# Can We Cluster ICU Treatment Strategies for Traumatic Brain Injury by Hospital Treatment Preferences?

Iris Ceyisakar, Jilske Huijben, Andrew Maas, Hester Lingsma, Nikki van Leeuwen, Cecilia Åkerlund, Krisztina Amrein, Nada Andelic, Lasse Andreassen, Audny Anke, et al.

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## To cite this version:

Iris Ceyisakar, Jilske Huijben, Andrew Maas, Hester Lingsma, Nikki van Leeuwen, et al. Can We Cluster ICU Treatment Strategies for Traumatic Brain Injury by Hospital Treatment Preferences?. Neurocritical Care, 2021, 36 (3), pp.846-856. 10.1007/s12028-021-01386-y. hal-04831486

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# Can We Cluster ICU Treatment Strategies for Traumatic Brain Injury by Hospital Treatment Preferences?

Iris E. Ceyisakar¹,²* ID, Jilske A. Huijben¹, Andrew I. R. Maas², Hester F. Lingsma¹ and Nikki van Leeuwen¹ CENTER-TBI participants and investigators

© 2021 The Author(s)

**Abstract**

**Background:** In traumatic brain injury (TBI), large between-center differences in treatment and outcome for patients managed in the intensive care unit (ICU) have been shown. The aim of this study is to explore if European neuro-trauma centers can be clustered, based on their treatment preference in different domains of TBI care in the ICU.

**Methods:** Provider profiles of centers participating in the Collaborative European Neurotrauma Effectiveness Research in TBI study were used to assess correlations within and between the predefined domains: intracranial pressure monitoring, coagulation and transfusion, surgery, prophylactic antibiotics, and more general ICU treatment policies. Hierarchical clustering using Ward's minimum variance method was applied to group data with the highest similarity. Heat maps were used to visualize whether hospitals could be grouped to uncover types of hospitals adhering to certain treatment strategies.

**Results:** Provider profiles were available from 66 centers in 20 different countries in Europe and Israel. Correlations within most of the predefined domains varied from low to high correlations (mean correlation coefficients 0.2–0.7). Correlations between domains were lower, with mean correlation coefficients of 0.2. Cluster analysis showed that policies could be grouped, but hospitals could not be grouped based on their preference.

**Conclusions:** Although correlations between treatment policies within domains were found, the failure to cluster hospitals indicates that a specific treatment choice within a domain is not a proxy for other treatment choices within or outside the domain. These results imply that studying the effects of specific TBI interventions on outcome can be based on between-center variation without being substantially confounded by other treatments.

**Trial registration:** We do not report the results of a health care intervention.

**Keywords:** Provider profiling, Between-hospital variation, Comparative effectiveness research, Traumatic brain injury

**Introduction**

Traumatic brain injury (TBI) remains a major global health issue, being one of the leading causes of mortality

and disability with 2.5 million reported cases each year within the European Union and United Kingdom [1–3].

The primary injury is irreversible, and the main focus of treatment is on avoiding and limiting secondary brain damage. In patients with severe TBI, this is often informed by intracranial pressure (ICP) or brain-metabolic monitoring. Previous studies have debated monitoring and treatment choices in TBI [4], and evidence

<footnote>*Correspondence: iris.kohen@gmail.com
¹Center for Medical Decision Making, Department of Public Health, Erasmus Medical Center, PO Box 2040, 3000, CA, Rotterdam, The Netherlands
Full list of author information is available at the end of the article</footnote>
underpinning monitoring and treatment recommendations is relatively weak.

This uncertainty is reflected in large between-center differences in processes and outcomes for patients treated in the intensive care unit (ICU) after TBI [5, 6]. The differences in treatment policy can be exploited to study treatment effectiveness in comparative effectiveness research (CER). One approach to CER is to identify the most effective treatment, by comparing hospitals' treatment choices and relating these to their outcomes. In recent years, this approach has gained popularity in TBI as a complementary approach to the evidence base provided by randomized controlled trials [7]. CER can be used to identify a causal relationship between a treatment and outcome if known and unknown confounders can be adequately adjusted for and if the treatment under investigation is not correlated with other treatment policies. To date, it is unknown whether certain treatment strategies in patients with TBI are related. Such knowledge would be essential when comparing outcomes on a hospital level within the framework of CER to study whether differences in outcomes can be attributed to the separate interventions.

If, on the other hand, multiple treatment choices are correlated, it gives the possibility to group these together and identify hospitals with, for example, a more aggressive treatment strategy. Conclusions could then only be drawn on a very general level: whether a more aggressive or a more passive treatment strategy is more effective. Within the framework of CER, however, this would make it impossible to study specific treatments and their effect on outcome because some specific treatment aspects within the strategy may be beneficial and others even harmful.

Focusing on the domains of ICP monitoring, prophylactic antibiotics, transfusion targets, and general ICU management, our aim was to investigate correlations between treatment policies and to explore if European neurotrauma centers can be clustered based on their treatment strategy in patients with TBI.

# Methods

## Collaborative European Neurotrauma Effectiveness Research in TBI Study

The Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study is a prospective longitudinal multicenter observational study conducted across Europe and Israel (ClinicalTrials.gov ref. NCT02210221) [8]. CENTER-TBI aims to better characterize and describe TBI in a European context and to further advance the care of patients with TBI within the broader international framework of the International Initiative for TBI Research (https://intbir.nih.gov/).

Principal investigators of each participating center in this study received questionnaires about the structures (type of facilities and equipment, the qualifications of medical staff and their organizations) and processes (treatment policies in different phases of TBI care) of their center: the provider profiling questionnaires [9]. Participants were explicitly asked for their general policy rather than for individual treatment preferences. General policy was defined as “the way the large majority of patients (> 75%) with a certain indication would be treated.” Detailed information about the content, development, and validation of the original 321 questions can be found in an earlier publication [9]. Baseline characteristics for centers were described using frequencies and percentages.

