful to all relevant stakeholder groups (clinicians, service-providers, researchers, health service planners and patients/families) and including outcomes of relevance to patients/families. Methods Collaborative consensus-based approaches (including Delphi and World Café methodologies) were employed. The study was divided into discrete phases, including collaborative working with other groups developing relevant core datasets and a two-stage Delphi process, with the aim of rationalizing the initially long data item list to a clinically feasible size. Results The initial stage of the process identified collection of 297 discrete data items by one or more of fifteen NHS paediatric rheumatology centres. Following the two-stage Delphi process, culminating in a consensus workshop (May 2015), the final approved CAPTURE-JIA dataset consists of 62 discrete and defined clinical data items including novel JIA-specific patient-reported outcome and experience measures. Conclusions CAPTURE-JIA is the first 'JIA core dataset' to include data items considered essential by key stakeholder groups engaged with leading and improving the clinical care of children and young people with JIA. Collecting essential patient information in a standard way is a major step towards improving the quality and consistency of clinical services, facilitating collaborative and effective working, benchmarking clinical services against quality indicators and aligning treatment strategies and clinical research opportunities. [ABSTRACT FROM AUTHOR]

Health-related information is increasingly being collected and stored digitally. These data, either structured or unstructured, are becoming the ubiquitous assets that might enable us to comprehensively map out a patient's health journey from an asymptomatic state of wellness to disease onset and its trajectory. These new data could provide rich real-world evidence for better clinical care and research, if they can be accessed, linked and analyzed—all of which are possible. In this review, these opportunities will be explored through a case vignette of a patient with OA, followed by discussion on how this digitalized real-world evidence could best be utilized, as well as the challenges of data access, quality and maintaining public trust. [ABSTRACT FROM AUTHOR]

The rise of precision oncology has made clinical decision making more complex than ever before. The oncology Data Network was established to enable the clinical community to efficiently access potentially practice‐changing insights from an extended network of cancer centers. This article describes the progress to date and calls for greater collaboration. [ABSTRACT FROM AUTHOR]

This investigation examines the dynamics associated with soliciting intimate information from consumers via computers. Experiment 1 identifies two factors—reciprocity and sequence—that affect the likelihood that people will reveal intimate information about themselves via a computer. Experiment 2 provides evidence that intimate information exchanges can affect how consumers behave in subsequent interactions. Implications for marketing research and practice are discussed. [ABSTRACT FROM AUTHOR]

Recent technological advances in echocardiography, with progressive miniaturization of ultrasound machines, have led to the development of handheld ultrasound devices (HUD). These devices, no larger than some mobile phones, can be used to perform partial, focused exams as an extension to the physical examination. The European Association of Cardiovascular Imaging (EACVI) acknowledges that the dissemination of appropriate HUD use is inevitable and desirable, because of its potential impact on patient management. However, as a scientific society of cardiac imaging, our role is to provide guidance in order to optimize patient benefit and minimize drawbacks from inappropriate use of this technology. This document provides updated recommendations for the use of HUD, including nomenclature, appropriateness, indications, operators, clinical environments, data management and storage, educational needs, and training of potential users. It also addresses gaps in evidence, controversial issues, and future technological developments. [ABSTRACT FROM AUTHOR]

Aim to compare the validity of data submitted from a UK level 1 trauma centre to the National Hip Fracture Database (NHFD) before and after the introduction of an electronic health record system (EHRS). Patients and methods a total of 3224 records were reviewed from July 2009 to July 2017. 2,133 were submitted between July 2009 and October 2014 and 1,091 between October 2014 and July 2017, representing data submitted before and after the introduction of the EHRS, respectively. Data submitted to the NHFD were scrutinised against locally held data. Results use of an EHRS was associated with significant reductions in NHFD errors. The operation coding error rate fell significantly from 23.2% (494/2133) to 7.6% (83/1091); P < 0.001. Prior to EHRS introduction, of the 109 deaths recorded in the NHFD, 64 (59%) were incorrect. In the EHRS dataset, all the 112 recorded deaths were correct (P < 0.001). There was no significant difference in the error rate for fracture coding. In the EHRS dataset, after controlling for sample month, entries utilising an operation note template with mandatory fields relevant to NHFD data were more likely to be error free than those not using the template (OR 2.69; 95% CI 1.92–3.78). Conclusion this study highlights a potential benefit of EHR systems, which offer automated data collection for auditing purposes. However, errors in data submitted to the NHFD remain, particularly in cases where an NHFD-specific operation note template is not used. Clinician engagement with new technologies is vital to avoid human error and ensure database integrity. [ABSTRACT FROM AUTHOR]

