Publications by authors named "Ari Ercole"

104 Publications

DeepClean: Self-Supervised Artefact Rejection for Intensive Care Waveform Data Using Deep Generative Learning.

Acta Neurochir Suppl 2021 ;131:235-241

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

Waveform physiological data are important in the treatment of critically ill patients in the intensive care unit. Such recordings are susceptible to artefacts, which must be removed before the data can be reused for alerting or reprocessed for other clinical or research purposes. Accurate removal of artefacts reduces bias and uncertainty in clinical assessment, as well as the false positive rate of ICU alarms, and is therefore a key component in providing optimal clinical care. In this work, we present DeepClean, a prototype self-supervised artefact detection system using a convolutional variational autoencoder deep neural network that avoids costly and painstaking manual annotation, requiring only easily obtained 'good' data for training. For a test case with invasive arterial blood pressure, we demonstrate that our algorithm can detect the presence of an artefact within a 10s sample of data with sensitivity and specificity around 90%. Furthermore, DeepClean was able to identify regions of artefacts within such samples with high accuracy, and we show that it significantly outperforms a baseline principal component analysis approach in both signal reconstruction and artefact detection. DeepClean learns a generative model and therefore may also be used for imputation of missing data.
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http://dx.doi.org/10.1007/978-3-030-59436-7_45DOI Listing
January 2021

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

Acta Neurochir Suppl 2021 ;131:181-185

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

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: To validate the CPPopt revised algorithm in a large single-centre retrospective cohort of TBI patients.

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: 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: This study validates, on a large cohort of patients, the new algorithm proposed for prospective use of CPPopt as a CPP target at bedside.
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http://dx.doi.org/10.1007/978-3-030-59436-7_36DOI Listing
January 2021

Patient's Clinical Presentation and CPPopt Availability: Any Association?

Acta Neurochir Suppl 2021 ;131:167-172

Department of Intensive Care, University Maastricht, Maastricht University Medical Center, Maastricht, The Netherlands.

Background: The 'optimal' CPP (CPPopt) concept is based on the vascular pressure reactivity index (PRx). The feasibility and effectiveness of CPPopt guided therapy in severe traumatic brain injury (TBI) patients is currently being investigated prospectively in the COGiTATE trial. At the moment there is no clear evidence that certain admission and treatment characteristics are associated with CPPopt availability (yield).

Objective: To test the relation between patients' admission and treatment characteristics and the average CPPopt yield.

Methods: Retrospective analysis of 230 patients from the CENTER-TBI high-resolution database with intracranial pressure (ICP) measured using an intraparenchymal probe. CPPopt was calculated using the algorithm set for the COGiTATE study. CPPopt yield was defined as the percentage of CPP monitored time (%) when CPPopt is available. The variables in the statistical model included age, admission Glasgow Coma Scale (GCS), gender, pupil response, hypoxia and hypotension at the scene, Marshall computed tomography (CT) score, decompressive craniectomy, injury severity score score and 24-h therapeutic intensity level (TIL) score.

Results: The median CPPopt yield was 80.7% (interquartile range 70.9-87.4%). None of the selected variables showed a significant statistical correlation with the CPPopt yield.

Conclusion: In this retrospective multicenter study, none of the selected admission and treatment variables were related to the CPPopt yield.
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http://dx.doi.org/10.1007/978-3-030-59436-7_34DOI Listing
January 2021

An Update on the COGiTATE Phase II Study: Feasibility and Safety of Targeting an Optimal Cerebral Perfusion Pressure as a Patient-Tailored Therapy in Severe Traumatic Brain Injury.

Acta Neurochir Suppl 2021 ;131:143-147

Department of Intensive Care Medicine, University of Maastricht, Maastricht University Medical Centre, Maastricht, The Netherlands.

Introduction: Monitoring of cerebral autoregulation (CA) in patients with a traumatic brain injury (TBI) can provide an individual 'optimal' cerebral perfusion pressure (CPP) target (CPPopt) at which CA is best preserved. This potentially offers an individualized precision medicine approach. Retrospective data suggest that deviation of CPP from CPPopt is associated with poor outcomes. We are prospectively assessing the feasibility and safety of this approach in the COGiTATE [CPPopt Guided Therapy: Assessment of Target Effectiveness] study. Its primary objective is to demonstrate the feasibility of individualizing CPP at CPPopt in TBI patients. The secondary objectives are to investigate the safety and physiological effects of this strategy.

Methods: The COGiTATE study has included patients in four European hospitals in Cambridge, Leuven, Nijmegen, and Maastricht (coordinating centre). Patients with severe TBI requiring intracranial pressure (ICP)-directed therapy are allocated into one of two groups. In the intervention group, CPPopt is calculated using a published (modified) algorithm. In the control group, the CPP target recommended in the Brain Trauma Foundation guidelines (CPP 60-70 mmHg) is used.

Results: Patient recruitment started in February 2018 and will continue until 60 patients have been studied. Fifty-one patients (85% of the intended total) have been recruited in October 2019. The first results are expected early 2021.

Conclusion: This prospective evaluation of the feasibility, safety and physiological implications of autoregulation-guided CPP management is providing evidence that will be useful in the design of a future phase III study in severe TBI patients.
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http://dx.doi.org/10.1007/978-3-030-59436-7_29DOI Listing
January 2021

Analysis of Cardio-Cerebral Crosstalk Events in an Adult Cohort from the CENTER-TBI Study.

Acta Neurochir Suppl 2021 ;131:39-42

Computer Laboratory, University of Cambridge, Cambridge, UK.

Objective: In a previous study, we observed the presence of simultaneous increases in intracranial pressure (ICP) and the heart rate (HR), which we denominated cardio-cerebral crosstalk (CC), and we related the number of such events to patient outcomes in a paediatric cohort. In this chapter, we present an extension of this work to an adult cohort from the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) study.

Methods: We implemented a sliding window algorithm to detect CC events. We considered subwindows of 10-min observations. If simultaneous increases of at least 20% in ICP and HR occurred with respect to the minimum ICP and HR values in the time windows, a CC event was detected. Correlation between the number of CC events and mortality was then obtained.

Results: The cohort consisted of 226 adults (aged 16-85 years). The number of CC events that were detected varied (mean 50, standard deviation 58). A point biserial correlation coefficient of -0.13 between mortality and CC was found. Although the correlation was weaker than that seen in the paediatric cohort (-0.30), the negative direction was replicated.

Conclusion: In this work, we first extracted CC events from ICP and HR observations of adult patients with traumatic brain injury and related the number of CC events to patient outcomes. Consistency with the previous results in the paediatric cohort was observed. The more crosstalk events occurred, the better the patient outcome was.
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http://dx.doi.org/10.1007/978-3-030-59436-7_9DOI Listing
January 2021

Sharing ICU Patient Data Responsibly Under the Society of Critical Care Medicine/European Society of Intensive Care Medicine Joint Data Science Collaboration: The Amsterdam University Medical Centers Database (AmsterdamUMCdb) Example.

