ArticleJournal of neurotrauma2014
Development of a database for translational spinal cord injury research.
Article in Journal of neurotrauma, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
34 citing papers in PubMed, 55 citations in OpenAlex.
- Scoping review of secondary studies using the Federal Interagency of Traumatic Brain Injury Research datasets.Brain injury · 2026Article
- Human induced pluripotent stem cell-derived neural stem/progenitor cell therapy for spinal cord injury: preclinical advances and translational perspectives.Stem cells translational medicine · 2026Review
- Prospective Harmonization, Common Data Elements, and Sharing Strategies for Multicenter Pre-Clinical Traumatic Brain Injury Research in the Translational Outcomes Project in Neurotrauma Consortium.Journal of neurotrauma · 2025Article
- Review
- Effect-Size Discrepancies in Literature Versus Raw Datasets from Experimental Spinal Cord Injury Studies: A CLIMBER Meta-Analysis.Neurotrauma reports · 2024Article
- TargetingiScience · 2022Article
- Reflections on Data Sharing Practices in Spinal Cord Injury Research.Neuroinformatics · 2022Article
- Harmonization-Information Trade-Offs for Sharing Individual Participant Data in Biomedicine.Harvard data science review · 2022Article
- Excavating FAIR Data: the Case of the Multicenter Animal Spinal Cord Injury Study (MASCIS), Blood Pressure, and Neuro-Recovery.Neuroinformatics · 2022Article
- Promoting FAIR Data Through Community-driven Agile Design: the Open Data Commons for Spinal Cord Injury (odc-sci.org).Neuroinformatics · 2022Review
- Machine intelligence identifies soluble TNFa as a therapeutic target for spinal cord injury.Scientific reports · 2021Article
- Reproducible analysis of disease space via principal components using the novel R package syndRomics.eLife · 2021Article
- Data Dissemination: Shortening the Long Tail of Traumatic Brain Injury Dark Data.Journal of neurotrauma · 2020Review
- Behavioral testing in animal models of spinal cord injury.Experimental neurology · 2020Review
- FAIR SCI Ahead: The Evolution of the Open Data Commons for Pre-Clinical Spinal Cord Injury Research.Journal of neurotrauma · 2020Review
- Exploration of surgical blood pressure management and expected motor recovery in individuals with traumatic spinal cord injury.Spinal cord · 2020Article
- The Influence of Neuron-Extrinsic Factors and Aging on Injury Progression and Axonal Repair in the Central Nervous System.Frontiers in cell and developmental biology · 2020Review
- Article
- A brief period of moderate noxious stimulation induces hemorrhage and impairs locomotor recovery after spinal cord injury.Physiology & behavior · 2019Article
- Preface - Practical and theoretical considerations for performing a multi-center preclinical biomarker discovery study of post-traumatic epileptogenesis: lessons learned from the EpiBioS4Rx consortium.Epilepsy research · 2019Review
Corrections and comments
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Authors and funding
29 authors at 14 institutions in 2 countries.
Funding
Abstract
Efforts to understand spinal cord injury (SCI) and other complex neurotrauma disorders at the pre-clinical level have shown progress in recent years. However, successful translation of basic research into clinical practice has been slow, partly because of the large, heterogeneous data sets involved. In this sense, translational neurological research represents a "big data" problem. In an effort to expedite translation of pre-clinical knowledge into standards of patient care for SCI, we describe the development of a novel database for translational neurotrauma research known as Visualized Syndromic Information and Outcomes for Neurotrauma-SCI (VISION-SCI). We present demographics, descriptive statistics, and translational syndromic outcomes derived from our ongoing efforts to build a multi-center, multi-species pre-clinical database for SCI models. We leveraged archived surgical records, postoperative care logs, behavioral outcome measures, and histopathology from approximately 3000 mice, rats, and monkeys from pre-clinical SCI studies published between 1993 and 2013. The majority of animals in the database have measures collected for health monitoring, such as weight loss/gain, heart rate, blood pressure, postoperative monitoring of bladder function and drug/fluid administration, behavioral outcome measures of locomotion, and tissue sparing postmortem. Attempts to align these variables with currently accepted common data elements highlighted the need for more translational outcomes to be identified as clinical endpoints for therapeutic testing. Last, we use syndromic analysis to identify conserved biological mechanisms of recovery after cervical SCI between rats and monkeys that will allow for more-efficient testing of therapeutics that will need to be translated toward future clinical trials.
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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.