Md Moshiur Rahman1*, K M Ziaur Rahman2 and Imrul Kaies3
1Assistant Professor, Neurosurgery Department, Holy Family Red Crescent Medical College, Dhaka, Bangladesh
2Resident, Neurosurgery Department, Holy Family Red Crescent Medical College, Dhaka, Bangladesh
3Medical Officer, Anaesthesia Department, Bangabandhu Sheikh Mujib Medical University (BSMMU), Dhaka
*Corresponding Author: Md Moshiur Rahman, Assistant Professor, Neurosurgery Department, Holy Family Red Crescent Medical College, Dhaka, Bangladesh.
Received: February 18, 2020; Published: February 28, 2020
Background: Haematoma volume is a strong predictor of morbidity and mortality in a spontaneous intracerebral hematoma. Timing of surgery, amount of clot removal, GCS on admission, pupillary abnormality and amount of bone removal of such cases are strong variables. A large amount of blood is causing impending herniation which is life-threatening and should be addressed immediately to reverse the situation.
Objective: The main goal of this study is to assess the predictive analysis in decompressive craniotomy for haemorrhagic stroke.
Method: A total of 72 cases were included in this study. This retrospective study was conducted in three private hospitals from 2009 to 2018. Male: Female was 3:2. Surgical outcome predictors were analyzed by using different variables- the timing of surgery, amount of clot removal, GCS on admission, pupillary abnormality, age of the patients and amount of bone removal.
Results: 8 patients died, 2 patients were in a vegetative state, 1 patient developed osteomyelitis in a bone flap and 1 had CSF leak and meningitis.
Conclusion: Decompressive craniotomy for large intracerebral hematoma is lifesaving. Among the variables- the timing of surgery and the amount of bone removal are strong predictors of the outcome of the surgery.
Keywords: Haematoma; Craniotomy; Decompressive; Intracerebral
Citation: Md Moshiur Rahman., et al. “Predictive Analysis in Decompressive Craniotomy for Haemorrhagic Stroke”. Acta Scientific Neurology 3.3 (2020): 12-16.
Copyright: © 2020 Md Moshiur Rahman., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.