The relationship between patient volume and mortality in NSW major trauma service hospitals.

INTRODUCTION: Conventional wisdom is that Major Trauma Services (MTS) treating larger volumes of severe trauma patients will have better outcomes than lower volume centres, but recent studies from Europe have questioned this relationship. We aimed to determine if there is a relationship between patient volume and outcome in New South Wales (NSW) MTS hospitals. MATERIALS AND METHODS: Retrospective observational study using data from the NSW State Trauma Registry from 2010 to 2019 inclusive. Adult patients with Injury Severity Score >15 transported directly to a NSW MTS were included. Outcome measures were mortality at hospital discharge, and intensive care unit and hospital length of stay. Generalised estimating equation models were created to determine the adjusted relationship between patient volume and the main outcome measures. RESULTS: The mean annual patient volume of the MTS ranged from 127.4 to 282.0 patients whilst the observed mortality rates p.a. ranged from 10.4 % to 17.19 %. Multivariate analysis, using low volume MTS as the reference, did not demonstrate a significant difference in mortality between high and low volume MTS (adjusted OR: 1.14 95 % CI: 0.98-1.25, P = 0.087). There was however a significant correlation between volume and length of hospital stay (adjusted ß; 0.024, 95 % CI, 0.182 - 1.089, P = 0.006). CONCLUSIONS: There was no mortality difference between high and low volume MTS demonstrated. Length of hospital stay significantly increased with increasing volume however.

Missing patient registrations in the Dutch National Trauma Registry of Southwest Netherlands: Prevalence and epidemiology.

INTRODUCTION: Health care patient records have been digitalised the past twenty years, and registries have been automated. Missing registrations are common, and can result in selection bias. OBJECTIVE: To assess the prevalence and characteristics of missed registrations in a Dutch regional trauma registry. METHODS: An automatically generated trauma registry export was done for ten out of eleven hospitals in trauma region Southwest Netherlands, between June 1 and August 31, 2020. Second, lists were checked for being falsely flagged as 'non-trauma'. Finally, a list was generated with trauma tick box flagged as 'trauma' but were not automatically in the export due to administrative errors. Automated and missed registration datasets were compared on patient characteristics and logistic regression models were run with random intercepts and missed registration as outcome variable on the complete dataset. RESULTS: A total of 2,230 automated registrations and 175 (7.3 %) missed registrations were included for the Dutch National Trauma Registry, ranging from 1 to 14 % between participating hospitals. Patients of the missed registration dataset had characteristics of a higher level of care, compared with patients of automated registrations. Level of trauma care (level II OR 0.464 95 % CI 0.328-0.666, p < 0.001; level III OR 0.179 95 % CI 0.092-0.325, p < 0.001), major trauma (OR 2.928 95 % CI 1.792-4.65, p < 0.001), ICU admission (OR 2.337 95 % CI 1.792-4.650, p < 0.001), and surgery (OR 1.871 95 % CI 1.371-2.570, p < 0.001) were potential predictors for missed registrations in multivariate logistic regression analysis. CONCLUSION: Missed registrations occur frequently and the rate of missed registrations differs greatly between hospitals. Automated and missed registration datasets display differences related to patients requiring more intensive care, which held for the major trauma subset. Checking for missed registrations is time consuming, automated registration lists need a human touch for validation and to be complete.

Evaluating associations between level of trauma care and outcomes of patients with specific severe injuries: A systematic review and meta-analysis.

