In a field where every second counts, researchers are speaking a unified language to accelerate the fight against stroke.
Imagine a library where every book is written in a different language, with no common cataloging system. Researchers trying to compare findings from different stroke studies faced a similar challenge—each clinical trial, each registry, and each hospital might collect patient information in slightly different ways. This lack of standardization meant that combining data across studies was extraordinarily difficult, potentially slowing the pace of discovery in a condition where every 40 seconds, someone in the United States experiences a stroke8 .
Incompatible datasets made combining research findings across studies nearly impossible, slowing progress in stroke treatment and prevention.
In 2006, NINDS launched the Common Data Element Project to develop data standards for neuroscience research4 .
The stroke-specific CDE initiative, launched in 2009, brought together leading international experts to create a standardized framework for collecting and reporting stroke research data.
At its core, a Common Data Element is a standardized way of defining and collecting a specific piece of information. Think of it as agreeing on a common measurement system—where once different studies might have measured blood pressure using different protocols or categories, a CDE establishes one precise method that all researchers can adopt.
Primary Goals
The NINDS CDE Project was created with four primary goals6 :
Stroke represents one of the most significant neurological burdens worldwide—it's the second most common cause of death globally and the most important cause of permanent disability in adults7 . In the United States alone, nearly 800,000 Americans experience a stroke each year, with 140,000 deaths annually, making it the leading cause of serious, long-term disability8 .
Americans experience stroke each year
Deaths from stroke annually in the US
Cause of serious long-term disability
Despite clear treatment guidelines and procedures for stroke patients, documentation practices varied widely between institutions and research studies. This lack of standardization created significant challenges for comparing results, pooling data for more powerful analyses, and understanding how findings applied across different patient populations.
The NINDS recognized that standardizing how stroke data is collected could decrease study start-up time, facilitate data sharing, and promote well-informed clinical practice guidelines2 . By creating this common research language, the Institute aimed to accelerate the pace of discovery in cerebrovascular disease research.
Creating a standardized vocabulary for stroke research was no small feat. It required the collaboration of 52 experts with diverse experience in NIH-funded cerebrovascular disease research. The working group represented a broad spectrum of specialties—adult and pediatric stroke, acute care and prevention, multiple medical specialties, and various care settings from prehospital to rehabilitation.
Experts identified nine critical content areas covering the full spectrum of stroke research and care
Subcommittees reviewed existing data elements from national registries and funded trials, refining and adding as needed
Through iterative discussions, the groups worked to consensus without formal Delphi methods
A draft was posted for public comment, with specific input solicited from 18 stroke organizations worldwide
The first published version of the Stroke CDEs contained 980 data elements organized into nine comprehensive content areas. To help researchers navigate this extensive collection, elements were classified into three tiers based on their readiness for widespread use and applicability across studies:
Commonly used in stroke research and recommended for consideration by many studies
More specialized elements appropriate for particular populations or study types
Promising but requiring additional validation before widespread use
| Domain | Description | Examples |
|---|---|---|
| Stroke Presentation | Initial symptoms and clinical features | Time of symptom onset, neurological deficits |
| Medical History and Prior Health Status | Pre-existing conditions and baseline health | Hypertension, diabetes, previous strokes |
| Stroke Types and Subtypes | Classification of stroke | Ischemic, hemorrhagic, etiology |
| Hospital Course and Acute Therapies | In-hospital treatments and progression | Thrombolysis, thrombectomy, complications |
| Imaging | Radiological assessments | CT, MRI, angiography findings |
| Laboratory Tests and Vital Signs | Physiological and biochemical measures | Blood tests, blood pressure, temperature |
| Long-Term Therapies | Ongoing prevention and management | Anticoagulation, rehabilitation therapies |
| Outcomes and Endpoints | Functional and clinical results | Disability scales, cognitive tests, quality of life |
| Biospecimens and Biomarkers | Biological samples and molecular indicators | Blood samples, genetic markers, prognostic tests |
| Tier | Description | Number of Elements | Percentage of Total |
|---|---|---|---|
| Core | Commonly used across many stroke studies | 163 | 16.6% |
| Supplemental | Specialized for specific populations or studies | 808 | 82.4% |
| Exploratory | Promising but requiring further validation | 9 | 1% |
organized across 9 content domains
The implementation of Stroke CDEs has brought tangible benefits to the research community, creating a more efficient and collaborative ecosystem for stroke science.
