Project description:BACKGROUND:The Injury Severity Score (ISS) is the most commonly used injury scoring system in trauma research and benchmarking. An ISS greater than 15 conventionally defines severe injury; however, no studies evaluate whether ISS performs similarly between adults and children. Our objective was to evaluate ISS and Abbreviated Injury Scale (AIS) to predict mortality and define optimal thresholds of severe injury in pediatric trauma. METHODS:Patients from the Pennsylvania trauma registry 2000-2013 were included. Children were defined as younger than 16 years. Logistic regression predicted mortality from ISS for children and adults. The optimal ISS cutoff for mortality that maximized diagnostic characteristics was determined in children. Regression also evaluated the association between mortality and maximum AIS in each body region, controlling for age, mechanism, and nonaccidental trauma. Analysis was performed in single and multisystem injuries. Sensitivity analyses with alternative outcomes were performed. RESULTS:Included were 352,127 adults and 50,579 children. Children had similar predicted mortality at ISS of 25 as adults at ISS of 15 (5%). The optimal ISS cutoff in children was ISS greater than 25 and had a positive predictive value of 19% and negative predictive value of 99% compared to a positive predictive value of 7% and negative predictive value of 99% for ISS greater than 15 to predict mortality. In single-system-injured children, mortality was associated with head (odds ratio, 4.80; 95% confidence interval, 2.61-8.84; p < 0.01) and chest AIS (odds ratio, 3.55; 95% confidence interval, 1.81-6.97; p < 0.01), but not abdomen, face, neck, spine, or extremity AIS (p > 0.05). For multisystem injury, all body region AIS scores were associated with mortality except extremities. Sensitivity analysis demonstrated ISS greater than 23 to predict need for full trauma activation, and ISS greater than 26 to predict impaired functional independence were optimal thresholds. CONCLUSION:An ISS greater than 25 may be a more appropriate definition of severe injury in children. Pattern of injury is important, as only head and chest injury drive mortality in single-system-injured children. These findings should be considered in benchmarking and performance improvement efforts. LEVEL OF EVIDENCE:Epidemiologic study, level III.
Project description:BackgroundChildren suffering nonaccidental trauma (NAT) are at high risk of death. It is unclear whether markers of injury severity for trauma center/system benchmarking such as Injury Severity Score (ISS) adequately characterize this. Our objective was to evaluate mortality prediction of ISS in children with NAT compared with accidental trauma (AT).MethodsPediatric patients younger than 16 years from the Pennsylvania state trauma registry 2000 to 2013 were included. Logistic regression predicted mortality from ISS for NAT and AT patients. Multilevel logistic regression determined the association between mortality and ISS while adjusting for age, vital signs, and injury pattern in NAT and AT patients. Similar models were performed for head Abbreviated Injury Scale (AIS). Sensitivity analysis examined impaired functional independence at discharge as an alternate outcome.ResultsFifty thousand five hundred seventy-nine patients were included with 1,866 (3.7%) NAT patients. Nonaccidental trauma patients had a similar rate of mortality at an ISS of 13 as an ISS of 25 for AT patients. Nonaccidental trauma patients also have higher mortality for a given head AIS level (range, 1.2-fold to 5.9-fold higher). Injury Severity Score was a significantly greater predictor of mortality in AT patients (adjusted odds rations [AOR], 1.14; 95% confidence interval [CI], 1.13-1.15; p < 0.01) than NAT patients (AOR, 1.09; 95% CI, 1.07-1.12; p < 0.01) per 1-point ISS increase, while head injury was a significantly greater predictor of mortality in NAT patients (AOR, 3.48; 95% CI, 1.54-8.32; p < 0.01) than AT patients (AOR, 1.21; 95% CI, 0.95-1.45; p = 0.12). Nonaccidental trauma patients had a higher rate of impaired functional independence at any given ISS or head AIS level than AT patients.ConclusionNonaccidental trauma patients have higher mortality and impaired function at a given ISS/head AIS than AT patients. Conventional ISS thresholds may underestimate risk and head injury is a more important predictor of mortality in the NAT population. These findings should be considered in system performance improvement and benchmarking efforts that rely on ISS for injury characterization.Level of evidenceEpidemiologic study, level III.
Project description:PurposeTo evaluate the predictive value of the Controlling Nutritional Status (CONUT) score and Injury Severity Score (ISS) in assessing physiological abnormalities and outcomes in trauma patients.MethodsA retrospective analysis was conducted on 354 trauma patients. Physiological parameters were assessed, including cardiovascular function, inflammatory response, liver and kidney function, and nutritional status. The CONUT score and ISS were calculated for each patient. Binary logistic regression was used to identify independent predictors of trauma severity. Receiver operating characteristic (ROC) curve analysis evaluated the predictive accuracy of the CONUT and ISS scores for adverse outcomes.ResultsSeverely injured patients exhibited more significant abnormalities in cardiovascular function, inflammatory response, liver and kidney function, and nutritional status compared to those with minor injuries. These patients had significantly higher CONUT scores. Logistic regression analysis identified white blood cell count, hemoglobin, and CONUT score as independent predictors of trauma severity. ROC analysis showed that both CONUT and ISS scores effectively predicted adverse outcomes, with ISS demonstrating better specificity.ConclusionThe CONUT and ISS scores are effective tools for predicting physiological abnormalities and adverse outcomes in trauma patients. Incorporating these scores into clinical practice may enhance prognostic assessments and improve management strategies for trauma patients.
