Clinical descriptors of disease trajectories in patients with traumatic brain injury in the intensive care unit (CENTER-TBI): a multicentre observational cohort study.


Journal

The Lancet. Neurology
ISSN: 1474-4465
Titre abrégé: Lancet Neurol
Pays: England
ID NLM: 101139309

Informations de publication

Date de publication:
14 Nov 2023
Historique:
received: 07 03 2023
revised: 31 08 2023
accepted: 08 09 2023
medline: 18 11 2023
pubmed: 18 11 2023
entrez: 17 11 2023
Statut: aheadofprint

Résumé

Patients with traumatic brain injury are a heterogeneous population, and the most severely injured individuals are often treated in an intensive care unit (ICU). The primary injury at impact, and the harmful secondary events that can occur during the first week of the ICU stay, will affect outcome in this vulnerable group of patients. We aimed to identify clinical variables that might distinguish disease trajectories among patients with traumatic brain injury admitted to the ICU. We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. We included patients aged 18 years or older with traumatic brain injury who were admitted to the ICU at one of the 65 CENTER-TBI participating centres, which range from large academic hospitals to small rural hospitals. For every patient, we obtained pre-injury data and injury features, clinical characteristics on admission, demographics, physiological parameters, laboratory features, brain biomarkers (ubiquitin carboxy-terminal hydrolase L1 [UCH-L1], S100 calcium-binding protein B [S100B], tau, neurofilament light [NFL], glial fibrillary acidic protein [GFAP], and neuron-specific enolase [NSE]), and information about intracranial pressure lowering treatments during the first 7 days of ICU stay. To identify clinical variables that might distinguish disease trajectories, we applied a novel clustering method to these data, which was based on a mixture of probabilistic graph models with a Markov chain extension. The relation of clusters to the extended Glasgow Outcome Scale (GOS-E) was investigated. Between Dec 19, 2014, and Dec 17, 2017, 4509 patients with traumatic brain injury were recruited into the CENTER-TBI core dataset, of whom 1728 were eligible for this analysis. Glucose variation (defined as the difference between daily maximum and minimum glucose concentrations) and brain biomarkers (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were consistently found to be the main clinical descriptors of disease trajectories (ie, the leading variables contributing to the distinguishing clusters) in patients with traumatic brain injury in the ICU. The disease trajectory cluster to which a patient was assigned in a model was analysed as a predictor together with variables from the IMPACT model, and prediction of both mortality and unfavourable outcome (dichotomised GOS-E ≤4) was improved. First-day ICU admission data are not the only clinical descriptors of disease trajectories in patients with traumatic brain injury. By analysing temporal variables in our study, variation of glucose was identified as the most important clinical descriptor that might distinguish disease trajectories in the ICU, which should direct further research. Biomarkers of brain injury (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were also top clinical descriptors over time, suggesting they might be important in future clinical practice. European Union 7th Framework program, Hannelore Kohl Stiftung, OneMind, Integra LifeSciences Corporation, and NeuroTrauma Sciences.

