title: Structured interview for mild traumatic brain injury after military blast: inter-rater agreement and development of diagnostic algorithm.
abstract: The existing gold standard for diagnosing a suspected previous mild traumatic brain injury (mTBI) is clinical interview. But it is prone to bias, especially for parsing the physical versus psychological effects of traumatic combat events, and its inter-rater reliability is unknown. Several standardized TBI interview instruments have been developed for research use but have similar limitations. Therefore, we developed the Virginia Commonwealth University (VCU) retrospective concussion diagnostic interview, blast version (VCU rCDI-B), and undertook this cross-sectional study aiming to 1) measure agreement among clinicians' mTBI diagnosis ratings, 2) using clinician consensus develop a fully structured diagnostic algorithm, and 3) assess accuracy of this algorithm in a separate sample. Two samples (n = 66; n = 37) of individuals within 2 years of experiencing blast effects during military deployment underwent semistructured interview regarding their worst blast experience. Five highly trained TBI physicians independently reviewed and interpreted the interview content and gave blinded ratings of whether or not the experience was probably an mTBI. Paired inter-rater reliability was extremely variable, with kappa ranging from 0.194 to 0.825. In sample 1, the physician consensus prevalence of probable mTBI was 84%. Using these diagnosis ratings, an algorithm was developed and refined from the fully structured portion of the VCU rCDI-B. The final algorithm considered certain symptom patterns more specific for mTBI than others. For example, an isolated symptom of "saw stars" was deemed sufficient to indicate mTBI, whereas an isolated symptom of "dazed" was not. The accuracy of this algorithm, when applied against the actual physician consensus in sample 2, was almost perfect (correctly classified = 97%; Cohen's kappa = 0.91). In conclusion, we found that highly trained clinicians often disagree on historical blast-related mTBI determinations. A fully structured interview algorithm was developed from their consensus diagnosis that may serve to enhance diagnostic standardization for clinical research in this population.
authors.affiliation: 1 Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University , Richmond, Virginia.
authors.forename: William C
authors.initials: WC
authors.lastname: Walker
authors.forename: David X
authors.initials: DX
authors.lastname: Cifu
authors.forename: Anne M
authors.initials: AM
authors.lastname: Hudak
authors.forename: Gary
authors.initials: G
authors.lastname: Goldberg
authors.forename: Richard D
authors.initials: RD
authors.lastname: Kunz
authors.forename: Adam P
authors.initials: AP
authors.lastname: Sima
mesh_terms: D000328:Adult; D000465:Algorithms; D001753:Blast Injuries / Q000150:complications*; D001930:Brain Injuries / Q000175:diagnosis* / Q000209:etiology; D003430:Cross-Sectional Studies; D005260:Female; D006801:Humans; D008297:Male; D008889:Military Personnel; D009483:Neuropsychological Tests; D015203:Reproducibility of Results; D012189:Retrospective Studies; D055815:Young Adult
keywords: adult brain injury; assessment tools; concussion; epidemiology; military injury; traumatic brain injury