## Predefined Treatment Domains

We selected 58 questions on the basis of expert consensus concerning care in the ICU setting, covering the domains of coagulation and transfusion, neurosurgery, ICP monitoring, prophylactic antibiotics, and general management. The selected questions were chosen before the analysis on the basis of clinical relevance. Follow-up, conditional questions (“if you answered A, then specify...”) and all open questions were excluded, aiming to obtain a standardized overview of treatment approaches.

Questions from predefined domains were chosen to enable stratification of hospitals over multiple domains. To determine possible underlying treatment strategies, polychoric correlation coefficients between questions were calculated [10]. Correlations were visualized with correlation plots, using only absolute values (between 0 and 1), as any negative correlations were as relevant as positive correlations in determining treatment strategies. Missing answers were disregarded for calculation of the correlation. Of the 58 questions, 44 questions were complete, and the other 12 had up to 8 out of 66 answers missing. We looked at correlations of questions *within* the predefined domains (exploring consistency in treatment policies within a specific domain) as well as correlations *between* the domains (exploring interdependencies of treatments between domains).

## Regrouping of Questions

After correlations were determined, the questions were grouped based on the data, ignoring the previously defined domains, with an hierarchical cluster analysis using Ward's minimum variance method, to group together the questions with the highest similarity [11]. This is an agglomerative clustering method in which the
data points (questions) are clustered (across all domains) in different steps until only questions with the greatest similarity form a cluster. We used the Bayesian inference criterion for *k*-means to determine the number of clusters that were to be formed [12, 13].

## Heat Maps

By using the same clustering algorithm, heat maps were made for each newly formed group of questions. Heat maps allow for the recognition of patterns in the preference of hospitals and made it possible to determine whether we could discern certain types of hospitals. This was performed on all complete cases: centers with missing answers within the cluster of questions were disregarded. For cluster two, 53 of the 66 participating hospitals were included in the heat map; for cluster five, 47 of the hospitals were included, and all other clusters included all participating hospitals. All analysis were performed in R version 3.3.0 using the following packages: plothatmap, RColorBrewer, foreign, cluster, corrplot, dplyr, and fmsb [14–21].

## Results

### CENTER-TBI Study

Provider profiling questionnaires were completed in 66 centers (97% response rate), mainly by intensivists (n=33, 50%) and neurosurgeons (n=23, 35%), but otherwise by administrative staff (n=11, 17%), neurologists (n=5, 8%), anesthesiologists (n=5, 8%), and a trauma surgeon (n=1, 2%). The majority of these centers had an academic affiliation (n=60, 91%). The center characteristics are described in Supplementary Table 1 and in more detail in a previous publication [9].

### Correlation within and Between Domains

Correlation between treatment policies within the pre-defined domains was variable (Fig. 1a–e). Correlations within the domain of prophylactic antibiotics (mean correlation coefficient = 0.6, range 0.4–0.8) ranged from moderate to strong, but questions were based on only one very specific topic. The correlation within the other domains was shown to be much lower (Table 1). Correlations between domains were lower, with mean correlation coefficients of 0.2 for each domain correlated with all other domains (Table 1 and Fig. 1f).

### Data-Driven Cluster Analysis

The cluster analysis revealed four clusters, one fewer compared with the clinically determined domains (Fig. 2). The grouping remained very similar to the

predefined domains, especially for the original domain of neurosurgery. A few questions did correlate with other subdomains, mainly due to overlap in topic of the questions. For example, the question, “Is a coagulation panel assessed prior to insertion of an ICP monitoring device?” could span the domains of coagulation and transfusion as well as ICP monitoring (Supplementary Table 2).

## Grouping of Hospitals

No hospital types were discernable in the heat maps made for each cluster of questions (Fig. 3, for the heat map of all the questions see Suppl. Figure 2). The heat maps served as a visual indication of the possibility to cluster the hospitals. Based on the visualization of these data, we have decided that further clustering should not be done. Although most similar questions had been grouped together, heat maps showed no clear pattern in the preferences of the hospitals, indicating that they could not be grouped based on their treatment tendencies.

## Discussion

This study aimed to group European neurotrauma centers into clusters based on their treatment preference in patients with TBI in a variety of domains. Hospitals could not be clustered based on their reported choices of treatment within the five domains of the provider profiling questionnaires. These results imply that it is unlikely that hospitals can be categorized as a certain type of hospital based on the treatment strategies they follow across multiple domains of monitoring and treatment in patients with TBI.

The lack of evident treatment policies across multiple domains might be explained by a lack of strong evidence of the effectiveness of certain treatments, leading to weak guideline recommendations, which may cause heterogeneity in treatment strategies across Europe [22]. However, it could also be the result of more individualized medicine, in which case treatment strategies are based on the individual patient and monitoring characteristics [1]. TBI is a complex heterogeneous syndrome that might not be captured with a single treatment strategy. With the advanced monitoring devices and the range of brain and system targeted therapies available, variation between centers in treatment strategies is likely.

