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 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.

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.

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.

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.

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.

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.

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.

The volume-outcome relationship in severely injured patients: A systematic review and meta-analysis.

BACKGROUND: The volume-outcome relationship in severely injured patients remains under debate and this has consequences for the designation of trauma centers. OBJECTIVES: The aim of this study was to evaluate the relationship between hospital or surgeon volume and health outcomes in severely injured patients. METHODS: Six electronic databases were searched from 1980 up to January 30, 2018, to identify studies that describe the relationship between hospital or surgeon volume and health outcomes in severely injured patients (preferably Injury Severity Score above 15). Selection of relevant studies, data extraction, and critical appraisal of the methodological quality were performed by two independent reviewers. Pooled adjusted and unadjusted estimates of the effect of volume on in-hospital mortality, only in study populations with Injury Severity Score greater than 15, were calculated with a random-effects meta-analysis. A mixed effects linear regression model was used to assess hospital volume as continuous parameter. RESULTS: Eighteen observational cohort studies were included. The majority (13 [72%] of 18) reported an association between higher hospital or surgeon volume and lower mortality rate. Overall, the quality of the included studies was reasonable, with insufficient adjustment as one of the most common limitations. Eight studies were included in the meta-analysis with a total of 222,418 patients. High hospital volume (>240 admitted severely injured patients per year) was associated with a lower risk of mortality (adjusted odds ratio, 0.85; 95% confidence interval, 0.76-0.94). Four studies were included in the regression model, providing a beta of -0.17 per 10 patients (95% CI, -0.27 to -0.07). There was no clear association between surgeon volume and mortality rates based on three available studies. CONCLUSION: Our systematic overview of the literature reveals a modest association between high-volume centers and lower mortality in severely injured patients, suggesting that designation of high-volume centers might improve outcomes among severely injured patients. LEVEL OF EVIDENCE: Systematic review and meta-analysis, level III. Systematic review registration number: PROSPERO registration ID CRD42017056729.

Letter to the Editor regarding the article: "identifying pre-hospital factors associated with outcome for major trauma patients in a regional trauma network: an exploratory study".

The aim of this Letter to the Editor was to report some methodological shortcomings in a recently published article. Issues regarding missing values and overfitting are mentioned. First, Complete Case (CC) analysis was used instead of an imputation method. Second, there was a high chance of overfitting and lack of model validation. In conclusion, the results of this study should be interpret with caution and further research is necessary.