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Gulamali F, Jayaraman P, Sawant AS, Desman J, Fox B, Chang A, Soong BY, Arivazagan N, Reynolds AS, Duong SQ, Vaid A, Kovatch P, Freeman R, Hofer IS, Sakhuja A, Dangayach NS, Reich DS, Charney AW, Nadkarni GN. Derivation, external and clinical validation of a deep learning approach for detecting intracranial hypertension. NPJ Digit Med 2024; 7:233. [PMID: 39237755 PMCID: PMC11377429 DOI: 10.1038/s41746-024-01227-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 08/13/2024] [Indexed: 09/07/2024] Open
Abstract
Increased intracranial pressure (ICP) ≥15 mmHg is associated with adverse neurological outcomes, but needs invasive intracranial monitoring. Using the publicly available MIMIC-III Waveform Database (2000-2013) from Boston, we developed an artificial intelligence-derived biomarker for elevated ICP (aICP) for adult patients. aICP uses routinely collected extracranial waveform data as input, reducing the need for invasive monitoring. We externally validated aICP with an independent dataset from the Mount Sinai Hospital (2020-2022) in New York City. The AUROC, accuracy, sensitivity, and specificity on the external validation dataset were 0.80 (95% CI, 0.80-0.80), 73.8% (95% CI, 72.0-75.6%), 73.5% (95% CI 72.5-74.5%), and 73.0% (95% CI, 72.0-74.0%), respectively. We also present an exploratory analysis showing aICP predictions are associated with clinical phenotypes. A ten-percentile increment was associated with brain malignancy (OR = 1.68; 95% CI, 1.09-2.60), intracerebral hemorrhage (OR = 1.18; 95% CI, 1.07-1.32), and craniotomy (OR = 1.43; 95% CI, 1.12-1.84; P < 0.05 for all).
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Affiliation(s)
- Faris Gulamali
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Pushkala Jayaraman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ashwin S Sawant
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jacob Desman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Benjamin Fox
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Annette Chang
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian Y Soong
- Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Naveen Arivazagan
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexandra S Reynolds
- Department of Neurosurgery and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Son Q Duong
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Akhil Vaid
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Patricia Kovatch
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Robert Freeman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ira S Hofer
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ankit Sakhuja
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Neha S Dangayach
- Department of Neurosurgery and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - David S Reich
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alexander W Charney
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Girish N Nadkarni
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
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Bögli SY, Cherchi MS, Beqiri E, Smielewski P. Association between EEG metrics and continuous cerebrovascular autoregulation assessment: a scoping review. Br J Anaesth 2024; 133:550-564. [PMID: 38644159 PMCID: PMC11347808 DOI: 10.1016/j.bja.2024.03.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 03/11/2024] [Accepted: 03/25/2024] [Indexed: 04/23/2024] Open
Abstract
OBJECTIVE Cerebrovascular autoregulation is defined as the capacity of cerebral blood vessels to maintain stable cerebral blood flow despite changing blood pressure. It is assessed using the pressure reactivity index (the correlation coefficient between mean arterial blood pressure and intracranial pressure). The objective of this scoping review is to describe the existing evidence concerning the association of EEG and cerebrovascular autoregulation in order to identify key concepts and detect gaps in the current knowledge. METHODS Embase, MEDLINE, SCOPUS, and Web of Science were searched considering articles between their inception up to September 2023. Inclusion criteria were human (paediatric and adult) and animal studies describing correlations between continuous EEG and cerebrovascular autoregulation assessments. RESULTS Ten studies describing 481 human subjects (67% adult, 59% critically ill) were identified. Seven studies assessed qualitative (e.g. seizures, epileptiform potentials) and five evaluated quantitative (e.g. bispectral index, alpha-delta ratio) EEG metrics. Cerebrovascular autoregulation was evaluated based on intracranial pressure, transcranial Doppler, or near infrared spectroscopy. Specific combinations of cerebrovascular autoregulation and EEG metrics were evaluated by a maximum of two studies. Seizures, highly malignant patterns or burst suppression, alpha peak frequency, and bispectral index were associated with cerebrovascular autoregulation. The other metrics showed either no or inconsistent associations. CONCLUSION There is a paucity of studies evaluating the link between EEG and cerebrovascular autoregulation. The studies identified included a variety of EEG and cerebrovascular autoregulation acquisition methods, age groups, and diseases allowing for few overarching conclusions. However, the preliminary evidence for the presence of an association between EEG metrics and cerebrovascular autoregulation prompts further in-depth investigations.
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Affiliation(s)
- Stefan Y Bögli
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
| | - Marina S Cherchi
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK; Department of Critical Care, Marqués de Valdecilla University Hospital, and Biomedical Research Institute (IDIVAL), Santander, Cantabria, Spain
| | - Erta Beqiri
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Peter Smielewski
- Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
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Hwang J, Akbar AF, Premraj L, Ritzl EK, Cho SM. Epidemiology of Seizures and Association With Mortality in Adult Patients Undergoing ECMO: A Systematic Review and Meta-analysis. Neurology 2024; 103:e209721. [PMID: 39079068 DOI: 10.1212/wnl.0000000000209721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Extracorporeal membrane oxygenation (ECMO) provides lifesaving support to patients with cardiopulmonary failure. Although seizures increase mortality risks among critically ill patients broadly, studies specific to adult ECMO patients have largely been limited to single-center studies. Thus, we aimed to perform a systematic review and meta-analyses of seizure prevalence, mortality, and their associations in adult ECMO patients. METHODS PubMed, EMBASE, Cochrane trial registry, Web of Science, and SCOPUS were searched on August 5, 2023. Following the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines, we included studies of adults undergoing venovenous ECMO (VV-ECMO), venoarterial ECMO (VA-ECMO), or extracorporeal cardiopulmonary resuscitation (ECPR) that reported seizures during ECMO. The extracted data included study characteristics, patient demographics, ECMO support, EEG monitoring, and seizures, organized by ECMO types. Forest plot and meta-regression analyses were performed. Bias assessment was performed with the Egger test and Newcastle-Ottawa Scale. RESULTS Twenty-three studies (n = 40,420, mean age = 51.8 years, male = 62%) were included. Data were extracted by ECMO type as follows: VV-ECMO (n = 16,633), non-ECPR VA-ECMO (n = 11,082), ECPR (n = 3,369), combination of VA-ECMO and ECPR (n = 240), and combination of all types (n = 9,096). The pooled seizure prevalence for all ECMO types was 3.0%, not significantly different across ECMO types (VV-ECMO = 2.0% [95% CI 0.8-4.5]; VA-ECMO = 3.5% [95% CI 1.7-7.0]; ECPR = 4.9% [95% CI 1.3-17.2]). The pooled mortality was lower for VV-ECMO (46.2% [95% CI 39.3-53.2]) than VA-ECMO (63.4% [95% CI 56.6-69.6]) and ECPR (61.5% [95% CI 57.3-65.6]). Specifically, for VV-ECMO, the pooled mortality of patients with and without seizures was 55.1% and 36.7%, respectively (relative risk = 1.5 [95% CI 1.3-1.7]). Similarly, for VA-ECMO, the pooled mortality of patients with and without seizures was 74.4% and 56.1%, respectively (relative risk = 1.3 [95% CI 1.2-1.5]). Meta-regression analyses demonstrated that seizure prevalence was not associated with prior neurologic comorbidities, adjusted for ECMO type and study year. DISCUSSION Seizures are infrequent during ECMO support. However, they were associated with increased mortality when present. Multi-institutional, larger-scale studies using standardized EEG monitoring are necessary to further understand the risk factors of specific classes of seizures for individual ECMO types, and their effects on mortality. Limitations of our study include missing data for details on seizure types, sedating/antiseizure medications used during ECMO, other ECMO-related complications, and EEG recording protocols.
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Affiliation(s)
- Jaeho Hwang
- From the Division of Epilepsy (J.H., E.K.R.), Department of Neurology; Division of Cardiac Surgery (A.F.A.), Department of Surgery, The Johns Hopkins Hospital, Baltimore, MD; Griffith University School of Medicine (L.P.), Gold Coast, Queensland, Australia; Division of Neurosciences Critical Care (E.K.R., S.-M.C.), Departments of Neurology, Neurosurgery, Anesthesiology, Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD; and Division of Intraoperative Neuromonitoring (E.K.R.), Department of Neurology, Massachusetts General Brigham, Boston
| | - Armaan F Akbar
- From the Division of Epilepsy (J.H., E.K.R.), Department of Neurology; Division of Cardiac Surgery (A.F.A.), Department of Surgery, The Johns Hopkins Hospital, Baltimore, MD; Griffith University School of Medicine (L.P.), Gold Coast, Queensland, Australia; Division of Neurosciences Critical Care (E.K.R., S.-M.C.), Departments of Neurology, Neurosurgery, Anesthesiology, Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD; and Division of Intraoperative Neuromonitoring (E.K.R.), Department of Neurology, Massachusetts General Brigham, Boston
| | - Lavienraj Premraj
- From the Division of Epilepsy (J.H., E.K.R.), Department of Neurology; Division of Cardiac Surgery (A.F.A.), Department of Surgery, The Johns Hopkins Hospital, Baltimore, MD; Griffith University School of Medicine (L.P.), Gold Coast, Queensland, Australia; Division of Neurosciences Critical Care (E.K.R., S.-M.C.), Departments of Neurology, Neurosurgery, Anesthesiology, Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD; and Division of Intraoperative Neuromonitoring (E.K.R.), Department of Neurology, Massachusetts General Brigham, Boston
| | - Eva K Ritzl
- From the Division of Epilepsy (J.H., E.K.R.), Department of Neurology; Division of Cardiac Surgery (A.F.A.), Department of Surgery, The Johns Hopkins Hospital, Baltimore, MD; Griffith University School of Medicine (L.P.), Gold Coast, Queensland, Australia; Division of Neurosciences Critical Care (E.K.R., S.-M.C.), Departments of Neurology, Neurosurgery, Anesthesiology, Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD; and Division of Intraoperative Neuromonitoring (E.K.R.), Department of Neurology, Massachusetts General Brigham, Boston
| | - Sung-Min Cho
- From the Division of Epilepsy (J.H., E.K.R.), Department of Neurology; Division of Cardiac Surgery (A.F.A.), Department of Surgery, The Johns Hopkins Hospital, Baltimore, MD; Griffith University School of Medicine (L.P.), Gold Coast, Queensland, Australia; Division of Neurosciences Critical Care (E.K.R., S.-M.C.), Departments of Neurology, Neurosurgery, Anesthesiology, Critical Care Medicine, The Johns Hopkins Hospital, Baltimore, MD; and Division of Intraoperative Neuromonitoring (E.K.R.), Department of Neurology, Massachusetts General Brigham, Boston
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Prasad A, Gilmore EJ, Kim JA, Begunova L, Olexa M, Beekman R, Falcone GJ, Matouk C, Ortega-Gutierrez S, Temkin NR, Barber J, Diaz-Arrastia R, de Havenon A, Petersen NH. Impact of Therapeutic Interventions on Cerebral Autoregulatory Function Following Severe Traumatic Brain Injury: A Secondary Analysis of the BOOST-II Study. Neurocrit Care 2024; 41:91-99. [PMID: 38158481 PMCID: PMC11285118 DOI: 10.1007/s12028-023-01896-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 11/17/2023] [Indexed: 01/03/2024]
Abstract
BACKGROUND The Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II randomized controlled trial used a tier-based management protocol based on brain tissue oxygen (PbtO2) and intracranial pressure (ICP) monitoring to reduce brain tissue hypoxia after severe traumatic brain injury. We performed a secondary analysis to explore the relationship between brain tissue hypoxia, blood pressure (BP), and interventions to improve cerebral perfusion pressure (CPP). We hypothesized that BP management below the lower limit of autoregulation would lead to cerebral hypoperfusion and brain tissue hypoxia that could be improved with hemodynamic augmentation. METHODS Of the 119 patients enrolled in the Brain Oxygen Optimization in Severe Traumatic Brain Injury Phase II trial, 55 patients had simultaneous recordings of arterial BP, ICP, and PbtO2. Autoregulatory function was measured by interrogating changes in ICP and PbtO2 in response to fluctuations in CPP using time-correlation analysis. The resulting autoregulatory indices (pressure reactivity index and oxygen reactivity index) were used to identify the "optimal" CPP and limits of autoregulation for each patient. Autoregulatory function and percent time with CPP outside personalized limits of autoregulation were calculated before, during, and after all interventions directed to optimize CPP. RESULTS Individualized limits of autoregulation were computed in 55 patients (mean age 38 years, mean monitoring time 92 h). We identified 35 episodes of brain tissue hypoxia (PbtO2 < 20 mm Hg) treated with CPP augmentation. Following each intervention, mean CPP increased from 73 ± 14 mm Hg to 79 ± 17 mm Hg (p = 0.15), and mean PbtO2 improved from 18.4 ± 5.6 mm Hg to 21.9 ± 5.6 mm Hg (p = 0.01), whereas autoregulatory function trended toward improvement (oxygen reactivity index 0.42 vs. 0.37, p = 0.14; pressure reactivity index 0.25 vs. 0.21, p = 0.2). Although optimal CPP and limits remained relatively unchanged, there was a significant decrease in the percent time with CPP below the lower limit of autoregulation in the 60 min after compared with before an intervention (11% vs. 23%, p = 0.05). CONCLUSIONS Our analysis suggests that brain tissue hypoxia is associated with cerebral hypoperfusion characterized by increased time with CPP below the lower limit of autoregulation. Interventions to increase CPP appear to improve autoregulation. Further studies are needed to validate the importance of autoregulation as a modifiable variable with the potential to improve outcomes.
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Affiliation(s)
- Ayush Prasad
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Emily J Gilmore
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Jennifer A Kim
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Liza Begunova
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Madelynne Olexa
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Rachel Beekman
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Guido J Falcone
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Charles Matouk
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT, USA
| | | | - Nancy R Temkin
- Department of Neurological Surgery, University of Washington, Seattle, WA, USA
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Jason Barber
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Ramon Diaz-Arrastia
- Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Adam de Havenon
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA
| | - Nils H Petersen
- Division of Neurocritical Care and Emergency, Department of Neurology, Yale University School of Medicine, 15 York St, LCI 1003, New Haven, CT, CT 06510, USA.
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Luna R, Basil B, Ewbank D, Kasturiarachi BM, Mizrahi MA, Ngwenya LB, Foreman B. Clinical Impact of Standardized Interpretation and Reporting of Multimodality Neuromonitoring Data. Crit Care Explor 2024; 6:e1139. [PMID: 39120075 PMCID: PMC11319310 DOI: 10.1097/cce.0000000000001139] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/10/2024] Open
Abstract
OBJECTIVE Evaluate the consistency and clinical impact of standardized multimodality neuromonitoring (MNM) interpretation and reporting within a system of care for patients with severe traumatic brain injury (sTBI). DESIGN Retrospective, observational historical case-control study. SETTING Single-center academic level I trauma center. INTERVENTIONS Standardized interpretation of MNM data summarized within daily reports. MEASUREMENTS MAIN RESULTS Consecutive patients with sTBI undergoing MNM were included. Historical controls were patients monitored before implementation of standardized MNM interpretation; cases were defined as patients with available MNM interpretative reports. Patient characteristics, physiologic data, and clinical outcomes were recorded, and clinical MNM reporting elements were abstracted. The primary outcome was the Glasgow Outcome Scale score 3-6 months postinjury. One hundred twenty-nine patients were included (age 42 ± 18 yr, 82% men); 45 (35%) patients were monitored before standardized MNM interpretation and reporting, and 84 (65%) patients were monitored after that. Patients undergoing standardized interpretative reporting received fewer hyperosmotic agents (3 [1-6] vs. 6 [1-8]; p = 0.04) and spent less time above an intracranial threshold of 22 mm Hg (22% ± 26% vs. 28% ± 24%; p = 0.05). The MNM interpretation cohort had a lower proportion of anesthetic days (48% [24-70%] vs. 67% [33-91%]; p = 0.02) and higher average end-tidal carbon dioxide during monitoring (34 ± 6 mm Hg vs. 32 ± 6 mm Hg; p < 0.01; d = 0.36). After controlling for injury severity, patients undergoing standardized MNM interpretation and reporting had an odds of 1.5 (95% CI, 1.37-1.59) for better outcomes. CONCLUSIONS Standardized interpretation and reporting of MNM data are a novel approach to provide clinical insight and to guide individualized critical care. In patients with sTBI, independent MNM interpretation and communication to bedside clinical care teams may result in improved intracranial pressure control, fewer medical interventions, and changes in ventilatory management. In this study, the implementation of a system for management, including standardized MNM interpretation, was associated with a significant improvement in outcome.
