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001-es BibID:BIBFORM107337
035-os BibID:(cikkazonosító)228 (scopus)85135370588 (wos)000831208500002
Első szerző:Åkerlund, Cecilia
Cím:Clustering identifies endotypes of traumatic brain injury in an intensive care cohort : a CENTER-TBI study / Ảkerlund Cecilia A. I., Holst Anders, Stocchetti Nino, Steyerberg Ewout W., Menon David K., Ercole Ari, Nelson David W., CENTER-TBI Participants and Investigators
Dátum:2022
ISSN:1364-8535
Megjegyzések:Abstract Background: While the Glasgow coma scale (GCS) is one of the strongest outcome predictors, the current classifcation 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. Methods: We 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. Results: Six stable endotypes were identifed with distinct GCS and composite systemic metabolic stress profles, 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 classifcation) and deranged metabolic profle, had a worse outcome than a cluster with ♭severe' GCS and a normal metabolic profle. Addition of cluster labels signifcantly 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 (both p<0.001). Conclusions: Six stable and clinically distinct TBI endotypes were identifed by probabilistic unsupervised clustering. In addition to presenting neurology, a profle of biochemical derangement was found to be an important distinguishing feature that was both biologically plausible and associated with outcome. Our work motivates refning current TBI classifcations with factors describing metabolic stress. Such data-driven clusters suggest TBI endotypes that merit investigation to identify bespoke treatment strategies to improve care. Trial registration The core study was registered with ClinicalTrials.gov, number NCT02210221, registered on August 06, 2014, with Resource Identifcation Portal (RRID: SCR_015582)
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Traumatic brain injury
Endotypes
Intensive care unit
Critical care
Unsupervised clustering
Machine learning
Megjelenés:Critical Care. - 26 : 1 (2022), p. 1-15. -
További szerzők:Holst, Anders Stocchetti, Nino Steyerberg, Ewout W. Menon, David Krishna Ercole, Ari Nelson, David W. Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI Participants and Investigators
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2.

001-es BibID:BIBFORM070421
Első szerző:Cnossen, Maryse C.
Cím:Variation in monitoring and treatment policies for intracranial hypertension in traumatic brain injury : a survey in 66 neurotrauma centers participating in the CENTER-TBI study / Maryse C. Cnossen, Jilske A. Huijben, Mathieu van der Jagt, Victor Volovici, Thomas van Essen, Suzanne Polinder, David Nelson, Ari Ercole, Nino Stocchetti, Giuseppe Citerio, Wilco C. Peul, Andrew I. R. Maas, David Menon, Ewout W. Steyerberg, Hester F. Lingsma, CENTER-TBI Investigators and Participants
Dátum:2017
ISSN:1364-8535 1466-609X
Megjegyzések:Background: No definitive evidence exists on how intracranial hypertension should be treated in patients withtraumatic brain injury (TBI). It is therefore likely that centers and practitioners individually balance potential benefitsand risks of different intracranial pressure (ICP) management strategies, resulting in practice variation. The aim ofthis study was to examine variation in monitoring and treatment policies for intracranial hypertension in patientswith TBI.Methods: A 29-item survey on ICP monitoring and treatment was developed on the basis of literature and expertopinion, and it was pilot-tested in 16 centers. The questionnaire was sent to 68 neurotrauma centers participatingin the Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study.Results: The survey was completed by 66 centers (97% response rate). Centers were mainly academic hospitals(n = 60, 91%) and designated level I trauma centers (n = 44, 67%). The Brain Trauma Foundation guidelines wereused in 49 (74%) centers. Approximately 90% of the participants (n = 58) indicated placing an ICP monitor inpatients with severe TBI and computed tomographic abnormalities. There was no consensus on other indicationsor on peri-insertion precautions. We found wide variation in the use of first- and second-tier treatments for elevatedICP. Approximately half of the centers were classified as using a relatively aggressive approach to ICP monitoring andtreatment (n = 32, 48%), whereas the others were considered more conservative (n = 34, 52%).Conclusions: Substantial variation was found regarding monitoring and treatment policies in patients with TBI andintracranial hypertension. The results of this survey indicate a lack of consensus between European neurotraumacenters and provide an opportunity and necessity for comparative effectiveness research.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
Traumatic brain injury
Intracranial hypertension
ICP
ICU
Comparative effectiveness research
Survey
Megjelenés:Critical Care. - 21/2017 (2017), p. 233-245. -
További szerzők:Huijben, Jilske A. van der Jagt, Mathieu Volovici, Victor van Essen, Thomas Polinder, Suzanne Nelson, David Ercole, Ari Stocchetti, Nino Citerio, Giuseppe Peul, Wilco C. Maas, Andrew I. R. Menon, David Krishna Steyerberg, Ewout W. Lingsma, Hester Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI Participants and Investigators
Pályázati támogatás:CENTER-TBI
Egyéb
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3.

