Purpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in... Show morePurpose: Enrolling traumatic brain injury (731) patients with an inability to provide informed consent in research is challenging. Alternatives to patient consent are not sufficiently embedded in European and national legislation, which allows procedural variation and bias. We aimed to quantify variations in informed consent policy and practice.Methods: Variation was explored in the CENTER-TBI study. Policies were reported by using a questionnaire and national legislation. Data on used informed consent procedures were available for 4498 patients from 57 centres across 17 European countries.Results: Variation in the use of informed consent procedures was found between and within EU member states. Proxy informed consent (N = 1377;64%) was the most frequently used type of consent in the ICU, followed by patient informed consent (N 426;20%) and deferred consent (N 334;16%). Deferred consent was only actively used in 15 centres (26%), although it was considered valid in 47 centres (82%).Conclusions: Alternatives to patient consent are essential for TBI research. While there seems to be concordance amongst national legislations, there is regional variability in institutional practices with respect to the use of different informed consent procedures. Variation could be caused by several reasons, including inconsistencies in clear legislation or knowledge of such legislation amongst researchers. (C) 2020 Published by Elsevier Inc. Show less
Background Paediatric Early Warning Scores (PEWSs) are being used increasingly in hospital wards to identify children at risk of clinical deterioration, but few scores exist that were designed for... Show moreBackground Paediatric Early Warning Scores (PEWSs) are being used increasingly in hospital wards to identify children at risk of clinical deterioration, but few scores exist that were designed for use in emergency care settings. To improve the prioritisation of children in the emergency department (ED), we developed and validated an ED-PEWS.Methods The TrIAGE project is a prospective European observational study based on electronic health record data collected between Jan 1, 2012, and Nov 1, 2015, from five diverse EDs in four European countries (Netherlands, the UK, Austria, and Portugal). This study included data from all consecutive ED visits of children under age 16 years. The main outcome measure was a three-category reference standard (high, intermediate, low urgency) that was developed as part of the TrIAGE project as a proxy for true patient urgency. The ED-PEWS was developed based on an ordinal logistic regression model, with cross-validation by setting. After completing the study, we fully externally validated the ED-PEWS in an independent cohort of febrile children from a different ED (Greece).Findings Of 119 209 children, 2007 (1.7%) were of high urgency and 29 127 (24.4%) of intermediate urgency, according to our reference standard. We developed an ED-PEWS consisting of age and the predictors heart rate, respiratory rate, oxygen saturation, consciousness, capillary refill time, and work of breathing. The ED-PEWS showed a cross-validated c-statistic of 0.86 (95% prediction interval 0.82-0.90) for high-urgency patients and 0.67 (0.61-0.73) for highurgency or intermediate-urgency patients. A cutoff of score of at least 15 was useful for identifying high-urgency patients with a specificity of 0.90 (95% CI 0.87-0.92) while a cutoff score of less than 6 was useful for identifying low-urgency patients with a sensitivity of 0.83 (0.81-0.85).Interpretation The proposed ED-PEWS can assist in identifying high-urgency and low-urgency patients in the ED, and improves prioritisation compared with existing PEWSs. Show less
Objective To develop a model and methodology for predicting the risk of Gleason upgrading in patients with prostate cancer on active surveillance (AS) and using the predicted risks to create risk... Show moreObjective To develop a model and methodology for predicting the risk of Gleason upgrading in patients with prostate cancer on active surveillance (AS) and using the predicted risks to create risk-based personalised biopsy schedules as an alternative to one-size-fits-all schedules (e.g. annually). Furthermore, to assist patients and doctors in making shared decisions on biopsy schedules, by providing them quantitative estimates of the burden and benefit of opting for personalised vs any other schedule in AS. Lastly, to externally validate our model and implement it along with personalised schedules in a ready to use web-application. Patients and Methods Repeat prostate-specific antigen (PSA) measurements, timing and results of previous biopsies, and age at baseline from the world's largest AS study, Prostate Cancer Research International Active Surveillance (PRIAS; 7813 patients, 1134 experienced upgrading). We fitted a Bayesian joint model for time-to-event and longitudinal data to this dataset. We then validated our model externally in the largest six AS cohorts of the Movember Foundation's third Global Action Plan (GAP3) database (>20 000 patients, 27 centres worldwide). Using the model predicted upgrading risks; we scheduled biopsies whenever a patient's upgrading risk was above a certain threshold. To assist patients/doctors in the choice of this threshold, and to compare the resulting personalised schedule with currently practiced schedules, along with the timing and the total number of biopsies (burden) planned, for each schedule we provided them with the time delay expected in detecting upgrading (shorter is better). Results The cause-specific cumulative upgrading risk at the 5-year follow-up was 35% in PRIAS, and at