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Kissing aneurysms of the internal carotid artery
Amit Kumar Sharma, Anita Jagetia, Arvind Kumar Srivastava, Daljit Singh
July-December 2020, 8(2):134-136
Kissing aneurysms (KAs) are rare and cause various problems when clipping of these aneurysms is attempted because they often partially adhere to each other. A 65-year-old female presented with subarachnoid haemorrhage due to a ruptured aneurysm originating from the left internal carotid artery (ICA)-posterior communicating artery A. She also had an unruptured aneurysm arising from the bifurcation of a left ICA-anterior choroidal artery A. Intraoperative findings revealed that these were KAs. Surgical clipping was performed. The postoperative period was uneventful. In this case report, we would like to stress the rarity of KAs and the difficulty in the diagnosis and management of such cases.
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Musings about surgery for intra-cranial arterio-venous malformations
A Raja
January-June 2020, 8(1):55-57
Introduction: Neurosurgery has evolved with the times and as with all things with a rich history, there is much to be learnt from experience and much to be re-iterated in the present. Aims and objectives: To reinforce the key basic points in AVM surgery, for the benefit of all neurosurgeons operating on AVMs. Materials: Based on personal experience from over he author recollects integral points and principles of the surgical management of intra-cranial arterio-venous malformations (AVMs), highlighting the basic elements such as planning, exposure, equipment use, intra-operative identification, and safe approach, execution and hemostasis. Conclusion: The success of AVM surgery depends highly on methodical planning and precise execution.
  1 1,471 97
Statistical corner: Using R to build, analyse and plot clinical neurological datasets
Mikko Jaakko Pyysalo, Teemu Vesterinen
July-December 2020, 8(2):107-112
Introduction: In the field of medical research, large volumes of data need to be analysed accurately, and it is crucial to pre-process the data before it can be analysed. The 'R' environment is a programming language and environment for statistical computing and graphics suitable for the analysis of data sets. Objectives: To provide examples on how to utilise the R language for data processing, and its usefulness for medical researchers. Materials and Methods: Two real world datasets, ie, data for: 'Effect of Morning Blood Pressure Peak on Early Progressive Ischemic Stroke: A Prospective Clinical Study' and data for: 'Impact of early surgery of ruptured cerebral aneurysms on vasospasm and hydrocephalus after SAH: our preliminary series' have been used to present an example for two different approaches for the process of data analysis using R. Results: Accurate and tidy data sets were obtained. Conclusions: R is a reliable environment for the processing of large data sets.
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