For future statistical analyses, our finding that the questions correlated mainly within their previously defined subdomain implies that all elements of TBI treatment can, and have to, be analyzed separately rather than combining different domains when relations between treatment and outcome are explored. The correlation of some questions with questions from a different domain could be attributed to overlap in the subject of the questions.
Correlations between questions of the 5 predefined domains

<figure><img src="image_4.png" /><figcaption>**Fig. 1** Correlation plot showing correlations between questions, grouped (squares) to show the five predefined domains: intracranial pressure (ICP) monitoring (a), coagulation and transfusion (b), surgery (c), prophylactic antibiotics (d), and more general ICU treatment policies (e), and correlations within and between the predefined domains (f). The correlations were calculated with Pearson correlations, and a higher correlation is visualized as a darker blue. ICU intensive care unit</figcaption></figure>
<table><caption>Table 1 Overview of the correlation coefficient calculated for questions within and between predefined domains</caption><thead><tr><th>Domain</th><th>Mean (SD)</th><th>Min</th><th>Max</th><th>Number of questions</th></tr></thead><tbody><tr><td colspan="5">Correlation coefficients for correlation between questions within the predefined domains</td></tr><tr><td>Coagulation &amp; transfusion targets</td><td>0.2 (0.2)</td><td>0</td><td>0.9</td><td>8</td></tr><tr><td>Neurosurgery</td><td>0.2 (0.2)</td><td>0</td><td>0.8</td><td>19</td></tr><tr><td>ICP monitoring</td><td>0.3 (0.2)</td><td>0</td><td>0.9</td><td>17</td></tr><tr><td>Prophylactic antibiotics</td><td>0.6 (0.2)</td><td>0.4</td><td>0.8</td><td>4</td></tr><tr><td>General management</td><td>0.3 (0.2)</td><td>0</td><td>1</td><td>9</td></tr><tr><td colspan="5">Correlation coefficients for questions between the predefined domains</td></tr><tr><td>Coagulation &amp; transfusion targets versus rest</td><td>0.2 (0.1)</td><td>0</td><td>0.7</td><td></td></tr><tr><td>Neurosurgery versus rest</td><td>0.2 (0.2)</td><td>0</td><td>0.9</td><td></td></tr><tr><td>ICP monitoring versus rest</td><td>0.2 (0.2)</td><td>0</td><td>0.9</td><td></td></tr><tr><td>Prophylactic antibiotics versus rest</td><td>0.2 (0.2)</td><td>0</td><td>0.9</td><td></td></tr><tr><td>General management versus rest</td><td>0.2 (0.1)</td><td>0</td><td>0.7</td><td></td></tr></tbody></table>

We used the Pearson correlation coefficient to determine correlations within domains (upper panel) and between domains (lower panel)

ICP intracranial pressure, Max maximum, Min minimum, SD standard deviation

Other reasons for correlations with other domains could be dependent on who is responsible for the decisions being made: for example, decisions for treatment of the patient are made by the neurosurgeon would have a higher chance of correlating with other decisions made by that neurosurgeon.

Based on our study, we may conclude that future CER analyses will be likely to measure a direct effect of one intervention on outcome instead of a general effect of multiple treatment effects. This is important knowledge to continue CER research within TBI, in which outcomes between centers are compared to find underlying differences in treatment. Although unmeasured confounders will always have to be considered, knowing that multiple treatments are not interdependent is a first step in further elucidating the effects of treatment choices. This study has its strengths and limitations. This study was conducted in multiple neurotrauma centers across Europe. The development and dissemination of the questionnaires was done in different phases. Two methods were used to determine relations between and within certain treatment strategy domains. With hierarchical cluster analyses, we confirmed the results of correlation analyses. However, our study also has its limitations; in a survey study using provider profiling questionnaires, centers only indicate their treatment strategy and do not provide an objective measure of real-time practice. This could overestimate or underestimate the use of general policies. The centers included in this study are mostly academic medical centers, and a more heterogeneous group of care providers could have potentially shown a clearer division

in hospital types. Previous studies from CENTER-TBI show that, even within the sample of mostly academic centers, substantial practice variation exists [23–25].

Further, the study is focused on hospitals in Europe, and it is possible that these findings cannot be extrapolated to other large regions, such as the United States.

Possibly better suited for the purpose of grouping hospitals would be a questionnaire that is more specific. Future research using a more detailed questionnaire might be a solution to increase reliability of indicated treatment preferences. More targeted questions could allow for a better and more thorough understanding. This would give insight into why decisions are made and by whom. However, the better we understand and the more specific the information is, the harder it will be to visualize, generalize, and simplify enough to be able to present it graphically.

This is the first study that studied underlying relations in treatment strategies, and these results need to be confirmed in other studies.

## Conclusions

We found correlations in treatment policies within domains, especially for neurosurgical interventions, but no evidence that hospitals could be clustered, indicating that a specific treatment choice within a domain is not a proxy for other treatment choices within or outside the domain. Because we did not find an indication that some centers, in general, were more eager to treat or reach higher treatment intensity levels overall, future TBI analyses should be conducted per specific treatment item
<figure><img src="image_5.png" /></figure>
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instead of per treatment domain. Furthermore, within
the CER paradigm, this implies that analyzing effects of
an intervention on outcome is likely to measure a direct
effect of that intervention without being substantially
confounded by a general effect of multiple treatments.

**Supplementary Information**

The online version contains supplementary material available at https://doi.org/10.1007/s12028-021-01386-y.

**Author details**

¹ Center for Medical Decision Making, Department of Public Health, Erasmus Medical Center, PO Box 2040, 3000, CA, Rotterdam, The Netherlands. ² Department of Neurosurgery, Antwerp University Hospital, University of Antwerp, Drie Eikenstraat 655, 2650 Antwerp, Belgium.

**Acknowledgments**

The authors thank all clinical and research staff at the CENTER-TBI sites for
completing the provider profiling questionnaires. Data used in preparation of
this manuscript were obtained in the context of CENTER-TBI, a large collabora-
tive project with the support of the European Commission 7th Framework
program (602150). The funder had no role in the design of the study and collection, analysis, and interpretation of data and in writing the manuscript.