001-es BibID:BIBFORM104823
035-os BibID:(WOS)000524528800009 (Scopus)85083076089
Első szerző:Gravesteijn, Benjamin Yaël
Cím:Toward a New Multi-Dimensional Classification of Traumatic Brain Injury : a Collaborative European NeuroTrauma Effectiveness Research for Traumatic Brain Injury Study / Benjamin Gravesteijn, Charlie Sewalt, Ari Ercole, Cecilia Akerlund, David Nelson, Andrew Maas, David Menon, Hester F. Lingsma, Ewout W. Steyerberg, CENTER-TBI collaboration
Dátum:2020
ISSN:0897-7151
Megjegyzések:Traumatic brain injury (TBI) is currently classified as mild, moderate, or severe TBI by trichotomizing the Glasgow Coma Scale (GCS). We aimed to explore directions for a more refined multidimensional classification system. For that purpose, we performed a hypothesis-free cluster analysis in the Collaborative European NeuroTrauma Effectiveness Research for TBI (CENTER-TBI) database: a European all-severity TBI cohort (n?=?4509). The first building block consisted of key imaging characteristics, summarized using principal component analysis from 12 imaging characteristics. The other building blocks were demographics, clinical severity, secondary insults, and cause of injury. With these building blocks, the patients were clustered into four groups. We applied bootstrap resampling with replacement to study the stability of cluster allocation. The characteristics that predominantly defined the clusters were injury cause, major extracranial injury, and GCS. The clusters consisted of 1451, 1534, 1006, and 518 patients, respectively. The clustering method was quite stable: the proportion of patients staying in one cluster after resampling and reclustering was 97.4% (95% confidence interval [CI]: 85.6?99.9%). These clusters characterized groups of patients with different functional outcomes: from mild to severe, 12%, 19%, 36%, and 58% of patients had unfavorable 6 month outcome. Compared with the mild and the upper intermediate cluster, the lower intermediate and the severe cluster received more key interventions. To conclude, four types of TBI patients may be defined by injury mechanism, presence of major extracranial injury and GCS. Describing patients according to these three characteristics could potentially capture differences in etiology and care pathways better than with GCS only.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Journal Of Neurotrauma. - 37 : 7 (2020), p. 1002-1010. -
További szerzők:Sewalt, Charlie Aletta Ercole, Ari Åkerlund, Cecilia Nelson, David Maas, Andrew I. R. Menon, David Krishna Lingsma, Hester Steyerberg, Ewout W. Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI collaborators
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4.

001-es BibID:BIBFORM104832
Első szerző:Gravesteijn, Benjamin Yaël
Cím:Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury / Benjamin Y. Gravesteijn, Daan Nieboer, Ari Ercole, Hester F. Lingsma, David Nelson, Ben van Calster, Ewout W. Steyerberg, CENTER-TBI collaborators
Dátum:2020
ISSN:0895-4356
Megjegyzések:Objective We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Machine learning
Prognosis
Traumatic brain injury
Prediction
Data science
Cohort study
Megjelenés:Journal Of Clinical Epidemiology. - 122 (2020), p. 95-107. -
További szerzők:Nieboer, Daan Ercole, Ari Lingsma, Hester Nelson, David Calster, Ben van Steyerberg, Ewout W. Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI collaborators
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5.