By providing ready-to-use data elements and case report forms, the CDE project eliminates the need for researchers to "reinvent the wheel" each time they design a new study4 . One of the explicit goals was to reduce the time and cost needed to develop data collection tools6 , allowing researchers to focus more resources on the scientific questions themselves rather than administrative setup.
With standardized data elements, combining information across multiple studies for meta-analyses becomes significantly easier. The CDE Project anticipated that less effort would be required to transform data into a common format for aggregation4 , potentially unlocking new insights from existing datasets that were previously incompatible.
Standardized definitions and collection methods improve the consistency and reliability of research data. The project provides uniform data descriptions and tools across NINDS-funded clinical studies6 , reducing variability introduced by differing data collection practices.
When research data is standardized and comparable, it provides a stronger foundation for developing evidence-based clinical guidelines. The Stroke CDE Project specifically aimed to promote well-informed clinical practice guidelines2 by ensuring that the research informing those guidelines follows consistent methodologies.
The NINDS provides a comprehensive set of tools and resources to support researchers in implementing CDEs in their studies. These resources are publicly available through the NINDS CDE website, creating an accessible toolkit for the research community.
| Tool | Description | Purpose | Format |
|---|---|---|---|
| Data Dictionary | Definitions, specifications, and response options for each data element | Ensure consistent understanding and application of each element | Searchable online database |
| Template Case Report Forms (CRFs) | Pre-formatted data collection forms logically organizing CDEs | Accelerate study startup and standardize data collection | Microsoft Word, PDF |
| Guidance Documents | Additional information about CDEs and their application | Support proper implementation and decision-making | Online documents |
| Instrument Notice of Copyright Documents | Information on recommended instruments | Facilitate legal use of copyrighted assessment tools | Online documents |
| Start-Up Resource Listing | All Core and Supplemental-Highly Recommended CDEs | Help researchers quickly identify essential elements | Online checklist |
The first iteration of Stroke CDEs, completed in 2010, was just the beginning. The working groups recognized that these standards would need to evolve with advancing science and technologies. As noted in the original publication, the CDEs are "an evolving resource that will be iteratively improved based on investigator use, new technologies, and emerging concepts and research findings".
This forward-looking perspective has proven accurate. In 2015, just five years after the initial release, a Stroke Oversight Committee reviewed the Core Stroke CDEs and determined needed classification updates based on disease stage and study type5 .
By 2018, a Stroke v2.0 CDE Working Group was convened to perform a comprehensive review and incorporate new areas such as Unruptured Cerebral Aneurysms and Subarachnoid Hemorrhage5 .
The CDE concept has also expanded beyond clinical research into preclinical studies. In January 2025, NINDS launched the Neurotrauma Preclinical Common Data Elements & Data Standards (NT-PRECEDS) Program3 , applying similar standardization principles to animal and basic science research. This creates an exciting opportunity to align data collection across the translational spectrum, from bench to bedside.
The NINDS Stroke Common Data Element Project represents a profound shift in how the scientific community approaches stroke research. By creating a standardized vocabulary for collecting and reporting data, this initiative has removed significant barriers to collaboration, data sharing, and comparison of results across studies.
Data Elements
Content Domains
Collaborating Experts
What began as an effort to bring order to the chaos of incompatible datasets has grown into a comprehensive framework that supports the entire stroke research ecosystem. The 980 data elements spanning nine content domains provide researchers with both the structure and flexibility needed to advance our understanding of cerebrovascular disease while ensuring that individual studies contribute to a larger, collective knowledge base.
As stroke continues to affect millions worldwide—with an aging population likely increasing its impact in coming years—the importance of efficient, collaborative research becomes ever more critical. The Stroke CDE Project exemplifies how strategic coordination and standardization can accelerate progress against neurological disorders, moving us closer to a world with better treatments, improved outcomes, and ultimately fewer lives affected by stroke.
To explore the NINDS Stroke Common Data Elements and access implementation resources, visit: www.commondataelements.ninds.nih.gov/Stroke.aspx