The CENTER-TBI participants and investigators: Cecilia Åkerlund<fnref n="1" />, Krisztina Amrein², Nada Andelic³, Lasse Andreassens<fnref n="4" />, Audny Anke<fnref n="5" />, Anna Antoni<fnref n="6" />, Gérard Audibert<fnref n="7" />, Philippe Azouvi<fnref n="8" />, Maria Luisa Azzolini<fnref n="9" />, Ronald Bartels<fnref n="10" />, Pål Barzó<fnref n="11" />, Romuald Beauvais<fnref n="12" />, Ronny Beer<fnref n="13" />, Bo-Michael Bellander<fnref n="14" />, Antonio Belli<fnref n="15" />, Habib Benali<fnref n="16" />, Maurizio Berardino<fnref n="17" />, Luigi Beretta<fnref n="9" />, Morten Blaabjerg<fnref n="18" />, Peter Bragge<fnref n="19" />, Alexandra Brazinova<fnref n="20" />, Vibeka Brinck<fnref n="21" />, Joanne Brooker<fnref n="22" />, Camilla Brorsson<fnref n="23" />, Andras Bukí<fnref n="24" />, Monika Bullinger<fnref n="25" />, Manuel Cabeleira<fnref n="26" />, Alessio Caccioppola<fnref n="27" />, Emiliana Calapii<fnref n="27" />, Maria Rosa Calvi<fnref n="9" />, Peter Cameron<fnref n="28" />, Guillermo Carbayo Lozano<fnref n="29" />, Marco Carbonara<fnref n="27" />, Simona Cavallo<fnref n="17" />, Giorgio Chevallard<fnref n="30" />, Arturo Chieregato<fnref n="30" />, Giuseppe Citerio<fnref n="31" />, 32, Hans Clusmann<fnref n="33" />, Mark Coburn<fnref n="34" />, Jonathan Coles<fnref n="35" />, Jamie D. Cooper<fnref n="36" />, Marta Correia<fnref n="37" />, Amra Čović<fnref n="38" />, Nicola Curry<fnref n="39" />, Endre Czeiter<fnref n="24" />, Marek Czosnyka<fnref n="26" />, Claire Dahyut-Fizelier<fnref n="40" />, Paul Dark<fnref n="41" />, Helen Dawes<fnref n="42" />, Véronique De Keyser<fnref n="43" />, Vincent Degos<fnref n="16" />, Francesco Della Corte⁴⁴, Hugo den Boogert<fnref n="10" />, Bart Depreiteres⁴⁵, Dula Đilvesti⁴⁶, Abhishek Dixit⁴⁷, Emma Donoghue<fnref n="22" />, Jens Dreier⁴⁸, Guy-Loup Dulière⁴⁹, Ari Ercole⁴⁷, Patrick Esser<fnref n="42" />, Erzsébet Ezer⁵⁰, Martin Fabricius⁵¹, Valery L. Feigin⁵², Kelly Foks⁵³, Shirin Frisvold⁵⁴, Alex Furmanov⁵⁵, Pablo Gagliardo⁵⁶, Damien Galanaud<fnref n="16" />, Dashiel Gantner<fnref n="28" />, Guoyi Gao<fnref n="27" />, Pradeep George<fnref n="28" />, Alexandre Ghuysen<fnref n="29" />, Lelde Giga<fnref n="30" />, Ben Glocke⁶¹, Jago Solubovic⁴⁶, Pedro A. Gomez<fnref n="26" />, Johannes Gratz⁶³, Benjamin Gravesteijn⁶⁴, Francesca Grossi⁴⁴, Russell L. Gruen⁶⁵, Deepak Gupta⁶⁶, Juanita A. Haagsma⁶⁴, Iain Hairsma⁶⁰, Raimund Helbok<fnref n="13" />, Eirik Helseth⁶⁸, Lindsay Horton⁶⁹, Jilse Huijben⁶⁴, Peter J. Hutchinson⁷⁰, Bram Jacobs⁷¹, Stefan Jankowski⁷², Mike Jarrett<fnref n="21" />, Ji-yao Jiang⁵⁸, Faye Johnson⁷³, Kelly Jones⁵², Mladen Karan⁴⁶, Angelos G. Kolias⁷⁰, Erwin Kompanje⁷⁴, Daniel Kondziella⁵¹, Evgenios Kornaropoulos⁴⁷, Lars-Owe Koskinen⁷⁵, Noémi Kovács⁷⁶, Ana Kowark⁷⁷, Alfonso Lagares⁵², Linda Lanyon⁵⁸, Steven Laureys⁷⁸, Fiona Lecky⁷⁹, 80, Didier Ledoux⁷⁸, Rolf Lefering⁸¹, Valerie Legrand⁸², Aurelie Lejeune⁸³, Leon Levi⁸⁴, Roger Lightfoot⁸⁵, Hester Lingsma⁶⁴, Andrew I.R. Maas<fnref n="43" />, Ana M. Castaño-León⁶², Marc Maegele⁸⁶, Marek Majdan<fnref n="20" />, Alex Manara⁸⁷, Geoffrey Manley⁸⁸, Costanza Martino⁸⁹, Hugues Maréchal⁴⁹, Julia Mattern⁹⁰, Catherine McMahon⁹¹, Béla Melegh⁹², David Menon⁴⁷, Tomas Menovsky<fnref n="43" />, Ana Mikolic⁶⁴, Benoit Misset⁷⁸, Visakh Muraleedharan⁵⁸, Lynnette Murray<fnref n="28" />, Ancuta Negru⁹³, David Nelson<fnref n="1" />, Virginia Newcombe⁴⁷, Daan Nieboer⁶⁴, József Nyírádi<fnref n="7" />, Otesile Olubukola⁷⁹, Matej Oresic⁹⁴, Fabrizio Ortolano<fnref n="27" />, Aarno Palotie⁹⁵, 96, 97, Paul M. Parizel⁹⁸, Jean-François Payen⁹⁹, Natascha Perera<fnref n="12" />, Vincent Perlbarg<fnref n="16" />, Paolo Persona¹⁰⁰, Wilco Peul¹⁰¹, Anna Piippo-Karjalainen¹⁰², Matti Pirinen⁹⁵, Dana Piscia⁶⁴, Horia Ples⁹³, Suzanne Polinder⁶⁴, Inigo Pomposo<fnref n="29" />, Jussi P. Posti¹⁰³, Louis Puybasset¹⁰⁴, Andreea Radoi¹⁰⁵, Arminas Ragauskas¹⁰⁶, Rahul Raj¹⁰², Malinka Rambadagalla¹⁰⁷, Isabel Retel Helmrich⁶⁴, Jonathan Rhodes¹⁰⁸, Sylvia Richardson¹⁰⁹, Sophie Richter⁴⁷, Samuli Ripatti⁹⁵, Saulius Rocka¹⁰⁶, Cecilie Roe¹¹⁰, Olav Roise¹¹¹, 112, Jonathan Rosand¹¹³, Jeffrey V. Rosenfeld¹¹⁴, Christina Rosenlund¹¹⁵, Guy Rosenthal⁵⁵, Rolf Rossaint⁷⁷, Sandra Rossi¹⁰⁰, Daniel Rueckert⁶¹, Martin Rucknák¹¹⁶, Juan Sahuquillo¹⁰⁵, Oliver Sakowitz⁹⁰, 117, Renan Sanchez-Porras¹¹⁷, Janos Sandor¹¹⁸, Nadine Schäfer⁸¹, Silke Schmidt¹¹⁹, Herbert Schoechl¹²⁰, Guus Schoonman¹²¹, Rico Frederik Schou¹²², Elisabeth Schwendenwein<fnref n="6" />, Charlie Sewalt⁶⁴, Ranjit D. Singh¹⁰¹, Toril Skandsen¹²³, 124, Peter Smielewski<fnref n="26" />, Abayomi Sorinola¹²⁵, Emmanuel Stamatakis⁴⁷, Simon Stanworth<fnref n="39" />, Robert Stevens¹²⁶, William Stewart¹²⁷, Ewout W. Steyerberg⁶⁴, 128, Nino Stocchetti¹²⁹, Nina Sundström¹³⁰, Rilkkä Takala¹³¹, Viktória Tamás¹²⁵, Tomas Tamosuitis¹³², Mark Steven Taylor<fnref n="20" />, Braden Te Ao⁵², Olli Tenovuo¹⁰³, Alice Theadom⁵², Matt Thomas⁸⁷, Dick Tibboel¹³³, Marjolein Timmers⁷⁴, Christos Tolas¹³⁴, Tony Trapani<fnref n="28" />, Maria Maria Tudora⁹³, Andreas Unterberg⁹⁰, Peter Vajkoczy¹³⁵, ShirleyVallance<fnref n="28" />, Egils Valeinis⁶⁰, Zoltán Vámos⁵⁰, Mathieu van der Jagt¹³⁶, Gregory Van der Steen⁴⁵, Joukje van der Naalt⁷¹, Jeroen T.J.M. van Dijck¹⁰¹, Inge A. van Erp¹⁰¹, Thomas A. van Essen¹⁰¹, Wim Van Hecke¹³⁷, Caroline van Heugten¹³⁸, Dominique Van Praag¹³⁹, Ernest van Veen⁶⁴, Thijs Vande Vyvvere¹³⁷, Roel P. J. van Wijk¹⁰¹, Alessia Vargiolu<fnref n="23" />, Emmanuel Vega⁸³, Kimberley Velt⁶⁴, Jan Verheyden¹³⁷, Paul M. Vespa¹⁴⁰, Anne Vik¹²³, 141, Rimantas Vilcinis¹³², Victor Volovici⁶⁷, Nicole von Steinbüchel<fnref n="38" />, Daphne Voormolen⁶⁴, Petar Vulekovic⁴⁶, Kevin K.W. Wang¹⁴², Daniel Whitehouse⁴⁷, Eveline Wiegers⁶⁴, Guy Williams⁴⁷, Lindsay Wilson⁶⁹, Stefan Winzeck⁴⁷, Stefan Wolf¹⁴³, Zhihui Yang¹¹³, Peter Ylén¹⁴⁴, Alexander Younsi⁹⁰, Frederick A. Zeiler⁴⁷, 145, Veronika Zelinkova<fnref n="20" />, Agate Ziverte⁶⁰, and Tommaso Zuerle<fnref n="27" />.