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Affiliation(s)
- Rudy Luna
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
| | - Barbara Basil
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
| | - Davis Ewbank
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
| | | | - Moshe A. Mizrahi
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
| | - Laura B. Ngwenya
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
- Department of Neurosurgery, University of Cincinnati, Cincinnati, OH
- Collaborative for Research on Acute Neurological Injuries (CRANI), Cincinnati, OH
| | - Brandon Foreman
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
- Collaborative for Research on Acute Neurological Injuries (CRANI), Cincinnati, OH
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Andreasen TH, Madsen FA, Barbateskovic M, Lindschou J, Gluud C, Møller K. Ketamine for Critically Ill Patients with Severe Acute Brain Injury: A Systematic Review with Meta-analysis and Trial Sequential Analysis of Randomized Clinical Trials. Neurocrit Care 2024:10.1007/s12028-024-02075-2. [PMID: 39085508 DOI: 10.1007/s12028-024-02075-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2024] [Accepted: 07/09/2024] [Indexed: 08/02/2024]
Abstract
BACKGROUND Patients with severe acute brain injury have a high risk of a poor clinical outcome due to primary and secondary brain injury. Ketamine reportedly inhibits cortical spreading depolarization, an electrophysiological phenomenon that has been associated with secondary brain injury, making ketamine potentially attractive for patients with severe acute brain injury. The aim of this systematic review is to explore the current literature regarding ketamine for patients with severe acute brain injury. METHODS We systematically searched international databases for randomized clinical trials comparing ketamine by any regimen versus placebo, no intervention, or any control drug for patients with severe acute brain injury. Two authors independently reviewed and selected trials for inclusion, extracted data, assessed risk of bias, and performed analysis using Review Manager and Trial Sequential Analysis. Evidence certainty was assessed using Grading of Recommendations Assessment, Development and Evaluation. The primary outcomes were the proportion of participants with an unfavorable functional outcome, the proportion of participants with one or more serious adverse events, and quality of life. RESULTS We identified five randomized trials comparing ketamine versus sufentanil, fentanyl, other sedatives, or saline (total N = 149 participants). All outcomes were at overall high risk of bias. The proportions of participants with one or more serious adverse events did not differ between ketamine and sufentanil or fentanyl (relative risk 1.45, 95% confidence interval 0.81-2.58; very low certainty). Trial sequential analysis showed that further trials are needed. CONCLUSIONS The level of evidence regarding the effects of ketamine on functional outcome and serious adverse events in patients with severe acute brain injury is very low. Ketamine may markedly, modestly, or not at all affect these outcomes. Large randomized clinical trials at low risk of bias are needed.
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Affiliation(s)
- Trine Hjorslev Andreasen
- Department of Neurosurgery, Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark.
| | - Frederik Andreas Madsen
- Department of Neuroanaesthesiology, Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Marija Barbateskovic
- Copenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Jane Lindschou
- Copenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Christian Gluud
- Copenhagen Trial Unit, Centre for Clinical Intervention Research, The Capital Region, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Regional Health Research, The Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Kirsten Møller
- Department of Neuroanaesthesiology, Neuroscience Centre, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, The Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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7
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Pansell J, Bottai M, Bell M, Rudberg PC, Friman O, Cooray C. Which compartments of the optic nerve and its sheath are associated with intracranial pressure? An exploratory study. J Neuroimaging 2024. [PMID: 39034603 DOI: 10.1111/jon.13224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Revised: 07/08/2024] [Accepted: 07/10/2024] [Indexed: 07/23/2024] Open
Abstract
BACKGROUND AND PURPOSE The optic nerve sheath diameter (ONSD) is a commonly used estimate of intracranial pressure (ICP). The rationale behind this is that pressure changes in the cerebrospinal fluid affect the optic nerve subarachnoid space (ONSAS) thickness. Still, possible effects on other compartments of the optic nerve sheath (ONS) have not been studied. This is the first study ever to analyze all measurable compartments of the ONS for associations with elevated ICP. METHODS We measured changes in ICP and changes in ONS compartments in 75 patients treated with invasive ICP monitoring at the Karolinska University Hospital. Associations between changes in ICP and changes in ONS compartments were estimated with generalized estimating equations. The potential to identify elevated ICP was assessed with the area under the receiver operating characteristic curve (AUROC) for ONS compartments associated with ICP changes. RESULTS Both ONSAS and perioptic dura mater thickness were significantly associated with changes in ICP in multivariable modeling. ONSAS was the only compartment that independently predicted changes in ICP, with an AUROC of 0.69 for predicting ICP increase. Still, both the perioptic dura mater thickness and the optic nerve diameter added value in predicting ICP changes in multivariable modeling. CONCLUSIONS The results from this study challenge the current understanding of the mechanism behind the association between ICP and ONSD. Contrary to the common opinion that ONSAS is the only affected compartment, this study shows a more complex picture. It suggests that all ONS compartments may add value in predicting changes in ICP.
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Affiliation(s)
- Jakob Pansell
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Matteo Bottai
- Division of Biostatistics, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Max Bell
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
- Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Peter C Rudberg
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
- Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ola Friman
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Charith Cooray
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
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Haberl H, Unterberg M, Adamzik M, Hagedorn A, Wolf A. [Current Aspects of Intensive Medical Care for Traumatic Brain Injury - Part 1 - Primary Treatment Strategies, Haemodynamic Management and Multimodal Monitoring]. Anasthesiol Intensivmed Notfallmed Schmerzther 2024; 59:450-465. [PMID: 39074790 DOI: 10.1055/a-2075-9351] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
This two-part article deals with the intensive medical care of traumatic brain injury. Part 1 addresses the primary treatment strategy, haemodynamic management and multimodal monitoring, Part 2 secondary treatment strategies, long-term outcome, neuroprognostics and chronification. Traumatic brain injury is a complex clinical entity with a high mortality rate. The primary aim is to maintain homeostasis based on physiological targeted values. In addition, further therapy must be geared towards intracranial pressure. In addition to this, there are other monitoring options that appear sensible from a pathophysiological point of view with appropriate therapy adjustment. However, there is still a lack of data on their effectiveness. A further aspect is the inflammation of the cerebrum with the "cross-talk" of the organs, which has a significant influence on further intensive medical care.
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Srichawla BS. Future of neurocritical care: Integrating neurophysics, multimodal monitoring, and machine learning. World J Crit Care Med 2024; 13:91397. [PMID: 38855276 PMCID: PMC11155497 DOI: 10.5492/wjccm.v13.i2.91397] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 01/27/2024] [Accepted: 03/06/2024] [Indexed: 06/03/2024] Open
Abstract
Multimodal monitoring (MMM) in the intensive care unit (ICU) has become increasingly sophisticated with the integration of neurophysical principles. However, the challenge remains to select and interpret the most appropriate combination of neuromonitoring modalities to optimize patient outcomes. This manuscript reviewed current neuromonitoring tools, focusing on intracranial pressure, cerebral electrical activity, metabolism, and invasive and noninvasive autoregulation monitoring. In addition, the integration of advanced machine learning and data science tools within the ICU were discussed. Invasive monitoring includes analysis of intracranial pressure waveforms, jugular venous oximetry, monitoring of brain tissue oxygenation, thermal diffusion flowmetry, electrocorticography, depth electroencephalography, and cerebral microdialysis. Noninvasive measures include transcranial Doppler, tympanic membrane displacement, near-infrared spectroscopy, optic nerve sheath diameter, positron emission tomography, and systemic hemodynamic monitoring including heart rate variability analysis. The neurophysical basis and clinical relevance of each method within the ICU setting were examined. Machine learning algorithms have shown promise by helping to analyze and interpret data in real time from continuous MMM tools, helping clinicians make more accurate and timely decisions. These algorithms can integrate diverse data streams to generate predictive models for patient outcomes and optimize treatment strategies. MMM, grounded in neurophysics, offers a more nuanced understanding of cerebral physiology and disease in the ICU. Although each modality has its strengths and limitations, its integrated use, especially in combination with machine learning algorithms, can offer invaluable information for individualized patient care.
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Affiliation(s)
- Bahadar S Srichawla
- Department of Neurology, University of Massachusetts Chan Medical School, Worcester, MA 01655, United States
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Lin J, Chen X, Zhang P, Xue Y, Feng Y, Ni Z, Tao Y, Wang Y, Liu J. Wireless Bioelectronics for In Vivo Pressure Monitoring with Mechanically-Compliant Hydrogel Biointerfaces. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2400181. [PMID: 38419474 DOI: 10.1002/adma.202400181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Revised: 02/16/2024] [Indexed: 03/02/2024]
Abstract
Recent electronics-tissues biointefacing technology has offered unprecedented opportunities for long-term disease diagnosis and treatment. It remains a grand challenge to robustly anchor the pressure sensing bioelectronics onto specific organs, since the periodically-varying stress generated by normal biological processes may pose high risk of interfacial failures. Here, a general yet reliable approach is reported to achieve the robust hydrogel interface between wireless pressure sensor and biological tissues/organs, featuring highly desirable mechanical compliance and swelling resistance, despite the direct contact with biofluids and dynamic conditions. The sensor is operated wirelessly through inductive coupling, characterizing minimal hysteresis, fast response times, excellent stability, and robustness, thus allowing for easy handling and eliminating the necessity for surgical extraction after a functional period. The operation of the wireless sensor has been demonstrated with a custom-made pressure sensing model and in vivo intracranial pressure monitoring in rats. This technology may be advantageous in real-time post-operative monitoring of various biological inner pressures after the reconstructive surgery, thus guaranteeing the timely treatment of lethal diseases.
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Affiliation(s)
- Jingsen Lin
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Xingmei Chen
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Pei Zhang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yu Xue
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yinghui Feng
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Zhipeng Ni
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yue Tao
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yafei Wang
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Ji Liu
- Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
- Shenzhen Key Laboratory of Intelligent Robotics and Flexible Manufacturing Systems, Southern University of Science and Technology, Shenzhen, 518055, China
- Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen, 518055, China
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11
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Erklauer JC, Lai YC. The State of the Field of Pediatric Multimodality Neuromonitoring. Neurocrit Care 2024; 40:1160-1170. [PMID: 37864125 DOI: 10.1007/s12028-023-01858-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Accepted: 09/08/2023] [Indexed: 10/22/2023]
Abstract
BACKGROUND The use of multimodal neuromonitoring in pediatrics is in its infancy relative to adult neurocritical care. Multimodal neuromonitoring encompasses the amalgamation of information from multiple individual neuromonitoring devices to gain a more comprehensive understanding of the condition of the brain. It allows for adaptation to the changing state of the brain throughout various stages of injury with potential to individualize and optimize therapies. METHODS Here we provide an overview of multimodal neuromonitoring in pediatric neurocritical care and its potential application in the future. RESULTS Multimodal neuromonitoring devices are key to the process of multimodal neuromonitoring, allowing for visualization of data trends over time and ideally improving the ability of clinicians to identify patterns and find meaning in the immense volume of data now encountered in the care of critically ill patients at the bedside. Clinical use in pediatrics requires more study to determine best practices and impact on patient outcomes. Potential uses include guidance for targets of physiological parameters in the setting of acute brain injury, neuroprotection for patients at high risk for brain injury, and neuroprognostication. Implementing multimodal neuromonitoring in pediatric patients involves interprofessional collaboration with the development of a simultaneous comprehensive program to support the use of multimodal neuromonitoring while maintaining the fundamental principles of the delivery of neurocritical care at the bedside. CONCLUSIONS The possible benefits of multimodal neuromonitoring are immense and have great potential to advance the field of pediatric neurocritical care and the health of critically ill children.
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Affiliation(s)
- Jennifer C Erklauer
- Divisions of Critical Care Medicine and Pediatric Neurology and Developmental Neurosciences, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA.
| | - Yi-Chen Lai
- Division of Critical Care Medicine, Department of Pediatrics, Baylor College of Medicine and Texas Children's Hospital, Houston, TX, USA
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Vitt JR, Mainali S. Artificial Intelligence and Machine Learning Applications in Critically Ill Brain Injured Patients. Semin Neurol 2024; 44:342-356. [PMID: 38569520 DOI: 10.1055/s-0044-1785504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
The utilization of Artificial Intelligence (AI) and Machine Learning (ML) is paving the way for significant strides in patient diagnosis, treatment, and prognostication in neurocritical care. These technologies offer the potential to unravel complex patterns within vast datasets ranging from vast clinical data and EEG (electroencephalogram) readings to advanced cerebral imaging facilitating a more nuanced understanding of patient conditions. Despite their promise, the implementation of AI and ML faces substantial hurdles. Historical biases within training data, the challenge of interpreting multifaceted data streams, and the "black box" nature of ML algorithms present barriers to widespread clinical adoption. Moreover, ethical considerations around data privacy and the need for transparent, explainable models remain paramount to ensure trust and efficacy in clinical decision-making.This article reflects on the emergence of AI and ML as integral tools in neurocritical care, discussing their roles from the perspective of both their scientific promise and the associated challenges. We underscore the importance of extensive validation in diverse clinical settings to ensure the generalizability of ML models, particularly considering their potential to inform critical medical decisions such as withdrawal of life-sustaining therapies. Advancement in computational capabilities is essential for implementing ML in clinical settings, allowing for real-time analysis and decision support at the point of care. As AI and ML are poised to become commonplace in clinical practice, it is incumbent upon health care professionals to understand and oversee these technologies, ensuring they adhere to the highest safety standards and contribute to the realization of personalized medicine. This engagement will be pivotal in integrating AI and ML into patient care, optimizing outcomes in neurocritical care through informed and data-driven decision-making.
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Affiliation(s)
- Jeffrey R Vitt
- Department of Neurological Surgery, UC Davis Medical Center, Sacramento, California
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, Virginia
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13
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Pansell J, Rudberg PC, Friman O, Bell M, Cooray C. Sex differences in the diagnostic value of optic nerve sheath diameter for assessing intracranial pressure. Sci Rep 2024; 14:9553. [PMID: 38664502 PMCID: PMC11045773 DOI: 10.1038/s41598-024-60489-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/23/2024] [Indexed: 04/28/2024] Open
Abstract
The optic nerve sheath diameter (ONSD) can predict elevated intracranial pressure (ICP) but it is not known whether diagnostic characteristics differ between men and women. This observational study was performed at the Karolinska University Hospital in Sweden to assess sex differences in diagnostic accuracy for ONSD. We included 139 patients (65 women), unconscious and/or sedated, with invasive ICP monitoring. Commonly used ONSD derived measurements and associated ICP measurements were collected. Linear regression analyses were performed with ICP as dependent variable and ONSD as independent variable. Area under the receiver operator characteristics curve (AUROC) analyses were performed with a threshold for elevated ICP ≥ 20 mmHg. Analyses were stratified by sex. Optimal cut-offs and diagnostic characteristics were estimated. The ONSD was associated with ICP in women. The AUROCs in women ranged from 0.70 to 0.83. In men, the ONSD was not associated with ICP and none of the AUROCs were significantly larger than 0.5. This study suggests that ONSD is a useful predictor of ICP in women but may not be so in men. If this finding is verified in further studies, this would call for a re-evaluation of the usage and interpretation of ONSD to estimate ICP.
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Affiliation(s)
- Jakob Pansell
- The Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
- The Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden.
| | - Peter C Rudberg
- The Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
- The Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ola Friman
- The Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
- The Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Max Bell
- The Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
- The Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Charith Cooray
- The Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
- The Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
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14
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Bagg MK, Hicks AJ, Hellewell SC, Ponsford JL, Lannin NA, O'Brien TJ, Cameron PA, Cooper DJ, Rushworth N, Gabbe BJ, Fitzgerald M. The Australian Traumatic Brain Injury Initiative: Statement of Working Principles and Rapid Review of Methods to Define Data Dictionaries for Neurological Conditions. Neurotrauma Rep 2024; 5:424-447. [PMID: 38660461 PMCID: PMC11040195 DOI: 10.1089/neur.2023.0116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2024] Open
Abstract
The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to develop a health informatics approach to collect data predictive of outcomes for persons with moderate-severe TBI across Australia. Central to this approach is a data dictionary; however, no systematic reviews of methods to define and develop data dictionaries exist to-date. This rapid systematic review aimed to identify and characterize methods for designing data dictionaries to collect outcomes or variables in persons with neurological conditions. Database searches were conducted from inception through October 2021. Records were screened in two stages against set criteria to identify methods to define data dictionaries for neurological conditions (International Classification of Diseases, 11th Revision: 08, 22, and 23). Standardized data were extracted. Processes were checked at each stage by independent review of a random 25% of records. Consensus was reached through discussion where necessary. Thirty-nine initiatives were identified across 29 neurological conditions. No single established or recommended method for defining a data dictionary was identified. Nine initiatives conducted systematic reviews to collate information before implementing a consensus process. Thirty-seven initiatives consulted with end-users. Methods of consultation were "roundtable" discussion (n = 30); with facilitation (n = 16); that was iterative (n = 27); and frequently conducted in-person (n = 27). Researcher stakeholders were involved in all initiatives and clinicians in 25. Importantly, only six initiatives involved persons with lived experience of TBI and four involved carers. Methods for defining data dictionaries were variable and reporting is sparse. Our findings are instructive for AUS-TBI and can be used to further development of methods for defining data dictionaries.