Crit Care Med 2021 Feb 24. Epub 2021 Feb 24.

Department of Intensive Care Medicine, Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Vrije Universiteit, Universiteit van Amsterdam, Amsterdam, The Netherlands. Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands. Department of Intensive Care Medicine, Erasmus MC, Rotterdam, The Netherlands. Division of Trauma, Surgical Critical Care and Emergency Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA. Department of Emergency Medicine, Durham VA Medical Center, Durham, NC. Executive Committee, Society of Critical Care Medicine, Mount Prospect, IL. Department of Intensive Care Medicine, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands. Executive Committee, European Society of Intensive Care Medicine, Brussels, Belgium. Department of Anaesthesia and Intensive Care, Humanitas Research Hospital, Humanitas University, Milan, Italy. Department of Medicine, University of Wisconsin, Madison, WI. Department of Critical Care Medicine, CRISMA Laboratory, University of Pittsburgh, Pittsburgh, PA. University of Cambridge, Cambridge, United Kingdom. Alan Turing Institute, London, United Kingdom. Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom. Data Science Section, European Society of Intensive Care Medicine, Brussels, Belgium.

Objectives: Critical care medicine is a natural environment for machine learning approaches to improve outcomes for critically ill patients as admissions to ICUs generate vast amounts of data. However, technical, legal, ethical, and privacy concerns have so far limited the critical care medicine community from making these data readily available. The Society of Critical Care Medicine and the European Society of Intensive Care Medicine have identified ICU patient data sharing as one of the priorities under their Joint Data Science Collaboration. To encourage ICUs worldwide to share their patient data responsibly, we now describe the development and release of Amsterdam University Medical Centers Database (AmsterdamUMCdb), the first freely available critical care database in full compliance with privacy laws from both the United States and Europe, as an example of the feasibility of sharing complex critical care data.

Setting: University hospital ICU.

Subjects: Data from ICU patients admitted between 2003 and 2016.

Interventions: We used a risk-based deidentification strategy to maintain data utility while preserving privacy. In addition, we implemented contractual and governance processes, and a communication strategy. Patient organizations, supporting hospitals, and experts on ethics and privacy audited these processes and the database.

Measurements And Main Results: AmsterdamUMCdb contains approximately 1 billion clinical data points from 23,106 admissions of 20,109 patients. The privacy audit concluded that reidentification is not reasonably likely, and AmsterdamUMCdb can therefore be considered as anonymous information, both in the context of the U.S. Health Insurance Portability and Accountability Act and the European General Data Protection Regulation. The ethics audit concluded that responsible data sharing imposes minimal burden, whereas the potential benefit is tremendous.

Conclusions: Technical, legal, ethical, and privacy challenges related to responsible data sharing can be addressed using a multidisciplinary approach. A risk-based deidentification strategy, that complies with both U.S. and European privacy regulations, should be the preferred approach to releasing ICU patient data. This supports the shared Society of Critical Care Medicine and European Society of Intensive Care Medicine vision to improve critical care outcomes through scientific inquiry of vast and combined ICU datasets.
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http://dx.doi.org/10.1097/CCM.0000000000004916DOI Listing
February 2021

Use and impact of high intensity treatments in patients with traumatic brain injury across Europe: a CENTER-TBI analysis.

Crit Care 2021 02 23;25(1):78. Epub 2021 Feb 23.

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

Purpose: To study variation in, and clinical impact of high Therapy Intensity Level (TIL) treatments for elevated intracranial pressure (ICP) in patients with traumatic brain injury (TBI) across European Intensive Care Units (ICUs).

Methods: We studied high TIL treatments (metabolic suppression, hypothermia (< 35 °C), intensive hyperventilation (PaCO < 4 kPa), and secondary decompressive craniectomy) in patients receiving ICP monitoring in the ICU stratum of the CENTER-TBI study. A random effect logistic regression model was used to determine between-centre variation in their use. A propensity score-matched model was used to study the impact on outcome (6-months Glasgow Outcome Score-extended (GOSE)), whilst adjusting for case-mix severity, signs of brain herniation on imaging, and ICP.

Results: 313 of 758 patients from 52 European centres (41%) received at least one high TIL treatment with significant variation between centres (median odds ratio = 2.26). Patients often transiently received high TIL therapies without escalation from lower tier treatments. 38% of patients with high TIL treatment had favourable outcomes (GOSE ≥ 5). The use of high TIL treatment was not significantly associated with worse outcome (285 matched pairs, OR 1.4, 95% CI [1.0-2.0]). However, a sensitivity analysis excluding high TIL treatments at day 1 or use of metabolic suppression at any day did reveal a statistically significant association with worse outcome.

Conclusion: Substantial between-centre variation in use of high TIL treatments for TBI was found and treatment escalation to higher TIL treatments were often not preceded by more conventional lower TIL treatments. The significant association between high TIL treatments after day 1 and worse outcomes may reflect aggressive use or unmeasured confounders or inappropriate escalation strategies.

Take Home Message: Substantial variation was found in the use of highly intensive ICP-lowering treatments across European ICUs and a stepwise escalation strategy from lower to higher intensity level therapy is often lacking. Further research is necessary to study the impact of high therapy intensity treatments.

Trial Registration: The core study was registered with ClinicalTrials.gov, number NCT02210221, registered 08/06/2014, https://clinicaltrials.gov/ct2/show/NCT02210221?id=NCT02210221&draw=1&rank=1 and with Resource Identification Portal (RRID: SCR_015582).
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http://dx.doi.org/10.1186/s13054-020-03370-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7901510PMC
February 2021

Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or curation.

Sci Rep 2020 12 17;10(1):22129. Epub 2020 Dec 17.

Division of Anaesthesia, Addenbrooke's Hospital, University of Cambridge, Hills Road, Cambridge, CB2 0QQ, UK.

Extensive monitoring in intensive care units (ICUs) generates large quantities of data which contain numerous trends that are difficult for clinicians to systematically evaluate. Current approaches to such heterogeneity in electronic health records (EHRs) discard pertinent information. We present a deep learning pipeline that uses all uncurated chart, lab, and output events for prediction of in-hospital mortality without variable selection. Over 21,000 ICU patients and tens of thousands of variables derived from the MIMIC-III database were used to train and validate our model. Recordings in the first few hours of a patient's stay were found to be strongly predictive of mortality, outperforming models using SAPS II and OASIS scores, AUROC 0.72 and 0.76 at 24 h respectively, within just 12 h of ICU admission. Our model achieves a very strong predictive performance of AUROC 0.85 (95% CI 0.83-0.86) after 48 h. Predictive performance increases over the first 48 h, but suffers from diminishing returns, providing rationale for time-limited trials of critical care and suggesting that the timing of decision making can be optimised and individualised.
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http://dx.doi.org/10.1038/s41598-020-79142-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7747558PMC
December 2020

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19.