BACKGROUND: Trauma networks have multiple designated levels of trauma care. This classification parallels concentration of major trauma care, creating innovations and improving outcome measures. OBJECTIVES: The objective of this study is to assess associations of level of trauma care with patient outcomes for populations with specific severe injuries. METHODS: A systematic literature search was conducted using six electronic databases up to April 19, 2022 (PROSPERO CRD42022327576). Studies comparing fatal, nonfatal clinical, or functional outcomes across different levels of trauma care for trauma populations with specific severe injuries or injured body region (Abbreviated Injury Scale score ≥3) were included. Two independent reviewers included studies, extracted data, and assessed quality. Unadjusted and adjusted pooled effect sizes were calculated with random-effects meta-analysis comparing Level I and Level II trauma centers. RESULTS: Thirty-five studies (1,100,888 patients) were included, of which 25 studies (n = 443,095) used for meta-analysis, suggesting a survival benefit for the severely injured admitted to a Level I trauma center compared with a Level II trauma center (adjusted odds ratio [OR], 1.15; 95% confidence interval [CI], 1.06-1.25). Adjusted subgroup analysis on in-hospital mortality was done for patients with traumatic brain injuries (OR, 1.23; 95% CI, 1.01-1.50) and hemodynamically unstable patients (OR, 1.09; 95% CI, 0.98-1.22). Hospital and intensive care unit length of stay resulted in an unadjusted mean difference of -1.63 (95% CI, -2.89 to -0.36) and -0.21 (95% CI, -1.04 to 0.61), respectively, discharged home resulted in an unadjusted OR of 0.92 (95% CI, 0.78-1.09). CONCLUSION: Severely injured patients admitted to a Level I trauma center have a survival benefit. Nonfatal outcomes were indicative for a longer stay, more intensive care, and more frequently posthospital recovery trajectories after being admitted to top levels of trauma care. Trauma networks with designated levels of trauma care are beneficial to the multidisciplinary character of trauma care. LEVEL OF EVIDENCE: Systematic review and meta-analysis; Level III.

Primary admission and secondary transfer of trauma patients to Dutch level I and level II trauma centers: predictors and outcomes.

PURPOSE: The importance and impact of determining which trauma patients need to be transferred between hospitals, especially considering prehospital triage systems, is evident. The objective of this study was to investigate the association between mortality and primary admission and secondary transfer of patients to level I and II trauma centers, and to identify predictors of primary and secondary admission to a designated level I trauma center. METHODS: Data from the Dutch Trauma Registry South West (DTR SW) was obtained. Patients ≥ 18 years who were admitted to a level I or level II trauma center were included. Patients with isolated burn injuries were excluded. In-hospital mortality was compared between patients that were primarily admitted to a level I trauma center, patients that were transferred to a level I trauma center, and patients that were primarily admitted to level II trauma centers. Logistic regression models were used to adjust for potential confounders. A subgroup analysis was done including major trauma (MT) patients (ISS > 15). Predictors determining whether patients were primarily admitted to level I or level II trauma centers or transferred to a level I trauma center were identified using logistic regression models. RESULTS: A total of 17,035 patients were included. Patients admitted primarily to a level I center, did not differ significantly in mortality from patients admitted primarily to level II trauma centers (Odds Ratio (OR): 0.73; 95% confidence interval (CI) 0.51-1.06) and patients transferred to level I centers (OR: 0.99; 95%CI 0.57-1.71). Subgroup analyses confirmed these findings for MT patients. Adjusted logistic regression analyses showed that age (OR: 0.96; 95%CI 0.94-0.97), GCS (OR: 0.81; 95%CI 0.77-0.86), AIS head (OR: 2.30; 95%CI 2.07-2.55), AIS neck (OR: 1.74; 95%CI 1.27-2.45) and AIS spine (OR: 3.22; 95%CI 2.87-3.61) are associated with increased odds of transfers to a level I trauma center. CONCLUSIONS: This retrospective study showed no differences in in-hospital mortality between general trauma patients admitted primarily and secondarily to level I trauma centers. The most prominent predictors regarding transfer of trauma patients were age and neurotrauma. These findings could have practical implications regarding the triage protocols currently used.

Primary versus early secondary referral to a specialized neurotrauma center in patients with moderate/severe traumatic brain injury: a CENTER TBI study.