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Affiliation(s)
- Matthew K. Bagg
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia
- Centre for Pain IMPACT, Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Health Sciences, University of Notre Dame Australia, Fremantle, Western Australia, Australia
| | - Amelia J. Hicks
- School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, Victoria, Australia
| | - Sarah C. Hellewell
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia
| | - Jennie L. Ponsford
- School of Psychological Sciences, Monash University, Melbourne, Victoria, Australia
- Monash-Epworth Rehabilitation Research Centre, Epworth Healthcare, Melbourne, Victoria, Australia
| | - Natasha A. Lannin
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
- Alfred Health, Melbourne, Victoria, Australia
| | - Terence J. O'Brien
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Victoria, Australia
| | - Peter A. Cameron
- National Trauma Research Institute, Melbourne, Victoria, Australia
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Emergency and Trauma Centre, The Alfred Hospital, Melbourne, Victoria, Australia
| | - D. Jamie Cooper
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Department of Intensive Care and Hyperbaric Medicine, The Alfred Hospital, Melbourne, Victoria, Australia
| | - Nick Rushworth
- Brain Injury Australia, Sydney, New South Wales, Australia
| | - Belinda J. Gabbe
- School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
- Health Data Research UK, Swansea University Medical School, Swansea University, Singleton Park, United Kingdom
| | - Melinda Fitzgerald
- Curtin Health Innovation Research Institute, Faculty of Health Sciences, Curtin University, Bentley, Western Australia, Australia
- Perron Institute for Neurological and Translational Science, Nedlands, Western Australia, Australia
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15
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Gomez A, Froese L, Griesdale D, Thelin EP, Raj R, van Iperenburg L, Tas J, Aries M, Stein KY, Gallagher C, Bernard F, Kramer AH, Zeiler FA. Prognostic value of near-infrared spectroscopy regional oxygen saturation and cerebrovascular reactivity index in acute traumatic neural injury: a CAnadian High-Resolution Traumatic Brain Injury (CAHR-TBI) Cohort Study. Crit Care 2024; 28:78. [PMID: 38486211 PMCID: PMC10938687 DOI: 10.1186/s13054-024-04859-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Accepted: 03/02/2024] [Indexed: 03/18/2024] Open
Abstract
BACKGROUND Near-infrared spectroscopy regional cerebral oxygen saturation (rSO2) has gained interest as a raw parameter and as a basis for measuring cerebrovascular reactivity (CVR) due to its noninvasive nature and high spatial resolution. However, the prognostic utility of these parameters has not yet been determined. This study aimed to identify threshold values of rSO2 and rSO2-based CVR at which outcomes worsened following traumatic brain injury (TBI). METHODS A retrospective multi-institutional cohort study was performed. The cohort included TBI patients treated in four adult intensive care units (ICU). The cerebral oxygen indices, COx (using rSO2 and cerebral perfusion pressure) as well as COx_a (using rSO2 and arterial blood pressure) were calculated for each patient. Grand mean thresholds along with exposure-based thresholds were determined utilizing sequential chi-squared analysis and univariate logistic regression, respectively. RESULTS In the cohort of 129 patients, there was no identifiable threshold for raw rSO2 at which outcomes were found to worsen. For both COx and COx_a, an optimal grand mean threshold value of 0.2 was identified for both survival and favorable outcomes, while percent time above - 0.05 was uniformly found to have the best discriminative value. CONCLUSIONS In this multi-institutional cohort study, raw rSO2was found to contain no significant prognostic information. However, rSO2-based indices of CVR, COx and COx_a, were found to have a uniform grand mean threshold of 0.2 and exposure-based threshold of - 0.05, above which clinical outcomes markedly worsened. This study lays the groundwork to transition to less invasive means of continuously measuring CVR.
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Affiliation(s)
- Alwyn Gomez
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada.
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
| | - Logan Froese
- Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Donald Griesdale
- Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia, Vancouver, BC, Canada
| | - Eric P Thelin
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Rahul Raj
- Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Levi van Iperenburg
- Department of Intensive Care, Maastricht University Medical Center+, Maastricht, The Netherlands
- School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Jeanette Tas
- Department of Intensive Care, Maastricht University Medical Center+, Maastricht, The Netherlands
- School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Marcel Aries
- Department of Intensive Care, Maastricht University Medical Center+, Maastricht, The Netherlands
- School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Kevin Y Stein
- Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
| | - Clare Gallagher
- Section of Neurosurgery, Department of Clinical Neurosciences, Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
| | - Francis Bernard
- Section of Critical Care, Department of Medicine, University of Montreal, Montreal, QC, Canada
| | - Andreas H Kramer
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada
- Department of Critical Care Medicine, University of Calgary, Calgary, AB, Canada
| | - Frederick A Zeiler
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Biomedical Engineering, Price Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- Department of Neurology, Karolinska University Hospital, Stockholm, Sweden
- Centre on Aging, University of Manitoba, Winnipeg, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK
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16
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Elmaleh Y, Yavchitz A, Léguillier T, Squara PA, Palpacuer C, Grégoire C. Feasibility of Prone Positioning for Brain-injured Patients with Severe Acute Respiratory Distress Syndrome: A Systematic Review and Pilot Study (ProBrain). Anesthesiology 2024; 140:495-512. [PMID: 38088786 DOI: 10.1097/aln.0000000000004875] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2024]
Abstract
BACKGROUND Prone position is a key component to treat hypoxemia in patients with severe acute respiratory distress syndrome. However, most studies evaluating it exclude patients with brain injuries without any medical evidence. METHODS This study includes a systematic review to determine whether brain-injured patients were excluded in studies evaluating prone position on acute respiratory distress syndrome; a prospective study including consecutive brain-injured patients needing prone position. The primary endpoint was the evaluation of cerebral blood flow using transcranial Doppler after prone positioning. Secondary outcomes were intracranial pressure, cerebral perfusion pressure, and tissue oxygen pressure. RESULTS From 8,183 citations retrieved, 120 studies were included in the systematic review. Among them, 90 studies excluded brain-injured patients (75%) without any justification, 16 included brain-injured patients (4 randomized, 7 nonrandomized studies, 5 retrospective), and 14 did not retrieve brain-injured data. Eleven patients were included in the authors' pilot study. No reduction of cerebral blood flow surrogates was observed during prone positioning, with diastolic speed values (mean ± SD) ranging from 37.7 ± 16.2 cm/s to 45.2 ± 19.3 cm/s for the right side (P = 0.897) and 39.6 ± 18.2 cm/s to 46.5 ± 21.3 cm/s for the left side (P = 0.569), and pulsatility index ranging from 1.14 ± 0.31 to 1.0 ± 0.32 for the right side (P = 0.145) and 1.14 ± 0.31 to 1.02 ± 0.2 for the left side (P = 0.564) before and during prone position. CONCLUSIONS Brain-injured patients are largely excluded from studies evaluating prone position in acute respiratory distress syndrome. However, cerebral blood flow seems not to be altered considering increasing of mean arterial pressure during the session. Systematic exclusion of brain-injured patients appears to be unfounded, and prone position, while at risk in brain-injured patients, should be evaluated on these patients to review recommendations, considering close monitoring of neurologic and hemodynamic parameters. EDITOR’S PERSPECTIVE
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Affiliation(s)
- Yoann Elmaleh
- Intensive Care Unit, Rothschild Foundation Hospital, Paris, France; Quincy Anesthesiology, Private Hospital Claude Galien, Boussy Saint Antoine, France
| | - Amélie Yavchitz
- Clinical Research Department, Rothschild Foundation Hospital, Paris, France
| | - Teddy Léguillier
- Clinical Research Department, Rothschild Foundation Hospital, Paris, France
| | | | - Clément Palpacuer
- Clinical Research Department, Rothschild Foundation Hospital, Paris, France
| | - Charles Grégoire
- Intensive Care Unit, Rothschild Foundation Hospital, Paris, France
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17
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Chopko A, Tian M, L'Huillier JC, Filipescu R, Yu J, Guo WA. Utility of intracranial pressure monitoring in patients with traumatic brain injuries: a propensity score matching analysis of TQIP data. Eur J Trauma Emerg Surg 2024; 50:173-184. [PMID: 36795136 DOI: 10.1007/s00068-023-02239-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 01/27/2023] [Indexed: 02/17/2023]
Abstract
PURPOSE Intracranial pressure monitoring (ICPM) is central to traumatic brain injury (TBI) management, but its utility is controversial. METHODS The 2016-2017 TQIP database was queried for isolated TBI. Patients with ICPM [(ICPM (+)] were propensity-score matched (PSM) to those without ICPM [ICPM (-)] and divided into three age groups by years (< 18, 18-54, ≥ 55). RESULTS PSM yielded 2125 patients in each group. Patients aged < 18 years had a higher survival probability (p = 0.013) and decreased mortality (p = 0.016) in the ICPM (+) group. Complications were higher and LOS was longer in ICPM (+) patients aged 18-54 years and ≥ 55 years, but not in patients aged < 18 years. CONCLUSIONS ICPM (+) is associated with a survival benefit without an increase in complications in patents aged < 18 years. In patients aged ≥ 18 years, ICPM (+) is associated with more complications and longer LOS without a survival benefit.
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Affiliation(s)
- Ashley Chopko
- Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 100 High Street, Buffalo, NY, 14203, USA
| | - Mingmei Tian
- Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, 401 Kimball Tower, Buffalo, NY, 14214, USA
| | - Joseph C L'Huillier
- Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 100 High Street, Buffalo, NY, 14203, USA
- Department of Epidemiology and Environmental Health, Division of Health Services Policy and Practice, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, Buffalo, NY, 14214, USA
| | - Radu Filipescu
- Department of Pediatric Surgery, John R. Oishei Children's Hospital, 818 Ellicott Street, Buffalo, NY, 14203, USA
| | - Jinhee Yu
- Department of Biostatistics, School of Public Health and Health Professions, University at Buffalo, 401 Kimball Tower, Buffalo, NY, 14214, USA
| | - Weidun A Guo
- Department of Surgery, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, 100 High Street, Buffalo, NY, 14203, USA.
- Erie County Medical Center, 462 Grider Street, Buffalo, NY, 14215, USA.
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18
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Shah VA, Hinson HE, Reznik ME, Hahn CD, Alexander S, Elmer J, Chou SHY. Common Data Elements for Disorders of Consciousness: Recommendations from the Working Group on Biospecimens and Biomarkers. Neurocrit Care 2024; 40:58-64. [PMID: 38087173 DOI: 10.1007/s12028-023-01883-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 10/18/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND In patients with disorders of consciousness (DoC), laboratory and molecular biomarkers may help define endotypes, identify therapeutic targets, prognosticate outcomes, and guide patient selection in clinical trials. We performed a systematic review to identify common data elements (CDEs) and key design elements (KDEs) for future coma and DoC research. METHODS The Curing Coma Campaign Biospecimens and Biomarkers work group, composed of seven invited members, reviewed existing biomarker and biospecimens CDEs and conducted a systematic literature review for laboratory and molecular biomarkers using predetermined search words and standardized methodology. Identified CDEs and KDEs were adjudicated into core, basic, supplemental, or experimental CDEs per National Institutes of Health classification based on level of evidence, reproducibility, and generalizability across different diseases through a consensus process. RESULTS Among existing National Institutes of Health CDEs, those developed for ischemic stroke, traumatic brain injury, and subarachnoid hemorrhage were most relevant to DoC and included. KDEs were common to all disease states and included biospecimen collection time points, baseline indicator, biological source, anatomical location of collection, collection method, and processing and storage methodology. Additionally, two disease core, nine basic, 24 supplemental, and 59 exploratory biomarker CDEs were identified. Results were summarized and generated into a Laboratory Data and Biospecimens Case Report Form (CRF) and underwent public review. A final CRF version 1.0 is reported here. CONCLUSIONS Exponential growth in biomarkers development has generated a growing number of potential experimental biomarkers associated with DoC, but few meet the quality, reproducibility, and generalizability criteria to be classified as core and basic biomarker and biospecimen CDEs. Identification and adaptation of KDEs, however, contribute to standardizing methodology to promote harmonization of future biomarker and biospecimens studies in DoC. Development of this CRF serves as a basic building block for future DoC studies.
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Affiliation(s)
- Vishank A Shah
- Departments of Anesthesiology and Critical Care Medicine, Neurology, Neurosurgery, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - H E Hinson
- Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Michael E Reznik
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Cecil D Hahn
- Division of Neurology, Department of Paediatrics, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada
| | - Sheila Alexander
- School of Nursing, University of Pittsburgh, Pittsburgh, PA, USA
| | - Jonathan Elmer
- Department of Critical Care Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Neurology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Department of Emergency Medicine, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Sherry H-Y Chou
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
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19
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Gulamali F, Jayaraman P, Sawant AS, Desman J, Fox B, Chang A, Soong BY, Arivazaghan N, Reynolds AS, Duong SQ, Vaid A, Kovatch P, Freeman R, Hofer IS, Sakhuja A, Dangayach NS, Reich DS, Charney AW, Nadkarni GN. Derivation, External Validation and Clinical Implications of a deep learning approach for intracranial pressure estimation using non-cranial waveform measurements. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.30.24301974. [PMID: 38352556 PMCID: PMC10863000 DOI: 10.1101/2024.01.30.24301974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/19/2024]
Abstract
Importance Increased intracranial pressure (ICP) is associated with adverse neurological outcomes, but needs invasive monitoring. Objective Development and validation of an AI approach for detecting increased ICP (aICP) using only non-invasive extracranial physiological waveform data. Design Retrospective diagnostic study of AI-assisted detection of increased ICP. We developed an AI model using exclusively extracranial waveforms, externally validated it and assessed associations with clinical outcomes. Setting MIMIC-III Waveform Database (2000-2013), a database derived from patients admitted to an ICU in an academic Boston hospital, was used for development of the aICP model, and to report association with neurologic outcomes. Data from Mount Sinai Hospital (2020-2022) in New York City was used for external validation. Participants Patients were included if they were older than 18 years, and were monitored with electrocardiograms, arterial blood pressure, respiratory impedance plethysmography and pulse oximetry. Patients who additionally had intracranial pressure monitoring were used for development (N=157) and external validation (N=56). Patients without intracranial monitors were used for association with outcomes (N=1694). Exposures Extracranial waveforms including electrocardiogram, arterial blood pressure, plethysmography and SpO2. Main Outcomes and Measures Intracranial pressure > 15 mmHg. Measures were Area under receiver operating characteristic curves (AUROCs), sensitivity, specificity, and accuracy at threshold of 0.5. We calculated odds ratios and p-values for phenotype association. Results The AUROC was 0.91 (95% CI, 0.90-0.91) on testing and 0.80 (95% CI, 0.80-0.80) on external validation. aICP had accuracy, sensitivity, and specificity of 73.8% (95% CI, 72.0%-75.6%), 99.5% (95% CI 99.3%-99.6%), and 76.9% (95% CI, 74.0-79.8%) on external validation. A ten-percentile increment was associated with stroke (OR=2.12; 95% CI, 1.27-3.13), brain malignancy (OR=1.68; 95% CI, 1.09-2.60), subdural hemorrhage (OR=1.66; 95% CI, 1.07-2.57), intracerebral hemorrhage (OR=1.18; 95% CI, 1.07-1.32), and procedures like percutaneous brain biopsy (OR=1.58; 95% CI, 1.15-2.18) and craniotomy (OR = 1.43; 95% CI, 1.12-1.84; P < 0.05 for all). Conclusions and Relevance aICP provides accurate, non-invasive estimation of increased ICP, and is associated with neurological outcomes and neurosurgical procedures in patients without intracranial monitoring.
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Affiliation(s)
- Faris Gulamali
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Pushkala Jayaraman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ashwin S. Sawant
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Jacob Desman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Benjamin Fox
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Annie Chang
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Brian Y. Soong
- Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Naveen Arivazaghan
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexandra S. Reynolds
- Department of Neurosurgery and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Son Q Duong
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Akhil Vaid
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Patricia Kovatch
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Robert Freeman
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ira S. Hofer
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Ankit Sakhuja
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Neha S. Dangayach
- Department of Neurosurgery and Neurology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - David S. Reich
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander W Charney
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N. Nadkarni
- The Charles Bronfman Institute of Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
- The Division of Data Driven and Digital Medicine, Icahn School of Medicine at Mount Sinai, New York, NY
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20
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Su L, Liu S, Long Y, Chen C, Chen K, Chen M, Chen Y, Cheng Y, Cui Y, Ding Q, Ding R, Duan M, Gao T, Gu X, He H, He J, Hu B, Hu C, Huang R, Huang X, Jiang H, Jiang J, Lan Y, Li J, Li L, Li L, Li W, Li Y, Lin J, Luo X, Lyu F, Mao Z, Miao H, Shang X, Shang X, Shang Y, Shen Y, Shi Y, Sun Q, Sun W, Tang Z, Wang B, Wang H, Wang H, Wang L, Wang L, Wang S, Wang Z, Wang Z, Wei D, Wu J, Wu Q, Xing X, Yang J, Yang X, Yu J, Yu W, Yu Y, Yuan H, Zhai Q, Zhang H, Zhang L, Zhang M, Zhang Z, Zhao C, Zheng R, Zhong L, Zhou F, Zhu W. Chinese experts' consensus on the application of intensive care big data. Front Med (Lausanne) 2024; 10:1174429. [PMID: 38264049 PMCID: PMC10804886 DOI: 10.3389/fmed.2023.1174429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2023] [Accepted: 11/09/2023] [Indexed: 01/25/2024] Open
Abstract
The development of intensive care medicine is inseparable from the diversified monitoring data. Intensive care medicine has been closely integrated with data since its birth. Critical care research requires an integrative approach that embraces the complexity of critical illness and the computational technology and algorithms that can make it possible. Considering the need of standardization of application of big data in intensive care, Intensive Care Medicine Branch of China Health Information and Health Care Big Data Society, Standard Committee has convened expert group, secretary group and the external audit expert group to formulate Chinese Experts' Consensus on the Application of Intensive Care Big Data (2022). This consensus makes 29 recommendations on the following five parts: Concept of intensive care big data, Important scientific issues, Standards and principles of database, Methodology in solving big data problems, Clinical application and safety consideration of intensive care big data. The consensus group believes this consensus is the starting step of application big data in the field of intensive care. More explorations and big data based retrospective research should be carried out in order to enhance safety and reliability of big data based models of critical care field.