Mach Learn 2020 Dec 9:1-14. Epub 2020 Dec 9.

University of Cambridge, Cambridge, UK.

The COVID-19 global pandemic is a threat not only to the health of millions of individuals, but also to the stability of infrastructure and economies around the world. The disease will inevitably place an overwhelming burden on healthcare systems that cannot be effectively dealt with by existing facilities or responses based on conventional approaches. We believe that a rigorous clinical and societal response can only be mounted by using intelligence derived from a variety of data sources to better utilize scarce healthcare resources, provide personalized patient management plans, inform policy, and expedite clinical trials. In this paper, we introduce five of the most important challenges in responding to COVID-19 and show how each of them can be addressed by recent developments in machine learning (ML) and artificial intelligence (AI). We argue that the integration of these techniques into local, national, and international healthcare systems will save lives, and propose specific methods by which implementation can happen swiftly and efficiently. We offer to extend these resources and knowledge to assist policymakers seeking to implement these techniques.
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http://dx.doi.org/10.1007/s10994-020-05928-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725494PMC
December 2020

Impact of duration and magnitude of raised intracranial pressure on outcome after severe traumatic brain injury: A CENTER-TBI high-resolution group study.

PLoS One 2020 14;15(12):e0243427. Epub 2020 Dec 14.

Department of Physiology and Pharmacology, Section of Perioperative Medicine and Intensive Care, Karolinska Institutet, Stockholm, Sweden.

Magnitude of intracranial pressure (ICP) elevations and their duration have been associated with worse outcomes in patients with traumatic brain injuries (TBI), however published thresholds for injury vary and uncertainty about these levels has received relatively little attention. In this study, we have analyzed high-resolution ICP monitoring data in 227 adult patients in the CENTER-TBI dataset. Our aim was to identify thresholds of ICP intensity and duration associated with worse outcome, and to evaluate the uncertainty in any such thresholds. We present ICP intensity and duration plots to visualize the relationship between ICP events and outcome. We also introduced a novel bootstrap technique to evaluate uncertainty of the equipoise line. We found that an intensity threshold of 18 ± 4 mmHg (2 standard deviations) was associated with worse outcomes in this cohort. In contrast, the uncertainty in what duration is associated with harm was larger, and safe durations were found to be population dependent. The pressure and time dose (PTD) was also calculated as area under the curve above thresholds of ICP. A relationship between PTD and mortality could be established, as well as for unfavourable outcome. This relationship remained valid for mortality but not unfavourable outcome after adjusting for IMPACT core variables and maximum therapy intensity level. Importantly, during periods of impaired autoregulation (defined as pressure reactivity index (PRx)>0.3) ICP events were associated with worse outcomes for nearly all durations and ICP levels in this cohort and there was a stronger relationship between outcome and PTD. Whilst caution should be exercised in ascribing causation in observational analyses, these results suggest intracranial hypertension is poorly tolerated in the presence of impaired autoregulation. ICP level guidelines may need to be revised in the future taking into account cerebrovascular autoregulation status considered jointly with ICP levels.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0243427PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7735618PMC
January 2021

Guidelines for Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD).

J Clin Transl Sci 2020 Mar 13;4(4):354-359. Epub 2020 Mar 13.

Division of Psychology, University of Stirling, Stirling, UK.

Background: High-quality data are critical to the entire scientific enterprise, yet the complexity and effort involved in data curation are vastly under-appreciated. This is especially true for large observational, clinical studies because of the amount of multimodal data that is captured and the opportunity for addressing numerous research questions through analysis, either alone or in combination with other data sets. However, a lack of details concerning data curation methods can result in unresolved questions about the robustness of the data, its utility for addressing specific research questions or hypotheses and how to interpret the results. We aimed to develop a framework for the design, documentation and reporting of data curation methods in order to advance the scientific rigour, reproducibility and analysis of the data.

Methods: Forty-six experts participated in a modified Delphi process to reach consensus on indicators of data curation that could be used in the design and reporting of studies.

Results: We identified 46 indicators that are applicable to the design, training/testing, run time and post-collection phases of studies.

Conclusion: The Data Acquisition, Quality and Curation for Observational Research Designs (DAQCORD) Guidelines are the first comprehensive set of data quality indicators for large observational studies. They were developed around the needs of neuroscience projects, but we believe they are relevant and generalisable, in whole or in part, to other fields of health research, and also to smaller observational studies and preclinical research. The DAQCORD Guidelines provide a framework for achieving high-quality data; a cornerstone of health research.
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http://dx.doi.org/10.1017/cts.2020.24DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7681114PMC
March 2020

Normalising renal tissue oxygen tension with higher inspired oxygen concentration may be falsely reassuring. Comment on Br J Anaesth 2020;125:192-200.

Authors:
Ari Ercole

Br J Anaesth 2021 01 10;126(1):e32. Epub 2020 Nov 10.

Division of Anaesthesia, University of Cambridge and Neurosciences/Trauma Critical Care Unit, Addenbrooke's Hospital, Cambridge, UK. Electronic address:

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http://dx.doi.org/10.1016/j.bja.2020.10.017DOI Listing
January 2021

Mechanical ventilation in patients with acute brain injury: recommendations of the European Society of Intensive Care Medicine consensus.

Intensive Care Med 2020 Dec 11;46(12):2397-2410. Epub 2020 Nov 11.

Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe St, Phipps 455, Baltimore, MD, 21287, USA.

Purpose: To provide clinical practice recommendations and generate a research agenda on mechanical ventilation and respiratory support in patients with acute brain injury (ABI).

Methods: An international consensus panel was convened including 29 clinician-scientists in intensive care medicine with expertise in acute respiratory failure, neurointensive care, or both, and two non-voting methodologists. The panel was divided into seven subgroups, each addressing a predefined clinical practice domain relevant to patients admitted to the intensive care unit (ICU) with ABI, defined as acute traumatic brain or cerebrovascular injury. The panel conducted systematic searches and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) method was used to evaluate evidence and formulate questions. A modified Delphi process was implemented with four rounds of voting in which panellists were asked to respond to questions (rounds 1-3) and then recommendation statements (final round). Strong recommendation, weak recommendation, or no recommendation were defined when > 85%, 75-85%, and < 75% of panellists, respectively, agreed with a statement.

Results: The GRADE rating was low, very low, or absent across domains. The consensus produced 36 statements (19 strong recommendations, 6 weak recommendations, 11 no recommendation) regarding airway management, non-invasive respiratory support, strategies for mechanical ventilation, rescue interventions for respiratory failure, ventilator liberation, and tracheostomy in brain-injured patients. Several knowledge gaps were identified to inform future research efforts.