most 50% in the GAP3 cohorts. In the PRIAS-based model, PSA velocity was a stronger predictor of upgrading (hazard ratio [HR] 2.47, 95% confidence interval [CI] 1.93-2.99) than the PSA level (HR 0.99, 95% CI 0.89-1.11). Our model had a moderate area under the receiver operating characteristic curve (0.6-0.7) in the validation cohorts. The prediction error was moderate (0.1-0.2) in theGAP3 cohorts where the impact of the PSA level and velocity on upgrading risk was similar to PRIAS, but large (0.2-0.3) otherwise. Our model required re-calibration of baseline upgrading risk in the validation cohorts. We implemented the validated models and the methodology for personalised schedules in a web-application (). Conclusions We successfully developed and validated a model for predicting upgrading risk, and providing risk-based personalised biopsy decisions in AS of prostate cancer. Personalised prostate biopsies are a novel alternative to fixed one-size-fits-all schedules, which may help to reduce unnecessary prostate biopsies, while maintaining cancer control. The model and schedules made available via a web-application enable shared decision-making on biopsy schedules by comparing fixed and personalised schedules on total biopsies and expected time delay in detecting upgrading. Show less
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... Show moreObjective: 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. (C) 2020 The Authors. Published by Elsevier Inc. Show less
Loss to follow-up or patient attrition is common in longitudinal studies of traumatic brain injury (TBI). Lack of understanding exists between the relation of study design and patient attrition.... Show moreLoss to follow-up or patient attrition is common in longitudinal studies of traumatic brain injury (TBI). Lack of understanding exists between the relation of study design and patient attrition. This review aimed to identify features of study design that are associated with attrition. We extended the analysis of a previous systematic review on missing data in 195 TBI studies using the Glasgow Outcome Scale Extended (GOSE) as an outcome measure. Studies that did not report attrition or had heterogeneous methodology were excluded, leaving 148 studies. Logistic regression found seven of the 14 design features studied to be associated with patient attrition. Four features were associated with an increase in attrition: greater follow-up frequency (odds ratio [OR]: 1.2, 95% confidence interval [CI]: 1.0-1.3), single rather than multi-center design (OR: 1.6, 95% CI: 1.2-2.2), enrollment of exclusively mild TBI patients (OR: 2.8, 95% CI: 1.6-4.9), and collection of the GOS by post or telephone without face-to-face contact (OR: 1.6, 95% CI:1.1-2.4). Conversely, two features were associated with a reduction in attrition: recruitment in an acute care setting defined as the ward or intensive care unit (OR: 0.58, 95% CI: 0.47-0.72) and a greater duration of time between injury and follow-up (OR: 0.93, 95% CI: 0.88-0.99). This review highlights design features that are associated with attrition and could be considered when planning for patient retention. Further work is needed to establish the mechanisms between the observed associations and potential remedies. Show less
Huijben, J.A.; Wiegers, E.J.A.; Ercole, A.; Keizer, N.F. de; Maas, A.I.R.; Steyerberg, E.W.; ... ; Jagt, M. van der 2020
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... Show moreBackground 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. Show less
Objective To assess the role of sex in the presentation and management of children attending the emergency department (ED). Design The TrIAGE project (TRiage Improvements Across General Emergency... Show moreObjective To assess the role of sex in the presentation and management of children attending the emergency department (ED). Design The TrIAGE project (TRiage Improvements Across General Emergency departments), a prospective observational study based on curated electronic health record data. Setting Five diverse European hospitals in four countries (Austria, The Netherlands, Portugal, UK). Participants All consecutive paediatric ED visits of children under the age of 16 during the study period (8-36 months between 2012 and 2015). Main outcome measures The association between sex (male of female) and diagnostic tests and disease management in general paediatric ED visits and in subgroups presenting with trauma or musculoskeletal, gastrointestinal and respiratory problems and fever. Results from the different hospitals were pooled in a random effects meta-analysis. Results 116 172 ED visits were included of which 63 042 (54%) by boys and 53 715 (46%) by girls. Boys accounted for the majority of ED visits in childhood, and girls in adolescence. After adjusting for age, triage urgency and clinical presentation, girls had more laboratory tests compared with boys (pooled OR 1.10, 95% CI 1.05 to 1.15). Additionally, girls had more laboratory tests in ED visits for respiratory problems (pooled OR 1.15, 95% CI 1.04 to 1.26) and more imaging in visits for trauma or musculoskeletal problems (pooled OR 1.10, 95% CI 1.01 to 1.20) and respiratory conditions (pooled OR 1.14, 95% CI 1.05 to 1.24). Girls with respiratory problems were less often treated with inhalation medication (pooled OR 0.76, 95% CI 0.70 to 0.83). There was no difference in hospital admission between the sexes (pooled OR 0.99, 95% CI 0.95 to 1.04). Conclusion In childhood, boys represent the majority of ED visits and they receive more inhalation medication. Unexpectedly, girls receive more diagnostic tests compared with boys. Further research is needed to investigate whether this is due to pathophysiological differences and differences in disease course, whether girls present signs and symptoms differently, or whether sociocultural factors are responsible. Show less