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Affiliation(s)
- Longxiang Su
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Shengjun Liu
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Yun Long
- Department of Critical Care Medicine, State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Chaodong Chen
- Department of Surgical Intensive Critical Unit, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China
| | - Kai Chen
- Department of Critical Care Medicine, Fujian Provincial Key Laboratory of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Provincial Center for Critical Care Medicine, Fuzhou, Fujian, China
| | - Ming Chen
- Department of Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Yaolong Chen
- Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Yisong Cheng
- Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Yating Cui
- Department of Critical Care Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qi Ding
- Department of Surgical Intensive Critical Unit, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China
| | - Renyu Ding
- Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Meili Duan
- Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Tao Gao
- Department of Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Xiaohua Gu
- Department of Critical Care Medicine, Northern Jiangsu People’s Hospital; Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Hongli He
- Intensive Care Unit, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, School of Medicine of University of Electronic Science and Technology, Chengdu, China
| | - Jiawei He
- Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Bo Hu
- Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Chang Hu
- Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Rui Huang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Xiaobo Huang
- Intensive Care Unit, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, School of Medicine of University of Electronic Science and Technology, Chengdu, China
| | - Huizhen Jiang
- Department of Information Center, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
| | - Jing Jiang
- Department of Critical Care Medicine, Chongqing General Hospital, Chongqing, China
| | - Yunping Lan
- Intensive Care Unit, Sichuan Academy of Medical Sciences & Sichuan Provincial People’s Hospital, School of Medicine of University of Electronic Science and Technology, Chengdu, China
| | - Jun Li
- Department of Critical Care Medicine, Fujian Provincial Key Laboratory of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Provincial Center for Critical Care Medicine, Fuzhou, Fujian, China
| | - Linfeng Li
- Medical Data Research Institute, Chongqing Medical University, Chongqing, China
| | - Lu Li
- Department of Critical Care Medicine, Zhongnan Hospital of Wuhan University, Wuhan, Hubei, China
| | - Wenxiong Li
- Department of Surgical Intensive Critical Unit, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China
| | - Yongzai Li
- Information Network Center, QiLu Hospital, ShanDong University, Jinan, China
| | - Jin Lin
- Department of Critical Care Medicine, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Xufei Luo
- Evidence-based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Feng Lyu
- Department of Computer Science and Engineering, Central South University, Changsha, China
| | - Zhi Mao
- Department of Critical Care Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - He Miao
- Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Xiaopu Shang
- Department of Information Management, Beijing Jiaotong University, Beijing, China
| | - Xiuling Shang
- Department of Critical Care Medicine, Fujian Provincial Key Laboratory of Critical Care Medicine, Shengli Clinical Medical College of Fujian Medical University, Fujian Provincial Hospital, Fujian Provincial Center for Critical Care Medicine, Fuzhou, Fujian, China
| | - You Shang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuwen Shen
- Intensive Care Unit of Cardiovascular Surgery Department, Qilu Hospital of Shandong University, Jinan, China
| | - Yinghuan Shi
- National Institute of Healthcare Data Science, Nanjing University, Nanjing, China
| | - Qihang Sun
- British Chinese Society of Health Informatics, Beijing, China
| | - Weijun Sun
- Faculty of Automation, Guangdong University of Technology, Guangzhou, China
| | - Zhiyun Tang
- Department of Intensive Care Unit, Zhejiang Provincial People’s Hospital, Affiliated People’s Hospital, Emergency and Intensive Care Unit Center, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Bo Wang
- Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Haijun Wang
- Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hongliang Wang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Li Wang
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences; School of Basic Medicine Peking Union Medical College, Beijing, China
| | - Luhao Wang
- Department of Critical Care Medicine, Sun Yat-Sen University First Affiliated Hospital, Guangzhou, China
| | - Sicong Wang
- Department of Critical Care Medicine, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China
| | - Zhanwen Wang
- Intensive Care Unit, XiangYa Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiang Ya Hospital, Central South University, Changsha, China
- Hunan Provincial Clinical Research Center for Critical Care Medicine, Xiang Ya Hospital, Central South University, Changsha, China
| | - Zhong Wang
- Department of Intensive Care Unit, The First Hospital of China Medical University, Shenyang, Liaoning, China
| | - Dong Wei
- National Institute of Healthcare Data Science, Nanjing University, Nanjing, China
| | - Jianfeng Wu
- Intensive Care Unit, XiangYa Hospital, Central South University, Changsha, China
| | - Qin Wu
- Department of Critical Care Medicine, West China Hospital of Sichuan University, Chengdu, China
| | - Xuezhong Xing
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences; School of Basic Medicine Peking Union Medical College, Beijing, China
| | - Jin Yang
- Department of Critical Care Medicine, Chongqing General Hospital, Chongqing, China
| | - Xianghong Yang
- Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiangquan Yu
- Department of Critical Care Medicine, Northern Jiangsu People’s Hospital; Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Wenkui Yu
- Department of Critical Care Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, Jiangsu, China
| | - Yuan Yu
- Intensive Care Unit of Cardiovascular Surgery Department, Qilu Hospital of Shandong University, Jinan, China
| | - Hao Yuan
- Department of Critical Care Medicine, Sun Yat-Sen University First Affiliated Hospital, Guangzhou, China
| | - Qian Zhai
- National Institute of Healthcare Data Science, Nanjing University, Nanjing, China
| | - Hao Zhang
- Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lina Zhang
- Intensive Care Unit, XiangYa Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiang Ya Hospital, Central South University, Changsha, China
- Hunan Provincial Clinical Research Center for Critical Care Medicine, Xiang Ya Hospital, Central South University, Changsha, China
| | - Meng Zhang
- Department of Critical Care Medicine, Chongqing General Hospital, Chongqing, China
| | - Zhongheng Zhang
- Department of Emergency Medicine, Key Laboratory of Precision Medicine in Diagnosis and Monitoring Research of Zhejiang Province, Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Chunguang Zhao
- Intensive Care Unit, XiangYa Hospital, Central South University, Changsha, China
- National Clinical Research Center for Geriatric Disorders, Xiang Ya Hospital, Central South University, Changsha, China
- Hunan Provincial Clinical Research Center for Critical Care Medicine, Xiang Ya Hospital, Central South University, Changsha, China
| | - Ruiqiang Zheng
- Department of Critical Care Medicine, Northern Jiangsu People’s Hospital; Clinical Medical College, Yangzhou University, Yangzhou, China
| | - Lei Zhong
- Department of Intensive Care Unit, National Cancer Center/National Clinical Research Center, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Feihu Zhou
- Department of Critical Care Medicine, The First Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Weiguo Zhu
- Department of General Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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21
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Foreman B, Kapinos G, Wainwright MS, Ngwenya LB, O'Phelan KH, LaRovere KL, Kirschen MP, Appavu B, Lazaridis C, Alkhachroum A, Maciel CB, Amorim E, Chang JJ, Gilmore EJ, Rosenthal ES, Park S. Practice Standards for the Use of Multimodality Neuromonitoring: A Delphi Consensus Process. Crit Care Med 2023; 51:1740-1753. [PMID: 37607072 PMCID: PMC11036878 DOI: 10.1097/ccm.0000000000006016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/24/2023]
Abstract
OBJECTIVES To address areas in which there is no consensus for the technologies, effort, and training necessary to integrate and interpret information from multimodality neuromonitoring (MNM). DESIGN A three-round Delphi consensus process. SETTING Electronic surveys and virtual meeting. SUBJECTS Participants with broad MNM expertise from adult and pediatric intensive care backgrounds. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Two rounds of surveys were completed followed by a virtual meeting to resolve areas without consensus and a final survey to conclude the Delphi process. With 35 participants consensus was achieved on 49% statements concerning MNM. Neurologic impairment and the potential for MNM to guide management were important clinical considerations. Experts reached consensus for the use of MNM-both invasive and noninvasive-for patients in coma with traumatic brain injury, aneurysmal subarachnoid hemorrhage, and intracranial hemorrhage. There was consensus that effort to integrate and interpret MNM requires time independent of daily clinical duties, along with specific skills and expertise. Consensus was reached that training and educational platforms are necessary to develop this expertise and to provide clinical correlation. CONCLUSIONS We provide expert consensus in the clinical considerations, minimum necessary technologies, implementation, and training/education to provide practice standards for the use of MNM to individualize clinical care.
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Affiliation(s)
- Brandon Foreman
- Department of Neurology & Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
| | - Gregory Kapinos
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Mark S Wainwright
- Division of Pediatric Neurology, Seattle Children's Hospital, University of Washington, Seattle, WA
| | - Laura B Ngwenya
- Department of Neurology & Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
- Department of Neurosurgery, University of Cincinnati, Cincinnati, OH
| | | | - Kerri L LaRovere
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
| | - Matthew P Kirschen
- Departments of Anesthesiology and Critical Care Medicine, Pediatrics and Neurology, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
| | - Brian Appavu
- Departments of Child Health and Neurology, Phoenix Children's, University of Arizona College of Medicine-Phoenix, Phoenix, AZ
| | - Christos Lazaridis
- Departments of Neurology and Neurosurgery, University of Chicago, Chicago, IL
| | | | - Carolina B Maciel
- Department of Neurology & Rehabilitation Medicine, University of Cincinnati, Cincinnati, OH
- Department of Neurosurgery, Icahn School of Medicine at Mount Sinai, New York, NY
- Division of Pediatric Neurology, Seattle Children's Hospital, University of Washington, Seattle, WA
- Department of Neurosurgery, University of Cincinnati, Cincinnati, OH
- Department of Neurology, University of Miami, Miami, FL
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, MA
- Departments of Anesthesiology and Critical Care Medicine, Pediatrics and Neurology, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA
- Departments of Child Health and Neurology, Phoenix Children's, University of Arizona College of Medicine-Phoenix, Phoenix, AZ
- Departments of Neurology and Neurosurgery, University of Chicago, Chicago, IL
- Departments of Neurology and Neurosurgery, University of Florida, Tampa, FL
- Department of Neurology, University of Utah, Salt Lake City, UT
- Department of Neurology, Yale University, New Haven, CT
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA
- Department of Critical Care and Georgetown University, Department of Neurology, MedStar Washington Hospital Center, Washington, DC
- Department of Neurology, Massachusetts General Hospital, Boston, MA
- Departments of Neurology and Biomedical Informatics, Columbia University, New York, NY
| | - Edilberto Amorim
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA
| | - Jason J Chang
- Department of Critical Care and Georgetown University, Department of Neurology, MedStar Washington Hospital Center, Washington, DC
| | | | - Eric S Rosenthal
- Department of Neurology, Massachusetts General Hospital, Boston, MA
| | - Soojin Park
- Departments of Neurology and Biomedical Informatics, Columbia University, New York, NY
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22
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Frontera JA, Fang T, Grayson K, Lalchan R, Dickstein L, Hussain MS, Kahn DE, Lord AS, Mazzuchin D, Melmed KR, Rutledge C, Zhou T, Lewis A. Poor Accuracy of Manually Derived Head Computed Tomography Parameters in Predicting Intracranial Hypertension After Nontraumatic Intracranial Hemorrhage. Neurocrit Care 2023; 39:677-689. [PMID: 36577900 DOI: 10.1007/s12028-022-01662-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Accepted: 12/08/2022] [Indexed: 12/29/2022]
Abstract
BACKGROUND The utility of head computed tomography (CT) in predicting elevated intracranial pressure (ICP) is known to be limited in traumatic brain injury; however, few data exist in patients with spontaneous intracranial hemorrhage. METHODS We conducted a retrospective review of prospectively collected data in patients with nontraumatic intracranial hemorrhage (subarachnoid hemorrhage [SAH] or intraparenchymal hemorrhage [IPH]) who underwent external ventricular drain (EVD) placement. Head CT scans performed immediately prior to EVD placement were quantitatively reviewed for features suggestive of elevated ICP, including temporal horn diameter, bicaudate index, basal cistern effacement, midline shift, and global cerebral edema. The modified Fisher score (mFS), intraventricular hemorrhage score, and IPH volume were also measured, as applicable. We calculated the accuracy, positive predictive value (PPV), and negative predictive value (NPV) of these radiographic features for the coprimary outcomes of elevated ICP (> 20 mm Hg) at the time of EVD placement and at any time during the hospital stay. Multivariable backward stepwise logistic regression analysis was performed to identify significant radiographic factors associated with elevated ICP. RESULTS Of 608 patients with intracranial hemorrhages enrolled during the study time frame, 243 (40%) received an EVD and 165 (n = 107 SAH, n = 58 IPH) had a preplacement head CT scan available for rating. Elevated opening pressure and elevated ICP during hospitalization were recorded in 48 of 152 (29%) and 103 of 165 (62%), respectively. The presence of ≥ 1 radiographic feature had only 32% accuracy for identifying elevated opening pressure (PPV 30%, NPV 58%, area under the curve [AUC] 0.537, 95% asymptotic confidence interval [CI] 0.436-0.637, P = 0.466) and 59% accuracy for predicting elevated ICP during hospitalization (PPV 63%, NPV 40%, AUC 0.514, 95% asymptotic CI 0.391-0.638, P = 0.820). There was no significant association between the number of radiographic features and ICP elevation. Head CT scans without any features suggestive of elevated ICP occurred in 25 of 165 (15%) patients. However, 10 of 25 (40%) of these patients had elevated opening pressure, and 15 of 25 (60%) had elevated ICP during their hospital stay. In multivariable models, mFS (adjusted odds ratio [aOR] 1.36, 95% CI 1.10-1.68) and global cerebral edema (aOR 2.93, 95% CI 1.27-6.75) were significantly associated with elevated ICP; however, their accuracies were only 69% and 60%, respectively. All other individual radiographic features had accuracies between 38 and 58% for identifying intracranial hypertension. CONCLUSIONS More than 50% of patients with spontaneous intracranial hemorrhage without radiographic features suggestive of elevated ICP actually had ICP > 20 mm Hg during EVD placement or their hospital stay. Morphological head CT findings were only 32% and 59% accurate in identifying elevated opening pressure and ICP elevation during hospitalization, respectively.
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Affiliation(s)
- Jennifer A Frontera
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA.
- Department of Neurosurgery, Mount Sinai School of Medicine, New York, NY, USA.