Conclusions: This consensus provides guidance for the care of patients admitted to the ICU with ABI. Evidence was generally insufficient or lacking, and research is needed to demonstrate the feasibility, safety, and efficacy of different management approaches.
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http://dx.doi.org/10.1007/s00134-020-06283-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7655906PMC
December 2020

Imputation of Ordinal Outcomes: A Comparison of Approaches in Traumatic Brain Injury.

J Neurotrauma 2021 Feb 13;38(4):455-463. Epub 2020 Nov 13.

Division of Psychology, University of Stirling, Stirling, United Kingdom.

Loss to follow-up and missing outcomes data are important issues for longitudinal observational studies and clinical trials in traumatic brain injury. One popular solution to missing 6-month outcomes has been to use the last observation carried forward (LOCF). The purpose of the current study was to compare the performance of model-based single-imputation methods with that of the LOCF approach. We hypothesized that model-based methods would perform better as they potentially make better use of available outcome data. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study ( = 4509) included longitudinal outcome collection at 2 weeks, 3 months, 6 months, and 12 months post-injury; a total of 8185 Glasgow Outcome Scale extended (GOSe) observations were included in the database. We compared single imputation of 6-month outcomes using LOCF, a multiple imputation (MI) panel imputation, a mixed-effect model, a Gaussian process regression, and a multi-state model. Model performance was assessed via cross-validation on the subset of individuals with a valid GOSe value within 180 ± 14 days post-injury ( = 1083). All models were fit on the entire available data after removing the 180 ± 14 days post-injury observations from the respective test fold. The LOCF method showed lower accuracy (i.e., poorer agreement between imputed and observed values) than model-based methods of imputation, and showed a strong negative bias (i.e., it imputed lower than observed outcomes). Accuracy and bias for the model-based approaches were similar to one another, with the multi-state model having the best overall performance. All methods of imputation showed variation across different outcome categories, with better performance for more frequent outcomes. We conclude that model-based methods of single imputation have substantial performance advantages over LOCF, in addition to providing more complete outcome data.
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http://dx.doi.org/10.1089/neu.2019.6858DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7875604PMC
February 2021

Systemic Markers of Injury and Injury Response Are Not Associated with Impaired Cerebrovascular Reactivity in Adult Traumatic Brain Injury: A Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) Study.

J Neurotrauma 2021 Apr 14;38(7):870-878. Epub 2020 Dec 14.

Division of Anesthesia, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom.

The role of extra-cranial injury burden and systemic injury response on cerebrovascular response in traumatic brain injury (TBI) is poorly documented. This study preliminarily assesses the association between admission features of extra-cranial injury burden on cerebrovascular reactivity. Using the Collaborative European Neurotrauma Effectiveness Research in TBI High-Resolution ICU (HR ICU) sub-study cohort, we evaluated those patients with both archived high-frequency digital intra-parenchymal intra-cranial pressure monitoring data of a minimum of 6 h in duration, and the presence of a digital copy of their admission computed tomography (CT) scan. Digital physiologic signals were processed for pressure reactivity index (PRx) and both the percent time above defined PRx thresholds and mean hourly dose above threshold. This was conducted for both the first 72 h and entire duration of recording. Admission extra-cranial injury characteristics and CT injury scores were obtained from the database, with quantitative contusion, edema, intraventricular hemorrhage, and extra-axial lesion volumes were obtained via semi-automated segmentation. Comparison between admission extra-cranial markers of injury and PRx metrics was conducted using Mann-Whitney U testing, and logistic regression techniques, adjusting for known CT injury metrics associated with impaired PRx. A total of 165 patients were included. Evaluating the entire ICU recording period, there was limited association between metrics of extra-cranial injury burden and impaired cerebrovascular reactivity. Using the first 72 h of recording, admission temperature ( = 0.042) and white blood cell % (WBC %;  = 0.013) were statistically associated with impaired cerebrovascular reactivity on Mann-Whitney U and univariate logistic regression. After adjustment for admission age, pupillary status, GCS motor score, pre-hospital hypoxia/hypotension, and intra-cranial CT characteristics associated with impaired reactivity, temperature ( = 0.021) and WBC % ( = 0.013) remained significantly associated with mean PRx values above +0.25 and +0.35, respectively. Markers of extra-cranial injury burden and systemic injury response do not appear to be strongly associated with impaired cerebrovascular reactivity in TBI during both the initial and entire ICU stay.
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http://dx.doi.org/10.1089/neu.2020.7304DOI Listing
April 2021

Variability in Serum Sodium Concentration and Prognostic Significance in Severe Traumatic Brain Injury: A Multicenter Observational Study.

Neurocrit Care 2020 Oct 2. Epub 2020 Oct 2.

Intensive Care Unit, Royal Melbourne Hospital, Level 5, B Block, Parkville, VIC, 3050, Australia.

Background/objective: Dysnatremia is common in severe traumatic brain injury (TBI) patients and may contribute to mortality. However, serum sodium variability has not been studied in TBI patients. We hypothesized that such variability would be independently associated with mortality.

Methods: We collected 6-hourly serum sodium levels for the first 7 days of ICU admission from 240 severe TBI patients in 14 neurotrauma ICUs in Europe and Australia. We evaluated the association between daily serum sodium standard deviation (dNa), an index of variability, and 28-day mortality.

Results: Patients were 46 ± 19 years of age with a median initial GCS of 6 [4-8]. Overall hospital mortality was 28%. Hypernatremia and hyponatremia occurred in 64% and 24% of patients, respectively. Over the first 7 days in ICU, serum sodium standard deviation was 2.8 [2.0-3.9] mmol/L. Maximum daily serum sodium standard deviation (dNa) occurred at a median of 2 [1-4] days after admission. There was a significant progressive decrease in dNa over the first 7 days (coefficient - 0.15 95% CI [- 0.18 to - 0.12], p < 0.001). After adjusting for baseline TBI severity, diabetes insipidus, the use of osmotherapy, the occurrence of hypernatremia, and hyponatremia and center, dNa was significantly independently associated with 28-day mortality (HR 1.27 95% CI (1.01-1.61), p = 0.048).

Conclusions: Our study demonstrates that daily serum sodium variability is an independent predictor of 28-day mortality in severe TBI patients. Further prospective investigations are necessary to confirm the significance of sodium variability in larger cohorts of TBI patients and test whether attenuating such variability confers outcome benefits to such patients.
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http://dx.doi.org/10.1007/s12028-020-01118-8DOI Listing
October 2020

End-tidal and arterial carbon dioxide gradient in serious traumatic brain injury after prehospital emergency anaesthesia: a retrospective observational study.

Emerg Med J 2020 Nov 14;37(11):674-679. Epub 2020 Sep 14.