<footnote n="1">¹Department of Physiology and Pharmacology, Section of Perioperative Medicine and Intensive Care, Karolinska Institutet, Stockholm, Sweden
²János Szentágothai Research Centre, University of Pécs, Pécs, Hungary
³Division of Surgery and Clinical Neuroscience, Department of Physical Medicine and Rehabilitation, Oslo University Hospital and University of Oslo, Oslo, Norway</footnote>

<footnote n="4">⁴Department of Neurosurgery, University Hospital Northern Norway, Tromso, Norway</footnote>

<footnote n="5">⁵Department of Physical Medicine and Rehabilitation, University Hospital Northern Norway, Tromso, Norway</footnote>

<footnote n="6">⁶Trauma Surgery, Medical University Vienna, Vienna, Austria</footnote>

<footnote n="7">⁷Department of Anesthesiology & Intensive Care, University Hospital Nancy, Nancy, France</footnote>

<footnote n="8">⁸Raymond Poincare hospital, Assistance Publique – Hopitaux de Paris, Paris, France</footnote>

<footnote n="9">⁹Department of Anesthesiology & Intensive Care, S Raffaele University Hospital, Milan, Italy</footnote>

<footnote n="10">¹⁰Department of Neurosurgery, Radboud University Medical Center, Nijmegen, The Netherlands</footnote>

<footnote n="11">¹¹Department of Neurosurgery, University of Szeged, Szeged, Hungary</footnote>

<footnote n="12">¹²International Projects Management, ARTTIC, Munchen, Germany</footnote>