Project description:Trauma patients with an ISS=75 have been deliberately excluded from some trauma studies because they were assumed to have "unsurvivable injuries." This study aimed to assess the true mortality among patients with an ISS=75, and to examine the characteristics and primary diagnoses of these patients. Retrospective review of the 2006-2010 U.S. Nationwide Emergency Department Sample (NEDS) generated 2,815 patients with an ISS=75 for analysis, representing an estimated 13,569 patients in the country. Dispositions from the emergency department and hospital for these patients were tabulated by trauma center level. Survivors and non-survivors were compared using Pearson's chi-square test. Primary diagnosis codes of these patients were tabulated by mortality status. Overall, about 48.6% of patients with an ISS=75 were discharged alive, 25.8% died and 25.6% had unknown mortality status. The mortality risks of these patients did not vary significantly across different levels of trauma centers (15.6% vs. 13.0%, P = 0.16). Non-survivors were more likely than survivors to: be male (81.2% vs. 74.4%, P < 0.0001), be over 65 years (20.3% vs. 10.2%, P < 0.0001), be uninsured (33.8% vs. 19.1%), have at least one chronic condition (58.0% vs. 43.7%, P <0.0001), sustain life-threatening injuries (79.2% vs. 49.4%, P<0.0001), sustain penetrating injuries (42.0% vs. 25.9%, P<0.0001), and have injuries caused by motor vehicle crashes (32.9% vs. 21.1%, P<0.0001) or firearms (21.9% vs. 4.4%, P<0.0001). The most frequent diagnosis code was 862.8 (injury to multiple and unspecified intrathoracic organs, without mention of open wound into cavity). Our results revealed that at least half of patients with an ISS=75 survived, demonstrating that the rationale for excluding patients with an ISS=75 from analysis is not always justified. To avoid bias and inaccurate results, trauma researchers should examine the mortality status of patients with an ISS=75 before exclusion, and explicitly describe their method of generating ISS scores.
Project description:Physiological, anatomical, and clinical laboratory analytic scoring systems (APACHE, Injury Severity Score (ISS)) have been utilized, with limited success, to predict outcome following injury. We hypothesized that a peripheral blood leukocyte gene expression score could predict outcome, including multiple organ failure, following severe blunt trauma. Contributor: The Inflammation and the Host Response to Injury Large Scale Collaborative Research Program Keywords: expression profiles cRNA derived from whole blood leukocytes obtained within 12 hours of hospital admission provided gene expression data for the entire genome that were used to create a gene expression score for each patient. Expression profiles from healthy volunteers were averaged to create a reference gene expression profile which was used to compute a difference from reference (DFR) score for each patient. This score described the overall genomic response of patients within the first 12 hours following severe blunt trauma. Regression models were used to compare the association of the DFR, APACHE and ISS scores with outcome.
Project description:BACKGROUND: Contemporary understanding of the biomechanics, natural history, and methods of treating thoracolumbar spine injuries continues to evolve. Current classification schemes of these injuries, however, can be either too simplified or overly complex for clinical use. METHODS: The Spine Trauma Group was given a survey to identify similarities in treatment algorithms for common thoracolumbar injuries, as well as to identify characteristics of injury that played a key role in the decision-making process. RESULTS: Based on the survey, the Spine Trauma Group has developed a classification system and an injury severity score (thoracolumbar injury classification and severity score, or TLICS), which may facilitate communication between physicians and serve as a guideline for treating these injuries. The classification system is based on the morphology of the injury, integrity of the posterior ligamentous complex, and neurological status of the patient. Points are assigned for each category, and the final total points suggest a possible treatment option. CONCLUSIONS: The usefulness of this new system will have to be proven in future studies investigating inter- and intraobserver reliability, as well as long-term outcome studies for operative and nonoperative treatment methods.
