Motor vehicle accident with complete loss of consciousness due to vasovagal syncope

Forty-two patients with persistent posttraumatic headache and postconcussion symptomatology following a motor vehicle accident completed the Self-Rating Scale of Memory Functions (SRSM), the Beck Depression Inventory (BDI), and brief memory testing. SRSM scores indicated that patients rated their memory as significantly impaired relative to their preinjury status. SRSM scores were not affected by such factors as age, education, gender, and loss of consciousness. However, significantly depressed patients rated their memory as more impaired on 14 of 18 SRSM items when compared with nondepressed patients. After controlling for depression, SRSM scores correlated significantly with objective performance on several memory tests. The implications of these findings are discussed.

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Open label trial of escitalopram in motor vehicle accident survivors with posttraumatic stress disorder

PsycEXTRA Dataset ◽

10.1037/e516222012-037 ◽

2010 ◽

Author(s):

R. Coronas ◽

M.G. del Alamo ◽

H.G. Arnau ◽

E.I. Soto ◽

D. Suarez

Keyword(s):

Posttraumatic Stress Disorder ◽

Posttraumatic Stress ◽

Stress Disorder ◽

Motor Vehicle ◽

Motor Vehicle Accident ◽

Open Label ◽

Vehicle Accident ◽

Open Label Trial

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Virtual reality and computer games in the treatment of driving phobia induced by a motor vehicle accident

PsycEXTRA Dataset ◽

10.1037/e705482011-064 ◽

2003 ◽

Author(s):

David Walshe ◽

Elizabeth Lewis ◽

Kathleen O'Sullivan ◽

Brenda K. Wiederhold ◽

Sun I. Kim

Keyword(s):

Virtual Reality ◽

Computer Games ◽

Motor Vehicle ◽

Motor Vehicle Accident ◽

Vehicle Accident

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Expectations of lawyers with regard to neuropsychological evaluations in motor vehicle accident claims.

Professional Psychology Research and Practice ◽

10.1037/pro0000311 ◽

2020 ◽

Vol 51 (6) ◽

pp. 642-648

Author(s):

Henk Johan Swanepoel ◽

Esmé Van Rensburg

Keyword(s):

Motor Vehicle ◽

Motor Vehicle Accident ◽

Vehicle Accident ◽

Neuropsychological Evaluations

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Machine Learning of Motor Vehicle Accident Categories from Narrative Data

Methods of Information in Medicine ◽

10.1055/s-0038-1634680 ◽

1996 ◽

Vol 35 (04/05) ◽

pp. 309-316 ◽

Cited By ~ 4

Author(s):

M. R. Lehto ◽

G. S. Sorock

Keyword(s):

Machine Learning ◽

Bayesian Model ◽

Keyword Search ◽

Motor Vehicle ◽

Motor Vehicle Accident ◽

Computer Search ◽

Vehicle Accident ◽

Learning Technique ◽

Expert Ratings ◽

Keyword Searches

Abstract:Bayesian inferencing as a machine learning technique was evaluated for identifying pre-crash activity and crash type from accident narratives describing 3,686 motor vehicle crashes. It was hypothesized that a Bayesian model could learn from a computer search for 63 keywords related to accident categories. Learning was described in terms of the ability to accurately classify previously unclassifiable narratives not containing the original keywords. When narratives contained keywords, the results obtained using both the Bayesian model and keyword search corresponded closely to expert ratings (P(detection)≥0.9, and P(false positive)≤0.05). For narratives not containing keywords, when the threshold used by the Bayesian model was varied between p>0.5 and p>0.9, the overall probability of detecting a category assigned by the expert varied between 67% and 12%. False positives correspondingly varied between 32% and 3%. These latter results demonstrated that the Bayesian system learned from the results of the keyword searches.

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Aspirated teeth - rigid or flexible bronchoscopy

Journal of Clinical Case reports and reviews ◽

10.36879/jccrr.19.000132 ◽

2019 ◽

pp. 1-2

Keyword(s):

Clinical Practice ◽

Foreign Bodies ◽

Motor Vehicle ◽

Motor Vehicle Accident ◽

Flexible Bronchoscopy ◽

Vehicle Accident

Tracheobronchial foreign bodies are a common problem in clinical practice. We present the case of a patient with three aspirated teeth following a motor vehicle accident.

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