- Cerebrovascular Center of the Neurological Institute, Cleveland Clinic, Cleveland, OH, USA.
| | - Taolin Fang
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Kammi Grayson
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Rebecca Lalchan
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Leah Dickstein
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
- Department of Neurosurgery, New York University School of Medicine, New York, NY, USA
| | - M Shazam Hussain
- Cerebrovascular Center of the Neurological Institute, Cleveland Clinic, Cleveland, OH, USA
| | - D Ethan Kahn
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Aaron S Lord
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Daniel Mazzuchin
- Department of Neurosurgery, New York University School of Medicine, New York, NY, USA
| | - Kara R Melmed
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
- Department of Neurosurgery, New York University School of Medicine, New York, NY, USA
| | - Caleb Rutledge
- Department of Neurosurgery, New York University School of Medicine, New York, NY, USA
| | - Ting Zhou
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
| | - Ariane Lewis
- Department of Neurology, New York University School of Medicine, 150 55th St., Brooklyn, New York, NY, USA
- Department of Neurosurgery, New York University School of Medicine, New York, NY, USA
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23
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Heino I, Sajanti A, Lyne SB, Frantzén J, Girard R, Cao Y, Ritala JF, Katila AJ, Takala RS, Posti JP, Saarinen AJ, Hellström S, Laukka D, Saarenpää I, Rahi M, Tenovuo O, Rinne J, Koskimäki J. Outcome and survival of surgically treated acute subdural hematomas and postcraniotomy hematomas - A retrospective cohort study. BRAIN & SPINE 2023; 3:102714. [PMID: 38105801 PMCID: PMC10724206 DOI: 10.1016/j.bas.2023.102714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Revised: 11/13/2023] [Accepted: 11/17/2023] [Indexed: 12/19/2023]
Abstract
Background The morbidity and mortality of acute subdural hematoma (aSDH) remains high. Several factors have been reported to affect the outcome and survival of these patients. In this study, we explored factors potentially associated with the outcome and survival of surgically treated acute subdural hematoma (aSDH), including postcraniotomy hematomas (PCHs). Methods This retrospective cohort study was conducted in a single tertiary university hospital between 2008 and 2012 and all aSDH patients that underwent surgical intervention were included. A total of 132 cases were identified for collection of demographics, clinical, laboratory, and imaging data. Univariate and multivariable analyses were performed to assess factors associated with three-month Glasgow Outcome Scale (GOS) and survival at one- and five-year. Results In this study, PCH (n = 14, 10.6%) was not associated with a worse outcome according to the 3- month GOS (p = 0.37) or one (p = 0.34) and five-year (p = 0.37) survival. The multivariable analysis showed that the volume of initial hematoma (p = 0.009) and Abbreviated Injury Scale score (p = 0.016) were independent predictors of the three-month GOS. Glasgow Coma Scale (GCS) score (p < 0.001 and p = 0.037) and age (p = 0.048 and p = 0.003) were predictors for one and five-year survival, while use of antiplatelet drug (p = 0.030), neuroworsening (p = 0.005) and smoking (p = 0.026) were significant factors impacting one year survival. In addition, blood alcohol level on admission was a predictor for five-year survival (p = 0.025). Conclusions These elucidations underscore that, although PCHs are pertinent, a comprehensive appreciation of multifarious variables is indispensable in aSDH prognosis. These findings are observational, not causal. Expanded research endeavors are advocated to corroborate these insights.
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Affiliation(s)
- Iiro Heino
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Antti Sajanti
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Seán B. Lyne
- Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Janek Frantzén
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Romuald Girard
- Neurovascular Surgery Program, Section of Neurosurgery, The University of Chicago Medicine and Biological Sciences, (5841 S. Maryland), Chicago, IL, 60637, USA
| | - Ying Cao
- Department of Radiation Oncology, Kansas University Medical Center, Kansas City, KS, 66160, USA
| | - Joel F. Ritala
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Ari J. Katila
- Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Riikka S.K. Takala
- Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Jussi P. Posti
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
- Neurocenter, Turku Brain Injury Center, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
- Department of Clinical Neurosciences, University of Turku, P.O. Box 52 (Kiinamyllynkatu 4-8), FI-20520, Turku, Finland
| | - Antti J. Saarinen
- Department of Paediatric Orthopaedic Surgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Santtu Hellström
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Dan Laukka
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Ilkka Saarenpää
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Melissa Rahi
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Olli Tenovuo
- Neurocenter, Turku Brain Injury Center, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
- Department of Clinical Neurosciences, University of Turku, P.O. Box 52 (Kiinamyllynkatu 4-8), FI-20520, Turku, Finland
| | - Jaakko Rinne
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
| | - Janne Koskimäki
- Neurocenter, Department of Neurosurgery, Turku University Hospital and University of Turku, P.O. Box 52 (Hämeentie 11), FI-20521, Turku, Finland
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24
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Fainberg NA, Silver MR, Arena JD, Landzberg EI, Banwell B, Gambrah-Lyles C, Kirschen MP, Madsen PJ, McLendon L, Narula S, Tucker AM, Huh JW, Kienzle MF. Invasive Multimodality Neuromonitoring to Manage Cerebral Edema in Pediatric Myelin Oligodendrocyte Glycoprotein Antibody-Associated Disease. Crit Care Explor 2023; 5:e1003. [PMID: 37929184 PMCID: PMC10624473 DOI: 10.1097/cce.0000000000001003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2023] Open
Abstract
Background Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is an inflammatory disorder of the CNS with a variety of clinical manifestations, including cerebral edema. Case Summary A 7-year-old boy presented with headaches, nausea, and somnolence. He was found to have cerebral edema that progressed to brainstem herniation. Invasive multimodality neuromonitoring was initiated to guide management of intracranial hypertension and cerebral hypoxia while he received empiric therapies for neuroinflammation. Workup revealed serum myelin oligodendrocyte glycoprotein antibodies. He survived with a favorable neurologic outcome. Conclusion We describe a child who presented with cerebral edema and was ultimately diagnosed with MOGAD. Much of his management was guided using data from invasive multimodality neuromonitoring. Invasive multimodality neuromonitoring may have utility in managing life-threatening cerebral edema due to neuroinflammation.
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Affiliation(s)
- Nina A Fainberg
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Maya R Silver
- Division of Child Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - John D Arena
- Division of Neurosurgery, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Elizabeth I Landzberg
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Brenda Banwell
- Division of Child Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Claudia Gambrah-Lyles
- Division of Child Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Matthew P Kirschen
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
- Division of Child Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Peter J Madsen
- Division of Neurosurgery, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Loren McLendon
- Division of Child and Adolescent Neurology, Mayo Clinic College of Medicine and Science, Jacksonville, FL
- Division of Pediatric Neurology, Nemours Children's Health, Jacksonville, FL
| | - Sona Narula
- Division of Child Neurology, Children's Hospital of Philadelphia, Departments of Neurology and Pediatrics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Alexander M Tucker
- Division of Neurosurgery, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Jimmy W Huh
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
| | - Martha F Kienzle
- Division of Critical Care Medicine, Children's Hospital of Philadelphia, Department of Anesthesiology and Critical Care Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA
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25
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Svedung Wettervik T, Engquist H, Hånell A, Howells T, Rostami E, Ronne-Engström E, Lewén A, Enblad P. Cerebral Microdialysis Monitoring of Energy Metabolism: Relation to Cerebral Blood Flow and Oxygen Delivery in Aneurysmal Subarachnoid Hemorrhage. J Neurosurg Anesthesiol 2023; 35:384-393. [PMID: 35543615 DOI: 10.1097/ana.0000000000000854] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 03/31/2022] [Indexed: 12/21/2022]
Abstract
INTRODUCTION In this study, we investigated the roles of cerebral blood flow (CBF) and cerebral oxygen delivery (CDO 2 ) in relation to cerebral energy metabolism after aneurysmal subarachnoid hemorrhage (aSAH). METHODS Fifty-seven adult aSAH patients treated on the neurointensive care unit at Uppsala, Sweden between 2012 and 2020, with at least 1 xenon-enhanced computed tomography (Xe-CT) scan in the first 14 days after ictus and concurrent microdialysis (MD) monitoring, were included in this retrospective study. CBF was measured globally and focally (around the MD catheter) with Xe-CT, and CDO 2 calculated. Cerebral energy metabolites were measured using MD. RESULTS Focal ischemia (CBF <20 mL/100 g/min around the MD catheter was associated with lower median [interquartile range]) MD-glucose (1.2 [0.7 to 2.2] mM vs. 2.3 [1.3 to 3.5] mM; P =0.05) and higher MD-lactate-pyruvate (LPR) ratio (34 [29 to 66] vs. 25 [21 to 32]; P =0.02). A compensated/normal MD pattern (MD-LPR <25) was observed in the majority of patients (22/23, 96%) without focal ischemia, whereas 4 of 11 (36%) patients with a MD pattern of poor substrate supply (MD-LPR >25, MD-pyruvate <120 µM) had focal ischemia as did 5 of 20 (25%) patients with a pattern of mitochondrial dysfunction (MD-LPR >25, MD-pyruvate >120 µM) ( P =0.04). Global CBF and CDO 2 , and focal CDO 2 , were not associated with the MD variables. CONCLUSIONS While MD is a feasible tool to study cerebral energy metabolism, its validity is limited to a focal area around the MD catheter. Cerebral energy disturbances were more related to low CBF than to low CDO 2 . Considering the high rate of mitochondrial dysfunction, treatments that increase CBF but not CDO 2 , such as hemodilution, may still benefit glucose delivery to drive anaerobic metabolism.
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Affiliation(s)
| | - Henrik Engquist
- Department of Surgical Sciences/Anesthesia and Intensive Care, Uppsala University, Uppsala, Sweden
| | | | | | | | | | - Anders Lewén
- Section of Neurosurgery, Department of Neuroscience
| | - Per Enblad
- Section of Neurosurgery, Department of Neuroscience
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26
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Gomez A, Griesdale D, Froese L, Yang E, Thelin EP, Raj R, Aries M, Gallagher C, Bernard F, Kramer AH, Zeiler FA. Temporal Statistical Relationship between Regional Cerebral Oxygen Saturation (rSO 2) and Brain Tissue Oxygen Tension (PbtO 2) in Moderate-to-Severe Traumatic Brain Injury: A Canadian High Resolution-TBI (CAHR-TBI) Cohort Study. Bioengineering (Basel) 2023; 10:1124. [PMID: 37892854 PMCID: PMC10604223 DOI: 10.3390/bioengineering10101124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 09/18/2023] [Accepted: 09/22/2023] [Indexed: 10/29/2023] Open
Abstract
Brain tissue oxygen tension (PbtO2) has emerged as a cerebral monitoring modality following traumatic brain injury (TBI). Near-infrared spectroscopy (NIRS)-based regional cerebral oxygen saturation (rSO2) can non-invasively examine cerebral oxygen content and has the potential for high spatial resolution. Past studies examining the relationship between PbtO2 and NIRS-based parameters have had conflicting results with varying degrees of correlation. Understanding this relationship will help guide multimodal monitoring practices and impact patient care. The aim of this study is to examine the relationship between PbtO2 and rSO2 in a cohort of TBI patients by leveraging contemporary statistical methods. A multi-institutional retrospective cohort study of prospectively collected data was performed. Moderate-to-severe adult TBI patients were included with concurrent rSO2 and PbtO2 monitoring during their stay in the intensive care unit (ICU). The high-resolution data were analyzed utilizing time series techniques to examine signal stationarity as well as the cross-correlation relationship between the change in PbtO2 and the change in rSO2 signals. Finally, modeling of the change in PbtO2 by the change in rSO2 was attempted utilizing linear methods that account for the autocorrelative nature of the data signals. A total of 20 subjects were included in the study. Cross-correlative analysis found that changes in PbtO2 were most significantly correlated with changes in rSO2 one minute earlier. Through mixed-effects and time series modeling of parameters, changes in rSO2 were found to often have a statistically significant linear relationship with changes in PbtO2 that occurred a minute later. However, changes in rSO2 were inadequate to predict changes in PbtO2. In this study, changes in PbtO2 were found to correlate most with changes in rSO2 approximately one minute earlier. While changes in rSO2 were found to contain information about future changes in PbtO2, they were not found to adequately model them. This strengthens the body of literature indicating that NIRS-based rSO2 is not an adequate substitute for PbtO2 in the management of TBI.
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Affiliation(s)
- Alwyn Gomez
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Donald Griesdale
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Logan Froese
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
| | - Eleen Yang
- Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC V6T 1Z4, Canada
| | - Eric P. Thelin
- Department of Neurology, Karolinska University Hospital, 171 76 Stockholm, Sweden
- Department of Clinical Neuroscience, Karolinska Institutet, 171 76 Stockholm, Sweden
| | - Rahul Raj
- Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, FI-00029 Helsinki, Finland
| | - Marcel Aries
- Department of Intensive Care, Maastricht University Medical Center, 6229 Maastricht, The Netherlands
- School of Mental Health and Neurosciences, University Maastricht, 6211 Maastricht, The Netherlands
| | - Clare Gallagher
- Section of Neurosurgery, Department of Clinical Neurosciences, University of Calgary, Calgary, AB T2N 1N4, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Francis Bernard
- Section of Critical Care, Department of Medicine, University of Montreal, Montreal, QC H3T 1J4, Canada
| | - Andreas H. Kramer
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB T2N 1N4, Canada
- Hotchkiss Brain Institute, University of Calgary, Calgary, AB T2N 1N4, Canada
- Department of Critical Care Medicine, University of Calgary, Calgary, AB T2N 1N4, Canada
| | - Frederick A. Zeiler
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Department of Clinical Neuroscience, Karolinska Institutet, 171 76 Stockholm, Sweden
- Centre on Aging, University of Manitoba, Winnipeg, MB R3T 2N2, Canada
- Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge CB2 1TN, UK
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27
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Ginstman F, Ghafouri B, Zsigmond P. Altered levels of transthyretin in human cerebral microdialysate after subarachnoid haemorrhage using proteomics; a descriptive pilot study. Proteome Sci 2023; 21:10. [PMID: 37420193 DOI: 10.1186/s12953-023-00210-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2022] [Accepted: 06/19/2023] [Indexed: 07/09/2023] Open
Abstract
BACKGROUND Subarachnoid haemorrhage (SAH) is one of the most severe forms of stroke in which delayed cerebral ischemia is one of the major complications. Neurointensive care aims at preventing and treating such complications and identification of biomarkers of early signs of ischemia might therefore be helpful. METHODS We aimed at describing proteome profile in cerebral microdialysate in four patients with aneurysmal SAH using two dimensional gel electrophoresis in combination with mass spectrometry in search for new biomarkers for delayed cerebral ischemia and to investigate if there were temporal fluctuations in those biomarkers over time after aneurysmal bleed. RESULTS The results showed transthyretin in nine different proteoforms (1001, 1102, 2101, 3101, 4101, 4102, 5001, 5101, 6101) in cerebral microdialysate samples from four patients having sustained SAH. Several proteoforms show highly differing levels and pooled analysis of all samples showed varying optical density related to time from aneurysmal bleed, indicating a temporal evolution. CONCLUSIONS Transthyretin proteoforms have not earlier been shown in cerebral microdialysate after SAH and we describe differing levels based on proteoform as well as time from subarachnoid bleed. Transthyretin is well known to be synthetized in choroid plexus, whilst intraparenchymal synthesis remains controversial. The results need to be confirmed in larger studies in order to further describe transthyretin.
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Affiliation(s)
- Fredrik Ginstman
- Department of Neurosurgery in Linköping and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
| | - Bijar Ghafouri
- Pain and Rehabilitation Center and Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden
| | - Peter Zsigmond
- Department of Neurosurgery in Linköping and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
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28
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Lam MSH, Luoma AMV, Reddy U. Acute perioperative neurological emergencies. Int Anesthesiol Clin 2023; 61:53-63. [PMID: 37249171 DOI: 10.1097/aia.0000000000000404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Affiliation(s)
- Michelle S H Lam
- Department of Neuroanaesthesia and Neurocritical Care, The National Hospital for Neurology and Neurosurgery, London, UK
| | - Astri M V Luoma
- Department of Neuroanaesthesia and Neurocritical Care, The National Hospital for Neurology and Neurosurgery, London, UK
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - Ugan Reddy
- Department of Neuroanaesthesia and Neurocritical Care, The National Hospital for Neurology and Neurosurgery, London, UK
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
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29
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Lewis A. International variability in the diagnosis and management of disorders of consciousness. Presse Med 2023; 52:104162. [PMID: 36564000 DOI: 10.1016/j.lpm.2022.104162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/31/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022] Open
Abstract
This manuscript explores the international variability in the diagnosis and management of disorders of consciousness (DoC). The identification, evaluation, intervention, exploration, prognostication and limitation of therapy for patients with DoC is reviewed through an international lens. The myriad factors that impact the diagnosis and management of DoC including 1) financial, 2) legal and regulatory, 3) cultural, 4) religious and 5) psychosocial considerations are discussed. As data comparing patients with DoC internationally are limited, findings from the general critical care or neurocritical care literature are described when information specific to patients with DoC is unavailable. There is a need for improvements in clinical care, education, advocacy and research related to patients with DoC worldwide. It is imperative to standardize methodology to evaluate consciousness and prognosticate outcome. Further, education is needed to 1) generate awareness of the impact of the aforementioned considerations on patients with DoC and 2) develop techniques to optimize communication about DoC with families. It is necessary to promote equity in access to expertise and resources for patients with DoC to enhance the care of patients with DoC worldwide. Improving understanding and management of patients with DoC requires harmonization of existing datasets, development of registries where none exist and establishment of international clinical trial networks that include patients in all phases along the spectrum of care. The work of international organizations like the Curing Coma Campaign can hopefully minimize international variability in the diagnosis and management of DoC and optimize care.
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Affiliation(s)
- Ariane Lewis
- Departments of Neurology and Neurosurgery, NYU Langone Medical Center, New York, NY, United States.
