Oral Rehabilitation of Severe Dentoalveolar Trauma: A Clinical Report

2012 ◽  
Vol 38 (6) ◽  
pp. 757-761 ◽  
Author(s):  
Fonda G. Robinson ◽  
Larry L. Cunningham

This clinical report describes the oral rehabilitation of an adult male who suffered severe dentoalveolar trauma as a result of a motor vehicle accident. The specific objectives of this treatment were to restore esthetics and masticatory function. Treatment included removal of fractured roots, placement of multiple endosseous implants, and placement of anterior and posterior metal-ceramic crowns and fixed partial dentures. Three year clinical examination revealed no pathology associated with the rehabilitation. The patient's esthetic and functional expectations were successfully achieved.

Author(s):  
Alireza Pournabi ◽  
Hamidreza Moslemi ◽  
Shervin Shafiei ◽  
Ramtin Dastgir ◽  
Kamyar Abbasi ◽  
...  

Here we report the management and further oral rehabilitation of a case suffering severe midface trauma following a motor vehicle accident where the patient was hit by a lorry


2003 ◽  
Author(s):  
David Walshe ◽  
Elizabeth Lewis ◽  
Kathleen O'Sullivan ◽  
Brenda K. Wiederhold ◽  
Sun I. Kim

1996 ◽  
Vol 35 (04/05) ◽  
pp. 309-316 ◽  
Author(s):  
M. R. Lehto ◽  
G. S. Sorock

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.


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.


Author(s):  
Tal Margaliot Kalifa ◽  
Misgav Rottenstreich ◽  
Eyal Mazaki ◽  
Hen Y. Sela ◽  
Schwartz Alon ◽  
...  

2021 ◽  
Author(s):  
Gaia S. Pocobelli ◽  
Mary A. Akosile ◽  
Ryan N. Hansen ◽  
Joanna Eavey ◽  
Robert D. Wellman ◽  
...  

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