The numbers of international collaborations among birth cohort studies designed to better understand asthma and allergies have increased in the last several years. However, differences in definitions and methods preclude direct pooling of original data on individual participants. As part of the Mechanisms of the Development of Allergy (MeDALL) Project, we harmonized data from 14 birth cohort studies (each with 3–20 follow-up periods) carried out in 9 European countries during 1990–1998 or 2003–2009. The harmonization process followed 6 steps: 1) organization of the harmonization panel; 2) identification of variables relevant to MeDALL objectives (candidate variables); 3) proposal of a definition for each candidate variable (reference definition); 4) assessment of the compatibility of each cohort variable with its reference definition (inferential equivalence) and classification of this inferential equivalence as complete, partial, or impossible ; 5) convocation of a workshop to agree on the reference definitions and classifications of inferential equivalence; and 6) preparation and delivery of data through a knowledge management portal. We agreed on 137 reference definitions. The inferential equivalence of 3,551 cohort variables to their corresponding reference definitions was classified as complete, partial, and impossible for 70%, 15%, and 15% of the variables, respectively. A harmonized database was delivered to MeDALL investigators. In asthma and allergy birth cohorts, the harmonization of data for pooled analyses is feasible, and high inferential comparability may be achieved. The MeDALL harmonization approach can be used in other collaborative projects. [ABSTRACT FROM AUTHOR]

With incomplete data, the "missing at random" (MAR) assumption is widely understood to enable unbiased estimation with appropriate methods. While the need to assess the plausibility of MAR and to perform sensitivity analyses considering "missing not at random" (MNAR) scenarios has been emphasized, the practical difficulty of these tasks is rarely acknowledged. With multivariable missingness, what MAR means is difficult to grasp, and in many MNAR scenarios unbiased estimation is possible using methods commonly associated with MAR. Directed acyclic graphs (DAGs) have been proposed as an alternative framework for specifying practically accessible assumptions beyond the MAR-MNAR dichotomy. However, there is currently no general algorithm for deciding how to handle the missing data given a specific DAG. Here we construct "canonical" DAGs capturing typical missingness mechanisms in epidemiologic studies with incomplete data on exposure, outcome, and confounding factors. For each DAG, we determine whether common target parameters are "recoverable," meaning that they can be expressed as functions of the available data distribution and thus estimated consistently, or whether sensitivity analyses are necessary. We investigate the performance of available-case and multiple-imputation procedures. Using data from waves 1–3 of the Longitudinal Study of Australian Children (2004–2008), we illustrate how our findings can guide the treatment of missing data in point-exposure studies. [ABSTRACT FROM AUTHOR]

Lesko et al. (Am J Epidemiol. 2022;191(12):2063–2070) propose a framework for descriptive epidemiology. This framework helps lay out some of the key issues in producing a useful descriptive work. Lesko et al. help emphasize the importance and value of descriptive work in epidemiology and public health. In this commentary, related issues are discussed and open questions are raised. [ABSTRACT FROM AUTHOR]

This article presents a new numerical method for facial reconstruction. The problem is the following: given a dry skull, reconstruct a virtual face that would help in the identification of the subject. The approach combines classical features as the use of a skulls/faces database and more original aspects: (1) an original shape matching method is used to link the unknown skull to the database templates; (2) the final face is seen as an elastic 3D mask that is deformed and adapted onto the unknown skull. In this method, the skull is considered as a whole surface and not restricted to some anatomical landmarks, allowing a dense description of the skull/face relationship. Also, the approach is fully automated. Various results are presented to show its efficiency. [ABSTRACT FROM AUTHOR]

The article offers information on the challenges faced in the field of toxicology. It discusses the importance of the proper peer review of methodologies, integrity and care in the interpretation of data and the conscientious appraisal of conclusions in the process of decision making for the purpose of human wellbeing.

Background This article provides an original method of estimating the prevalence of injecting drug users (IDU) in France. Method In order to overcome legal restrictions hampering data linkage, the method relies on a single-source capture–recapture framework and makes use of individual data collected by a standardized survey conducted within treatment centres. Taking the hierarchical structure of data collection into consideration, a multilevel Zelterman regression model was used. Results In 2014, last year IDU were thought to be 103 800 (85 300; 130 000), prevalence of 2.6‰ (2.1; 3.2), and last month IDU 86 000 (69 200; 110 400), prevalence of 2.2‰ (1.7; 2.7). Estimates have been broken down by gender, revealing a 3 to 1 ratio of male-to-female; and age, showing young adults less prone to regular use of injection. It is thought that one IDU out of three was seen in treatment centres in 2014. Conclusion The number of last month IDU has remained stable when compared with the last available figures calculated in 2006. Nowadays IDU include heroin, buprenorphine, polydrug and stimulant users. This greater diversity ought to be taken into account by prevention policies, and underlines the need for perennial monitoring of IDU. [ABSTRACT FROM AUTHOR]