001-es BibID:BIBFORM104936
035-os BibID:(Scopus)85045401878 (WOS)000429979700001 (cikkazonosító)90
Első szerző:Huijben, Jilske A.
Cím:Variation in general supportive and preventive intensive care management of traumatic brain injury : a survey in 66 neurotrauma centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study / Jilske A. Huijben, Victor Volovici, Maryse C. Cnossen, Iain K. Haitsma, Nino Stocchetti, Andrew I. R. Maas, David K. Menon, Ari Ercole, Giuseppe Citerio, David Nelson, Suzanne Polinder, Ewout W. Steyerberg, Hester F. Lingsma, Mathieu van der Jagt, CENTER-TBI Investigators and Participants
Dátum:2018
ISSN:1364-8535
Megjegyzések:Abstract Background: General supportive and preventive measures in the intensive care management of traumatic brain injury (TBI) aim to prevent or limit secondary brain injury and optimize recovery. The aim of this survey was to assess and quantify variation in perceptions on intensive care unit (ICU) management of patients with TBI in European neurotrauma centers. Methods: We performed a survey as part of the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. We analyzed 23 questions focused on: 1) circulatory and respiratory management; 2) fever control; 3) use of corticosteroids; 4) nutrition and glucose management; and 5) seizure prophylaxis and treatment. Results: The survey was completed predominantly by intensivists (n = 33, 50%) and neurosurgeons (n = 23, 35%) from 66 centers (97% response rate). The most common cerebral perfusion pressure (CPP) target was > 60 mmHg (n = 39, 60%) and/or an individualized target (n = 25, 38%). To support CPP, crystalloid fluid loading (n = 60, 91%) was generally preferred over albumin (n = 15, 23%), and vasopressors (n = 63, 96%) over inotropes (n = 29, 44%). The most commonly reported target of partial pressure of carbon dioxide in arterial blood (PaCO2) was 36?40 mmHg (4.8?5.3 kPa) in case of controlled intracranial pressure (ICP) < 20 mmHg (n = 45, 69%) and PaCO2 target of 30-35 mmHg (4?4.7 kPa) in case of raised ICP (n = 40, 62%). Almost all respondents indicated to generally treat fever (n = 65, 98%) with paracetamol (n = 61, 92%) and/or external cooling (n = 49, 74%). Conventional glucose management (n = 43, 66%) was preferred over tight glycemic control (n = 18, 28%). More than half of the respondents indicated to aim for full caloric replacement within 7 days (n = 43, 66%) using enteral nutrition (n = 60, 92%). Indications for and duration of seizure prophylaxis varied, and levetiracetam wasmostly reported as the agent of choice for both seizure prophylaxis (n = 32, 49%) and treatment (n = 40, 61%). Conclusions: Practice preferences vary substantially regarding general supportive and preventive measures in TBI patients at ICUs of European neurotrauma centers. These results provide an opportunity for future comparative effectiveness research, since a more evidence-based uniformity in good practices in general ICU management could have a major impact on TBI outcome.
Tárgyszavak:Orvostudományok Elméleti orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Megjelenés:Critical Care. - 22 : 1 (2018), p. 1-9. -
További szerzők:Volovici, Victor Cnossen, Maryse C. Haitsma, Iain Stocchetti, Nino Maas, Andrew I. R. Menon, David Krishna Ercole, Ari Citerio, Giuseppe Nelson, David Polinder, Suzanne Steyerberg, Ewout W. Lingsma, Hester Jagt, Mathieu van der Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI Participants and Investigators
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6.

001-es BibID:BIBFORM107489
035-os BibID:(Scopus)85071987996 (WOS)000485784000017
Első szerző:Steyerberg, Ewout W.