Project description:Physiological, anatomical, and clinical laboratory analytic scoring systems (APACHE, Injury Severity Score (ISS)) have been utilized, with limited success, to predict outcome following injury. We hypothesized that a peripheral blood leukocyte gene expression score could predict outcome, including multiple organ failure, following severe blunt trauma. Contributor: The Inflammation and the Host Response to Injury Large Scale Collaborative Research Program Keywords: expression profiles
Project description:Reduced telomere length (TL) and structural brain abnormalities have been reported in patients with schizophrenia (SZ) and bipolar disorder (BD). Childhood traumatic events are more frequent in SZ and BD than in healthy individuals (HC), and based on recent findings in healthy individuals could represent one important factor for TL and brain aberrations in patients. The study comprised 1024 individuals (SZ [n = 373]; BD [n = 249] and HC [n = 402]). TL was measured by quantitative polymerase chain reaction (qPCR), and childhood trauma was assessed using the Childhood Trauma Questionnaire (CTQ). Diagnosis was obtained by the Structured Clinical Interview (SCID) for the diagnostic and statistical manual of mental disorders-IV (DSM-IV). FreeSurfer was used to obtain regional and global brain volumes from T1-weighted magnetic resonance imaging (MRI) brain scans. All analyses were adjusted for current age and sex. Patients had on average shorter TL (F = 7.87, p = 0.005, Cohen's d = 0.17) and reported more childhood trauma experiences than HC (χ2 = 148.9, p < 0.001). Patients with a history of childhood sexual, physical or emotional abuse had shorter TL relative to HC and to patients without a history of childhood abuse (F = 6.93, p = 0.006, Cohen's d = 0.16). After adjusting for childhood abuse, no difference in TL was observed between patients and HC (p = 0.12). There was no statistically significant difference in reported childhood abuse exposure or TL between SZ and BD. Our analyses revealed no significant associations between TL and clinical characteristics or brain morphometry. We demonstrate shorter TL in SZ and BD compared with HC and showed that TL is sensitive to childhood trauma experiences. Further studies are needed to identify the biological mechanisms of this relationship.
Project description:BackgroundPrecise models are necessary to estimate mortality risk following traumatic injury to inform clinical decision making or quantify hospital performance. The Trauma and Injury Severity Score (TRISS) has been the historical gold standard in survival prediction but its limitations are well-characterized. The present study used International Classification of Diseases 10th Revision (ICD-10) injury codes with machine learning approaches to develop models whose performance was compared to that of TRISS.MethodsThe 2015-2017 National Trauma Data Bank was used to identify patients following trauma-related admission. Injury codes from ICD-10 were grouped by clinical relevance into 1,495 variables. The TRISS score, which comprises the Injury Severity Score, age, mechanism (blunt vs penetrating) as well as highest 24-hour values for systolic blood pressure (SBP), respiratory rate (RR) and Glasgow Coma Scale (GCS) was calculated for each patient. A base eXtreme gradient boosting model (XGBoost), a machine learning technique, was developed using injury variables as well as age, SBP, RR, mechanism and GCS. Prediction of in-hospital survival and other in-hospital complications were compared between both models using receiver operating characteristic (ROC) and reliability plots. A complete XGBoost model, containing injury variables, vitals, demographic information and comorbidities, was additionally developed.ResultsOf 1,380,740 patients, 1,338,417 (96.9%) survived to discharge. Compared to survivors, those who died were older and had a greater prevalence of penetrating injuries (18.0% vs 9.44%). The base XGBoost model demonstrated a greater receiver-operating characteristic (ROC) than TRISS (0.950 vs 0.907) which persisted across sub-populations and secondary endpoints. Furthermore, it exhibited high calibration across all risk levels (R2 = 0.998 vs 0.816). The complete XGBoost model had an exceptional ROC of 0.960.ConclusionsWe report improved performance of machine learning models over TRISS. Our model may improve stratification of injury severity in clinical and quality improvement settings.
Project description:BACKGROUND:Fibrinogen concentrate (FC) is frequently used to treat bleeding trauma patients, although the clinical effects are not well known. In this study we describe demographic and clinical outcome data in a cohort of trauma patients receiving FC, compared to a matched control group, who did not receive FC. METHODS:This retrospective, single-center, observational study included adult trauma patients admitted to a level 1-trauma center in Sweden between January 2013 and June 2015. The study population consisted of patients to whom FC was administrated within 24 h (n = 138, "Fib+"). Patients with Injury Severity Score (ISS) > 49 and/or deceased within 1 h from arrival were excluded (n = 30). Controls (n = 108) were matched for age, gender and ISS ("Fib-"). Primary outcome was mortality (24 h-/30 days-/1 year-), and secondary outcomes were blood transfusions, thromboembolic events and organ failure. RESULTS:The Fib+ group, despite having similar ISS as Fib-, had higher prevalence of penetrating trauma and lower Glasgow Coma Scale (GCS), indicating more severe injuries. Patients receiving FC had a higher mortality after 24 h/ 30 days/ 1 year compared to controls (Fib-). However, in a propensity score matched model, the differences in mortality between Fib+ and Fib- were no longer significant. Blood transfusions were more common in the Fib+ group, but no difference was observed in thromboembolic events or organ failure. In both groups, low as well as high P-fibrinogen levels at arrival were associated with increased mortality, with the lowest mortality observed at P-fibrinogen values of 2-3 g/l. CONCLUSIONS:Despite equal ISS, patients receiving FC had a higher mortality compared to the control group, presumably associated to the fact that these patients were bleeding and physiologically deranged on arrival. When applying a propensity score matching approach, the difference in mortality between the groups was no longer significant. No differences were observed between the groups regarding thromboembolic events or organ failure, despite higher transfusion volumes in patients receiving FC.