Over-Complete Discrete Wavelet Transformation of the Normal Auditory Brainstem Response Improves Prediction of Outcome following Severe Acute Closed Head Injury
| Autor: | Kate M. Phillips, Andrew P. Bradley, Wayne J. Wilson, Ross Darnell, Kylie T. Snell, Jane A. Chapple |
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| Rok vydání: | 2006 |
| Předmět: |
Adult
Male medicine.medical_specialty Auditory Pathways Multivariate analysis Adolescent Physiology Audiology Logistic regression Speech and Hearing Discriminant function analysis Predictive Value of Tests Head Injuries Closed Evoked Potentials Auditory Brain Stem Reaction Time otorhinolaryngologic diseases medicine Humans Glasgow Coma Scale Head injury Middle Aged medicine.disease Sensory Systems Logistic Models Auditory brainstem response Acoustic Stimulation Otorhinolaryngology Anesthesia Predictive value of tests Acute Disease Multivariate Analysis Closed head injury Female sense organs Psychology |
| Zdroj: | Audiology and Neurotology. 11:249-258 |
| ISSN: | 1421-9700 1420-3030 |
| Popis: | Previous research has shown that complex statistical analysis (discriminant function analysis) of a ‘normal’ auditory brainstem response (ABR) result can improve this measure’s ability to predict subject outcome following severe acute closed head injury (ACHI). We hypothesized that adding the ABR’s time-frequency information to such an analysis would improve this predictive value even further. ‘Normal’ ABR results were sampled from 69 severe ACHI subjects (22 of whom died and 47 of whom lived) and their time-frequency information extracted using an over-complete discrete wavelet transformation (OCDWT). A series of logistic regression analyses then showed correct predictions of death and survival as follows: ABR measures only 72 and 89% (respectively), ABR OCDWT measures only 82 and 89% (respectively), and ABR and ABR OCDWT measures combined 86 and 93% (respectively). These results showed that the addition of time-frequency information can improve the ability of the ‘normal’ ABR result to predict outcome following severe ACHI. |
| Databáze: | OpenAIRE |
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