Objective: There is a paucity of studies on the optimal thresholds for neurointensive care (NIC) targets such as intracranial pressure (ICP) and cerebral perfusion pressure (CPP) in spontaneous intracerebral hemorrhage (sICH). There is also a need to clarify the role of cerebral pressure autoregulatory disturbances (pressure reactivity index [PRx]) and to determine if the autoregulatory CPP target (optimal CPP [CPPopt]) is superior to traditional fixed CPP targets in sICH. In this study, the authors aimed to explore the role of ICP, PRx, CPP, and CPPopt insults in sICH patients treated in the NIC unit.
View Article and Find Full Text PDFObjective: The main aim was to determine the incidence, risk factors, clinical phenotypes, and response to shunt surgery in chronic, shunt-dependent hydrocephalus (SDHC) after aneurysmal subarachnoid hemorrhage (aSAH).
Methods: In this observational, single-center study, 849 aSAH patients treated at Uppsala University Hospital, between 2008-2018, were included. Variables on demography, injury severity, treatments, chronic hydrocephalus presentation, and outcome were evaluated.
Single-cell MALDI mass spectrometry imaging (MSI) of lipids and metabolites >200 Da has recently come to the forefront of biomedical research and chemical biology. However, cell-targeting and metabolome-preserving methods for analysis of low mass, hydrophilic metabolites (<200 Da) in large cell populations are lacking. Here, the PRISM-MS (PRescan Imaging for Small Molecule - Mass Spectrometry) mass-guided MSI workflow is presented, which enables space-efficient single cell lipid and metabolite analysis.
View Article and Find Full Text PDFBackground: Timing of surgical evacuation of mass lesions in traumatic brain injury (TBI) is crucial. However, due to geographical variations, transportation time to the nearest neurosurgical department may be long. To save time, general surgeons at a local hospital may perform the operation, despite more limited experience in neurosurgical techniques.
View Article and Find Full Text PDFBackground: In neurointensive care, increased intracranial pressure (ICP) is a feared secondary brain insult in traumatic brain injury (TBI). A system that predicts ICP insults before they emerge may facilitate early optimization of the physiology, which may in turn lead to stopping the predicted ICP insult from occurring. The aim of this study was to evaluate the performance of different artificial intelligence models in predicting the risk of ICP insults.
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