Department of Research, Audit, Innovation, & Development (RAID), East Anglian Air Ambulance, Norwich, UK.

Objectives: In the UK, 20% of patients with severe traumatic brain injury (TBI) receive prehospital emergency anaesthesia (PHEA). Current guidance recommends an end-tidal carbon dioxide (ETCO) of 4.0-4.5 kPa (30.0-33.8 mm Hg) to achieve a low-normal arterial partial pressure of CO (PaCO), and reduce secondary brain injury. This recommendation assumes a 0.5 kPa (3.8 mm Hg) ETCO-PaCO gradient. However, the gradient in the acute phase of TBI is unknown. The primary aim was to report the ETCO-PaCO gradient of TBI patients at hospital arrival.

Methods: A retrospective cohort study of adult patients with serious TBI, who received a PHEA by a prehospital critical care team in the East of England between 1 April 2015 and 31 December 2017. Linear regression was performed to test for correlation and reported as R-squared (R). A Bland-Altman plot was used to test for paired ETCO and PaCO agreement and reported with 95% CI. ETCO-PaCO gradient data were compared with a two-tailed, unpaired, t-test.

Results: 107 patients were eligible for inclusion. Sixty-seven patients did not receive a PaCO sample within 30 min of hospital arrival and were therefore excluded. Forty patients had complete data and were included in the final analysis; per protocol. The mean ETCO-PaCO gradient was 1.7 (±1.0) kPa (12.8 mm Hg), with moderate correlation (R=0.23, p=0.002). The Bland-Altman bias was 1.7 (95% CI 1.4 to 2.0) kPa with upper and lower limits of agreement of 3.6 (95% CI 3.0 to 4.1) kPa and -0.2 (95% CI -0.8 to 0.3) kPa, respectively. There was no evidence of a larger gradient in more severe TBI (p=0.29). There was no significant gradient correlation in patients with a coexisting serious thoracic injury (R=0.13, p=0.10), and this cohort had a larger ETCO-PaCO gradient, 2.0 (±1.1) kPa (15.1 mm Hg), p=0.01. Patients who underwent prehospital arterial blood sampling had an arrival PaCO of 4.7 (±0.2) kPa (35.1 mm Hg).

Conclusion: There is only moderate correlation of ETCO and PaCO at hospital arrival in patients with serious TBI. The mean ETCO-PaCO gradient was 1.7 (±1.0) kPa (12.8 mm Hg). Lower ETCO targets than previously recommended may be safe and appropriate, and there may be a role for prehospital PaCO measurement.
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http://dx.doi.org/10.1136/emermed-2019-209077DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7588597PMC
November 2020

Descriptive analysis of low versus elevated intracranial pressure on cerebral physiology in adult traumatic brain injury: a CENTER-TBI exploratory study.

Acta Neurochir (Wien) 2020 11 4;162(11):2695-2706. Epub 2020 Sep 4.

Brain Physics Lab, Division of Neurosurgery, Dept of Clinical Neurosciences, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.

Background: To date, the cerebral physiologic consequences of persistently elevated intracranial pressure (ICP) have been based on either low-resolution physiologic data or retrospective high-frequency data from single centers. The goal of this study was to provide a descriptive multi-center analysis of the cerebral physiologic consequences of ICP, comparing those with normal ICP to those with elevated ICP.

Methods: The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) High-Resolution Intensive Care Unit (HR-ICU) sub-study cohort was utilized. The first 3 days of physiologic recording were analyzed, evaluating and comparing those patients with mean ICP < 15 mmHg versus those with mean ICP > 20 mmHg. Various cerebral physiologic parameters were derived and evaluated, including ICP, brain tissue oxygen (PbtO), cerebral perfusion pressure (CPP), pulse amplitude of ICP (AMP), cerebrovascular reactivity, and cerebral compensatory reserve. The percentage time and dose above/below thresholds were also assessed. Basic descriptive statistics were employed in comparing the two cohorts.

Results: 185 patients were included, with 157 displaying a mean ICP below 15 mmHg and 28 having a mean ICP above 20 mmHg. For admission demographics, only admission Marshall and Rotterdam CT scores were statistically different between groups (p = 0.017 and p = 0.030, respectively). The high ICP group displayed statistically worse CPP, PbtO, cerebrovascular reactivity, and compensatory reserve. The high ICP group displayed worse 6-month mortality (p < 0.0001) and poor outcome (p = 0.014), based on the Extended Glasgow Outcome Score.

Conclusions: Low versus high ICP during the first 72 h after moderate/severe TBI is associated with significant disparities in CPP, AMP, cerebrovascular reactivity, cerebral compensatory reserve, and brain tissue oxygenation metrics. Such ICP extremes appear to be strongly related to 6-month patient outcomes, in keeping with previous literature. This work provides multi-center validation for previously described single-center retrospective results.
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http://dx.doi.org/10.1007/s00701-020-04485-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7550280PMC
November 2020

Prehospital Management of Traumatic Brain Injury across Europe: A CENTER-TBI Study.

Prehosp Emerg Care 2020 Oct 1:1-15. Epub 2020 Oct 1.

Received May 5, 2020 from Department of Public Health, Erasmus Medical Center, Rotterdam, the Netherlands (BYG, CAS, HFL, EWS); Department of Pathophysiology and Transplantation, Milan University, Milan, Italy (NS); School of Medicine and Surgery, University Milano - Bicocca, Milan, Italy (GC); Department of Neurosurgery, Antwerp University Hospital and University of Antwerp, Belgium (AIRM); Division of Anaesthesia, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK (AE, DKM); Institute of Medical Psychology and Medical Sociology, Universitätsmedizin Göttingen, Göttingen (NVS); Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, the Netherlands (EWS); Division of Physiology, University of Stirling, Stirling, UK (LW); Center for Urgent and Emergency Care Research, Health Services Research Section, School of Health and Related Research, University of Sheffield, Sheffield, UK (FEL); Emergency Department, Salford Royal Hospital, Salford, UK (FEL). Revision received August 23, 2020; accepted for publication August 24, 2020.

Background: Prehospital care for traumatic brain injury (TBI) is important to prevent secondary brain injury. We aim to compare prehospital care systems within Europe and investigate the association of system characteristics with the stability of patients at hospital arrival.

Methods: We studied TBI patients who were transported to CENTER-TBI centers, a pan-European, prospective TBI cohort study, by emergency medical services between 2014 and 2017. The association of demographic factors, injury severity, situational factors, and interventions associated with on-scene time was assessed using linear regression. We used mixed effects models to investigate the case mix adjusted variation between countries in prehospital times and interventions. The case mix adjusted impact of on-scene time and interventions on hypoxia (oxygen saturation <90%) and hypotension (systolic blood pressure <100mmHg) at hospital arrival was analyzed with logistic regression.