Background The number of abortions of fetuses with Down syndrome in England and Wales reported by the Department of Health (DH) differs from that reported by the National Down Syndrome Cytogenetic Register (NDSCR). The aim of this study was to investigate the reasons for this. Methods Abortions in 2011 and 2012 from DH were matched to those from NDSCR. The number of cases not reported to either source was estimated. Results An estimated 2240 abortions of fetuses with Down syndrome occurred in 2011/12; NDSCR estimated 2208 and DH 1100. One thousand and six abortions were identified in both data sets, including 145 (14%) which were not recorded by DH as having Down syndrome. Abortions in NDSCR that were not matched in DH occurred throughout England and Wales and at all gestational ages. An estimated 61 abortions of fetuses with Down syndrome were not reported to DH or NDSCR. Conclusions The number of abortions of fetuses with Down syndrome reported by the NDSCR is more complete than that reported by the DH. DH data for abortions with other congenital anomalies are also likely to be underestimates, and more accurate estimates are available from BINOCAR regional congenital anomaly registers. [ABSTRACT FROM AUTHOR]

Initially submitted November 24, 2014; accepted for publication May 20, 2015. We propose taking advantage of methodology for missing data to estimate relationships and adjust outcomes in a meta-analysis where a continuous covariate is differentially categorized across studies. The proposed method incorporates all available data in an implementation of the expectation-maximization algorithm. We use simulations to demonstrate that the proposed method eliminates bias that would arise by ignoring a covariate and generalizes the meta-analytical approach for incorporating covariates that are not uniformly categorized. The proposed method is illustrated in an application for estimating diarrhea incidence in children aged ≤59 months. [ABSTRACT FROM AUTHOR]

Motivation: Discovery of novel splicing from RNA sequence data remains a critical and exciting focus of transcriptomics, but reduced alignment power impedes expression quantification of novel splice junctions. Results: Here, we profile performance characteristics of two-pass alignment, which separates splice junction discovery from quantification. Per sample, across a variety of transcriptome sequencing datasets, two-pass alignment improved quantification of at least 94% of simulated novel splice junctions, and provided as much as 1.7-fold deeper median read depth over those splice junctions. We further demonstrate that two-pass alignment works by increasing alignment of reads to splice junctions by short lengths, and that potential alignment errors are readily identifiable by simple classification. Taken together, two-pass alignment promises to advance quantification and discovery of novel splicing events. [ABSTRACT FROM AUTHOR]

Motivation: Proteins often recognize their interaction partners on the basis of short linear motifs located in disordered regions on proteins' surface. Experimental techniques that study such motifs use short peptides to mimic the structural properties of interacting proteins. Continued development of these methods allows for large-scale screening, resulting in vast amounts of peptide sequences, potentially containing information on multiple protein-protein interactions. Processing of such datasets is a complex but essential task for large-scale studies investigating protein-protein interactions. Results: The software tool presented in this article is able to rapidly identify multiple clusters of sequences carrying shared specificity motifs in massive datasets from various sources and generate multiple sequence alignments of identified clusters. The method was applied on a previously published smaller dataset containing distinct classes of ligands for SH3 domains, as well as on a new, an order of magnitude larger dataset containing epitopes for several monoclonal antibodies. The software successfully identified clusters of sequences mimicking epitopes of antibody targets, as well as secondary clusters revealing that the antibodies accept some deviations from original epitope sequences. Another test indicates that processing of even much larger datasets is computationally feasible. [ABSTRACT FROM AUTHOR]

Cancer epidemiologists have a long history of combining data sets in pooled analyses, often harmonizing heterogeneous data from multiple studies into 1 large data set. Although there are useful websites on data harmonization with recommendations and support, there is little research on best practices in data harmonization; each project conducts harmonization according to its own internal standards. The field would be greatly served by charting the process of data harmonization to enhance the quality of the harmonized data. Here, we describe the data harmonization process utilized at the Fred Hutchinson Cancer Research Center (Seattle, Washington) by the coordinating centers of several research projects. We describe a 6-step harmonization process, including: 1) identification of questions the harmonized data set is required to answer; 2) identification of high-level data concepts to answer those questions; 3) assessment of data availability for data concepts; 4) development of common data elements for each data concept; 5) mapping and transformation of individual data points to common data elements; and 6) quality-control procedures. Our aim here is not to claim a "correct" way of doing data harmonization but to encourage others to describe their processes in order that we can begin to create rigorous approaches. We also propose a research agenda around this issue. [ABSTRACT FROM AUTHOR]

