ArticleJournal of clinical and translational science2020
Guidelines for Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD).
Article in Journal of clinical and translational science, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- Critical care trends across five waves of COVID-19 in Pakistan: A multi-center observational study from the Pakistan Registry of Intensive CarE (PRICE).BMC infectious diseases · 2026Observational
- A Standardized Guideline for Assessing Extracted Electronic Health Records Cohorts: A Scoping Review.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2025Article
- Health Service Utilization by Women Members and Non-Members of Community-Based Health Insurance Schemes in Sidama, Southern Ethiopia, 2024: A Comparative Cross-Sectional Study.Health services insights · 2025Article
- The California collaborative network to promote data driven care and improve outcomes in early psychosis (EPI-CAL) project: rationale, background, design and methodology.BMC psychiatry · 2024Article
- Longitudinal natural history studies based on real-world data in rare diseases: Opportunity and a novel approach.Molecular genetics and metabolism · 2024Review
- Harmonizing data on correlates of sleep in children within and across neurodevelopmental disorders: lessons learned from an Ontario Brain Institute cross-program collaboration.Frontiers in neuroinformatics · 2024Article
- Challenges and best practices for digital unstructured data enrichment in health research: A systematic narrative review.PLOS digital health · 2023Article
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- REVersal of nEuromusculAr bLocking Agents in Patients Undergoing General Anaesthesia (REVEAL Study).Journal of clinical medicine · 2023Article
- De-identified data quality assessment approaches by data vendors who license data to healthcare and life sciences researchers.JAMIA open · 2022Article
- Traumatic brain injury: progress and challenges in prevention, clinical care, and research.The Lancet. Neurology · 2022Review
- Data Collection Theory in Healthcare Research: The Minimum Dataset in Quantitative Studies.Clinics and practice · 2022Article
- Clinical and organizational factors associated with mortality during the peak of first COVID-19 wave: the global UNITE-COVID study.Intensive care medicine · 2022Article
- Development and implementation of the National Heart, Lung, and Blood Institute COVID-19 common data elements.Journal of clinical and translational science · 2022Article
- Best practices in the real-world data life cycle.PLOS digital health · 2022Review
- A Standards Organization for Open and FAIR Neuroscience: the International Neuroinformatics Coordinating Facility.Neuroinformatics · 2022Review
- Common Data Elements to Facilitate Sharing and Re-use of Participant-Level Data: Assessment of Psychiatric Comorbidity Across Brain Disorders.Frontiers in psychiatry · 2022Article
- A Manual for the Glasgow Outcome Scale-Extended Interview.Journal of neurotrauma · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundHigh-quality data are critical to the entire scientific enterprise, yet the complexity and effort involved in data curation are vastly under-appreciated. This is especially true for large observational, clinical studies because of the amount of multimodal data that is captured and the opportunity for addressing numerous research questions through analysis, either alone or in combination with other data sets. However, a lack of details concerning data curation methods can result in unresolved questions about the robustness of the data, its utility for addressing specific research questions or hypotheses and how to interpret the results. We aimed to develop a framework for the design, documentation and reporting of data curation methods in order to advance the scientific rigour, reproducibility and analysis of the data.
methodsForty-six experts participated in a modified Delphi process to reach consensus on indicators of data curation that could be used in the design and reporting of studies.
resultsWe identified 46 indicators that are applicable to the design, training/testing, run time and post-collection phases of studies.
conclusionThe Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD) Guidelines are the first comprehensive set of data quality indicators for large observational studies. They were developed around the needs of neuroscience projects, but we believe they are relevant and generalisable, in whole or in part, to other fields of health research, and also to smaller observational studies and preclinical research. The DAQCORD Guidelines provide a framework for achieving high-quality data; a cornerstone of health research.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.