Format

Send to

Choose Destination
Arch Surg. 2002 Mar;137(3):285-90.

Determinants of mortality in patients with severe blunt head injury.

Author information

1
Department of Surgery, Baylor College of Medicine, Houston, TX, USA. schreibm@ohsu.edu

Abstract

CONTEXT:

Head injury is the leading cause of traumatic death in the United States.

HYPOTHESIS:

A set of clinical parameters available soon after injury can be used to accurately predict outcome in patients with severe blunt head trauma.

DESIGN:

Validation cohort study.

SETTING:

Urban level I trauma center.

PATIENTS AND METHODS:

Data from patients with severe blunt head injury, as defined by inability to follow commands, were prospectively entered into a neurosurgical database and analyzed. The impact on survival of 23 potentially predictive parameters was studied using univariate analysis. Logistic regression models were used to control for confounding factors and to assess interactions between variables, whose significance was determined by univariate analysis. Goodness of fit was calculated with the Hosmer-Lemeshow c statistic. The predictability of the logistic model was evaluated by measuring the area under the receiver operating characteristic curve (AUC).

RESULTS:

Logistic regression analysis revealed that 5 risk factors were independently associated with death. These variables included systemic hypotension in the emergency department, midline shift on computed tomographic scan, intracranial hypertension, and absence of pupillary light reflex. A low Glasgow Coma Scale score and advanced age were found to be highly correlated risk factors that, when combined, were independently associated with mortality. The model showed acceptable goodness of fit, and the AUC was 80.5%.

CONCLUSIONS:

Systemic hypotension and intracranial hypertension are the only independent risk factors for mortality that can be readily treated during the initial management of patients with severe head injuries. When used together, Glasgow Coma Scale score and age are significant predictors of mortality.

PMID:
11888450
DOI:
10.1001/archsurg.137.3.285
[Indexed for MEDLINE]

Supplemental Content

Full text links

Icon for Silverchair Information Systems
Loading ...
Support Center