BACKGROUND: Prehospital care for patients with traumatic brain injury (TBI) varies with some emergency medical systems recommending direct transport of patients with moderate to severe TBI to hospitals with specialist neurotrauma care (SNCs). The aim of this study is to assess variation in levels of early secondary referral within European SNCs and to compare the outcomes of directly admitted and secondarily transferred patients. METHODS: Patients with moderate and severe TBI (Glasgow Coma Scale < 13) from the prospective European CENTER-TBI study were included in this study. All participating hospitals were specialist neuroscience centers. First, adjusted between-country differences were analysed using random effects logistic regression where early secondary referral was the dependent variable, and a random intercept for country was included. Second, the adjusted effect of early secondary referral on survival to hospital discharge and functional outcome [6 months Glasgow Outcome Scale Extended (GOSE)] was estimated using logistic and ordinal mixed effects models, respectively. RESULTS: A total of 1347 moderate/severe TBI patients from 53 SNCs in 18 European countries were included. Of these 1347 patients, 195 (14.5%) were admitted after early secondary referral. Secondarily referred moderate/severe TBI patients presented more often with a CT abnormality: mass lesion (52% vs. 34%), midline shift (54% vs. 36%) and acute subdural hematoma (77% vs. 65%). After adjusting for case-mix, there was a large European variation in early secondary referral, with a median OR of 1.69 between countries. Early secondary referral was not associated with functional outcome (adjusted OR 1.07, 95% CI 0.78-1.69), nor with survival at discharge (1.05, 0.58-1.90). CONCLUSIONS: Across Europe, substantial practice variation exists in the proportion of secondarily referred TBI patients at SNCs that is not explained by case mix. Within SNCs early secondary referral does not seem to impact functional outcome and survival after stabilisation in a non-specialised hospital. Future research should identify which patients with TBI truly benefit from direct transportation.

Identifying trauma patients with benefit from direct transportation to Level-1 trauma centers.

BACKGROUND: Prehospital triage protocols typically try to select patients with Injury Severity Score (ISS) above 15 for direct transportation to a Level-1 trauma center. However, ISS does not necessarily discriminate between patients who benefit from immediate care at Level-1 trauma centers. The aim of this study was to assess which patients benefit from direct transportation to Level-1 trauma centers. METHODS: We used the American National Trauma Data Bank (NTDB), a retrospective observational cohort. All adult patients (ISS > 3) between 2015 and 2016 were included. Patients who were self-presenting or had isolated limb injury were excluded. We used logistic regression to assess the association of direct transportation to Level-1 trauma centers with in-hospital mortality adjusted for clinically relevant confounders. We used this model to define benefit as predicted probability of mortality associated with transportation to a non-Level-1 trauma center minus predicted probability associated with transportation to a Level-1 trauma center. We used a threshold of 1% as absolute benefit. Potential interaction terms with transportation to Level-1 trauma centers were included in a penalized logistic regression model to study which patients benefit. RESULTS: We included 388,845 trauma patients from 232 Level-1 centers and 429 Level-2/3 centers. A small beneficial effect was found for direct transportation to Level-1 trauma centers (adjusted Odds Ratio: 0.96, 95% Confidence Interval: 0.92-0.99) which disappeared when comparing Level-1 and 2 versus Level-3 trauma centers. In the risk approach, predicted benefit ranged between 0 and 1%. When allowing for interactions, 7% of the patients (n = 27,753) had more than 1% absolute benefit from direct transportation to Level-1 trauma centers. These patients had higher AIS Head and Thorax scores, lower GCS and lower SBP. A quarter of the patients with ISS > 15 were predicted to benefit from transportation to Level-1 centers (n = 26,522, 22%). CONCLUSIONS: Benefit of transportation to a Level-1 trauma centers is quite heterogeneous across patients and the difference between Level-1 and Level-2 trauma centers is small. In particular, patients with head injury and signs of shock may benefit from care in a Level-1 trauma center. Future prehospital triage models should incorporate more complete risk profiles.

The definition of major trauma using different revisions of the abbreviated injury scale.