<footnote n="13">¹³Department of Neurology, Neurological Intensive Care Unit, Medical University of Innsbruck, Innsbruck, Austria</footnote>

<footnote n="14">¹⁴Department of Neurosurgery & Anesthesia & intensive care medicine, Karolinska University Hospital, Stockholm, Sweden</footnote>

<footnote n="15">¹⁵NIHR Surgical Reconstruction and Microbiology Research Centre, Birming- ham, UK</footnote>

<footnote n="16">¹⁶Anesthesie-Réanimation, Assistance Publique – Hopitaux de Paris, Paris, France</footnote>

<footnote n="17">¹⁷Department of Anesthesia & ICU, AOU Città della Salute e della Scienza di Torino - Orthopedic and Trauma Center, Torino, Italy</footnote>

<footnote n="18">¹⁸Department of Neurology, Odense University Hospital, Odense, Denmark</footnote>

<footnote n="19">¹⁹BehaviourWorks Australia, Monash Sustainability Institute, Monash University, Victoria, Australia</footnote>

<footnote n="20">²⁰Department of Public Health, Faculty of Health Sciences and Social Work, Trnava University, Trnava, Slovakia</footnote>

<footnote n="21">²¹Quesgen Systems Inc., Burlingame, California, USA</footnote>

<footnote n="22">²²Australian & New Zealand Intensive Care Research Centre, Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia</footnote>

<footnote n="23">²³Department of Surgery and Perioperative Science, Umeå University, Umeå, Sweden</footnote>

<footnote n="24">²⁴Department of Neurosurgery, Medical School, University of Pécs, Hungary and Neurotrauma Research Group, János Szentágothai Research Centre, University of Pécs, Hungary</footnote>

<footnote n="25">²⁵Department of Medical Psychology, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany</footnote>

<footnote n="26">²⁶Brain Physics Lab, Division of Neurosurgery, Dept of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK</footnote>

<footnote n="27">²⁷NIRO ICU, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milan, Italy</footnote>

<footnote n="28">²⁸ANZIC Research Centre, Monash University, Department of Epidemiology and Preventive Medicine, Melbourne, Victoria, Australia</footnote>

<footnote n="29">²⁹Department of Neurosurgery, Hospital of Cruces, Bilbao, Spain</footnote>

<footnote n="30">³⁰Neurolntensive Care, Niguarda Hospital, Milan, Italy</footnote>

<footnote n="31">³¹School of Medicine and Surgery, Università Milano Bicocca, Milano, Italy</footnote>

<footnote n="32">³²Neurolntensive Care, ASST de Monza, Monza, Italy</footnote>

<footnote n="33">³³Department of Neurosurgery, Medical Faculty RWTH Aachen University, Aachen, Germany</footnote>

<footnote n="34">³⁴Department of Anesthesiology and Intensive Care Medicine, University Hospital Bonn, Bonn, Germany</footnote>

<footnote n="35">³⁵Department of Anesthesia & Neurointensive Care, Cambridge University Hospital NHS Foundation Trust, Cambridge, UK</footnote>

<footnote n="36">³⁶School of Public Health & PM, Monash University and The Alfred Hospital, Melbourne, Victoria, Australia</footnote>

<footnote n="37">³⁷Radiology/MRI department, MRC Cognition and Brain Sciences Unit, Cambridge, UK</footnote>

<footnote n="38">³⁸Institute of Medical Psychology and Medical Sociology, Universitätsmedizin Göttingen, Göttingen, Germany</footnote>

<footnote n="39">³⁹Oxford University Hospitals NHS Trust, Oxford, UK</footnote>

<footnote n="40">⁴⁰Intensive Care Unit, CHU Poitiers, Poitiers, France</footnote>

<footnote n="41">⁴¹University of Manchester NIHR Biomedical Research Centre, Critical Care Directorate, Salford Royal Hospital NHS Foundation Trust, Salford, UK</footnote>

<footnote n="42">⁴²Movement Science Group, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK</footnote>

<footnote n="43">⁴³Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Edegem, Belgium</footnote>
⁴⁴Department of Anesthesia & Intensive Care, Maggiore Della Carità Hospital, Novara, Italy

⁴⁵Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium

⁴⁶Department of Neurosurgery, Clinical centre of Vojvodina, Faculty of Medicine, University of Novi Sad, Novi Sad, Serbia

⁴⁷Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK

⁴⁸Center for Stroke Research Berlin, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

⁴⁹Intensive Care Unit, CHR Citadelle, Liège, Belgium

⁵⁰Department of Anaesthesiology and Intensive Therapy, University of Pécs, Pécs, Hungary

⁵¹Departments of Neurology, Clinical Neurophysiology and Neuroanesthesiology, Region Hovedstaden Rigshospitalet, Copenhagen, Denmark

⁵²National Institute for Stroke and Applied Neurosciences, Faculty of Health and Environmental Studies, Auckland University of Technology, Auckland, New Zealand

⁵³Department of Neurology, Erasmus MC, Rotterdam, the Netherlands

⁵⁴Department of Anesthesiology and Intensive care, University Hospital Northern Norway, Tromso, Norway

⁵⁵Department of Neurosurgery, Hadassah-hebrew University Medical center, Jerusalem, Israel

⁵⁶Fundación Instituto Valenciano de Neurorrehabilitación (FIVAN), Valencia, Spain

⁵⁷Department of Neurosurgery, Shanghai Renji hospital, Shanghai Jiaotong University/school of medicine, Shanghai, China

⁵⁸Karolinska Institutet, INCF International Neuroinformatics Coordinating Facility, Stockholm, Sweden

⁵⁹Emergency Department, CHU, Liège, Belgium

⁶⁰Neurosurgery clinic, Pauls Stradins Clinical University Hospital, Riga, Latvia

⁶¹Department of Computing, Imperial College London, London, UK

⁶²Department of Neurosurgery, Hospital Universitario 12 de Octubre, Madrid, Spain

