Optimal Cerebral Perfusion Pressure Assessed with a Multi-Window Weighted Approach Adapted for Prospective Use: A Validation Study.


Journal

Acta neurochirurgica. Supplement
ISSN: 0065-1419
Titre abrégé: Acta Neurochir Suppl
Pays: Austria
ID NLM: 100962752

Informations de publication

Date de publication:
2021
Historique:
entrez: 11 4 2021
pubmed: 12 4 2021
medline: 5 6 2021
Statut: ppublish

Résumé

Pressure reactivity index (PRx)-cerebral perfusion pressure (CPP) relationships over a given time period can be used to detect a value of CPP at which PRx shows the best autoregulation (optimal CPP, or CPPopt). Algorithms for continuous assessment of CPPopt in traumatic brain injury (TBI) patients reached the desired high yield with a multi-window approach (CPPopt_MA). However, the calculations were tested on retrospective manually cleaned datasets. Moreover, CPPopt false-positive values can be generated from non-physiological variations of intracranial pressure (ICP) and arterial blood pressure (ABP). Therefore, the algorithm robustness was improved, making it suitable for prospective bedside application (COGiTATE trial). To validate the CPPopt revised algorithm in a large single-centre retrospective cohort of TBI patients. 840 TBI patients were included. CPPopt yield, stability and ability to discriminate outcome groups were compared to CPPopt_MA and the Brain Trauma Foundation (BTF) guideline reference. CPPopt yield was lower than CPPopt_MA yield (85% and 90%, p < 0.001), but, importantly, with increased stability (p < 0.0001). The ∆(CPP-CPPopt) could distinguish the mortality and survival outcome (t = -6.7, p < 0.0001) with a statistical significance higher than the ∆CPP calculated with the guideline reference (CPP-60) (t = -4.5, p < 0.0001). This study validates, on a large cohort of patients, the new algorithm proposed for prospective use of CPPopt as a CPP target at bedside.

Sections du résumé

BACKGROUND BACKGROUND
Pressure reactivity index (PRx)-cerebral perfusion pressure (CPP) relationships over a given time period can be used to detect a value of CPP at which PRx shows the best autoregulation (optimal CPP, or CPPopt). Algorithms for continuous assessment of CPPopt in traumatic brain injury (TBI) patients reached the desired high yield with a multi-window approach (CPPopt_MA). However, the calculations were tested on retrospective manually cleaned datasets. Moreover, CPPopt false-positive values can be generated from non-physiological variations of intracranial pressure (ICP) and arterial blood pressure (ABP). Therefore, the algorithm robustness was improved, making it suitable for prospective bedside application (COGiTATE trial).
OBJECTIVE OBJECTIVE
To validate the CPPopt revised algorithm in a large single-centre retrospective cohort of TBI patients.
METHODS METHODS
840 TBI patients were included. CPPopt yield, stability and ability to discriminate outcome groups were compared to CPPopt_MA and the Brain Trauma Foundation (BTF) guideline reference.
RESULTS RESULTS
CPPopt yield was lower than CPPopt_MA yield (85% and 90%, p < 0.001), but, importantly, with increased stability (p < 0.0001). The ∆(CPP-CPPopt) could distinguish the mortality and survival outcome (t = -6.7, p < 0.0001) with a statistical significance higher than the ∆CPP calculated with the guideline reference (CPP-60) (t = -4.5, p < 0.0001).
CONCLUSION CONCLUSIONS
This study validates, on a large cohort of patients, the new algorithm proposed for prospective use of CPPopt as a CPP target at bedside.

Identifiants

pubmed: 33839842
doi: 10.1007/978-3-030-59436-7_36
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

181-185

Références

Liu X, Maurits NM, Aries MJH et al (2017) Monitoring of optimal cerebral perfusion pressure in traumatic brain injured patients using a multi-window weighting algorithm. J Neurotrauma 34(22):3081–3088
doi: 10.1089/neu.2017.5003
Cabeleira M, Czosnyka M, Liu X, Donnelly J, Smielewski P (2018) Occurrence of CPPopt values in uncorrelated ICP and ABP time series. Acta Neurochir Suppl.:143–146
Beqiri E, Smielewski P, Robba C et al (2019) Feasibility of individualised severe traumatic brain injury management using an automated assessment of optimal cerebral perfusion pressure: the COGiTATE phase II study protocol. BMJ Open 9(9):e030727
doi: 10.1136/bmjopen-2019-030727
Carney N, Totten AM, Hawryluk GWJ et al (2016) Guidelines for the management of severe traumatic brain injury, 4th edn
Depreitere B, Güiza F, Van Den BG, Schuhmann MU, Maier G, Piper I, Meyfroidt G (2014) Pressure autoregulation monitoring and cerebral perfusion pressure target recommendation in patients with severe traumatic brain injury based on minute-by-minute monitoring data. J Neurosurg 120(120):1451–1457
doi: 10.3171/2014.3.JNS131500
Aries MJH, Czosnyka M, Budohoski KP et al (2012) Continuous determination of optimal cerebral perfusion pressure in traumatic brain injury*. Crit Care Med. https://doi.org/10.1097/CCM.0b013e3182514eb6

Auteurs

Erta Beqiri (E)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK. erta.beqiri@gmail.com.
Department of Physiology and Transplantation, Milan University, Milano, Italy. erta.beqiri@gmail.com.

Ari Ercole (A)

Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK.

Marcel J Aries (MJ)

Department of Intensive Care, Maastricht UMC, HX Maastricht, The Netherlands.

Manuel Cabeleira (M)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Andras Czigler (A)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Department of Neurosurgery and Szentagothai Research Center, University of Pecs, Medical School, Pecs, Hungary.

Annalisa Liberti (A)

Department of Physiology and Transplantation, Milan University, Milano, Italy.
Department of Intensive Care, Maastricht UMC, HX Maastricht, The Netherlands.

Jeanette Tas (J)

Department of Intensive Care, Maastricht UMC, HX Maastricht, The Netherlands.

Joseph Donnelly (J)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Xiuyun Liu (X)

Department of Anesthesiology and Critical Care Medicine, School of Medicine, Johns Hopkins University, Baltimore, MD, USA.

Marta Fedriga (M)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Department of Anesthesia, Critical care and Emergency, Spedali Civili University Hospital, Brescia, Italy.

Ka Hing Chu (KH)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Frederick A Zeiler (FA)

Division of Anaesthesia, Department of Medicine, Addenbrooke's Hospital, University of Cambridge, Cambridge, UK.
Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Department of Anatomy and Cell Science, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada.
Biomedical Engineering, Faculty of Engineering, University of Manitoba, Winnipeg, MB, Canada.

Marek Czosnyka (M)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Peter Smielewski (P)

Brain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

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