BACKGROUND: A threshold Injury Severity Score (ISS) ≥ 16 is common in classifying major trauma (MT), although the Abbreviated Injury Scale (AIS) has been extensively revised over time. The aim of this study was to determine effects of different AIS revisions (1998, 2008 and 2015) on clinical outcome measures. METHODS: A retrospective observational cohort study including all primary admitted trauma patients was performed (in 2013-2014 AIS98 was used, in 2015-2016 AIS08, AIS08 mapped to AIS15). Different ISS thresholds for MT and their corresponding observed mortality and intensive care (ICU) admission rates were compared between AIS98, AIS08, and AIS15 with Chi-square tests and logistic regression models. RESULTS: Thirty-nine thousand three hundred seventeen patients were included. Thresholds ISS08 ≥ 11 and ISS15 ≥ 12 were similar to a threshold ISS98 ≥ 16 for in-hospital mortality (12.9, 12.9, 13.1% respectively) and ICU admission (46.7, 46.2, 46.8% respectively). AIS98 and AIS08 differed significantly for in-hospital mortality in ISS 4-8 (χ2 = 9.926, p = 0.007), ISS 9-11 (χ2 = 13.541, p = 0.001), ISS 25-40 (χ2 = 13.905, p = 0.001) and ISS 41-75 (χ2 = 7.217, p = 0.027). Mortality risks did not differ significantly between AIS08 and AIS15. CONCLUSION: ISS08 ≥ 11 and ISS15 ≥ 12 perform similarly to a threshold ISS98 ≥ 16 for in-hospital mortality and ICU admission. This confirms studies evaluating mapped datasets, and is the first to present an evaluation of implementation of AIS15 on registry datasets. Defining MT using appropriate ISS thresholds is important for quality indicators, comparing datasets and adjusting for injury severity. LEVEL OF EVIDENCE: Prognostic and epidemiological, level III.

The Relationship between Hospital Volume and In-Hospital Mortality of Severely Injured Patients in Dutch Level-1 Trauma Centers.

Centralization of trauma centers leads to a higher hospital volume of severely injured patients (Injury Severity Score (ISS) > 15), but the effect of volume on outcome remains unclear. The aim of this study was to determine the association between hospital volume of severely injured patients and in-hospital mortality in Dutch Level-1 trauma centers. A retrospective observational cohort study was performed using the Dutch trauma registry. All severely injured adults (ISS > 15) admitted to a Level-1 trauma center between 2015 and 2018 were included. The effect of hospital volume on in-hospital mortality was analyzed with random effects logistic regression models with a random intercept for Level-1 trauma center, adjusted for important demographic and injury characteristics. A total of 11,917 severely injured patients from 13 Dutch Level-1 trauma centers was included in this study. Hospital volume varied from 120 to 410 severely injured patients per year. Observed mortality rates varied between 12% and 24% per center. After case-mix correction, no statistically significant differences between low- and high-volume centers were demonstrated (adjusted odds ratio 0.97 per 50 extra patients per year, 95% Confidence Interval 0.90-1.04, p = 0.44). The variation in hospital volume of the included Level-1 trauma centers was not associated with the outcome of severely injured patients. Our results suggest that well-organized trauma centers with a similar organization of care could potentially achieve comparable outcomes.

Missing Data in Prediction Research: A Five-Step Approach for Multiple Imputation, Illustrated in the CENTER-TBI Study.

In medical research, missing data is common. In acute diseases, such as traumatic brain injury (TBI), even well-conducted prospective studies may suffer from missing data in baseline characteristics and outcomes. Statistical models may simply drop patients with any missing values, potentially leaving a selected subset of the original cohort. Imputation is widely accepted by methodologists as an appropriate way to deal with missing data. We aim to provide practical guidance on handling missing data for prediction modeling. We hereto propose a five-step approach, centered around single and multiple imputation: 1) explore the missing data patterns; 2) choose a method of imputation; 3) perform imputation; 4) assess diagnostics of the imputation; and 5) analyze the imputed data sets. We illustrate these five steps with the estimation and validation of the IMPACT (International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury) prognostic model in 1375 patients from the CENTER-TBI database, included in 53 centers across 17 countries, with moderate or severe TBI in the prospective European CENTER-TBI study. Future prediction modeling studies in acute diseases may benefit from following the suggested five steps for optimal statistical analysis and interpretation, after maximal effort has been made to minimize missing data.

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

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.

The association between level of trauma care and clinical outcome measures: A systematic review and meta-analysis.