⁶³Department of Anesthesia, Critical Care and Pain Medicine, Medical University of Vienna, Austria

⁶⁴Division of Public Health, Erasmus Medical Center-University Medical Center, Rotterdam, The Netherlands

⁶⁵College of Health and Medicine, Australian National University, Canberra, Australia

⁶⁶Department of Neurosurgery, Neurosciences Centre & JPN Apex trauma centre, All India Institute of Medical Sciences, New Delhi-110029, India

⁶⁷Department of Neurosurgery, Erasmus MC, Rotterdam, the Netherlands

⁶⁸Department of Neurosurgery, Oslo University Hospital, Oslo, Norway

⁶⁹Division of Psychology, University of Stirling, Stirling, UK

⁷⁰Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital & University of Cambridge, Cambridge, UK

⁷¹Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands

⁷²Neurointensive Care, Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, UK

⁷³Salford Royal Hospital NHS Foundation Trust Acute Research Delivery Team, Salford, UK

⁷⁴Department of Intensive Care and Department of Ethics and Philosophy of Medicine, Erasmus Medical Center, Rotterdam, The Netherlands

⁷⁵Department of Clinical Neuroscience, Neurosurgery, Umeå University, Umeå, Sweden

⁷⁶Hungarian Brain Research Program - Grant No. KTIA_13_NAP-A-II/8, University of Pécs, Pécs, Hungary

⁷⁷Department of Anaesthesiology, University Hospital of Aachen, Aachen, Germany

⁷⁸Cyclotron Research Center, University of Liège, Liège, Belgium

⁷⁹Centre for Urgent and Emergency Care Research (CURE), Health Services Research Section, School of Health and Related Research (SchHARR), University of Sheffield, Sheffield, UK

⁸⁰Emergency Department, Salford Royal Hospital, Salford UK

⁸¹Institute of Research in Operative Medicine (IFOM), Witten/Herdecke University, Cologne, Germany

⁸²VP Global Project Management CNS, ICON, Paris, France

⁸³Department of Anesthesiology-Intensive Care, Lille University Hospital, Lille, France

⁸⁴Department of Neurosurgery, Rambam Medical Center, Haifa, Israel

⁸⁵Department of Anesthesiology & Intensive Care, University Hospitals Southampton NHS Trust, Southampton, UK

⁸⁶Cologne-Merheim Medical Center (CMMC), Department of Traumatology, Orthopedic Surgery and Sportmedicine, Witten/Herdecke University, Cologne, Germany

⁸⁷Intensive Care Unit, Southmead Hospital, Bristol, Bristol, UK

⁸⁸Department of Neurological Surgery, University of California, San Francisco, California, USA

⁸⁹Department of Anesthesia & Intensive Care, M. Bufalini Hospital, Cesena, Italy

⁹⁰Department of Neurosurgery, University Hospital Heidelberg, Heidelberg, Germany

⁹¹Department of Neurosurgery, The Walton centre NHS Foundation Trust, Liverpool, UK

⁹²Department of Medical Genetics, University of Pécs, Pécs, Hungary

⁹³Department of Neurosurgery, Emergency County Hospital Timisoara, Timisoara, Romania

⁹⁴School of Medical Sciences, Örebro University, Örebro, Sweden

⁹⁵Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland

⁹⁶Analytic and Translational Genetics Unit, Department of Medicine; Psychiatric & Neurodevelopmental Genetics Unit, Department of Psychiatry; Department of Neurology, Massachusetts General Hospital, Boston, MA, USA

⁹⁷Program in Medical and Population Genetics; The Stanley Center for Psychiatric Research, The Broad Institute of MIT and Harvard, Cambridge, MA, USA

⁹⁸Department of Radiology, University of Antwerp, Edegem, Belgium

⁹⁹Department of Anesthesiology & Intensive Care, University Hospital of Grenoble, Grenoble, France

¹⁰Department of Anesthesia & Intensive Care, Azienda Ospedaliera Università di Padova, Padova, Italy

¹⁰¹Dept. of Neurosurgery, Leiden University Medical Center, Leiden, The Netherlands and Dept. of Neurosurgery, Medical Center Haaglanden, The Hague, The Netherlands

¹⁰²Department of Neurosurgery, Helsinki University Central Hospital

¹⁰³Division of Clinical Neurosciences, Department of Neurosurgery and Turku Brain Injury Centre, Turku University Hospital and University of Turku, Turku, Finland

¹⁰⁴Department of Anesthesiology and Critical Care, Pitié-Salpêtrière Teaching Hospital, Assistance Publique, Hôpitaux de Paris and University Pierre et Marie Curie, Paris, France

¹⁰⁵Neurotraumatology and Neurosurgery Research Unit (UNINN), Vall d'Hebron Research Institute, Barcelona, Spain

¹⁰⁶Department of Neurosurgery, Kaunas University of technology and Vilnius University, Vilnius, Lithuania

¹⁰⁷Department of Neurosurgery, Rezekne Hospital, Latvia

¹⁰⁸Department of Anaesthesia, Critical Care & Pain Medicine NHS Lothian & University of Edinburgh, Edinburgh, UK

¹⁰⁹Director, MRC Biostatistics Unit, Cambridge Institute of Public Health, Cambridge, UK

¹¹⁰Department of Physical Medicine and Rehabilitation, Oslo University Hospital/University of Oslo, Oslo, Norway

¹¹¹Division of Orthopedics, Oslo University Hospital, Oslo, Norway

¹¹²Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway

¹¹³Broad Institute, Cambridge MA Harvard Medical School, Boston MA, Massachusetts General Hospital, Boston MA, USA

¹¹⁴National Trauma Research Institute, The Alfred Hospital, Monash University, Melbourne, Victoria, Australia

