Prediction of outcome utilizing both physiological and biochemical parameters in severe head injury

Journal of Neurotrauma

Volumn 26, Issue 8, 2009, Pages 1177-1182

  Low, David ^a   Kuralmani, Vellaisamy ^b   Ng, See Kiong ^b   Lee, Kah Keow ^a   Ng, Ivan ^a   Ang, Beng Ti ^a  

^a NATIONAL NEUROSCIENCE INSTITUTE   (Singapore)

^b INSTITUTE FOR INFOCOMM RESEARCH   (Singapore)

Author keywords

Decision tree; Head injury prediction; Logistic regression; Severe traumatic brain injury

Indexed keywords

ACCURACY; ARTICLE; BRAIN OXYGEN TENSION; CLINICAL ARTICLE; CONTROLLED STUDY; DECISION TREE; GLASGOW OUTCOME SCALE; HEAD INJURY; HUMAN; INJURY SEVERITY; INTERMETHOD COMPARISON; INTRACRANIAL PRESSURE; LOGISTIC REGRESSION ANALYSIS; MEAN ARTERIAL PRESSURE; MICRODIALYSIS; OUTCOME ASSESSMENT; PERFUSION PRESSURE; PREDICTION; RELIABILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; BLOOD PRESSURE; BRAIN INJURIES; CRANIOCEREBRAL TRAUMA; FEMALE; MALE; PHYSIOLOGY; PREDICTIVE VALUE; PROGNOSIS; PROSPECTIVE STUDY;

BLOOD PRESSURE; BRAIN INJURIES; CRANIOCEREBRAL TRAUMA; DECISION TREES; FEMALE; GLASGOW OUTCOME SCALE; HUMANS; INTRACRANIAL PRESSURE; LOGISTIC MODELS; MALE; MICRODIALYSIS; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; PROGNOSIS; PROSPECTIVE STUDIES;

EID: 68349120144     PISSN: 08977151     EISSN: None     Source Type: Journal    
DOI: 10.1089/neu.2008.0841     Document Type: Article

References (17)

1. Andrews, J.D., Sleeman, D.H., Statham, P.F., McQuatt, A., Corruble, V., Jones, P.A., Howells, T.P., and Macmillan, C.S. (2002). Predicting recovery in patients suffering from traumatic brain injury by using admission variables and physiological data: a comparison between decision tree analysis and logistic regression. J. Neurosurgery 97, 326-336. (Pubitemid 34827332)
2. Brain Trauma Foundation. (2007). Guidelines for the management of severe traumatic brain injury, 3rd edition. J. Neurotrauma 24, Supple. 1.
3. Choi, S.C., Barnes, T.Y., Bullock, M.S., Germanson, T.A., Maarmarou, A., and Young, H.F. (1994). Temporal profile of outcome in severe head injury. J. Neurosurgery 81, 169-173. (Pubitemid 24237992)
4. Choi, S.C., Muiselaar, J.P., Barnes, T.Y., Marmarou, A., Brooks, D.M., and Young, H.F. (1991). Prediction tree for severely head-injured patients. J. Neurosurgery 75, 251-255.
5. Choi, S.C., and Barnes, T.Y. (1996). Predicting outcome in the head-injured patient. in: Neurotrauma. R.K. Narayan, J.E. Wilberger, and J.T. Povlishock (eds), McGraw-Hill: NY, pps. 779-792.
6. Czosnyka, M., Smielewski, P., Kirkpatrick, P., Laing, R.J., Menon, D., and Pickard, J.D. (1997). Continuous assessment of the cerebral vasomotor reactivity in head injury. Neurosurgery 41,11-19. (Pubitemid 27282076)
7. Hukkelhoven, C.W., Steyerberg, E.W., Habbema, J.D., Farace, E., Marmarou, A., Murray, G.D., Marshall, L.F., and Maas, A. (2005). Predicting outcome after traumatic brain injury: development and validation of a prognostic score based on admission characteristics. J. Neurotrauma 22, 1025-1039. (Pubitemid 41532542)
8. Hutchinson, P.J., O'Connell, M.T., Al-Rawi, P.G., Maskell, L.B., KettWhite, R., Gupta, A.K., Richards, H.K., Hutchinson, D.B., Kirkpatrick, P.J., and Pickard, J.D. (2000). Clinical cerebral microdialysis: a methodological study. J. Neurosurg. 93, 37-43. (Pubitemid 30457321)
9. Johnston, A.J., and Gupta, A.K. (2002). Advanced monitoring in the neurology intensive care unit. Microdialysis. Curr. Opin. Crit. Care 81, 121-127.
10. Lang, E.W., Lagopoulus, J., Griffith, J., Yip, K., Yam, A., Mudaliar, Y., Mehdorn, H.M., and Dorsch, N.W. (2003). Cerebral vasomotor reactivity testing in head injury: the link between pressure and flow. J. Neurol. Neurosurg. Psychiatry 74, 1053-1059.
11. Le Roux, P.D., Newell, D.W., Lam, A.M., Grady, M.S., and Winn, H.R. (1997). Cerebral arteriovenous oxygen difference: a predictor of cerebral infarction and outcome in patients with severe head injury. J. Neurosurgery 87, 1-8. (Pubitemid 27271020)
12. Mulvey, J.M., Dorsch, N.W., Mudaliar, Y., and Lang, E.W. (2004). Multimodality monitoring in severe traumatic brain injury: the role of brain tissue oxygenation monitoring. Neurocritical Care 1, 391-402. (Pubitemid 41278358)
13. Pang, B.C., Vellaisamy, K., Joshi, R., Yin, H.L., Lee, K.K., Ang, B.T., Li, J.Y., Leong, T.Y., and Ng, I. (2007). Hybrid outcome prediction model for severe traumatic brain injury. J. Neurotrauma 24, 136-146. (Pubitemid 46214419)
14. Quinlan, R. (1993). C4.5 Programs for Machine Learning. Morgan Kaufmann Publishers: San Mateo, CA.
15. 2 to outcome after severe head injury. Crit. Care Med. 26, 1576-1581.
16. Van Santbrink, H., Maas, A.I., and Avezaat, C.J. (1996). Continuous monitoring of partial pressure of brain tissue oxygen in patients with severe head injury. Neurosurgery 38, 21-31. (Pubitemid 26002379)
17. Wang, E.C., Ang, B.T., Wong, J., Lim, J., and Ng, I. (2006). Characterization of cerebrovascular reactivity after craniectomy for acute brain injury. Br. J. Neurosurg. 20, 24-30.