Sections du résumé

BACKGROUND BACKGROUND
Patients with traumatic brain injury are a heterogeneous population, and the most severely injured individuals are often treated in an intensive care unit (ICU). The primary injury at impact, and the harmful secondary events that can occur during the first week of the ICU stay, will affect outcome in this vulnerable group of patients. We aimed to identify clinical variables that might distinguish disease trajectories among patients with traumatic brain injury admitted to the ICU.
METHODS METHODS
We used data from the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) prospective observational cohort study. We included patients aged 18 years or older with traumatic brain injury who were admitted to the ICU at one of the 65 CENTER-TBI participating centres, which range from large academic hospitals to small rural hospitals. For every patient, we obtained pre-injury data and injury features, clinical characteristics on admission, demographics, physiological parameters, laboratory features, brain biomarkers (ubiquitin carboxy-terminal hydrolase L1 [UCH-L1], S100 calcium-binding protein B [S100B], tau, neurofilament light [NFL], glial fibrillary acidic protein [GFAP], and neuron-specific enolase [NSE]), and information about intracranial pressure lowering treatments during the first 7 days of ICU stay. To identify clinical variables that might distinguish disease trajectories, we applied a novel clustering method to these data, which was based on a mixture of probabilistic graph models with a Markov chain extension. The relation of clusters to the extended Glasgow Outcome Scale (GOS-E) was investigated.
FINDINGS RESULTS
Between Dec 19, 2014, and Dec 17, 2017, 4509 patients with traumatic brain injury were recruited into the CENTER-TBI core dataset, of whom 1728 were eligible for this analysis. Glucose variation (defined as the difference between daily maximum and minimum glucose concentrations) and brain biomarkers (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were consistently found to be the main clinical descriptors of disease trajectories (ie, the leading variables contributing to the distinguishing clusters) in patients with traumatic brain injury in the ICU. The disease trajectory cluster to which a patient was assigned in a model was analysed as a predictor together with variables from the IMPACT model, and prediction of both mortality and unfavourable outcome (dichotomised GOS-E ≤4) was improved.
INTERPRETATION CONCLUSIONS
First-day ICU admission data are not the only clinical descriptors of disease trajectories in patients with traumatic brain injury. By analysing temporal variables in our study, variation of glucose was identified as the most important clinical descriptor that might distinguish disease trajectories in the ICU, which should direct further research. Biomarkers of brain injury (S100B, NSE, NFL, tau, UCH-L1, and GFAP) were also top clinical descriptors over time, suggesting they might be important in future clinical practice.
FUNDING BACKGROUND
European Union 7th Framework program, Hannelore Kohl Stiftung, OneMind, Integra LifeSciences Corporation, and NeuroTrauma Sciences.

Identifiants

pubmed: 37977157
pii: S1474-4422(23)00358-7
doi: 10.1016/S1474-4422(23)00358-7
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Investigateurs