Results: Among 3878 patients, the greatest driver of longer on-scene time was intubation (+8.3 min, 95% CI: 5.6-11.1). Secondary referral was associated with shorter on-scene time (-5.0 min 95% CI: -6.2- -3.8). Between countries, there was a large variation in response (range: 12-25 min), on-scene (range: 16-36 min) and travel time (range: 15-32 min) and in prehospital interventions. These variations were not explained by patient factors such as conscious level or severity of injury (expected OR between countries: 1.8 for intubation, 1.8 for IV fluids, 2.0 for helicopter). On-scene time was not associated with the regional EMS policy (p= 0.58). Hypotension and/or hypoxia were seen in 180 (6%) and 97 (3%) patients in the overall cohort and in 13% and 7% of patients with severe TBI (GCS <8). The largest association with secondary insults at hospital arrival was with major extracranial injury: the OR was 3.6 (95% CI: 2.6-5.0) for hypotension and 4.4 (95% CI: 2.9-6.7) for hypoxia.

Discussion: Hypoxia and hypotension continue to occur in patients who suffer a TBI, and remain relatively common in severe TBI. Substantial variation in prehospital care exists for patients after TBI in Europe, which is only partially explained by patient factors.
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http://dx.doi.org/10.1080/10903127.2020.1817210DOI Listing
October 2020

Association between Physiological Signal Complexity and Outcomes in Moderate and Severe Traumatic Brain Injury: A CENTER-TBI Exploratory Analysis of Multi-Scale Entropy.

J Neurotrauma 2021 Jan 23;38(2):272-282. Epub 2020 Sep 23.

Brain Physics Laboratory, Division of Neurosurgery, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom.

In traumatic brain injury (TBI), preliminary retrospective work on signal entropy suggests an association with global outcome. The goal of this study was to provide multi-center validation of the association between multi-scale entropy (MSE) of cardiovascular and cerebral physiological signals, with six-month outcome. Using the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) high-resolution intensive care unit (ICU) cohort, we selected patients with a minimum of 72 h of physiological recordings and a documented six-month Glasgow Outcome Scale Extended (GOSE) score. The 10-sec summary data for heart rate (HR), mean arterial pressure (MAP), intracranial pressure (ICP), and pulse amplitude of ICP (AMP) were derived across the first 72 h of data. The MSE complexity index (MSE-Ci) was determined for HR, MAP, ICP, and AMP, with the association between MSE and dichotomized six-month outcomes assessed using Mann-Whitney testing and logistic regression analysis. A total of 160 patients had a minimum of 72 h of recording and a documented outcome. Decreased HR MSE-Ci (7.3 [interquartile range (IQR) 5.4 to 10.2] vs. 5.1 [IQR 3.1 to 7.0];  = 0.002), lower ICP MSE-Ci (11.2 [IQR 7.5 to 14.2] vs. 7.3 [IQR 6.1 to 11.0];  = 0.009), and lower AMP MSE-Ci (10.9 [IQR 8.0 to 13.7] vs. 8.7 [IQR 6.6 to 11.0];  = 0.022), were associated with death. Similarly, lower HR MSE-Ci (8.0 [IQR 6.2 to 10.9] vs. 6.2 [IQR 3.9 to 8.7];  = 0.003) and lower ICP MSE-Ci (11.4 [IQR 8.6 to 14.4)] vs. 9.2 [IQR 6.0 to 13.5]), were associated with unfavorable outcome. Logistic regression analysis confirmed that lower HR MSE-Ci and ICP MSE-Ci were associated with death and unfavorable outcome at six months. These findings suggest that a reduction in cardiovascular and cerebrovascular system entropy is associated with worse outcomes. Further work in the field of signal complexity in TBI multi-modal monitoring is required.
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http://dx.doi.org/10.1089/neu.2020.7249DOI Listing
January 2021

Optimal Timing of External Ventricular Drainage after Severe Traumatic Brain Injury: A Systematic Review.

J Clin Med 2020 Jun 25;9(6). Epub 2020 Jun 25.

Division of Neurosurgery, Department of Clinical Neurosciences, Addenbrooke's Hospital and University of Cambridge, Cambridge CB2 0QQ, UK.

External ventricular drainage (EVD) may be used for therapeutic cerebrospinal fluid (CSF) drainage to control intracranial pressure (ICP) after traumatic brain injury (TBI). However, there is currently uncertainty regarding the optimal timing for EVD insertion. This study aims to compare patient outcomes for patients with early and late EVD insertion. Following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines, MEDLINE/EMBASE/Scopus/Web of Science/Cochrane Central Register of Controlled Trials were searched for published literature involving at least 10 severe TBI (sTBI) patients from their inception date to December 2019. Outcomes assessed were mortality, functional outcome, ICP control, length of stay, therapy intensity level, and complications. Twenty-one studies comprising 4542 sTBI patients with an EVD were included; 19 of the studies included patients with an early EVD, and two studies had late EVD placements. The limited number of studies, small sample sizes, imbalance in baseline characteristics between the groups and poor methodological quality have limited the scope of our analysis. We present the descriptive statistics highlighting the current conflicting data and the overall lack of reliable research into the optimal timing of EVD. There is a clear need for high quality comparisons of early vs. late EVD insertion on patient outcomes in sTBI.
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http://dx.doi.org/10.3390/jcm9061996DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7356750PMC
June 2020

Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study.

Lancet Glob Health 2020 08 2;8(8):e1018-e1026. Epub 2020 Jul 2.

The Alan Turing Institute, London, UK; Cambridge Centre for Artificial Intelligence in Medicine, Cambridge, UK; Department of Applied Mathematics and Theoretical Physics and Department of Population Health, University of Cambridge, Cambridge, UK; Department of Electrical and Computer Engineering, University of California Los Angeles, Los Angeles, CA, USA.

Background: Brazil ranks second worldwide in total number of COVID-19 cases and deaths. Understanding the possible socioeconomic and ethnic health inequities is particularly important given the diverse population and fragile political and economic situation. We aimed to characterise the COVID-19 pandemic in Brazil and assess variations in mortality according to region, ethnicity, comorbidities, and symptoms.

Methods: We conducted a cross-sectional observational study of COVID-19 hospital mortality using data from the SIVEP-Gripe (Sistema de Informação de Vigilância Epidemiológica da Gripe) dataset to characterise the COVID-19 pandemic in Brazil. In the study, we included hospitalised patients who had a positive RT-PCR test for severe acute respiratory syndrome coronavirus 2 and who had ethnicity information in the dataset. Ethnicity of participants was classified according to the five categories used by the Brazilian Institute of Geography and Statistics: Branco (White), Preto (Black), Amarelo (East Asian), Indígeno (Indigenous), or Pardo (mixed ethnicity). We assessed regional variations in patients with COVID-19 admitted to hospital by state and by two socioeconomically grouped regions (north and central-south). We used mixed-effects Cox regression survival analysis to estimate the effects of ethnicity and comorbidity at an individual level in the context of regional variation.