Motivation: Next-generation sequencing produces vast amounts of data with errors that are difficult to distinguish from true biological variation when coverage is low. Results: We demonstrate large reductions in error frequencies, especially for high-error-rate reads, by three independent means: (i) filtering reads according to their expected number of errors, (ii) assembling overlapping read pairs and (iii) for amplicon reads, by exploiting unique sequence abundances to perform error correction. We also show that most published paired read assemblers calculate incorrect posterior quality scores. Availability and implementation: These methods are implemented in the USEARCH package. Binaries are freely available at http://drive5.com/usearch. [ABSTRACT FROM AUTHOR]

Background: The implications of sharing one’s health data are far-reaching. Potential applications of health data range from the delivery of treatments tailored to individuals’ characteristics to improvements in public health, while also posing concerns about privacy, social justice and equity. Making informed decisions about health data sharing thus requires thorough consideration of the scientific, ethical and personal implications of donations. This study assessed participants’ preferences regarding decision-making about health data sharing for research, including the need for support by data counsellors. Methods: This observational cross-sectional study includes 159 patients and 479 carers followed at two reference centres for rare diseases in a Portuguese academic hospital, between June 2019 and March 2020. Participants were asked about preferred modes of decision-making: deciding on their own, deciding with support from another person, or delegating the decision to someone else. Those who responded the last two options also reported who they would choose for support or delegation: family or friends; a data counsellor; a professional with no specific training on data counselling; other. Data were analysed using descriptive and inferential statistics. Results: The majority of respondents would prefer to decide with support (62%), 37% would prefer to decide on their own and 1% would opt to delegate the decision of sharing health data. Among those who expressed a preference for support, 60% would like to rely on a data counsellor. Carers, older and higher educated participants, and those with upper white-collar occupations and who were satisfied with their own health were significantly more likely to select data counsellors as their preferred source of support when engaging in decision-making about health data sharing for research (p < 0.05). Conclusions: This study supports recommendations for the creation of a new professional specialty of health data counsellors. Key messages: Most participants express the need for support in making decisions about health data sharing for research, with 60% preferring support from a data counsellor. As a new professional specialism, health data counselling can help to advance informed public participation in health research. [ABSTRACT FROM AUTHOR]

Motivation: Extracellular vesicles (EVs) are spherical bilayered proteolipids, harboring various bioactive molecules. Due to the complexity of the vesicular nomenclatures and components, online searches for EV-related publications and vesicular components are currently challenging. Results: We present an improved version of EVpedia, a public database for EVs research. This community web portal contains a database of publications and vesicular components, identification of orthologous vesicular components, bioinformatic tools and a personalized function. EVpedia includes 6879 publications, 172 080 vesicular components from 263 high-throughput datasets, and has been accessed more than 65 000 times from more than 750 cities. In addition, about 350 members from 73 international research groups have participated in developing EVpedia. This free web-based database might serve as a useful resource to stimulate the emerging field of EV research. [ABSTRACT FROM AUTHOR]

The article focuses on the importance of computer information retrieval to the working scientists. Several scientists are responsible of gathering and maintaining references, citations and reprints in different forms, as well as in searching and indexing. Information retrieval will help them in saving time and effort because it can be easily used in searching and pointing important items and citations. The process only requires logical decisions and card input which provides limitless categorization possibilities.

Background: China significantly opened its healthcare market through a series of market-opening policies in 2000–1. This study aims to explore the direct consequences of these policies—the growth of private hospitals, their workforce characteristics compared with public hospitals in China and the source of their healthcare workforce.Methods: First, we performed a segmented regression analysis of a longitudinal data series of the number of hospitals in China between 1990 and 2009 to examine the before and after effects of the market-opening policy on private hospitals. Then, to highlight the workforce differences between private and public hospitals, provincial survey data collected in 2009 were compared with data from a second database collected in 2002 to detect the mobility of medical staff from the public to the private hospitals.Results: The number of private hospitals rapidly increased after 2001, and the yearly growth rate increased from 19 to 205, represented primarily by an increase in specialty hospitals. Approximately 22.03% of the physicians in private hospitals are over the age of 60, whereas this proportion in public hospitals is only 2.97%. In 2008, at least 4.1% of the staff working in private hospitals had previously worked in local public hospitals in 2001.Conclusion: The broad expansion of private hospitals since 2001 is most likely the result of an unbiased market policy environment for private hospitals. Moreover, specific features of the hospital–physician relationship in China may account for the unbalanced age distribution feature among doctors and the mobility of the healthcare workforce in private hospitals. [ABSTRACT FROM AUTHOR]