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30
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de Almeida Souza D, Branco MW, Carraro Junior H, Zocolotti AMD, Takeda SYM, Valderramas S. Mechanical hyperinflation maneuver and intracranial compliance of critical neurological patients: protocol for a randomized controlled equivalence trial. Trials 2023; 24:348. [PMID: 37218023 DOI: 10.1186/s13063-023-07362-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 05/08/2023] [Indexed: 05/24/2023] Open
Abstract
BACKGROUND Mechanical hyperinflation maneuver (MHM) is a technique known for optimizing bronchial hygiene and respiratory mechanics; however, its effects on intracranial compliance are not known. METHODS Sixty patients aged ≥ 18 years, with clinical diagnosis of acute stroke, confirmed by neuroimaging examination, with onset of symptoms within 72 h, under mechanical ventilation through tracheal tube, will participate in this study. Participants will be randomly allocated into 2 groups: experimental group (n = 30)-MHM plus tracheal aspiration-and control group (n = 30)-tracheal aspiration only. Intracranial compliance will be measured by a non-invasive technique using Brain4care BcMM-R-2000 sensor. This will be the primary outcome. Results will be recorded at 5 times: T0 (start of monitoring), T1 (moment before MHM), T2 (moment after the MHM and before tracheal aspiration), T3 (moment after tracheal aspiration), T4, and T5 (monitoring 10 and 20 min after T3). Secondary outcomes are respiratory mechanics and hemodynamic parameters. DISCUSSION This study will be the first clinical trial to examine the effects and safety of MHM on intracranial compliance measured by non-invasive monitoring. Limitation includes the impossibility of blinding the physical therapist who will supervise the interventions. It is expected with this study to demonstrate that MHM can improve respiratory mechanics and hemodynamic parameters and provide a safe intervention with no changes in intracranial compliance in stroke patients.
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Affiliation(s)
- Daniela de Almeida Souza
- Internal Medicine and Health Sciences, Universidade Federal Do Parana, Avenida Coronel Francisco H. Dos Santos, 100, Caixa Postal 19031, Centro Politécnico, Jardim das Américas, Curitiba, PR, 81531-980, Brazil.
- Physiotherapist from Empresa Brasileira de Serviços Hospitalares, Rio de Janeiro, Brazil.
| | - Marina Wolff Branco
- Internal Medicine and Health Sciences, Universidade Federal Do Parana, Avenida Coronel Francisco H. Dos Santos, 100, Caixa Postal 19031, Centro Politécnico, Jardim das Américas, Curitiba, PR, 81531-980, Brazil
| | | | - Ana Márcia Delattre Zocolotti
- Department of Prevention and Rehabilitation in Physiotherapy of the Universidade Federal Do Parana, Curitiba, PR, Brazil
| | - Sibele Yoko Mattozo Takeda
- Department of Prevention and Rehabilitation in Physiotherapy of the Universidade Federal Do Parana, Curitiba, PR, Brazil
| | - Silvia Valderramas
- Internal Medicine and Health Sciences and Department of Prevention and Rehabilitation in Physical Therapy, Universidade Federal Do Parana, Curitiba, PR, Brazil
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31
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Vitt JR, Loper NE, Mainali S. Multimodal and autoregulation monitoring in the neurointensive care unit. Front Neurol 2023; 14:1155986. [PMID: 37153655 PMCID: PMC10157267 DOI: 10.3389/fneur.2023.1155986] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 04/04/2023] [Indexed: 05/10/2023] Open
Abstract
Given the complexity of cerebral pathology in patients with acute brain injury, various neuromonitoring strategies have been developed to better appreciate physiologic relationships and potentially harmful derangements. There is ample evidence that bundling several neuromonitoring devices, termed "multimodal monitoring," is more beneficial compared to monitoring individual parameters as each may capture different and complementary aspects of cerebral physiology to provide a comprehensive picture that can help guide management. Furthermore, each modality has specific strengths and limitations that depend largely on spatiotemporal characteristics and complexity of the signal acquired. In this review we focus on the common clinical neuromonitoring techniques including intracranial pressure, brain tissue oxygenation, transcranial doppler and near-infrared spectroscopy with a focus on how each modality can also provide useful information about cerebral autoregulation capacity. Finally, we discuss the current evidence in using these modalities to support clinical decision making as well as potential insights into the future of advanced cerebral homeostatic assessments including neurovascular coupling.
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Affiliation(s)
- Jeffrey R. Vitt
- Department of Neurological Surgery, UC Davis Medical Center, Sacramento, CA, United States
- Department of Neurology, UC Davis Medical Center, Sacramento, CA, United States
| | - Nicholas E. Loper
- Department of Neurological Surgery, UC Davis Medical Center, Sacramento, CA, United States
| | - Shraddha Mainali
- Department of Neurology, Virginia Commonwealth University, Richmond, VA, United States
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Okyay RD, Küçükosman G, Köksal BG, Pişkin Ö, Ayoğlu H. Effects of Supraglottic Airway Devices on Hemodynamic Response and Optic Nerve Sheath Diameter: Proseal LMA, LMA Supreme, and I-gel LMA. MEDICINA (KAUNAS, LITHUANIA) 2023; 59:medicina59040753. [PMID: 37109710 PMCID: PMC10146641 DOI: 10.3390/medicina59040753] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 04/06/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023]
Abstract
Background and Objectives: Supraglottic airway devices (SADs) are known to be useful in eliminating the drawbacks of laryngoscopy and tracheal intubation, especially ocular pressure and stress responses. The ultrasonographic measurement of optic nerve sheath diameter (ONSD) reflects increases in intracranial pressure (ICP). In our study, we aimed to compare the effects of SADs on hemodynamic response and ONSD. Materials and Methods: Our prospective study included 90 ASA I-II patients over the age of 18 who did not have a history of difficult intubation or ophthalmic pathology. The patients were randomly divided into three groups based on the laryngeal mask airway (LMA) devices used: ProSeal LMA (pLMA, n = 30), LMA Supreme (sLMA, n = 30), and I-gel (n = 30). The bilateral ONSD measurements and hemodynamic data of the patients who underwent standard anesthesia induction and monitoring were recorded before induction (T0) and 1 min (T1), 5 min (T5), and 10 min (T10) after SAD placement. Results: At all measurement times, the hemodynamic responses and ONSD values of the groups were similar. In all three groups, intergroup hemodynamic changes at T0 and T1 were similar and higher than those at other times of measurement (p < 0.001). The ONSD values of all groups increased at T1, and they tended to return to baseline values afterward (p < 0.001). Conclusions: We concluded that all three SADs could be used safely because they preserved both hemodynamic stability and ONSD changes in their placement processes, and they did not cause elevations in ONSD to an extent that would lead to increased ICP.
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Affiliation(s)
- Rahşan Dilek Okyay
- Anesthesiology and Reanimation Department, Faculty of Medicine, Zonguldak Bülent Ecevit University, Zonguldak 67600, Turkey
| | - Gamze Küçükosman
- Anesthesiology and Reanimation Department, Faculty of Medicine, Zonguldak Bülent Ecevit University, Zonguldak 67600, Turkey
| | - Bengü Gülhan Köksal
- Anesthesiology and Reanimation Department, Faculty of Medicine, Zonguldak Bülent Ecevit University, Zonguldak 67600, Turkey
| | - Özcan Pişkin
- Anesthesiology and Reanimation Department, Faculty of Medicine, Zonguldak Bülent Ecevit University, Zonguldak 67600, Turkey
| | - Hilal Ayoğlu
- Anesthesiology and Reanimation Department, Faculty of Medicine, Zonguldak Bülent Ecevit University, Zonguldak 67600, Turkey
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Svedung Wettervik T, Lewén A, Enblad P. Fine tuning of neurointensive care in aneurysmal subarachnoid hemorrhage: From one-size-fits-all towards individualized care. World Neurosurg X 2023; 18:100160. [PMID: 36818739 PMCID: PMC9932216 DOI: 10.1016/j.wnsx.2023.100160] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 01/20/2023] [Accepted: 01/22/2023] [Indexed: 01/25/2023] Open
Abstract
Aneurysmal subarachnoid hemorrhage (aSAH) is a severe type of acute brain injury with high mortality and burden of neurological sequelae. General management aims at early aneurysm occlusion to prevent re-bleeding, cerebrospinal fluid drainage in case of increased intracranial pressure and/or acute hydrocephalus, and cerebral blood flow augmentation in case of delayed ischemic neurological deficits. In addition, the brain is vulnerable to physiological insults in the acute phase and neurointensive care (NIC) is important to optimize the cerebral physiology to avoid secondary brain injury. NIC has led to significantly better neurological recovery following aSAH, but there is still great room for further improvements. First, current aSAH NIC management protocols are to some extent extrapolated from those in traumatic brain injury, notwithstanding important disease-specific differences. Second, the same NIC management protocols are applied to all aSAH patients, despite great patient heterogeneity. Third, the main variables of interest, intracranial pressure and cerebral perfusion pressure, may be too superficial to fully detect and treat several important pathomechanisms. Fourth, there is a lack of understanding not only regarding physiological, but also cellular and molecular pathomechanisms and there is a need to better monitor and treat these processes. This narrative review aims to discuss current state-of-the-art NIC of aSAH, knowledge gaps in the field, and future directions towards a more individualized care in the future.
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Affiliation(s)
- Teodor Svedung Wettervik
- Department of Medical Sciences, Section of Neurosurgery, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Anders Lewén
- Department of Medical Sciences, Section of Neurosurgery, Uppsala University, SE-751 85, Uppsala, Sweden
| | - Per Enblad
- Department of Medical Sciences, Section of Neurosurgery, Uppsala University, SE-751 85, Uppsala, Sweden
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Waak M, Laing J, Nagarajan L, Lawn N, Harvey AS. Continuous electroencephalography in the intensive care unit: A critical review and position statement from an Australian and New Zealand perspective. CRIT CARE RESUSC 2023; 25:9-19. [PMID: 37876987 PMCID: PMC10581281 DOI: 10.1016/j.ccrj.2023.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2023]
Abstract
Objectives This article aims to critically review the literature on continuous electroencephalography (cEEG) monitoring in the intensive care unit (ICU) from an Australian and New Zealand perspective and provide recommendations for clinicians. Design and review methods A taskforce of adult and paediatric neurologists, selected by the Epilepsy Society of Australia, reviewed the literature on cEEG for seizure detection in critically ill neonates, children, and adults in the ICU. The literature on routine EEG and cEEG for other indications was not reviewed. Following an evaluation of the evidence and discussion of controversial issues, consensus was reached, and a document that highlighted important clinical, practical, and economic considerations regarding cEEG in Australia and New Zealand was drafted. Results This review represents a summary of the literature and consensus opinion regarding the use of cEEG in the ICU for detection of seizures, highlighting gaps in evidence, practical problems with implementation, funding shortfalls, and areas for future research. Conclusion While cEEG detects electrographic seizures in a significant proportion of at-risk neonates, children, and adults in the ICU, conferring poorer neurological outcomes and guiding treatment in many settings, the health economic benefits of treating such seizures remain to be proven. Presently, cEEG in Australian and New Zealand ICUs is a largely unfunded clinical resource that is subsequently reserved for the highest-impact patient groups. Wider adoption of cEEG requires further research into impact on functional and health economic outcomes, education and training of the neurology and ICU teams involved, and securement of the necessary resources and funding to support the service.
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Affiliation(s)
- Michaela Waak
- Paediatric Critical Care Research Group, Child Health Research Centre, The University of Queensland, Brisbane, Australia
- Paediatric Intensive Care Unit, Queensland Children's Hospital, South Brisbane, Australia
| | - Joshua Laing
- Department of Neurosciences, Central Clinical School, Monash University, Melbourne, Australia
- Comprehensive Epilepsy Program, Alfred Health, Melbourne, Australia
- Department of Neurology, The Royal Melbourne Hospital, Melbourne, Australia
| | - Lakshmi Nagarajan
- Department of Neurology, Perth Children's Hospital, Perth, Australia
- Faculty of Health and Medical Sciences, University of Western Australia, Perth, Australia
- Telethon Kids Institute, Perth Children's Hospital, Perth, Australia
| | - Nicholas Lawn
- Western Australian Adult Epilepsy Service, Sir Charles Gardiner Hospital, Perth, Australia
| | - A. Simon Harvey
- Department of Neurology, The Royal Children's Hospital, Melbourne, Australia
- Department of Paediatrics, The University of Melbourne, Melbourne, Australia
- Neurosciences Research Group, Murdoch Children's Research Institute, Melbourne, Australia
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Heck C. Invasive Neuromonitoring in the Stroke Patient. Crit Care Nurs Clin North Am 2023; 35:83-94. [PMID: 36774009 DOI: 10.1016/j.cnc.2022.10.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
With advances in technology, the options to manage patients with neurologic injuries are often complex. Critical care management of neurologic injury has historically focused on the prevention of secondary ischemic injury through aggressive management of intracranial pressure (ICP) and maintenance of adequate cerebral perfusion pressure (CPP). However, ICP monitoring alone does not identify ischemic changes that herald patient deterioration. Advocates of multimodality monitoring cite the value of early detection of changes in brain oxygenation levels and brain metabolism as advantageous in optimizing stroke outcomes. ICP monitoring alone should not be the sole source of information on which therapy is guided but should be incorporated into the arsenal of emerging and promising invasive neuromonitoring devices.
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Affiliation(s)
- Carey Heck
- Adult-Gerontology Acute Care Nurse Practitioner Program, Thomas Jefferson University, 901 Walnut Street, Suite 815, Philadelphia, PA 19107, USA.
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36
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Fan TH, Rosenthal ES. Physiological Monitoring in Patients with Acute Brain Injury: A Multimodal Approach. Crit Care Clin 2023; 39:221-233. [PMID: 36333033 DOI: 10.1016/j.ccc.2022.06.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Neurocritical care management of acute brain injury (ABI) is focused on identification, prevention, and management of secondary brain injury (SBI). Physiologic monitoring of the brain and other organ systems has a role to predict patient recovery or deterioration, guide individualized therapeutic interventions, and measure response to treatment, with the goal of improving patient outcomes. In this review, we detail how specific physiologic markers of brain injury and neuromonitoring tools are integrated and used in ABI patients to develop therapeutic approaches to prevent SBI.
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Affiliation(s)
- Tracey H Fan
- Department of Neurology, Division of Neurocritical Care, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02493, USA; Department of Neurology, Division of Neurocritical Care, Brigham and Women's Hospital, 55 Fruit Street, Boston, MA 02493, USA
| | - Eric S Rosenthal
- Department of Neurology, Division of Neurocritical Care, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02493, USA; Department of Neurology, Division of Clinical Neurophysiology, Massachusetts General Hospital, 55 Fruit Street, Boston, MA 02493, USA.
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Gelormini C, Caricato A, Pastorino R, Guerino Biasucci D, Ioannoni E, Montano N, Stival E, Signorelli F, Melchionda I, Albanese A, Marchese E, Silva S, Antonelli M. Brain tissue oxygenation monitoring in subarachnoid hemorrhage for the detection of delayed ischemia: a systematic review and meta-analysis. Minerva Anestesiol 2023; 89:96-103. [PMID: 36745118 DOI: 10.23736/s0375-9393.22.16468-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Subarachnoid hemorrhage (SAH) is a severe subtype of stroke which can be caused by the rupture of an intracranial aneurysm. Following SAH, about 30% of patients develop a late neurologic deterioration due to a delayed cerebral ischemia (DCI). This is a metanalysis and systematic review on the association between values of brain tissue oxygenation (PbtO2) and DCI in patients with SAH. EVIDENCE ACQUISITION The protocol was written according to the PRISMA-P (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines and approved by the International Prospective Register of Systematic Reviews (PROSPERO registration number CRD42021229338). Relevant literature published up to August 1, 2022 was systematically searched throughout the databases MEDLINE, WEB OF SCIENCE, SCOPUS. A systematic review and metanalysis was carried out. The studies considered eligible were those published in English; that enrolled adult patients (≥18years) admitted to neurointensive care units with aneurysmal SAH (aSAH); that reported presence of multimodality monitoring including PbtO2 and detection of DCI during the period of monitoring. EVIDENCE SYNTHESIS We founded 286 studies, of which six considered eligible. The cumulative mean of PbtO2 was 19.5 mmHg in the ischemic group and 24.1mmHg in the non ischemic group. The overall mean difference of the values of PbtO2 between the patients with or without DCI resulted significantly different (-4.32 mmHg [IC 95%: -5.70, -2.94], without heterogeneity, I2 = 0%, and a test for overall effect with P<0.00001). CONCLUSIONS PbtO2 values were significantly lower in patients with DCI. Waiting for definitive results, monitoring of PbtO2 should be considered as a complementary parameter for multimodal monitoring of the risk of DCI in patients with SAH.
