Nalini Sehgal1, Debra B Gordon2, Scott Hetzel3, Miroslav Misha Backonja2,4. 1. Department of Orthopedics and Rehabilitation Medicine, University of Wisconsin, Madison, Wisconsin, USA. 2. Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington, USA. 3. Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin, USA. 4. Department of Neurology, University of Washington, Seattle, Washington, USA.
Abstract
OBJECTIVES: This is a prospective, blinded, case-control study of patients with chronic pain using body diagrams and colored markers to show the distribution and quality of pain and sensory symptoms (aching, burning, tingling, numbness, and sensitivity to touch) experienced in affected body parts. METHODS: Two pain physicians, blinded to patients' clinical diagnoses, independently reviewed and classified each colored pain drawing (CPD) for presence of neuropathic pain (NeuP) vs. non-neuropathic pain (NoP). A clinical diagnosis (gold standard) of NeuP was made in 151 of 213 (70.9%) enrolled patients. RESULTS: CPD assessment at "first glance" by both examiners resulted in correctly categorizing 137 (64.3% by examiner 1) and 156 (73.2% by examiner 2) CPDs. Next, classification of CPDs by both physicians, using predefined criteria of spatial distribution and quality of pain-sensory symptoms, improved concordance to 212 of 213 CPDs (Kappa = 0.99). The diagnostic ability to correctly identify NeuP and NoP by both examiners increased to 171 (80.2%) CPDs, with 80.1% sensitivity and 80.6% specificity (Kappa = 0.56 [95% confidence interval: 0.44-0.68]). The severity scores for pain and sensory symptoms (burning, tingling, numbness, and sensitivity to touch) on the Neuropathic Pain Questionnaire were significantly elevated in NeuP vs. NoP (P < 0.001). CONCLUSIONS: This study demonstrates good performance characteristics of CPDs in identifying patients with NeuP through the use of a simple and easy-to-apply classification scheme. We suggest use of CPDs as a bedside screening tool and as a method for phenotypic profiling of patients by the quality and distribution of pain and sensory symptoms.
OBJECTIVES: This is a prospective, blinded, case-control study of patients with chronic pain using body diagrams and colored markers to show the distribution and quality of pain and sensory symptoms (aching, burning, tingling, numbness, and sensitivity to touch) experienced in affected body parts. METHODS: Two pain physicians, blinded to patients' clinical diagnoses, independently reviewed and classified each colored pain drawing (CPD) for presence of neuropathic pain (NeuP) vs. non-neuropathic pain (NoP). A clinical diagnosis (gold standard) of NeuP was made in 151 of 213 (70.9%) enrolled patients. RESULTS: CPD assessment at "first glance" by both examiners resulted in correctly categorizing 137 (64.3% by examiner 1) and 156 (73.2% by examiner 2) CPDs. Next, classification of CPDs by both physicians, using predefined criteria of spatial distribution and quality of pain-sensory symptoms, improved concordance to 212 of 213 CPDs (Kappa = 0.99). The diagnostic ability to correctly identify NeuP and NoP by both examiners increased to 171 (80.2%) CPDs, with 80.1% sensitivity and 80.6% specificity (Kappa = 0.56 [95% confidence interval: 0.44-0.68]). The severity scores for pain and sensory symptoms (burning, tingling, numbness, and sensitivity to touch) on the Neuropathic Pain Questionnaire were significantly elevated in NeuP vs. NoP (P < 0.001). CONCLUSIONS: This study demonstrates good performance characteristics of CPDs in identifying patients with NeuP through the use of a simple and easy-to-apply classification scheme. We suggest use of CPDs as a bedside screening tool and as a method for phenotypic profiling of patients by the quality and distribution of pain and sensory symptoms.
Authors: T G Mayer; R J Gatchel; N Kishino; J Keeley; P Capra; H Mayer; J Barnett; V Mooney Journal: Spine (Phila Pa 1976) Date: 1985 Jul-Aug Impact factor: 3.468
Authors: Benedict J Alter; Nathan P Anderson; Andrea G Gillman; Qing Yin; Jong-Hyeon Jeong; Ajay D Wasan Journal: PLoS One Date: 2021-08-04 Impact factor: 3.240