OBJECTIVE: To establish a model based on clinical and anamnestic data easily available in the out-of-hospital setting, which facilitates the differential diagnosis between cerebral infarction and intracranial hemorrhage. DESIGN: Retrospective study that simulates a prospective approach. SETTING: Emergency Department of the University Hospital in Vienna, Austria. PATIENTS AND PARTICIPANTS: Data of 224 patients with either intracranial hemorrhage or cerebral infarction were prospectively collected. Uni-and multivariate analysis was performed to identify neurological symptoms and anamnestic data, which were associated with either intracranial hemorrhage or cerebral infarction. MEASUREMENTS AND RESULTS: Unilateral weakness or sensory loss was observed more frequently in patients with infarction compared to hemorrhage (69.8 % vs 11.9 %, P < 0.001). The frequency of patients with impaired level of consciousness was significantly higher in the hemorrhage group compared to the infarction group (59.3 % vs 3.8 %, P < 0.001). A multivariate logistic regression analysis showed that hypertension (OR = 0.31, 95 % CI = 0.12-0.76, P = 0.01), diabetes (OR = 0.17, 95% CI = 0.04-0.68, P = 0.01), and unilateral weakness or sensory loss (OR = 0.10, 95 % CI = 0.04-0.26, P < 0.001) were significantly associated with cerebral infarction. Impaired level of consciousness was significantly related to hemorrhage (OR = 13.41, 95 % CI = 3.92-45.91, P < 0.001). On the basis of the logistic regression analysis, we generated a scoring system for the out-of-hospital diagnosis between infarction and hemorrhage. The values of the score lay between -3 and +3. The probability of infarction increases when the score becomes negative, and the probability for hemorrhage increases when the score becomes positive. CONCLUSION: Our model is a useful guideline for the differential diagnosis between cerebral infarction and intracranial hemorrhage in the out-of-hospital setting, as it is based on easily available clinical and anamnestic parameters.
OBJECTIVE: To establish a model based on clinical and anamnestic data easily available in the out-of-hospital setting, which facilitates the differential diagnosis between cerebral infarction and intracranial hemorrhage. DESIGN: Retrospective study that simulates a prospective approach. SETTING: Emergency Department of the University Hospital in Vienna, Austria. PATIENTS AND PARTICIPANTS: Data of 224 patients with either intracranial hemorrhage or cerebral infarction were prospectively collected. Uni-and multivariate analysis was performed to identify neurological symptoms and anamnestic data, which were associated with either intracranial hemorrhage or cerebral infarction. MEASUREMENTS AND RESULTS:Unilateral weakness or sensory loss was observed more frequently in patients with infarction compared to hemorrhage (69.8 % vs 11.9 %, P < 0.001). The frequency of patients with impaired level of consciousness was significantly higher in the hemorrhage group compared to the infarction group (59.3 % vs 3.8 %, P < 0.001). A multivariate logistic regression analysis showed that hypertension (OR = 0.31, 95 % CI = 0.12-0.76, P = 0.01), diabetes (OR = 0.17, 95% CI = 0.04-0.68, P = 0.01), and unilateral weakness or sensory loss (OR = 0.10, 95 % CI = 0.04-0.26, P < 0.001) were significantly associated with cerebral infarction. Impaired level of consciousness was significantly related to hemorrhage (OR = 13.41, 95 % CI = 3.92-45.91, P < 0.001). On the basis of the logistic regression analysis, we generated a scoring system for the out-of-hospital diagnosis between infarction and hemorrhage. The values of the score lay between -3 and +3. The probability of infarction increases when the score becomes negative, and the probability for hemorrhage increases when the score becomes positive. CONCLUSION: Our model is a useful guideline for the differential diagnosis between cerebral infarction and intracranial hemorrhage in the out-of-hospital setting, as it is based on easily available clinical and anamnestic parameters.
Authors: Mark E Mullins; Michael H Lev; Dawid Schellingerhout; R Gilberto Gonzalez; Pamela W Schaefer Journal: AJNR Am J Neuroradiol Date: 2005-10 Impact factor: 3.825
Authors: Matthias Hohlrieder; Josef Hinterhoelzl; Hanno Ulmer; Christiane Lang; Wolfgang Hackl; Andreas Kampfl; Arnulf Benzer; Erich Schmutzhard; Robert Gassner Journal: Intensive Care Med Date: 2003-05-24 Impact factor: 17.440