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Affiliation(s)
- Camilla Gelormini
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy -
| | - Anselmo Caricato
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Roberta Pastorino
- Department of Woman, Child, and Public Health, Gemelli University Hospital IRCCS, Rome, Italy
| | - Daniele Guerino Biasucci
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Eleonora Ioannoni
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Nicola Montano
- Section of Neurosurgery, Department of Neuroscience, IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Eleonora Stival
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Francesco Signorelli
- Section of Neurosurgery, Department of Neuroscience, IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Isabella Melchionda
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Alessio Albanese
- Section of Neurosurgery, Department of Neuroscience, IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Enrico Marchese
- Section of Neurosurgery, Department of Neuroscience, IRCCS A. Gemelli University Polyclinic Foundation, Sacred Heart Catholic University, Rome, Italy
| | - Serena Silva
- Unit of Neurointensive Care, Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
| | - Massimo Antonelli
- Department of Anesthesiology, Intensive Care and Emergency Medicine, IRCCS A. Gemelli University Polyclinic Foundation, Rome, Italy
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Pansell J, Bell M, Rudberg P, Friman O, Cooray C. Optic nerve sheath diameter in intracranial hypertension: Measurement external or internal of the dura mater? J Neuroimaging 2023; 33:58-66. [PMID: 36197323 PMCID: PMC10092179 DOI: 10.1111/jon.13062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 09/05/2022] [Accepted: 09/23/2022] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND AND PURPOSE Optic nerve sheath diameter (ONSD) is a promising metric to estimate intracranial pressure (ICP). There is no consensus whether ONSD should be measured external (ONSDext) or internal (ONSDint) of the dura mater. Expert opinion favors ONSDint, though without clear evidence to support this. Adjustments of ONSD for eye diameter (ED) and optic nerve diameter (OND) have been suggested to improve precision. We examined the diagnostic accuracy of ONSDext and ONSDint for estimating ICP, unadjusted as well as adjusted for ED and OND. METHODS We performed an observational cohort study, measuring ONSDext and ONSDint in patients with invasive ICP monitoring at Karolinska University Hospital in Stockholm, Sweden. We used ONSDext and ONSDint unadjusted as well as adjusted for ED and for OND. We compared the area under the receiver operator characteristics curve (AUROC) for these methods. Thresholds for elevated ICP were set at ≥20 and ≥22 mmHg, respectively. RESULTS We included 220 measurements from 100 patients. Median ONSDext and ONSDint were significantly different at 6.7 and 5.2 mm (p = .00). There was no significant difference in AUROC for predicting elevated ICP between ONSDext and ONSDint (.67 vs. .64, p = .31). Adjustment for ED yielded better diagnostic accuracy (AUROC, cutoff, sensitivity, specificity) for ONSDext/ED (.76, .29, .81, .62) and ONSDint/ED (.71, .24, .5, .89). CONCLUSIONS ONSDext and ONSDint differ significantly and are not interchangeable. However, there were no significant differences in diagnostic accuracy between ONSDext and ONSDint. Adjustment for ED may improve diagnostic accuracy of ONSD.
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Affiliation(s)
- Jakob Pansell
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Max Bell
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden.,Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Peter Rudberg
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden.,Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Ola Friman
- Department of Anesthesia and Intensive Care Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Charith Cooray
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Neurophysiology, Karolinska University Hospital, Stockholm, Sweden
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Gomez A, Sekhon M, Griesdale D, Froese L, Yang E, Thelin EP, Raj R, Aries M, Gallagher C, Bernard F, Kramer AH, Zeiler FA. Cerebrovascular pressure reactivity and brain tissue oxygen monitoring provide complementary information regarding the lower and upper limits of cerebral blood flow control in traumatic brain injury: a CAnadian High Resolution-TBI (CAHR-TBI) cohort study. Intensive Care Med Exp 2022; 10:54. [PMID: 36550386 PMCID: PMC9780411 DOI: 10.1186/s40635-022-00482-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 12/05/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Brain tissue oxygen tension (PbtO2) and cerebrovascular pressure reactivity monitoring have emerged as potential modalities to individualize care in moderate and severe traumatic brain injury (TBI). The relationship between these modalities has had limited exploration. The aim of this study was to examine the relationship between PbtO2 and cerebral perfusion pressure (CPP) and how this relationship is modified by the state of cerebrovascular pressure reactivity. METHODS A retrospective multi-institution cohort study utilizing prospectively collected high-resolution physiologic data from the CAnadian High Resolution-TBI (CAHR-TBI) Research Collaborative database collected between 2011 and 2021 was performed. Included in the study were critically ill TBI patients with intracranial pressure (ICP), arterial blood pressure (ABP), and PbtO2 monitoring treated in any one of three CAHR-TBI affiliated adult intensive care units (ICU). The outcome of interest was how PbtO2 and CPP are related over a cohort of TBI patients and how this relationship is modified by the state of cerebrovascular reactivity, as determined using the pressure reactivity index (PRx). RESULTS A total of 77 patients met the study inclusion criteria with a total of 377,744 min of physiologic data available for the analysis. PbtO2 produced a triphasic curve when plotted against CPP like previous population-based plots of cerebral blood flow (CBF) versus CPP. The triphasic curve included a plateau region flanked by regions of relative ischemia (hypoxia) and hyperemia (hyperoxia). The plateau region shortened when cerebrovascular pressure reactivity was disrupted compared to when it was intact. CONCLUSIONS In this exploratory analysis of a multi-institution high-resolution physiology TBI database, PbtO2 seems to have a triphasic relationship with CPP, over the entire cohort. The CPP range over which the plateau exists is modified by the state of cerebrovascular reactivity. This indicates that in critically ill TBI patients admitted to ICU, PbtO2 may be reflective of CBF.
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Affiliation(s)
- Alwyn Gomez
- grid.21613.370000 0004 1936 9609Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada ,grid.21613.370000 0004 1936 9609Present Address: Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB Canada
| | - Mypinder Sekhon
- grid.17091.3e0000 0001 2288 9830Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC Canada ,grid.17091.3e0000 0001 2288 9830Present Address: Division of Critical Care, Department of Medicine, University of British Columbia, Vancouver, BC Canada
| | - Donald Griesdale
- grid.17091.3e0000 0001 2288 9830Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC Canada
| | - Logan Froese
- grid.21613.370000 0004 1936 9609Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB Canada
| | - Eleen Yang
- grid.17091.3e0000 0001 2288 9830Department of Anesthesiology, Pharmacology & Therapeutics, University of British Columbia, Vancouver, BC Canada
| | - Eric P. Thelin
- grid.24381.3c0000 0000 9241 5705Department of Neurology, Karolinska University Hospital, Stockholm, Sweden ,grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Rahul Raj
- grid.7737.40000 0004 0410 2071Department of Neurosurgery, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Marcel Aries
- grid.412966.e0000 0004 0480 1382Department of Intensive Care, Maastricht University Medical Center, Maastricht, The Netherlands ,grid.5012.60000 0001 0481 6099School of Mental Health and Neurosciences, University Maastricht, Maastricht, The Netherlands
| | - Clare Gallagher
- grid.22072.350000 0004 1936 7697Section of Neurosurgery, Department of Clinical Neurosciences, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Department of Clinical Neurosciences, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Francis Bernard
- grid.14848.310000 0001 2292 3357Section of Critical Care, Department of Medicine, University of Montreal, Montreal, QC Canada
| | - Andreas H. Kramer
- grid.22072.350000 0004 1936 7697Department of Critical Care Medicine, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Department of Clinical Neurosciences, University of Calgary, Calgary, Canada ,grid.22072.350000 0004 1936 7697Hotchkiss Brain Institute, University of Calgary, Calgary, Canada
| | - Frederick A. Zeiler
- grid.21613.370000 0004 1936 9609Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Canada ,grid.21613.370000 0004 1936 9609Present Address: Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB Canada ,grid.21613.370000 0004 1936 9609Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB Canada ,grid.4714.60000 0004 1937 0626Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden ,grid.21613.370000 0004 1936 9609Centre On Aging, University of Manitoba, Winnipeg, Canada ,grid.5335.00000000121885934Division of Anaesthesia, Department of Medicine, Addenbrooke’s Hospital, University of Cambridge, Cambridge, UK
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40
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Tas J, Czosnyka M, van der Horst ICC, Park S, van Heugten C, Sekhon M, Robba C, Menon DK, Zeiler FA, Aries MJH. Cerebral multimodality monitoring in adult neurocritical care patients with acute brain injury: A narrative review. Front Physiol 2022; 13:1071161. [PMID: 36531179 PMCID: PMC9751622 DOI: 10.3389/fphys.2022.1071161] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Accepted: 11/07/2022] [Indexed: 07/27/2023] Open
Abstract
Cerebral multimodality monitoring (MMM) is, even with a general lack of Class I evidence, increasingly recognized as a tool to support clinical decision-making in the neuroscience intensive care unit (NICU). However, literature and guidelines have focused on unimodal signals in a specific form of acute brain injury. Integrating unimodal signals in multiple signal monitoring is the next step for clinical studies and patient care. As such, we aimed to investigate the recent application of MMM in studies of adult patients with traumatic brain injury (TBI), subarachnoid hemorrhage (SAH), intracerebral hemorrhage (ICH), acute ischemic stroke (AIS), and hypoxic ischemic brain injury following cardiac arrest (HIBI). We identified continuous or daily updated monitoring modalities and summarized the monitoring setting, study setting, and clinical characteristics. In addition, we discussed clinical outcome in intervention studies. We identified 112 MMM studies, including 11 modalities, over the last 7 years (2015-2022). Fifty-eight studies (52%) applied only two modalities. Most frequently combined were ICP monitoring (92 studies (82%)) together with PbtO2 (63 studies (56%). Most studies included patients with TBI (59 studies) or SAH (53 studies). The enrollment period of 34 studies (30%) took more than 5 years, whereas the median sample size was only 36 patients (q1- q3, 20-74). We classified studies as either observational (68 studies) or interventional (44 studies). The interventions were subclassified as systemic (24 studies), cerebral (10 studies), and interventions guided by MMM (11 studies). We identified 20 different systemic or cerebral interventions. Nine (9/11, 82%) of the MMM-guided studies included clinical outcome as an endpoint. In 78% (7/9) of these MMM-guided intervention studies, a significant improvement in outcome was demonstrated in favor of interventions guided by MMM. Clinical outcome may be improved with interventions guided by MMM. This strengthens the belief in this application, but further interdisciplinary collaborations are needed to overcome the heterogeneity, as illustrated in the present review. Future research should focus on increasing sample sizes, improved data collection, refining definitions of secondary injuries, and standardized interventions. Only then can we proceed with complex outcome studies with MMM-guided treatment.
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Affiliation(s)
- Jeanette Tas
- Maastricht University Medical Center +, Department of Intensive Care Medicine, Maastricht University, Maastricht, Netherlands
- School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, Netherlands
| | - Marek Czosnyka
- Brain Physics Laboratory, Department of Clinical Neurosciences, Division of Neurosurgery, University of Cambridge, Cambridge, United Kingdom
| | - Iwan C. C. van der Horst
- Maastricht University Medical Center +, Department of Intensive Care Medicine, Maastricht University, Maastricht, Netherlands
- Cardiovascular Research Institute Maastricht (CARIM), Maastricht, Netherlands
| | - Soojin Park
- Departments of Neurology and Biomedical Informatics, Columbia University, New York, NY, United States
| | - Caroline van Heugten
- School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, Netherlands
- Department of Neuropsychology and Psychopharmacology, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Mypinder Sekhon
- Division of Critical Care Medicine, Department of Medicine, University of British Columbia, Vancouver, BC, Canada
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, BC, Canada
| | - Chiara Robba
- Department of Anaesthesia and Intensive Care, Policlinico Santino IRCCS for Oncology and Neuroscience, Dipartimento di Scienze Chirurgiche Diagnostiche Integrate, University of Genova, Genova, Italy
| | - David K. Menon
- University Division of Anaesthesia, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
| | - Frederick A. Zeiler
- University Division of Anaesthesia, Addenbrooke’s Hospital, University of Cambridge, Cambridge, United Kingdom
- Department of Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada
- Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Department of Human Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- Centre on Aging, University of Manitoba, Winnipeg, MB, Canada
- Department of Clinical Neuroscience, Karolinska Institute, Stockholm, Sweden
| | - Marcel J. H. Aries
- Maastricht University Medical Center +, Department of Intensive Care Medicine, Maastricht University, Maastricht, Netherlands
- School for Mental Health and Neuroscience (MHeNS), Maastricht University, Maastricht, Netherlands
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Sarigul B, De Macêdo Filho LJM, Hawryluk GWJ. Invasive Monitoring in Traumatic Brain Injury. CURRENT SURGERY REPORTS 2022. [DOI: 10.1007/s40137-022-00332-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Siwicka-Gieroba D, Robba C, Gołacki J, Badenes R, Dabrowski W. Cerebral Oxygen Delivery and Consumption in Brain-Injured Patients. J Pers Med 2022; 12:1763. [PMID: 36573716 PMCID: PMC9698645 DOI: 10.3390/jpm12111763] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2022] [Revised: 10/12/2022] [Accepted: 10/17/2022] [Indexed: 12/30/2022] Open
Abstract
Organism survival depends on oxygen delivery and utilization to maintain the balance of energy and toxic oxidants production. This regulation is crucial to the brain, especially after acute injuries. Secondary insults after brain damage may include impaired cerebral metabolism, ischemia, intracranial hypertension and oxygen concentration disturbances such as hypoxia or hyperoxia. Recent data highlight the important role of clinical protocols in improving oxygen delivery and resulting in lower mortality in brain-injured patients. Clinical protocols guide the rules for oxygen supplementation based on physiological processes such as elevation of oxygen supply (by mean arterial pressure (MAP) and intracranial pressure (ICP) modulation, cerebral vasoreactivity, oxygen capacity) and reduction of oxygen demand (by pharmacological sedation and coma or hypothermia). The aim of this review is to discuss oxygen metabolism in the brain under different conditions.
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Affiliation(s)
- Dorota Siwicka-Gieroba
- Department of Anaesthesiology and Intensive Care, Medical University in Lublin, 20-954 Lublin, Poland
| | - Chiara Robba
- Department of Anesthesiology and Intensive Care, San Martino Policlinico Hospital, IRCCS for Oncology and Neurosciences, 16132 Genoa, Italy
- Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, 16132 Genoa, Italy
| | - Jakub Gołacki
- Department of Anaesthesiology and Intensive Care, Medical University in Lublin, 20-954 Lublin, Poland
| | - Rafael Badenes
- Department of Anesthesiology and Surgical-Trauma Intensive Care, Hospital Clinic Universitari, University of Valencia, 46010 Valencia, Spain
| | - Wojciech Dabrowski
- Department of Anaesthesiology and Intensive Care, Medical University in Lublin, 20-954 Lublin, Poland
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Alanazi AH, Adil MS, Lin X, Chastain DB, Henao-Martínez AF, Franco-Paredes C, Somanath PR. Elevated Intracranial Pressure in Cryptococcal Meningoencephalitis: Examining Old, New, and Promising Drug Therapies. Pathogens 2022; 11:783. [PMID: 35890028 PMCID: PMC9321092 DOI: 10.3390/pathogens11070783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 07/02/2022] [Accepted: 07/07/2022] [Indexed: 02/05/2023] Open
Abstract
Despite the availability of effective antifungal therapy, cryptococcal meningoencephalitis (CM) remains associated with elevated mortality. The spectrum of symptoms associated with the central nervous system (CNS) cryptococcosis is directly caused by the high fungal burden in the subarachnoid space and the peri-endothelial space of the CNS vasculature, which results in intracranial hypertension (ICH). Management of intracranial pressure (ICP) through aggressive drainage of cerebrospinal fluid by lumbar puncture is associated with increased survival. Unfortunately, these procedures are invasive and require specialized skills and supplies that are not readily available in resource-limited settings that carry the highest burden of CM. The institution of pharmacologic therapies to reduce the production or increase the resorption of cerebrospinal fluid would likely improve clinical outcomes associated with ICH in patients with CM. Here, we discuss the potential role of multiple pharmacologic drug classes such as diuretics, corticosteroids, and antiepileptic agents used to decrease ICP in various neurological conditions as potential future therapies for CM.
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Affiliation(s)
- Abdulaziz H. Alanazi
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia, Augusta, GA 30902, USA; (A.H.A.); (M.S.A.)
- Research Department, Charlie Norwood VA Medical Center, Augusta, GA 30912, USA
| | - Mir S. Adil
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia, Augusta, GA 30902, USA; (A.H.A.); (M.S.A.)
- Research Department, Charlie Norwood VA Medical Center, Augusta, GA 30912, USA
| | - Xiaorong Lin
- Department of Microbiology, University of Georgia, Athens, GA 30602, USA;
| | - Daniel B. Chastain
- Department of Clinical and Administrative Pharmacy, UGA College of Pharmacy, SWGA Clinical Campus, Phoebe Putney Memorial Hospital, Albany, GA 31701, USA;
| | - Andrés F. Henao-Martínez
- Division of Infectious Diseases, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA; (A.F.H.-M.); (C.F.-P.)
| | - Carlos Franco-Paredes
- Division of Infectious Diseases, University of Colorado, Anschutz Medical Campus, Aurora, CO 80045, USA; (A.F.H.-M.); (C.F.-P.)
- Hospital Infantil de México, Federico Gómez, Ciudad de México 06720, Mexico
| | - Payaningal R. Somanath
- Clinical and Experimental Therapeutics, College of Pharmacy, University of Georgia, Augusta, GA 30902, USA; (A.H.A.); (M.S.A.)