¹¹⁵Department of Neurosurgery, Odense University Hospital, Odense, Denmark

¹¹⁶International Neurotrauma Research Organisation, Vienna, Austria

¹¹⁷Klinik für Neurochirurgie, Klinikum Ludwigsburg, Ludwigsburg, Germany

¹¹⁸Division of Biostatistics and Epidemiology, Department of Preventive Medicine, University of Debrecen, Debrecen, Hungary

¹¹⁹Department Health and Prevention, University Greifswald, Greifswald, Germany

¹²⁰Department of Anaesthesiology and Intensive Care, AUVA Trauma Hospital, Salzburg, Austria
¹²¹Department of Neurology, Elisabeth-TweeSteden Ziekenhuis, Tilburg, the Netherlands

¹²²Department of Neuroanesthesia and Neurointensive Care, Odense University Hospital, Odense, Denmark

¹²³Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology, NTNU, Trondheim, Norway

¹²⁴Department of Physical Medicine and Rehabilitation, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway

¹²⁵Department of Neurosurgery, University of Pécs, Pécs, Hungary

¹²⁶Division of Neuroscience Critical Care, John Hopkins University School of Medicine, Baltimore, USA

¹²⁷Department of Neuropathology, Queen Elizabeth University Hospital and University of Glasgow, Glasgow, UK

¹²⁸Dept. of Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands

¹²⁹Department of Pathophysiology and Transplantation, Milan University, and Neuroscience ICU, Fondazione IRCCS Cà Granda Ospedale Maggiore Policlinico, Milano, Italy

¹³⁰Department of Radiation Sciences, Biomedical Engineering, Umeå University, Umeå, Sweden

¹³¹Perioperative Services, Intensive Care Medicine and Pain Management, Turku University Hospital and University of Turku, Turku, Finland

¹³²Department of Neurosurgery, Kaunas University of Health Sciences, Kaunas, Lithuania

¹³³Intensive Care and Department of Pediatric Surgery, Erasmus Medical Center, Sophia Children's Hospital, Rotterdam, The Netherlands

¹³⁴Department of Neurosurgery, Kings college London, London, UK

¹³⁵Neurologie, Neurochirurgie und Psychiatrie, Charité – Universitätsmedizin Berlin, Berlin, Germany

¹³⁶Department of Intensive Care Adults, Erasmus MC– University Medical Center Rotterdam, Rotterdam, the Netherlands

¹³⁷icoMetrix NV, Leuven, Belgium

¹³⁸Movement Science Group, Faculty of Health and Life Sciences, Oxford Brookes University, Oxford, UK

¹³⁹Psychology Department, Antwerp University Hospital, Edegem, Belgium

¹⁴⁰Director of Neurocritical Care, University of California, Los Angeles, USA

¹⁴¹Department of Neurosurgery, St. Olav's Hospital, Trondheim University Hospital, Trondheim, Norway

¹⁴²Department of Emergency Medicine, University of Florida, Gainesville, Florida, USA

¹⁴³Department of Neurosurgery, Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany

¹⁴⁴VTT Technical Research Centre, Tampere, Finland

¹⁴⁵Section of Neurosurgery, Department of Surgery, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, MB, Canada

### Author contributions

HFL and IEC planned the study, IEC, JAH, and NVL wrote the article, and IEC analyzed the data. JAH and AIRM provided insight into clinic processes. AIRM and HFL provided valuable input in the writing process and expert knowledge. All authors revised and approved the final version of the manuscript.

### Source of support

The authors' work on this study is partly funded by the European Union seventh Framework Program (grant 602150) for Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI). Additional support for CENTER-TBI was obtained from the Hannelore Kohl Stiftung (Germany), OneMind (USA), Integra LifeSciences Corporation (USA), and NeuroTrauma Sciences (USA).

### Availability of data and material

The datasets generated and/or analysed during the current study are not publicly available because participants gave no consent for data sharing. The datasets generated and/or analysed during the current study are not publicly available because participants gave no consent for data sharing.

### Conflicts of interest

All authors are (partly) funded by the CENTER-TBI study, which is in essence a comparative effectiveness research study. Findings of this study concern

the use of CENTER-TBI in comparative effectiveness research, which could be noted as competing interests.

We confirm that the manuscript complies with all instructions to authors and that authorship requirements have been met and the final manuscript was approved by all authors. Further we confirm that this manuscript has not been published elsewhere and is not under consideration by another journal

### Ethical approval/informed consent

The CENTER-TBI study (EC grant 602150) has been conducted in accordance with all relevant laws of the EU if directly applicable or of direct effect and all relevant laws of the country where the recruiting sites were located, including but not limited to, the relevant privacy and data protection laws and regulations (the "Privacy Law"), the relevant laws and regulations on the use of human materials, and all relevant guidance relating to clinical studies from time to time in force including, but not limited to, the ICH Harmonised Tripartite Guideline for Good Clinical Practice (CPMP/ICH/135/95) ("ICH GCP") and the World Medical Association Declaration of Helsinki entitled "Ethical Principles for Medical Research Involving Human Subjects." Informed Consent by the patients and/or the legal representative/next of kin was obtained, accordingly to the local legislations, for all patients recruited in the Core Dataset of CENTER-TBI and documented in the e-CRF. Ethical approval was obtained for each recruiting sites. The list of sites, Ethical Committees, approval numbers and approval dates can be found here: https://www.center-tbi.eu/project/ethical-approval. The Center for Medical Decision Making, Department of Public Health, Erasmus MC as well as the Department of Neurosurgery, Antwerp University Hospital and University of Antwerp cooperated in the development and realization of the study, and therefore participating researchers had access to the data.

### Open Access

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

### Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Received: 26 February 2021 Accepted: 20 October 2021

Published: 6 December 2021

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