Cecilia Åkerlund (C)
Krisztina Amrein (K)
Nada Andelic (N)
Lasse Andreassen (L)
Audny Anke (A)
Anna Antoni (A)
Gérard Audibert (G)
Philippe Azouvi (P)
Maria Luisa Azzolini (ML)
Ronald Bartels (R)
Pál Barzó (P)
Romuald Beauvais (R)
Ronny Beer (R)
Bo-Michael Bellander (BM)
Antonio Belli (A)
Habib Benali (H)
Maurizio Berardino (M)
Luigi Beretta (L)
Morten Blaabjerg (M)
Peter Bragge (P)
Alexandra Brazinova (A)
Vibeke Brinck (V)
Joanne Brooker (J)
Camilla Brorsson (C)
Andras Buki (A)
Monika Bullinger (M)
Manuel Cabeleira (M)
Alessio Caccioppola (A)
Emiliana Calappi (E)
Maria Rosa Calvi (MR)
Peter Cameron (P)
Guillermo Carbayo Lozano (G)
Marco Carbonara (M)
Simona Cavallo (S)
Giorgio Chevallard (G)
Arturo Chieregato (A)
Giuseppe Citerio (G)
Hans Clusmann (H)
Mark Coburn (M)
Jonathan Coles (J)
Jamie D Cooper (JD)
Marta Correia (M)
Amra Čović (A)
Nicola Curry (N)
Endre Czeiter (E)
Marek Czosnyka (M)
Claire DahyotFizelier (C)
Paul Dark (P)
Helen Dawes (H)
Véronique De Keyser (V)
Vincent Degos (V)
Francesco Della Corte (F)
Hugo den Boogert (H)
Bart Depreitere (B)
Đula Đilvesi (Đ)
Abhishek Dixit (A)
Emma Donoghue (E)
Jens Dreier (J)
GuyLoup Dulière (G)
Ari Ercole (A)
Patrick Esser (P)
Erzsébet Ezer (E)
Martin Fabricius (M)
Valery L Feigin (VL)
Kelly Foks (K)
Shirin Frisvold (S)
Alex Furmanov (A)
Pablo Gagliardo (P)
Damien Galanaud (D)
Dashiell Gantner (D)
Guoyi Gao (G)
Pradeep George (P)
Alexandre Ghuysen (A)
Lelde Giga (L)
Ben Glocker (B)
Jagoš Golubovic (J)
Pedro A Gomez (PA)
Johannes Gratz (J)
Benjamin Gravesteijn (B)
Francesca Grossi (F)
Russell L Gruen (RL)
Deepak Gupta (D)
Juanita A Haagsma (JA)
Iain Haitsma (I)
Raimund Helbok (R)
Eirik Helseth (E)
Lindsay Horton (L)
Jilske Huijben (J)
Peter J Hutchinson (PJ)
Bram Jacobs (B)
Stefan Jankowski (S)
Mike Jarrett (M)
Jiyao Jiang (J)
Faye Johnson (F)
Kelly Jones (K)
Mladen Karan (M)
Angelos G Kolias (AG)
Erwin Kompanje (E)
Daniel Kondziella (D)
Evgenios Kornaropoulos (E)
LarsOwe Koskinen (L)
Noémi Kovács (N)
Ana Kowark (A)
Alfonso Lagares (A)
Linda Lanyon (L)
Steven Laureys (S)
Fiona Lecky (F)
Didier Ledoux (D)
Rolf Lefering (R)
Valerie Legrand (V)
Aurelie Lejeune (A)
Leon Levi (L)
Roger Lightfoot (R)
Hester Lingsma (H)
Andrew I R Maas (AIR)
Ana M CastañoLeón (AM)
Marc Maegele (M)
Marek Majdan (M)
Alex Manara (A)
Geoffrey Manley (G)
Costanza Martino (C)
Hugues Maréchal (H)
Julia Mattern (J)
Catherine McMahon (C)
Béla Melegh (B)
David Menon (D)
Tomas Menovsky (T)
Ana Mikolic (A)
Benoit Misset (B)
Visakh Muraleedharan (V)
Lynnette Murray (L)
Ancuta Negru (A)
David Nelson (D)
Virginia Newcombe (V)
Daan Nieboer (D)
József Nyirádi (J)
Otesile Olubukola (O)
Matej Oresic (M)
Fabrizio Ortolano (F)
Aarno Palotie (A)
Paul M Parizel (PM)
JeanFrançois Payen (J)
Natascha Perera (N)
Vincent Perlbarg (V)
Paolo Persona (P)
Wilco Peul (W)
Anna Piippo-Karjalainen (A)
Matti Pirinen (M)
Dana Pisica (D)
Horia Ples (H)
Suzanne Polinder (S)
Inigo Pomposo (I)
Jussi P Posti (JP)
Louis Puybasset (L)
Andreea Radoi (A)
Arminas Ragauskas (A)
Rahul Raj (R)
Malinka Rambadagalla (M)
Isabel Retel Helmrich (I)
Jonathan Rhodes (J)
Sylvia Richardson (S)
Sophie Richter (S)
Samuli Ripatti (S)
Saulius Rocka (S)
Cecilie Roe (C)
Olav Roise (O)
Jonathan Rosand (J)
Jeffrey V Rosenfeld (JV)
Christina Rosenlund (C)
Guy Rosenthal (G)
Rolf Rossaint (R)
Sandra Rossi (S)
Daniel Rueckert (D)
Martin Rusnák (M)
Juan Sahuquillo (J)
Oliver Sakowitz (O)
Renan SanchezPorras (R)
Janos Sandor (J)
Nadine Schäfer (N)
Silke Schmidt (S)
Herbert Schoechl (H)
Guus Schoonman (G)
Rico Frederik Schou (RF)
Elisabeth Schwendenwein (E)
Charlie Sewalt (C)
Ranjit D Singh (RD)
Toril Skandsen (T)
Peter Smielewski (P)
Abayomi Sorinola (A)
Emmanuel Stamatakis (E)
Simon Stanworth (S)
Robert Stevens (R)
William Stewart (W)
Ewout W Steyerberg (EW)
Nino Stocchetti (N)
Nina Sundström (N)
Riikka Takala (R)
Viktória Tamás (V)
Tomas Tamosuitis (T)
Mark Steven Taylor (MS)
Braden Te Ao (BT)
Olli Tenovuo (O)
Alice Theadom (A)
Matt Thomas (M)
Dick Tibboel (D)
Marjolein Timmers (M)
Christos Tolias (C)
Tony Trapani (T)
Cristina Maria Tudora (CM)
Andreas Unterberg (A)
Peter Vajkoczy (P)
Shirley Vallance (S)
Egils Valeinis (E)
Zoltán Vámos (Z)
Mathieu van der Jagt (M)
Gregory Van der Steen (G)
Joukje van der Naalt (J)
Jeroen T J M van Dijck (JTJM)
Inge A M van Erp (IAM)
Thomas A van Essen (TA)
Wim Van Hecke (W)
Caroline van Heugten (C)
Dominique Van Praag (D)
Ernest van Veen (E)
Thijs Vande Vyvere (T)
Roel P J van Wijk (RPJ)
Alessia Vargiolu (A)
Emmanuel Vega (E)
Kimberley Velt (K)
Jan Verheyden (J)
Paul M Vespa (PM)
Anne Vik (A)
Rimantas Vilcinis (R)
Victor Volovici (V)
Nicole von Steinbüchel (N)
Daphne Voormolen (D)
Petar Vulekovic (P)
Kevin K W Wang (KKW)
Daniel Whitehouse (D)
Eveline Wiegers (E)
Guy Williams (G)
Lindsay Wilson (L)
Stefan Winzeck (S)
Stefan Wolf (S)
Zhihui Yang (Z)
Peter Ylén (P)
Alexander Younsi (A)
Frederick A Zeiler (FA)
Veronika Zelinkova (V)
Agate Ziverte (A)
Tommaso Zoerle (T)