Findings: Of 99 557 patients in the SIVEP-Gripe dataset, we included 11 321 patients in our study. 9278 (82·0%) of these patients were from the central-south region, and 2043 (18·0%) were from the north region. Compared with White Brazilians, Pardo and Black Brazilians with COVID-19 who were admitted to hospital had significantly higher risk of mortality (hazard ratio [HR] 1·45, 95% CI 1·33-1·58 for Pardo Brazilians; 1·32, 1·15-1·52 for Black Brazilians). Pardo ethnicity was the second most important risk factor (after age) for death. Comorbidities were more common in Brazilians admitted to hospital in the north region than in the central-south, with similar proportions between the various ethnic groups. States in the north had higher HRs compared with those of the central-south, except for Rio de Janeiro, which had a much higher HR than that of the other central-south states.

Interpretation: We found evidence of two distinct but associated effects: increased mortality in the north region (regional effect) and in the Pardo and Black populations (ethnicity effect). We speculate that the regional effect is driven by increasing comorbidity burden in regions with lower levels of socioeconomic development. The ethnicity effect might be related to differences in susceptibility to COVID-19 and access to health care (including intensive care) across ethnicities. Our analysis supports an urgent effort on the part of Brazilian authorities to consider how the national response to COVID-19 can better protect Pardo and Black Brazilians, as well as the population of poorer states, from their higher risk of dying of COVID-19.

Funding: None.
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http://dx.doi.org/10.1016/S2214-109X(20)30285-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7332269PMC
August 2020

Identification of factors associated with morbidity and postoperative length of stay in surgically managed chronic subdural haematoma using electronic health records: a retrospective cohort study.

BMJ Open 2020 06 30;10(6):e037385. Epub 2020 Jun 30.

Neurocritical Care Department and Department of Anaesthesia, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK.

Introduction: Chronic subdural haematoma (cSDH) tends to occur in older patients, often with significant comorbidity. The incidence and effect of medical complications as well as the impact of intraoperative management strategies are now attracting increasing interest.

Objectives: We used electronic health record data to study the profile of in-hospital morbidity and examine associations between various intraoperative events and postoperative stay.

Design, Setting And Participants: Single-centre, retrospective cohort of 530 cases of cSDH (2014-2019) surgically evacuated under general anaesthesia at a neurosciences centre in Cambridge, UK.

Methods And Outcome Definition: Complications were defined using a modified Electronic Postoperative Morbidity Score. Association between complications and intraoperative care (time with mean arterial pressure <80 mm Hg, time outside of end-tidal carbon dioxide (ETCO) range of 3-5 kPa, maintenance anaesthetic, operative time and opioid dose) on postoperative stay was assessed using Cox regression.

Results: 53 (10%) patients suffered myocardial injury, while 24 (4.5%) suffered acute renal injury. On postoperative day 3 (D3), 280 (58% of remaining) inpatients suffered at least 1 complication. D7 rate was comparable (57%). Operative time was the only intraoperative event associated with postoperative stay (HR for discharge: 0.97 (95% CI: 0.95 to 0.99)). On multivariable analysis, postoperative complications (0.61 (0.55 to 0.68)), anticoagulation (0.45 (0.37 to 0.54)) and cognitive impairment (0.71 (0.58 to 0.87)) were associated with time to discharge.

Conclusions: There is a high postoperative morbidity burden in this cohort, which was associated with postoperative stay. We found no evidence of an association between intraoperative events and postoperative stay.
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http://dx.doi.org/10.1136/bmjopen-2020-037385DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7328896PMC
June 2020

Between-centre differences for COVID-19 ICU mortality from early data in England.

Intensive Care Med 2020 09 22;46(9):1779-1780. Epub 2020 Jun 22.

University of Cambridge Division of Anaesthesia, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 0QQ, UK.

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http://dx.doi.org/10.1007/s00134-020-06150-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7306496PMC
September 2020

Evaluation of the relationship between slow-waves of intracranial pressure, mean arterial pressure and brain tissue oxygen in TBI: a CENTER-TBI exploratory analysis.

J Clin Monit Comput 2020 May 16. Epub 2020 May 16.

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

Brain tissue oxygen (PbtO) monitoring in traumatic brain injury (TBI) has demonstrated strong associations with global outcome. Additionally, PbtO signals have been used to derive indices thought to be associated with cerebrovascular reactivity in TBI. However, their true relationship to slow-wave vasogenic fluctuations associated with cerebral autoregulation remains unclear. The goal of this study was to investigate the relationship between slow-wave fluctuations of intracranial pressure (ICP), mean arterial pressure (MAP) and PbtO over time. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution ICU sub-study cohort, we evaluated those patients with recorded high-frequency digital intra-parenchymal ICP and PbtO monitoring data of a minimum of 6 h in duration. Digital physiologic signals were processed for ICP, MAP, and PbtO slow-waves using a moving average filter to decimate the high-frequency signal. The first 5 days of recording were analyzed. The relationship between ICP, MAP and PbtO slow-waves over time were assessed using autoregressive integrative moving average (ARIMA) and vector autoregressive integrative moving average (VARIMA) modelling, as well as Granger causality testing. A total of 47 patients were included. The ARIMA structure of ICP and MAP were similar in time, where PbtO displayed different optimal structure. VARIMA modelling and IRF plots confirmed the strong directional relationship between MAP and ICP, demonstrating an ICP response to MAP impulse. PbtO slow-waves, however, failed to demonstrate a definite response to ICP and MAP slow-wave impulses. These results raise questions as to the utility of PbtO in the derivation of cerebrovascular reactivity measures in TBI. There is a reproducible relationship between slow-wave fluctuations of ICP and MAP, as demonstrated across various time-series analytic techniques. PbtO does not appear to reliably respond in time to slow-wave fluctuations in MAP, as demonstrated on various VARIMA models across all patients. These findings suggest that PbtO should not be utilized in the derivation of cerebrovascular reactivity metrics in TBI, as it does not appear to be responsive to changes in MAP in the slow-waves. These findings corroborate previous results regarding PbtO based cerebrovascular reactivity indices.
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http://dx.doi.org/10.1007/s10877-020-00527-6DOI Listing
May 2020

Machine learning in intensive care medicine: ready for take-off?

Intensive Care Med 2020 07 12;46(7):1486-1488. Epub 2020 May 12.

Department of Intensive Care Medicine, Research VUmc Intensive Care (REVIVE), Amsterdam Medical Data Science (AMDS), Amsterdam Cardiovascular Sciences (ACS), Amsterdam Infection and Immunity Institute (AI&II), Amsterdam UMC, Location VUmc, VU Amsterdam, Amsterdam, The Netherlands.

