Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine
A wide range of acute brain injuries, including both traumatic and non-traumatic causes, can result in elevated intracranial pressure (ICP), which in turn can cause further secondary injury to the brain, initiating a vicious cascade of propagating injury. Elevated ICP is therefore a neurological inj...
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| Language: | English |
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Elsevier
2025-01-01
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| Series: | Neurotherapeutics |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1878747924001946 |
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| author | Rohan Mathur Lin Cheng Josiah Lim Tej D. Azad Peter Dziedzic Eleanor Belkin Ivanna Joseph Bhagyashri Bhende Sudha Yellapantula Niteesh Potu Austen Lefebvre Vishank Shah Susanne Muehlschlegel Julian Bosel Tamas Budavari Jose I. Suarez |
| author_facet | Rohan Mathur Lin Cheng Josiah Lim Tej D. Azad Peter Dziedzic Eleanor Belkin Ivanna Joseph Bhagyashri Bhende Sudha Yellapantula Niteesh Potu Austen Lefebvre Vishank Shah Susanne Muehlschlegel Julian Bosel Tamas Budavari Jose I. Suarez |
| author_sort | Rohan Mathur |
| collection | DOAJ |
| description | A wide range of acute brain injuries, including both traumatic and non-traumatic causes, can result in elevated intracranial pressure (ICP), which in turn can cause further secondary injury to the brain, initiating a vicious cascade of propagating injury. Elevated ICP is therefore a neurological injury that requires intensive monitoring and time-sensitive interventions. Patients at high risk for developing elevated ICP undergo placement of invasive ICP monitors including external ventricular drains, intraparenchymal ICP monitors, and lumbar drains. These monitors all generate an ICP waveform, but each has its own unique caveats in monitoring and accuracy. Current ICP monitoring and management clinical guidelines focus on the mean ICP derived from the ICP waveform, with standard thresholds of treating ICP greater than 20 mmHg or 22 mmHg applied broadly to a wide range of patients. However, this one-size fits all approach has been criticized and there is a need to develop personalized, evidence-based and possibly multi-factorial precision-medicine based approaches to the problem. This paper provides historical and physiological context to the problem of elevated ICP, provides an overview of the challenges of the current paradigm of ICP management strategies, and discusses advances in ICP waveform analysis, emerging non-invasive ICP monitoring techniques, and applications of machine learning to create predictive algorithms. |
| format | Article |
| id | doaj-art-3af7a78825114cbfaf5b30ed703bfc63 |
| institution | Kabale University |
| issn | 1878-7479 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Neurotherapeutics |
| spelling | doaj-art-3af7a78825114cbfaf5b30ed703bfc632025-02-01T04:11:53ZengElsevierNeurotherapeutics1878-74792025-01-01221e00507Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicineRohan Mathur0Lin Cheng1Josiah Lim2Tej D. Azad3Peter Dziedzic4Eleanor Belkin5Ivanna Joseph6Bhagyashri Bhende7Sudha Yellapantula8Niteesh Potu9Austen Lefebvre10Vishank Shah11Susanne Muehlschlegel12Julian Bosel13Tamas Budavari14Jose I. Suarez15Division of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Corresponding authors.Division of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Corresponding authors.Department of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USADepartment of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USADepartment of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USAMedical Informatics Corporation, Houston, TX, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurology, University Hospital Heidelberg, Heidelberg, GermanyDepartment of Applied Mathematics and Statistics, Johns Hopkins University Whiting School of Engineering, Baltimore, MD, USADivision of Neurosciences Critical Care, Johns Hopkins School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Anesthesiology & Critical Care Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USAA wide range of acute brain injuries, including both traumatic and non-traumatic causes, can result in elevated intracranial pressure (ICP), which in turn can cause further secondary injury to the brain, initiating a vicious cascade of propagating injury. Elevated ICP is therefore a neurological injury that requires intensive monitoring and time-sensitive interventions. Patients at high risk for developing elevated ICP undergo placement of invasive ICP monitors including external ventricular drains, intraparenchymal ICP monitors, and lumbar drains. These monitors all generate an ICP waveform, but each has its own unique caveats in monitoring and accuracy. Current ICP monitoring and management clinical guidelines focus on the mean ICP derived from the ICP waveform, with standard thresholds of treating ICP greater than 20 mmHg or 22 mmHg applied broadly to a wide range of patients. However, this one-size fits all approach has been criticized and there is a need to develop personalized, evidence-based and possibly multi-factorial precision-medicine based approaches to the problem. This paper provides historical and physiological context to the problem of elevated ICP, provides an overview of the challenges of the current paradigm of ICP management strategies, and discusses advances in ICP waveform analysis, emerging non-invasive ICP monitoring techniques, and applications of machine learning to create predictive algorithms.http://www.sciencedirect.com/science/article/pii/S1878747924001946Intracranial pressureHistoryExternal ventricular drainMachine learningAcute brain injuryICP prediction |
| spellingShingle | Rohan Mathur Lin Cheng Josiah Lim Tej D. Azad Peter Dziedzic Eleanor Belkin Ivanna Joseph Bhagyashri Bhende Sudha Yellapantula Niteesh Potu Austen Lefebvre Vishank Shah Susanne Muehlschlegel Julian Bosel Tamas Budavari Jose I. Suarez Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine Neurotherapeutics Intracranial pressure History External ventricular drain Machine learning Acute brain injury ICP prediction |
| title | Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine |
| title_full | Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine |
| title_fullStr | Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine |
| title_full_unstemmed | Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine |
| title_short | Evolving concepts in intracranial pressure monitoring - from traditional monitoring to precision medicine |
| title_sort | evolving concepts in intracranial pressure monitoring from traditional monitoring to precision medicine |
| topic | Intracranial pressure History External ventricular drain Machine learning Acute brain injury ICP prediction |
| url | http://www.sciencedirect.com/science/article/pii/S1878747924001946 |
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