Cím:Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI : a European prospective, multicentre, longitudinal, cohort study / Ewout W. Steyerberg, Eveline Wiegers, Charlie Sewalt, Andras Buki, Giuseppe Citerio, Véronique De Keyser, Ari Ercole, Kevin Kunzmann, Linda Lanyon, Fiona Lecky, Hester Lingsma, Geoffrey Manley, David Nelson, Wilco Peul, Nino Stocchetti, Nicole von Steinbüchel, Thijs Vande Vyvere, Jan Verheyden, Lindsay Wilson, Andrew I. R. Maas, David K. Menon, CENTER-TBI Participants and Investigators
Dátum:2019
ISSN:1474-4422 1474-4465
Megjegyzések:Background The burden of traumatic brain injury (TBI) poses a large public health and societal problem, but the characteristics of patients and their care pathways in Europe are poorly understood. We aimed to characterise patient case-mix, care pathways, and outcomes of TBI. Methods CENTER-TBI is a Europe-based, observational cohort study, consisting of a core study and a registry. Inclusion criteria for the core study were a clinical diagnosis of TBI, presentation fewer than 24 h after injury, and an indication for CT. Patients were differentiated by care pathway and assigned to the emergency room (ER) stratum (patients who were discharged from an emergency room), admission stratum (patients who were admitted to a hospital ward), or intensive care unit (ICU) stratum (patients who were admitted to the ICU). Neuroimages and biospecimens were stored in repositories and outcome was assessed at 6 months after injury. We used the IMPACT core model for estimating the expected mortality and proportion with unfavourable Glasgow Outcome Scale Extended (GOSE) outcomes in patients with moderate or severe TBI (Glasgow Coma Scale [GCS] score ?12). The core study was registered with ClinicalTrials.gov, number NCT02210221, and with Resource Identification Portal (RRID: SCR_015582). Findings Data from 4509 patients from 18 countries, collected between Dec 9, 2014, and Dec 17, 2017, were analysed in the core study and from 22 782 patients in the registry. In the core study, 848 (19%) patients were in the ER stratum, 1523 (34%) in the admission stratum, and 2138 (47%) in the ICU stratum. In the ICU stratum, 720(36%) patients had mild TBI (GCS score 13?15). Compared with the core cohort, the registry had a higher proportion of patients in the ER (9839 [43%]) and admission (8571 [38%]) strata, with more than 95% of patients classified as having mild TBI. Patients in the core study were older than those in previous studies (median age 50 years [IQR 30?66], 1254 [28%] aged >65 years), 462 (11%) had serious comorbidities, 772 (18%) were taking anticoagulant or antiplatelet medication, and alcohol was contributory in 1054 (25%) TBIs. MRI and blood biomarker measurement enhanced characterisation of injury severity and type. Substantial inter-country differences existed in care pathways and practice. Incomplete recovery at 6 months (GOSE <8) was found in 207 (30%) patients in the ER stratum, 665 (53%) in the admission stratum, and 1547 (84%) in the ICU stratum. Among patients with moderate-to-severe TBI in the ICU stratum, 623 (55%) patients had unfavourable outcome at 6 months (GOSE <5), similar to the proportion predicted by the IMPACT prognostic model (observed to expected ratio 1?06 [95% CI 0?97?1?14]), but mortality was lower than expected (0?70 [0?62?0?76])
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
traumatic brain injury
Megjelenés:Lancet Neurology. - 18 : 10 (2019), p. 923-934. -
További szerzők:Wiegers, Eveline Janine Anna Sewalt, Charlie Aletta Buki András Citerio, Giuseppe Keyser, Véronique de Ercole, Ari Kunzmann, Kevin Lanyon, Linda Lecky, Fiona Lingsma, Hester Manley, Geoffrey T. Nelson, David Peul, Wilco C. Stocchetti, Nino von Steinbuechel, Nicole Vande Vyvere, Thijs Verheyden, Jan Wilson, Lindsay Maas, Andrew I. R. Menon, David Krishna Sándor János (1966-) (orvos-epidemiológus) CENTER-TBI Participants and Investigators
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