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http://dx.doi.org/10.1007/s00134-020-06045-yDOI Listing
July 2020

Brain Tissue Oxygen and Cerebrovascular Reactivity in Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury Exploratory Analysis of Insult Burden.

J Neurotrauma 2020 09 4;37(17):1854-1863. Epub 2020 May 4.

Division of Anaesthesia, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom.

Pressure reactivity index (PRx) and brain tissue oxygen (PbtO) are associated with outcome in traumatic brain injury (TBI). This study explores the relationship between PRx and PbtO in adult moderate/severe TBI. Using the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high resolution intensive care unit (ICU) sub-study cohort, we evaluated those patients with archived high-frequency digital intraparenchymal intracranial pressure (ICP) and PbtO monitoring data of, a minimum of 6 h in duration, and the presence of a 6 month Glasgow Outcome Scale -Extended (GOSE) score. Digital physiological signals were processed for ICP, PbtO, and PRx, with the % time above/below defined thresholds determined. The duration of ICP, PbtO, and PRx derangements was characterized. Associations with dichotomized 6-month GOSE (alive/dead, and favorable/unfavorable outcome; ≤ 4 = unfavorable), were assessed. A total of 43 patients were included. Severely impaired cerebrovascular reactivity was seen during elevated ICP and low PbtO episodes. However, most of the acute ICU physiological derangements were impaired cerebrovascular reactivity, not ICP elevations or low PbtO episodes. Low PbtO without PRx impairment was rarely seen. % time spent above PRx threshold was associated with mortality at 6 months for thresholds of 0 (area under the curve [AUC] 0.734,  = 0.003), > +0.25 (AUC 0.747,  = 0.002) and > +0.35 (AUC 0.745,  = 0.002). Similar relationships were not seen for % time with ICP >20 mm Hg, and PbtO < 20 mm Hg in this cohort. Extreme impairment in cerebrovascular reactivity is seen during concurrent episodes of elevated ICP and low PbtO. However, the majority of the deranged cerebral physiology seen during the acute ICU phase is impairment in cerebrovascular reactivity, with most impairment occurring in the presence of normal PbtO levels. Measures of cerebrovascular reactivity appear to display the most consistent associations with global outcome in TBI, compared with ICP and PbtO.
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http://dx.doi.org/10.1089/neu.2020.7024DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7484893PMC
September 2020

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury.

J Clin Epidemiol 2020 06 20;122:95-107. Epub 2020 Mar 20.

Departments of Public Health, Erasmus MC - University Medical Centre Rotterdam, Rotterdam, the Netherlands; Department of Biomedical Data Sciences, Leiden University Medical Centre, Leiden, the Netherlands.

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.
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http://dx.doi.org/10.1016/j.jclinepi.2020.03.005DOI Listing
June 2020

Diffuse Intracranial Injury Patterns Are Associated with Impaired Cerebrovascular Reactivity in Adult Traumatic Brain Injury: A CENTER-TBI Validation Study.

J Neurotrauma 2020 07 6;37(14):1597-1608. Epub 2020 Apr 6.

Division of Anesthesia, Division of Neurosurgery, Addenbrooke's Hospital, University of Cambridge, Cambridge, United Kingdom.

Recent single-center retrospective analysis displayed the association between admission computed tomography (CT) markers of diffuse intracranial injury and worse cerebrovascular reactivity. The goal of this study was to further explore these associations using the prospective multi-center Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) high-resolution intensive care unit (HR ICU) data set. Using the CENTER-TBI HR ICU sub-study cohort, we evaluated those patients with both archived high-frequency digital physiology (100 Hz or higher) and the presence of a digital admission CT scan. Physiological signals were processed for pressure reactivity index (PRx) and both the percent (%) time above defined PRx thresholds and mean hourly dose above threshold. Admission CT injury scores were obtained from the database. Quantitative contusion, edema, intraventricular hemorrhage (IVH), and extra-axial lesion volumes were obtained via semi-automated segmentation. Comparison between admission CT characteristics and PRx metrics was conducted using Mann-U, Jonckheere-Terpstra testing, with a combination of univariate linear and logistic regression techniques. A total of 165 patients were included. Cisternal compression and high admission Rotterdam and Helsinki CT scores, and Marshall CT diffuse injury sub-scores were associated with increased percent (%) time and hourly dose above PRx threshold of 0, +0.25, and +0.35 ( < 0.02 for all). Logistic regression analysis displayed an association between deep peri-contusional edema and mean PRx above a threshold of +0.25. These results suggest that diffuse injury patterns, consistent with acceleration/deceleration forces, are associated with impaired cerebrovascular reactivity. Diffuse admission intracranial injury patterns appear to be consistently associated with impaired cerebrovascular reactivity, as measured through PRx. This is in keeping with the previous single-center retrospective literature on the topic. This study provides multi-center validation for those results, and provides preliminary data to support potential risk stratification for impaired cerebrovascular reactivity based on injury pattern.
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http://dx.doi.org/10.1089/neu.2019.6959DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7336886PMC
July 2020

Quality indicators for patients with traumatic brain injury in European intensive care units: a CENTER-TBI study.

Crit Care 2020 03 4;24(1):78. Epub 2020 Mar 4.

Department of Intensive Care Adults, Erasmus MC- University Medical Center Rotterdam, Rotterdam, The Netherlands.

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measurement and improvement.

Methods: Our analysis was based on 2006 adult patients admitted to 54 ICUs between 2014 and 2018, enrolled in the CENTER-TBI study. Indicator scores were calculated as percentage adherence for structure and process indicators and as event rates or median scores for outcome indicators. Feasibility was quantified by the completeness of the variables. Discriminability was determined by the between-centre variation, estimated with a random effect regression model adjusted for case-mix severity and quantified by the median odds ratio (MOR). Statistical uncertainty of outcome indicators was determined by the median number of events per centre, using a cut-off of 10.

Results: A total of 26/42 indicators could be calculated from the CENTER-TBI database. Most quality indicators proved feasible to obtain with more than 70% completeness. Sub-optimal adherence was found for most quality indicators, ranging from 26 to 93% and 20 to 99% for structure and process indicators. Significant (p < 0.001) between-centre variation was found in seven process and five outcome indicators with MORs ranging from 1.51 to 4.14. Statistical uncertainty of outcome indicators was generally high; five out of seven had less than 10 events per centre.

Conclusions: Overall, nine structures, five processes, but none of the outcome indicators showed potential for quality improvement purposes for TBI patients in the ICU. Future research should focus on implementation efforts and continuous reevaluation of quality indicators.

Trial Registration: The core study was registered with ClinicalTrials.gov, number NCT02210221, registered on August 06, 2014, with Resource Identification Portal (RRID: SCR_015582).
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http://dx.doi.org/10.1186/s13054-020-2791-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7057641PMC
March 2020