Informations de copyright

Copyright © 2023 Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests DKM reports grants, personal fees, and non-financial support from GlaxoSmithKline; personal fees from Neurotrauma Sciences, Lantmannen, Pressura, and Pfizer, outside of the submitted work. SB reports grants from the Gates Cambridge foundation fellowship during the conduct of this study. PS receives parts of licensing fee for the ICM+ software from Cambridge Enterprise, UK, during the conduct of this study. ES receives royalties from Springer during the conduct of this study. All other authors declare no competing interests.

Auteurs

Cecilia A I Åkerlund (CAI)

Department of Physiology and Pharmacology, Section of Anaesthesiology and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Function Perioperative Medicine and Intensive Care, Karolinska University Hospital Solna, Stockholm, Sweden.

Anders Holst (A)

School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.

Shubhayu Bhattacharyay (S)

Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK.

Nino Stocchetti (N)

Department of Physiopathology and Transplant, Milan University, Milan, Italy; Fondazione IRCCS, Cà Granda Ospedale Maggiore Policlinico, Milan, Italy.

Ewout Steyerberg (E)

Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands.

Peter Smielewski (P)

Clinical Neuroscience, University of Cambridge, Cambridge, UK.

David K Menon (DK)

Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK.

Ari Ercole (A)

Division of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK; Centre for Artificial Intelligence in Medicine, University of Cambridge, Cambridge, UK.

David W Nelson (DW)

Department of Physiology and Pharmacology, Section of Anaesthesiology and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden; Function Perioperative Medicine and Intensive Care, Karolinska University Hospital Solna, Stockholm, Sweden. Electronic address: david.nelson@regionstockholm.se.

Classifications MeSH