BACKGROUND: With implementation of trauma systems, a level of trauma care classification was introduced. Use of such a system has been linked to significant improvements in survival and other outcomes. OBJECTIVES: The aim of this study was assessing the association between level of trauma care and fatal and nonfatal outcome measures for general and major trauma (MT) populations. METHODS: A systematic literature search was conducted using six electronic databases up to December 18, 2019. Studies comparing mortality or nonfatal outcomes between different levels of trauma care in general and MT populations (preferably Injury Severity Score of >15) were included. Two independent reviewers performed selection of relevant studies, data extraction, and a quality assessment of included articles. With a random-effects meta-analysis, adjusted and unadjusted pooled effect sizes were calculated for level I versus non-level I trauma centers. RESULTS: Twenty-two studies were included. Quality of the included studies was good; however, adjustment for comorbidity (32%) and interhospital transfer (38%) was performed less frequently. Nine (60%) of the 15 studies analyzing in-hospital mortality in general trauma populations reported a survival benefit for level I trauma centers. Level I trauma centers were not associated with higher mortality than non-level I trauma centers (adjusted odd ratio, 0.97; 95% confidence interval, 0.61-1.52). Of the 11 studies reporting in-hospital mortality in MT populations, 10 (91%) reported a survival benefit for level I trauma centers. Level I trauma centers were associated with lower mortality than non-level I trauma centers (adjusted odd ratio, 0.77; 95% confidence interval, 0.69-0.87). CONCLUSION: The association between level of trauma care and in-hospital mortality is evident for MT populations; however, this does not hold for general trauma populations. Level I trauma centers produce improved survival in MT populations. This association could not be proven for nonfatal outcomes in general and MT populations because of inconsistencies in the body of evidence. LEVEL OF EVIDENCE: Systematic review and meta-analysis, level III.

Tracheal intubation in traumatic brain injury: a multicentre prospective observational study.

BACKGROUND: We aimed to study the associations between pre- and in-hospital tracheal intubation and outcomes in traumatic brain injury (TBI), and whether the association varied according to injury severity. METHODS: Data from the international prospective pan-European cohort study, Collaborative European NeuroTrauma Effectiveness Research for TBI (CENTER-TBI), were used (n=4509). For prehospital intubation, we excluded self-presenters. For in-hospital intubation, patients whose tracheas were intubated on-scene were excluded. The association between intubation and outcome was analysed with ordinal regression with adjustment for the International Mission for Prognosis and Analysis of Clinical Trials in TBI variables and extracranial injury. We assessed whether the effect of intubation varied by injury severity by testing the added value of an interaction term with likelihood ratio tests. RESULTS: In the prehospital analysis, 890/3736 (24%) patients had their tracheas intubated at scene. In the in-hospital analysis, 460/2930 (16%) patients had their tracheas intubated in the emergency department. There was no adjusted overall effect on functional outcome of prehospital intubation (odds ratio=1.01; 95% confidence interval, 0.79-1.28; P=0.96), and the adjusted overall effect of in-hospital intubation was not significant (odds ratio=0.86; 95% confidence interval, 0.65-1.13; P=0.28). However, prehospital intubation was associated with better functional outcome in patients with higher thorax and abdominal Abbreviated Injury Scale scores (P=0.009 and P=0.02, respectively), whereas in-hospital intubation was associated with better outcome in patients with lower Glasgow Coma Scale scores (P=0.01): in-hospital intubation was associated with better functional outcome in patients with Glasgow Coma Scale scores of 10 or lower. CONCLUSION: The benefits and harms of tracheal intubation should be carefully evaluated in patients with TBI to optimise benefit. This study suggests that extracranial injury should influence the decision in the prehospital setting, and level of consciousness in the in-hospital setting. CLINICAL TRIAL REGISTRATION: NCT02210221.

The volume-outcome relationship among severely injured patients admitted to English major trauma centres: a registry study.

BACKGROUND: Many countries have centralized and dedicated trauma centres with high volumes of trauma patients. However, the volume-outcome relationship in severely injured patients (Injury Severity Score (ISS) > 15) remains unclear. The aim of this study was to determine the association between hospital volume and outcomes in Major Trauma Centres (MTCs). METHODS: A retrospective observational cohort study was conducted using the Trauma Audit and Research Network (TARN) consisting of all English Major Trauma Centres (MTCs). Severely injured patients (ISS > 15) admitted to a MTC between 2013 and 2016 were included. The effect of hospital volume on outcome was analysed with random effects logistic regression models with a random intercept for centre and was tested for nonlinearity. Primary outcome was in-hospital mortality. RESULTS: A total of 47,157 severely injured patients from 28 MTCs were included in this study. Hospital volume varied from 69 to 781 severely injured patients per year. There were small between-centre differences in mortality after adjusting for important demographic and injury severity characteristics (adjusted 95% odds ratio range: 0.99-1.01). Hospital volume was found to be linear and not associated with in-hospital mortality (adjusted odds ratio (aOR) 1.02 per 10 patients, 95% confidence interval (CI) 0.68-1.54, p = 0.92). CONCLUSIONS: Despite the large variation in volume of the included MTCs, no relationship between hospital volume and outcome of severely injured patients was found. These results suggest that centres with similar structure and processes of care can achieve comparable outcomes in severely injured patients despite the number of severely injured patients they treat.

