Clustering identifies endotypes of traumatic brain injury in an intensive care cohort: a CENTER-TBI study
Authors: Åkerlund Cecilia A. I. , Holst Anders , Stocchetti Nino , Steyerberg Ewout W. , Menon David K. , Ercole Ari , Nelson David W. ,   the CENTER-TBI Participants and Investigators, Åkerlund Cecilia , Amrein Krisztina , Andelic Nada , Andreassen Lasse , Anke Audny , Antoni Anna , Audibert Gérard , Azouvi Philippe , Azzolini Maria Luisa , Bartels Ronald , Barzó Pál , Beauvais Romuald , Beer Ronny , Bellander Bo-Michael , Belli Antonio , Benali Habib , Berardino Maurizio , Beretta Luigi , Blaabjerg Morten , Bragge Peter , Brazinova Alexandra , Brinck Vibeke , Brooker Joanne , Brorsson Camilla , Buki Andras , Bullinger Monika , Cabeleira Manuel , Caccioppola Alessio , Calappi Emiliana , Calvi Maria Rosa , Cameron Peter , Lozano Guillermo Carbayo , Carbonara Marco , Cavallo Simona , Chevallard Giorgio , Chieregato Arturo , Citerio Giuseppe , Clusmann Hans , Coburn Mark , Coles Jonathan , Cooper Jamie D. , Correia Marta , Čović Amra , Curry Nicola , Czeiter Endre , Czosnyka Marek , DahyotFizelier Claire , Dark Paul , Dawes Helen , De Keyser Véronique , Degos Vincent , Corte Francesco Della , Boogert Hugo den , Depreitere Bart , Đilvesi Đula , Dixit Abhishek , Donoghue Emma , Dreier Jens , Dulière GuyLoup , Ercole Ari , Esser Patrick , Ezer Erzsébet , Fabricius Martin , Feigin Valery L. , Foks Kelly , Frisvold Shirin , Furmanov Alex , Gagliardo Pablo , Galanaud Damien , Gantner Dashiell , Gao Guoyi , George Pradeep , Ghuysen Alexandre , Giga Lelde , Glocker Ben , Golubovic Jagoš , Gomez Pedro A. , Gratz Johannes , Gravesteijn Benjamin , Grossi Francesca , Gruen Russell L. , Gupta Deepak , Haagsma Juanita A. , Haitsma Iain , Helbok Raimund , Helseth Eirik , Horton Lindsay , Huijben Jilske , Hutchinson Peter J. , Jacobs Bram , Jankowski Stefan , Jarrett Mike , Jiang Jiyao , Johnson Faye , Jones Kelly , Karan Mladen , Kolias Angelos G. , Kompanje Erwin , Kondziella Daniel , Kornaropoulos Evgenios , Koskinen LarsOwe , Kovács Noémi , Kowark Ana , Lagares Alfonso , Lanyon Linda , Laureys Steven , Lecky Fiona , Ledoux Didier , Lefering Rolf , Legrand Valerie , Lejeune Aurelie , Levi Leon , Lightfoot Roger , Lingsma Hester , Maas Andrew I. R. , CastañoLeón Ana M. , Maegele Marc , Majdan Marek , Manara Alex , Manley Geoffrey , Martino Costanza , Maréchal Hugues , Mattern Julia , McMahon Catherine , Melegh Béla , Menon David , Menovsky Tomas , Mikolic Ana , Misset Benoit , Muraleedharan Visakh , Murray Lynnette , Negru Ancuta , Nelson David , Newcombe Virginia , Nieboer Daan , Nyirádi József , Olubukola Otesile , Oresic Matej , Ortolano Fabrizio , Palotie Aarno , Parizel Paul M. , Payen JeanFrançois , Perera Natascha , Perlbarg Vincent , Persona Paolo , Peul Wilco , Piippo-Karjalainen Anna , Pirinen Matti , Pisica Dana , Ples Horia , Polinder Suzanne , Pomposo Inigo , Posti Jussi P. , Puybasset Louis , Radoi Andreea , Ragauskas Arminas , Raj Rahul , Rambadagalla Malinka , Helmrich Isabel Retel , Rhodes Jonathan , Richardson Sylvia , Richter Sophie , Ripatti Samuli , Rocka Saulius , Roe Cecilie , Roise Olav , Rosand Jonathan , Rosenfeld Jeffrey V. , Rosenlund Christina , Rosenthal Guy , Rossaint Rolf , Rossi Sandra , Rueckert Daniel , Rusnák Martin , Sahuquillo Juan , Sakowitz Oliver , SanchezPorras Renan , Sandor Janos , Schäfer Nadine , Schmidt Silke , Schoechl Herbert , Schoonman Guus , Schou Rico Frederik , Schwendenwein Elisabeth , Sewalt Charlie , Singh Ranjit D. , Skandsen Toril , Smielewski Peter , Sorinola Abayomi , Stamatakis Emmanuel , Stanworth Simon , Stevens Robert , Stewart William , Steyerberg Ewout W. , Stocchetti Nino , Sundström Nina , Takala Riikka , Tamás Viktória , Tamosuitis Tomas , Taylor Mark Steven , Ao Braden Te , Tenovuo Olli , Theadom Alice , Thomas Matt , Tibboel Dick , Timmers Marjolein , Tolias Christos , Trapani Tony , Tudora Cristina Maria , Unterberg Andreas , Vajkoczy Peter , Vallance Shirley , Valeinis Egils , Vámos Zoltán , van der Jagt Mathieu , Van der Steen Gregory , van der Naalt Joukje , van Dijck Jeroen T. J. M. , van Erp Inge A. , van Essen Thomas A. , Van Hecke Wim , van Heugten Caroline , Van Praag Dominique , van Veen Ernest , Vyvere Thijs Vande , van Wijk Roel P. J. , Vargiolu Alessia , Vega Emmanuel , Velt Kimberley , Verheyden Jan , Vespa Paul M. , Vik Anne , Vilcinis Rimantas , Volovici Victor , von Steinbüchel Nicole , Voormolen Daphne , Vulekovic Petar , Wang Kevin K. W. , Whitehouse Daniel , Wiegers Eveline , Williams Guy , Wilson Lindsay , Winzeck Stefan , Wolf Stefan , Yang Zhihui , Ylén Peter , Younsi Alexander , Zeiler Frederick A. , Zelinkova Veronika , Ziverte Agate , Zoerle Tommaso 
Published: July 2022

AbstractBackgroundWhile the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classification of traumatic brain injury (TBI) as ‘mild’, ‘moderate’ or ‘severe’ based on this fails to capture enormous heterogeneity in pathophysiology and treatment response. We hypothesized that data-driven characterization of TBI could identify distinct endotypes and give mechanistic insights.MethodsWe developed an unsupervised statistical clustering model based on a mixture of probabilistic graphs for presentation (< 24 h) demographic, clinical, physiological, laboratory and imaging data to identify subgroups of TBI patients admitted to the intensive care unit in the CENTER-TBI dataset (N = 1,728). A cluster similarity index was used for robust determination of optimal cluster number. Mutual information was used to quantify feature importance and for cluster interpretation.ResultsSix stable endotypes were identified with distinct GCS and composite systemic metabolic stress profiles, distinguished by GCS, blood lactate, oxygen saturation, serum creatinine, glucose, base excess, pH, arterial partial pressure of carbon dioxide, and body temperature. Notably, a cluster with ‘moderate’ TBI (by traditional classification) and deranged metabolic profile, had a worse outcome than a cluster with ‘severe’ GCS and a normal metabolic profile. Addition of cluster labels significantly improved the prognostic precision of the IMPACT (International Mission for Prognosis and Analysis of Clinical trials in TBI) extended model, for prediction of both unfavourable outcome and mortality (bothp < 0.001).ConclusionsSix stable and clinically distinct TBI endotypes were identified by probabilistic unsupervised clustering. In addition to presenting neurology, a profile of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refining current TBI classifications with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care.Trial registrationThe core study was registered with ClinicalTrials.gov, numberNCT02210221, registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582).