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Sensitivity and Specificity of the Coma Recovery Scale-Revised Total Score in Detection of Conscious Awareness
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Sep 03 2015
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Source: Arch Phys Med Rehabil. 97(3):490-492.e1.
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Details:
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Alternative Title:Arch Phys Med Rehabil
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Personal Author:
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Description:Objective
The aim of this report is to describe the sensitivity and specificity of Coma Recovery Scale-Revised (CRS-R) total scores in detecting conscious awareness.
Design
Data were retrospectively extracted from the medical records of patients enrolled in a specialized Disorders of Consciousness (DoC) program. Sensitivity and specificity analyses were completed using CRS-R-derived diagnoses of Minimally Conscious State (MCS) or Emerged from Minimal Conscious State (EMCS) as the reference standard for conscious awareness and the total CRS-R score as the “test criterion”. A receiver operating curve (ROC) was constructed to demonstrate the optimal CRS-R total cut-off score for maximizing sensitivity and specificity.
Setting
Specialized DoC program
Participants
252 patients enrolled in the DoC program (157 male; mean age = 49 years; mean time from injury =48 days; traumatic etiology=127, non-traumatic etiology=125; diagnosis of coma or VS=72, diagnosis of MCS or EMCS=182)
Interventions
Not applicable.
Main Outcome Measure(s)
Sensitivity and specificity of CRS-R total scores in detecting conscious awareness
Results
A CRS-R total score of 10 or higher yielded a sensitivity of 0.78 for correct identification of patients in MCS or EMCS, and specificity of 1.00 for correct identification of patients who did not meet criteria for either of these diagnoses (i.e., were diagnosed with VS or coma). The area under the curve (AUC) in the ROC analysis is 0.98.
Conclusion(s)
A total CRS-R score of 10 or higher provides strong evidence of conscious awareness but resulted in a false negative diagnostic error in 22% of patients who demonstrated conscious awareness based on CRS-R diagnostic criteria . A cut-off score of 8 provides the best balance between sensitivity and specificity, accurately classifying 93% of cases. The “optimal” total score cut-off will vary depending on the user's objective.
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Pubmed ID:26342571
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Pubmed Central ID:PMC5018674
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