- Research Department, Charlie Norwood VA Medical Center, Augusta, GA 30912, USA
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Chang N, Rasmussen L. Exploring Trends in Neuromonitoring Use in a General Pediatric ICU: The Need for Standardized Guidance. CHILDREN (BASEL, SWITZERLAND) 2022; 9:934. [PMID: 35883918 PMCID: PMC9324621 DOI: 10.3390/children9070934] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/15/2022] [Accepted: 06/21/2022] [Indexed: 12/26/2022]
Abstract
Neuromonitoring has become more standardized in adult neurocritical care, but the utility of different neuromonitoring modalities in children remains debated. We aimed to describe the use of neuromonitoring in critically ill children with and without primary neurological diseases. We conducted a retrospective review of patients admitted to a 32-bed, non-cardiac PICU during a 12-month period. Neuro-imaging, electroencephalogram (EEG), cerebral oximetry (NIRS), automated pupillometry, transcranial doppler (TCD), intracranial pressure (ICP) monitoring, brain tissue oxygenation (PbtO2), primary diagnosis, and outcome were extracted. Neuromonitoring use by primary diagnosis and associations with outcome were observed. Of 1946 patients, 420 received neuro-imaging or neuromonitoring. Primary non-neurological diagnoses most frequently receiving neuromonitoring were respiratory, hematologic/oncologic, gastrointestinal/liver, and infectious/inflammatory. The most frequently used technologies among non-neurological diagnoses were neuro-imaging, EEG, pupillometry, and NIRS. In the multivariate analysis, pupillometry use was associated with mortality, and EEG, NIRS, and neuro-imaging use were associated with disability. Frequencies of TCD and PbtO2 use were too small for analysis. Neuromonitoring is prevalent among various diagnoses in the PICU, without clear benefit on outcomes when used in an ad hoc fashion. We need standard guidance around who, when, and how neuromonitoring should be applied to improve the care of critically ill children.
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Affiliation(s)
- Nathan Chang
- Pediatric Critical Care Medicine and Neurocritical Care, Lucile Packard Children’s Hospital Stanford, Palo Alto, CA 94304, USA;
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Francoeur CL, Lauzier F, Brassard P, Turgeon AF. Near Infrared Spectroscopy for Poor Grade Aneurysmal Subarachnoid Hemorrhage-A Concise Review. Front Neurol 2022; 13:874393. [PMID: 35518206 PMCID: PMC9062216 DOI: 10.3389/fneur.2022.874393] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Accepted: 03/14/2022] [Indexed: 11/13/2022] Open
Abstract
Delayed cerebral ischemia (DCI) disproportionately affects poor grade aneurysmal subarachnoid hemorrhage (aSAH) patients. An unreliable neurological exam and the lack of appropriate monitoring leads to unrecognized DCI, which in turn is associated with severe long-term deficits and higher mortality. Near Infrared Spectroscopy (NIRS) offers simple, continuous, real time, non-invasive cerebral monitoring. It provides regional cerebral oxygen saturation (c-rSO2), which reflects the balance between cerebral oxygen consumption and supply. Reports have demonstrated a good correlation with other cerebral oxygen and blood flow monitoring, and credible cerebrovascular reactivity indices were also derived from NIRS signals. Multiple critical c-rSO2 values have been reported in aSAH patients, based on various thresholds, duration, variation from baseline or cerebrovascular reactivity indices. Some were associated with vasospasm, some with DCI and others with clinical outcomes. However, the poor grade aSAH population has not been specifically studied and no randomized clinical trial has been published. The available literature does not support a specific NIRS-based intervention threshold to guide diagnostic or treatment in aSAH patients. We review herein the fundamental basic concepts behind NIRS technology, relationship of c-rSO2 to other brain monitoring values and their potential clinical interpretation. We follow with a critical evaluation of the use of NIRS in the aSAH population, more specifically its ability to diagnose vasospasm, to predict DCI and its association to outcome. In summary, NIRS might offer significant potential for poor grade aSAH in the future. However, current evidence does not support its use in clinical decision-making, and proper technology evaluation is required.
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Affiliation(s)
- Charles L. Francoeur
- Population Health and Optimal Health Practices Research Unit (Trauma—Emergency—Critical Care Medicine), Centre Hospitalier Universitaire (CHU) de Québec—Université Laval Research Centre, Université Laval, Québec City, QC, Canada
- Department of Anesthesiology and Critical Care, CHU de Québec—Université Laval, Critical Care Division, Québec City, QC, Canada
- Critical Care Medicine Service, CHU de Québec—Université Laval, Québec City, QC, Canada
| | - François Lauzier
- Population Health and Optimal Health Practices Research Unit (Trauma—Emergency—Critical Care Medicine), Centre Hospitalier Universitaire (CHU) de Québec—Université Laval Research Centre, Université Laval, Québec City, QC, Canada
- Department of Anesthesiology and Critical Care, CHU de Québec—Université Laval, Critical Care Division, Québec City, QC, Canada
- Critical Care Medicine Service, CHU de Québec—Université Laval, Québec City, QC, Canada
| | - Patrice Brassard
- Department of Kinesiology, Faculty of Medicine, Université Laval, Québec City, QC, Canada
- Research Center of the Institut Universitaire de Cardiologie et de Pneumologie de Québec, Québec City, QC, Canada
| | - Alexis F. Turgeon
- Population Health and Optimal Health Practices Research Unit (Trauma—Emergency—Critical Care Medicine), Centre Hospitalier Universitaire (CHU) de Québec—Université Laval Research Centre, Université Laval, Québec City, QC, Canada
- Department of Anesthesiology and Critical Care, CHU de Québec—Université Laval, Critical Care Division, Québec City, QC, Canada
- Critical Care Medicine Service, CHU de Québec—Université Laval, Québec City, QC, Canada
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Mainali S, Cardim D, Sarwal A, Merck LH, Yeatts SD, Czosnyka M, Shutter L. Prolonged Automated Robotic TCD Monitoring in Acute Severe TBI: Study Design and Rationale. Neurocrit Care 2022; 37:267-275. [PMID: 35381966 DOI: 10.1007/s12028-022-01483-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Accepted: 03/01/2022] [Indexed: 10/18/2022]
Abstract
BACKGROUND Transcranial Doppler ultrasonography (TCD) is a portable, bedside, noninvasive diagnostic tool used for the real-time assessment of cerebral hemodynamics. Despite the evident utility of TCD and the ability of this technique to function as a stethoscope to the brain, its use has been limited to specialized centers because of the dearth of technical and clinical expertise required to acquire and interpret the cerebrovascular parameters. Additionally, the conventional pragmatic episodic TCD monitoring protocols lack dynamic real-time feedback to guide time-critical clinical interventions. Fortunately, with the recent advent of automated robotic TCD technology in conjunction with the automated software for TCD data processing, we now have the technology to automatically acquire TCD data and obtain clinically relevant information in real-time. By obviating the need for highly trained clinical personnel, this technology shows great promise toward a future of widespread noninvasive monitoring to guide clinical care in patients with acute brain injury. METHODS Here, we describe a proposal for a prospective observational multicenter clinical trial to evaluate the safety and feasibility of prolonged automated robotic TCD monitoring in patients with severe acute traumatic brain injury (TBI). We will enroll patients with severe non-penetrating TBI with concomitant invasive multimodal monitoring including, intracranial pressure, brain tissue oxygenation, and brain temperature monitoring as part of standard of care in centers with varying degrees of TCD availability and experience. Additionally, we propose to evaluate the correlation of pertinent TCD-based cerebral autoregulation indices such as the critical closing pressure, and the pressure reactivity index with the brain tissue oxygenation values obtained invasively. CONCLUSIONS The overarching goal of this study is to establish safety and feasibility of prolonged automated TCD monitoring for patients with TBI in the intensive care unit and identify clinically meaningful and pragmatic noninvasive targets for future interventions.
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Affiliation(s)
- Shraddha Mainali
- Department of Neurology, Virginial Commonwealth University, Richmond, VA, USA.
| | - Danilo Cardim
- Department of Neurology, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Aarti Sarwal
- Department of Neurology, Wake Forest School of Medicine, Winston Salem, NC, USA
| | - Lisa H Merck
- Departments of Emergency Medicine and Neurology, University of Florida College of Medicine, Gainesville, FL, USA
| | - Sharon D Yeatts
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Marek Czosnyka
- Brain Physics Laboratory, Neurosurgical Unit, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Lori Shutter
- Department of Critical Care Medicine, Neurology, and Neurosurgery, University of Pittsburgh, Pittsburgh, PA, USA
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Abstract
PURPOSE OF REVIEW Severe traumatic brain injury (TBI) is an extremely serious health problem, especially in low-middle income countries (LMICs). The prevalence of severe TBI continues to increase in LMICs. Major limitations in the chain of care for TBI patients are common in LMICs including suboptimal or nonexistent prehospital care, overburdened emergency services, lack of trained human resources and limited availability of ICUs. Basic neuromonitoring, such as intracranial pressure, are unavailable or underutilized and advanced techniques are not available. RECENT FINDINGS Attention to fundamental principles of TBI care in LMICs, including early categorization, prevention and treatment of secondary insults, use of low-cost technology for evaluation of intracranial bleeding and neuromonitoring, and emphasis on education of human resources and multidisciplinary work, are particularly important in LMICs. Institutional collaborations between high-income and LMICs have developed evidence focused on available resources. Accordingly, an expert group have proposed consensus recommendations for centers without availability of invasive brain monitoring. SUMMARY Severe TBI is very prevalent in LMIC and neuromonitoring is often not available in these environments. When intracranial pressure monitors are not available, careful attention to changes on clinical examination, serial imaging and noninvasive monitoring techniques can help recognize intracranial hypertension and effectively guide treatment decisions.
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Cruz Navarro J, Ponce Mejia LL, Robertson C. A Precision Medicine Agenda in Traumatic Brain Injury. Front Pharmacol 2022; 13:713100. [PMID: 35370671 PMCID: PMC8966615 DOI: 10.3389/fphar.2022.713100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Accepted: 02/25/2022] [Indexed: 11/13/2022] Open
Abstract
Traumatic brain injury remains a leading cause of death and disability across the globe. Substantial uncertainty in outcome prediction continues to be the rule notwithstanding the existing prediction models. Additionally, despite very promising preclinical data, randomized clinical trials (RCTs) of neuroprotective strategies in moderate and severe TBI have failed to demonstrate significant treatment effects. Better predictive models are needed, as the existing validated ones are more useful in prognosticating poor outcome and do not include biomarkers, genomics, proteonomics, metabolomics, etc. Invasive neuromonitoring long believed to be a "game changer" in the care of TBI patients have shown mixed results, and the level of evidence to support its widespread use remains insufficient. This is due in part to the extremely heterogenous nature of the disease regarding its etiology, pathology and severity. Currently, the diagnosis of traumatic brain injury (TBI) in the acute setting is centered on neurological examination and neuroimaging tools such as CT scanning and MRI, and its treatment has been largely confronted using a "one-size-fits-all" approach, that has left us with many unanswered questions. Precision medicine is an innovative approach for TBI treatment that considers individual variability in genes, environment, and lifestyle and has expanded across the medical fields. In this article, we briefly explore the field of precision medicine in TBI including biomarkers for therapeutic decision-making, multimodal neuromonitoring, and genomics.
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Affiliation(s)
- Jovany Cruz Navarro
- Departments of Anesthesiology and Neurosurgery, Baylor College of Medicine, Houston, TX, United States
| | - Lucido L. Ponce Mejia
- Departments of Neurosurgery and Neurology, LSU Health Science Center, New Orleans, LA, United States
| | - Claudia Robertson
- Department of Neurosurgery, Baylor College of Medicine, Houston, TX, United States
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49
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Neuromonitoring in Severe Traumatic Brain Injury: A Bibliometric Analysis. Neurocrit Care 2022; 36:1044-1052. [PMID: 35075580 DOI: 10.1007/s12028-021-01428-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/17/2021] [Indexed: 10/19/2022]
Abstract
Traumatic brain injury (TBI) is the leading cause of mortality and disability among trauma-related injuries. Neuromonitoring plays an essential role in the management and prognosis of patients with severe TBI. Our bibliometric study aimed to identify the knowledge base, define the research front, and outline the social networks on neuromonitoring in severe TBI. We conducted an electronic search for articles related to neuromonitoring in severe TBI in Scopus. A descriptive analysis retrieved evidence on the most productive authors and countries, the most cited articles, the most frequently publishing journals, and the most common author's keywords. Through a three-step network extraction process, we performed a collaboration analysis among universities and countries, a cocitation analysis, and a word cooccurrence analysis. A total of 1884 records formed the basis of our bibliometric study. We recorded an increasing scientific interest in the use of neuromonitoring in severe TBI. Czosnyka, Hutchinson, Menon, Smielewski, and Stocchetti were the most productive authors. The most cited document was a review study by Maas et al. There was an extensive collaboration among universities. The most common keywords were "intracranial pressure," with an increasing interest in magnetic resonance imaging and cerebral perfusion pressure monitoring. Neuromonitoring constitutes an area of active research. The present findings indicate that intracranial pressure monitoring plays a pivotal role in the management of severe TBI. Scientific interest shifts to magnetic resonance imaging and individualized patient care on the basis of optimal cerebral perfusion pressure.
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50
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Kirschen MP, LaRovere K, Balakrishnan B, Erklauer J, Francoeur C, Ganesan SL, Jayakar A, Lovett M, Luchette M, Press CA, Wolf M, Ferrazzano P, Wainwright MS, Appavu B. A Survey of Neuromonitoring Practices in North American Pediatric Intensive Care Units. Pediatr Neurol 2022; 126:125-130. [PMID: 34864306 PMCID: PMC9135309 DOI: 10.1016/j.pediatrneurol.2021.11.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Accepted: 11/06/2021] [Indexed: 12/17/2022]
Abstract
BACKGROUND Neuromonitoring is the use of continuous measures of brain physiology to detect clinically important events in real-time. Neuromonitoring devices can be invasive or non-invasive and are typically used on patients with acute brain injury or at high risk for brain injury. The goal of this study was to characterize neuromonitoring infrastructure and practices in North American pediatric intensive care units (PICUs). METHODS An electronic, web-based survey was distributed to 70 North American institutions participating in the Pediatric Neurocritical Care Research Group. Questions related to the clinical use of neuromonitoring devices, integrative multimodality neuromonitoring capabilities, and neuromonitoring infrastructure were included. Survey results were presented using descriptive statistics. RESULTS The survey was completed by faculty at 74% (52 of 70) of institutions. All 52 institutions measure intracranial pressure and have electroencephalography capability, whereas 87% (45 of 52) use near-infrared spectroscopy and 40% (21/52) use transcranial Doppler. Individual patient monitoring decisions were driven by institutional protocols and collaboration between critical care, neurology, and neurosurgery attendings. Reported device utilization varied by brain injury etiology. Only 15% (eight of 52) of institutions utilized a multimodality neuromonitoring platform to integrate and synchronize data from multiple devices. A database of neuromonitoring patients was maintained at 35% (18 of 52) of institutions. Funding for neuromonitoring programs was variable with contributions from hospitals (19%, 10 of 52), private donations (12%, six of 52), and research funds (12%, six of 52), although 73% (40 of 52) have no dedicated funds. CONCLUSIONS Neuromonitoring indications, devices, and infrastructure vary by institution in North American pediatric critical care units. Noninvasive modalities were utilized more liberally, although not uniformly, than invasive monitoring. Further studies are needed to standardize the acquisition, interpretation, and reporting of clinical neuromonitoring data, and to determine whether neuromonitoring systems impact neurological outcomes.
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Affiliation(s)
- Matthew P Kirschen
- Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania.
| | - Kerri LaRovere
- Department of Neurology, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Binod Balakrishnan
- Division of Pediatric Critical Care Medicine, Children's Wisconsin, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - Jennifer Erklauer
- Departments of Critical Care Medicine and Neurology, Texas Children's Hospital, Houston, Texas
| | - Conall Francoeur
- Department of Pediatrics, CHU de Québec - Université Laval Research Center, Quebec City, Quebec, Canada
| | - Saptharishi Lalgudi Ganesan
- Department of Paediatrics, Children's Hospital of Western Ontario, Schulich School of Medicine & Dentistry at the Western University, London, Ontario, Canada
| | - Anuj Jayakar
- Department of Neurology, Nicklaus Children's Hospital, Miami, Florida
| | - Marlina Lovett
- Division of Critical Care Medicine, Department of Pediatrics, Nationwide Children's Hospital, The Ohio State University College of Medicine, Columbus, Ohio
| | - Matthew Luchette
- Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Craig A Press
- Department of Pediatrics, Children's Hospital of Philadelphia, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania; Department of Pediatrics, University of Colorado School of Medicine, Aurora, Colorado
| | - Michael Wolf
- Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Peter Ferrazzano
- Division of Critical Care Medicine, Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Mark S Wainwright
- Division of Pediatric Neurology, University of Washington School of Medicine, Seattle, Washington
| | - Brian Appavu
- Department of Neurosciences, Barrow Neurological Institute at Phoenix Children's Hospital, University of Arizona College of Medicine - Phoenix, Phoenix, UK
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