Recovery of health-related quality of life after burn injuries: An individual participant data meta-analysis.

BACKGROUND: A prominent outcome measure within burn care is health related quality of life (HRQL). Until now, no model for long-term recovery of HRQL exists for adult burn patients which requires large samples with repeated measurements. Re-use and the combination of existing data is a way to achieve larger data samples that enable the estimation of long-term recovery models. The aim of this secondary data analysis was to assess the recovery of HRQL after a burn injury over time. METHODS AND FINDINGS: Data from ten European studies on generic HRQL assessed in adult burn patients (either with the EQ-5D or SF-36) from five different countries were merged into one dataset. SF-36 outcomes were transformed into EQ-5D outcomes. A 24-month recovery of HRQL (EQ-5D utility) was modeled using a linear mixed-effects model and adjusted for important patient and burn characteristics. Subgroups of patients with mild and intermediate burns (≤20% total body surface area (TBSA) burned) and with major burns (>20% TBSA burned) were compared. The combined database included 1687 patients with a mean age of 43 (SD 15) years and a median %TBSA burned of 9% (IQR 4-18). There was large improvement in HRQL up to six months after burns, and HRQL remained relatively stable afterwards (studied up to 24 months post burn). However, the estimated EQ-5D utility scores remained below the norm scores of the general population. In this large sample, females, patients with a long hospital stay and patients with major burns had a delayed and worse recovery. The proportion of patients that reported problems for the EQ-5D dimensions ranged from 100% (pain/discomfort at baseline in patients with major burns) to 10% (self-care ≥3 months after injury in patients with mild and intermediate burns). After 24 months, both subgroups of burn patients did not reach the level of the general population in the dimensions pain/discomfort and anxiety/depression, and patients with major burns in the dimension usual activities. A main limitation of the study includes that the variables in the model were limited to age, gender, %TBSA, LOS and time since burn as these were the only variables available in all datasets. CONCLUSIONS: The 24-month recovery model can be used in clinical practice to inform patients on expected HRQL outcomes and provide clinicians insights into the expected recovery of HRQL. In this way, a delayed recovery can be recognized in an early stage and timely interventions can be started in order to improve patient outcomes. However, external validation of the developed model is needed before implementation into clinical practice. Furthermore, our study showed the benefit of secondary data usage within the field of burns.

Toward a New Multi-Dimensional Classification of Traumatic Brain Injury: A Collaborative European NeuroTrauma Effectiveness Research for Traumatic Brain Injury Study.

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.

Post-Concussion Symptoms in Complicated vs. Uncomplicated Mild Traumatic Brain Injury Patients at Three and Six Months Post-Injury: Results from the CENTER-TBI Study.

The aim of this study was to assess the occurrence of post-concussion symptoms and post-concussion syndrome (PCS) in a large cohort of patients after complicated and uncomplicated mild traumatic brain injury (mTBI) at three and six months post-injury. Patients were included through the prospective cohort study: Collaborative European NeuroTrauma Effectiveness Research (CENTER-TBI). Patients enrolled with mTBI (Glasgow Coma Scale 13-15) were further differentiated into complicated and uncomplicated mTBI based on the presence or absence of computed tomography abnormalities, respectively. The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) assessed post-concussion symptoms and PCS according to the mapped ICD-10 classification method. The occurrence of post-concussion symptoms and syndrome at both time points was calculated. Chi square tests were used to test for differences between and within groups. Logistic regression was performed to analyse the association between complicated versus uncomplicated mTBI and the prevalence of PCS. Patients after complicated mTBI reported slightly more post-concussion symptoms compared to those after uncomplicated mTBI. A higher percentage of patients after complicated mTBI were classified as having PCS at three (complicated: 46% vs. uncomplicated: 35%) and six months (complicated: 43% vs. uncomplicated 34%). After adjusting for baseline covariates, the effect of complicated versus uncomplicated mTBI at three months appeared minimal: odds ratio 1.25 (95% confidence interval: 0.95-1.66). Although patients after complicated mTBI report slightly more post-concussion symptoms and show higher PCS rates compared to those after uncomplicated mTBI at three and six months, complicated mTBI was only found a weak indicator for these problems.

