These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Predictors of decompressive hemicraniectomy in malignant middle cerebral artery stroke. Author: Kamran S, Salam A, Akhtar N, D'soza A, Shuaib A. Journal: Neurosurg Rev; 2019 Mar; 42(1):175-181. PubMed ID: 29651563. Abstract: Identification of factors in malignant middle cerebral artery (MMCA) stroke patients that may be useful in selecting patients for DHC. This study was a retrospective multicenter study of patients referred for DHC based on the criteria of the randomized control trials of DHC in MMCA stroke. Demographic, clinical, and radiology data were analyzed. Patients who underwent DHC were compared to those who survived without surgery. Two hundred three patients with MMCA strokes were identified: 137 underwent DHC, 47 survived without DHC, and 19 refused surgery and died. Multivariate analysis identified the following factors determining DHC in MMCA stroke: age < 55 years (OR 8.5, 95% CI 3.3-22.1, P < 0.001), MCA with involvement of additional vascular territories (anterior cerebral artery, posterior cerebral artery (OR 4.8, 95% CI 1.5-14.9, P = 0.007), septum pellucidum displacement ≥ 7.5 mm (OR 4.8, 95% CI 1.9-11.7, P = 0.001), diabetes (OR 3.7, 95% CI 1.3-10.6, P = 0.012), infarct growth rate (IGR) ml/h (OR 1.11, 95% CI 1.02-1.2, P = 0.015), and temporal lobe involvement (OR 2.5, 95% CI 1.01-6.1, P = 0.048). The internal validation of the multivariate logistic regression model using bootstrapping analysis showed marginal bias. Among patients with MMCA infarctions, an increased possibility of DHC is associated with younger age, MCA with additional infarction, septum pellucidum deviation of > 7.5 mm, diabetes, IGR, and temporal lobe involvement. The presence of these risk factors identifies those MMCA stroke patients who may require DHC. Bootstrapping analysis indicated the model is good enough to predict the outcome in general population.[Abstract] [Full Text] [Related] [New Search]