Brinkman-Stoppelenburg, A.; Polinder, S.; Olij, B.F.; Berg, B. van den; Gunnink, N.; Hendriks, M.P.; ... ; Heide, A. van der 2019
Background Early palliative care team consultation has been shown to reduce costs of hospital care. The objective of this study was to investigate the association between palliative care team (PCT)... Show moreBackground Early palliative care team consultation has been shown to reduce costs of hospital care. The objective of this study was to investigate the association between palliative care team (PCT) consultation and the content and costs of hospital care in patients with advanced cancer. Material and Methods A prospective, observational study was conducted in 12 Dutch hospitals. Patients with advanced cancer and an estimated life expectancy of less than 1 year were included. We compared hospital care during 3 months of follow-up for patients with and without PCT involvement. Propensity score matching was used to estimate the effect of PCTs on costs of hospital care. Additionally, gamma regression models were estimated to assess predictors of hospital costs. Results We included 535 patients of whom 126 received PCT consultation. Patients with PCT had a worse life expectancy (life expectancy <3 months: 62% vs. 31%, p < .01) and performance status (p < .01, e.g., WHO status higher than 2:54% vs. 28%) and more often had no more options for anti-tumour therapy (57% vs. 30%, p < .01). Hospital length of stay, use of most diagnostic procedures, medication and other therapeutic interventions were similar. The total mean hospital costs were euro8,393 for patients with and euro8,631 for patients without PCT consultation. Analyses using propensity scores to control for observed confounding showed no significant difference in hospital costs. Conclusions PCT consultation for patients with cancer in Dutch hospitals often occurs late in the patients' disease trajectories, which might explain why we found no effect of PCT consultation on costs of hospital care. Earlier consultation could be beneficial to patients and reduce costs of care. Show less
Introduction Controversy exists about the optimal treatment for patients with a traumatic acute subdural haematoma (ASDH) and an intracerebral haematoma/contusion (t-ICH). Treatment varies largely... Show moreIntroduction Controversy exists about the optimal treatment for patients with a traumatic acute subdural haematoma (ASDH) and an intracerebral haematoma/contusion (t-ICH). Treatment varies largely between different regions. The effect of this practice variation on patient outcome is unknown. Here, we present the protocol for a prospective multicentre observational study aimed at comparing the effectiveness of different treatment strategies in patients with ASDH and/or t-ICH. Specifically, the aims are to compare (1) an acute surgical approach to an expectant approach and (2) craniotomy to decompressive craniectomy when evacuating the haematoma.Methods and analysis Patients presenting to the emergency room with an ASDH and/or an t-ICH are eligible for inclusion. Standardised prospective data on patient and injury characteristics, treatment and outcome will be collected on 1000 ASDH and 750 t-ICH patients in 60-70 centres within two multicentre prospective observational cohort studies: the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) and Neurotraumatology Quality Registry (Net-QuRe). The interventions of interest are acute surgery, defined as surgery directly after the first CT at presentation versus late or no surgery and craniotomy versus decompressive craniectomy. The primary outcome measure is the Glasgow Outcome Score-Extended at 6 months. Secondary outcome measures include in-hospital mortality, quality of life and neuropsychological tests. In the primary analysis, the effect of treatment preference (eg, proportion of patients in which the intervention under study is preferred) per hospital will be analysed with random effects ordinal regression models, adjusted for casemix and stratified by study. Such a hospital-level approach reduces confounding by the indication. Sensitivity analyses will include propensity score matching, with treatment defined on patient level. This study is designed to determine the best acute management strategy for ASDH and t-ICH by exploiting the existing between-hospital variability in surgical management.Ethics and dissemination Ethics approval was obtained in all participating countries. Results of surgical management of ASDH and t-ICH/contusion will separately be submitted for publication in a peer-reviewed journal. Show less
Clinical prediction models aim to provide estimates of absolute risk for a diagnostic or prognostic endpoint. Such models may be derived from data from various studies in the context of a meta... Show moreClinical prediction models aim to provide estimates of absolute risk for a diagnostic or prognostic endpoint. Such models may be derived from data from various studies in the context of a meta-analysis. We describe and propose approaches for assessing heterogeneity in predictor effects and predictions arising from models based on data from different sources. These methods are illustrated in a case study with patients suffering from traumatic brain injury, where we aim to predict 6-month mortality based on individual patient data using meta-analytic techniques (15 studies, n = 11 022 patients). The insights into various aspects of heterogeneity are important to develop better models and understand problems with the transportability of absolute risk predictions. Show less
