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A severity-based classification framework for dry needling unintended responses and adverse events: An expert
Gary A Kearns1, Austin Sheldon2, Tiffany Barrett3
1Texas Tech University Health Sciences Center, Department of Rehabilitation Sciences, School of Health Professions, Lubbock, TX, USA.
Musculoskeletal Science & Practice
|July 14, 2026
Summary
Experts established a framework for classifying unintended responses (UR) and adverse events (AE) after dry needling (DN). This consensus-based approach prioritizes severity and functional impact for better clinical reporting and communication.
Area of Science:
- Clinical Practice Guidelines
- Rehabilitation Medicine
- Patient Safety
Background:
- Dry needling (DN) is a therapeutic intervention with potential for unintended responses (UR) and adverse events (AE).
- A standardized framework for defining and classifying these events is lacking, hindering consistent reporting and clinical communication.
Purpose of the Study:
- To develop an expert-derived, consensus-based framework for defining and classifying unintended responses (UR) and adverse events (AE) following dry needling (DN).
- To establish clear criteria for distinguishing between UR and AE based on expert consensus.
Main Methods:
- A modified 3-round electronic Delphi process was employed with 65 DN experts from nine countries.
- Eligibility criteria included extensive DN practice, clinical experience, and teaching/scholarship.
- Consensus was defined as ≥80% agreement, median ≥3, and interquartile range ≤1.
Main Results:
- A consensus framework was developed, categorizing URs (e.g., bleeding, neurologic, autonomic responses) and classifying AEs by severity.
- Severity and functional impact were prioritized over response type for distinguishing UR from AE.
- Four operational AE categories were defined, ranging from Minor Expected to Severe; pain and discomfort did not reach consensus as an UR category.
Conclusions:
- An expert-derived framework for classifying DN AEs along a severity spectrum was established, pending validation.
- The framework emphasizes severity and functional impact, potentially improving clinical documentation, patient communication, and research reporting consistency.