Case-mix, care pathways, and outcomes in patients with traumatic brain injury in CENTER-TBI: a European prospective, multicentre, longitudinal, cohort study.

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]). INTERPRETATION: Patients with TBI who presented to European centres in the core study were older than were those in previous observational studies and often had comorbidities. Overall, most patients presented with mild TBI. The incomplete recovery of many patients should motivate precision medicine research and the identification of best practices to improve these outcomes. FUNDING: European Union 7th Framework Programme, the Hannelore Kohl Stiftung, OneMind, and Integra LifeSciences Corporation.

The volume-outcome relationship for hip fractures: a systematic review and meta-analysis of 2,023,469 patients.

Background and purpose - It has been hypothesized that hospitals and surgeons with high caseloads of hip fracture patients have better outcomes, but empirical studies have reported contradictory results. This systematic review and meta-analysis evaluates the volume-outcome relationship among patients with hip fracture patients. Methods - A search of different databases was performed up to February 2018. Selection of relevant studies, data extraction, and critical appraisal of the methodological quality was performed by 2 independent reviewers. A random-effects meta-analysis using studies with comparative cut-offs was performed to estimate the effect of hospital and surgeon volume on outcome, defined as in-hospital mortality and postoperative complications. Results - 24 studies comprising 2,023,469 patients were included. Overall, the quality was reasonable. 11 studies reported better health outcomes in high-volume centers and 2 studies reported better health outcomes in low-volume centers. In the meta-analysis of 11 studies there was a statistically non-significant association between higher hospital volume and both lower in-hospital mortality (adjusted odds ratio (aOR) 0.87, 95% confidence interval (CI) 0.73-1.04) and fewer postoperative complications (aOR 0.87, CI 0.75-1.02). Four studies on surgeon volume were included in the meta-analysis and showed a minor association between higher surgeon volume and in-hospital mortality (aOR 0.92, CI 0.76-1.12). Interpretation - This systematic review and meta-analysis did not find an evident effect of hospital or surgeon volume on health outcomes. Future research without volume cut-offs is needed to examine whether a true volume-outcome relationship exists.

Improvement of the performance of survival prediction in the ageing blunt trauma population: A cohort study.

INTRODUCTION: The overestimation of survival predictions in the ageing trauma population results in negative benchmark numbers in hospitals that mainly treat elderly patients. The aim of this study was to develop and validate a modified Trauma and Injury Severity Score (TRISS) for accurate survival prediction in the ageing blunt trauma population. METHODS: This retrospective study was conducted with data from two Dutch Trauma regions. Missing values were imputed. New prediction models were created in the development set, including age (continuous or categorical) and Anesthesiologists Physical Status (ASA). The models were externally validated. Subsets were created based on age (≥75 years) and the presence of hip fracture. Model performance was assessed by proportion explained variance (Nagelkerke R2), discrimination (Area Under the curve of the Receiver Operating Characteristic, AUROC) and visually with calibration plots. A final model was created based on both datasets. RESULTS: No differences were found between the baseline characteristics of the development dataset (n = 15,530) and the validation set (n = 15,504). The inclusion of ASA in the prediction models showed significant improved discriminative abilities in the two subsets (e.g. AUROC of 0.52 [95% CI: 0.46, 0.58] vs. 0.74 [95% CI: 0.69, 0.78] for elderly patients with hip fracture) and an increase in the proportion explained variance (R2 = 0.32 to R2 = 0.35 in the total cohort). The final model showed high agreement between observed and predicted survival in the calibration plot, also in the subsets. CONCLUSIONS: Including ASA and age (continuous) in survival prediction is a simple adjustment of the TRISS methodology to improve survival predictions in the ageing blunt trauma population. A new model is presented, through which even patients with isolated hip fractures could be included in the evaluation of trauma care.