Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision

dc.contributor.authorJones, Christopher W.
dc.contributor.authorAn, Xinming
dc.contributor.authorJi, Yinyao
dc.contributor.authorLiu, Mochuan
dc.contributor.authorZeng, Donglin
dc.contributor.authorHouse, Stacey L.
dc.contributor.authorBeaudoin, Francesca L.
dc.contributor.authorStevens, Jennifer S.
dc.contributor.authorNeylan, Thomas C.
dc.contributor.authorClifford, Gari D.
dc.contributor.authorJovanovic, Tanja
dc.contributor.authorLinnstaedt, Sarah D.
dc.contributor.authorGermine, Laura T.
dc.contributor.authorBollen, Kenneth A.
dc.contributor.authorRauch, Scott L.
dc.contributor.authorHaran, John P.
dc.contributor.authorStorrow, Alan B.
dc.contributor.authorLewandowski, Christopher
dc.contributor.authorMusey, Paul I., Jr.
dc.contributor.authorHendry, Phyllis L.
dc.contributor.authorSheikh, Sophia
dc.contributor.authorPunches, Brittany E.
dc.contributor.authorLyons, Michael S.
dc.contributor.authorKurz, Michael C.
dc.contributor.authorSwor, Robert A.
dc.contributor.authorMcGrath, Meghan E.
dc.contributor.authorHudak, Lauren A.
dc.contributor.authorPascual, Jose L.
dc.contributor.authorSeamon, Mark J.
dc.contributor.authorDatner, Elizabeth M.
dc.contributor.authorHarris, Erica
dc.contributor.authorChang, Anna M.
dc.contributor.authorPearson, Claire
dc.contributor.authorPeak, David A.
dc.contributor.authorMerchant, Roland C.
dc.contributor.authorDomeier, Robert M.
dc.contributor.authorRathlev, Niels K.
dc.contributor.authorO'Neil, Brian J.
dc.contributor.authorSergot, Paulina
dc.contributor.authorSanchez, Leon D.
dc.contributor.authorBruce, Steven E.
dc.contributor.authorMiller, Mark W.
dc.contributor.authorPietrzak, Robert H.
dc.contributor.authorJoormann, Jutta
dc.contributor.authorBarch, Deanna M.
dc.contributor.authorPizzagalli, Diego A.
dc.contributor.authorSheridan, John F.
dc.contributor.authorSmoller, Jordan W.
dc.contributor.authorHarte, Steven E.
dc.contributor.authorElliott, James M.
dc.contributor.authorKoenen, Karestan C.
dc.contributor.authorRessler, Kerry J.
dc.contributor.authorKessler, Ronald C.
dc.contributor.authorMcLean, Samuel A.
dc.contributor.departmentEmergency Medicine, School of Medicine
dc.date.accessioned2024-09-03T10:38:31Z
dc.date.available2024-09-03T10:38:31Z
dc.date.issued2023
dc.description.abstractStudy objective: To derive and initially validate a brief bedside clinical decision support tool that identifies emergency department (ED) patients at high risk of substantial, persistent posttraumatic stress symptoms after a motor vehicle collision. Methods: Derivation (n=1,282, 19 ED sites) and validation (n=282, 11 separate ED sites) data were obtained from adults prospectively enrolled in the Advancing Understanding of RecOvery afteR traumA study who were discharged from the ED after motor vehicle collision-related trauma. The primary outcome was substantial posttraumatic stress symptoms at 3 months (Posttraumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders-5 ≥38). Logistic regression derivation models were evaluated for discriminative ability using the area under the curve and the accuracy of predicted risk probabilities (Brier score). Candidate posttraumatic stress predictors assessed in these models (n=265) spanned a range of sociodemographic, baseline health, peritraumatic, and mechanistic domains. The final model selection was based on performance and ease of administration. Results: Significant 3-month posttraumatic stress symptoms were common in the derivation (27%) and validation (26%) cohort. The area under the curve and Brier score of the final 8-question tool were 0.82 and 0.14 in the derivation cohort and 0.76 and 0.17 in the validation cohort. Conclusion: This simple 8-question tool demonstrates promise to risk-stratify individuals with substantial posttraumatic stress symptoms who are discharged to home after a motor vehicle collision. Both external validation of this instrument, and work to further develop more accurate tools, are needed. Such tools might benefit public health by enabling the conduct of preventive intervention trials and assisting the growing number of EDs that provide services to trauma survivors aimed at promoting psychological recovery.
dc.eprint.versionAuthor's manuscript
dc.identifier.citationJones CW, An X, Ji Y, et al. Derivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision. Ann Emerg Med. 2023;81(3):249-261. doi:10.1016/j.annemergmed.2022.08.011
dc.identifier.urihttps://hdl.handle.net/1805/43070
dc.language.isoen_US
dc.publisherElsevier
dc.relation.isversionof10.1016/j.annemergmed.2022.08.011
dc.relation.journalAnnals of Emergency Medicine
dc.rightsPublisher Policy
dc.sourcePMC
dc.subjectTraffic accidents
dc.subjectHospital emergency service
dc.subjectMotor vehicles
dc.subjectPost-traumatic stress disorders
dc.titleDerivation and Validation of a Brief Emergency Department-Based Prediction Tool for Posttraumatic Stress After Motor Vehicle Collision
dc.typeArticle
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