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1.
《Injury》2016,47(11):2459-2464
IntroductionIn the Lower-Middle Income Country setting, we validate trauma severity scoring systems, namely Injury Severity Score (ISS), New Injury Severity Scale (NISS) score, the Kampala Trauma Score (KTS), Revised Trauma Score (RTS) score and the TRauma Injury Severity Score (TRISS) using Indian trauma patients.Patients and methodsFrom 1 September 2013 to 28 February 2015, we conducted a prospective multi-centre observational cohort study of trauma patients in four Indian university hospitals, in three megacities, Kolkata, Mumbai and Delhi. All adult patients presenting to the casualty department with a history of injury and who were admitted to inpatient care were included. The primary outcome was in-hospital mortality within 30-days of admission. The sensitivity and specificity of each score to predict inpatient mortality within 30 days was assessed by the areas under the receiver operating characteristic curve (AUC). Model fit for the performance of individual scoring systems was accomplished by using the Akaike Information criterion (AIC).ResultsIn a registry of 8791 adult trauma patients, we had a cohort of 7197 patients eligible for the study. 4091 (56.8%)patients had all five scores available and was the sample for a complete case analysis. Over a 30-day period, the scores (AUC) was TRISS (0.82), RTS (0.81), KTS (0.74), NISS (0.65) and ISS (0.62). RTS was the most parsimonious model with the lowest AIC score. Considering overall mortality, both physiologic scores (RTS, KTS) had better discrimination and goodness-of-fit than ISS or NISS. The ability of all Injury scores to predict early mortality (24 h) was better than late mortality (30 day).ConclusionOn-admission physiological scores outperformed the more expensive anatomy-based ISS and NISS. The retrospective nature of ISS and TRISS score calculations and incomplete imaging in LMICs precludes its use in the casualty department of LMICs. They will remain useful for outcome comparison across trauma centres. Physiological scores like the RTS and KTS will be the practical score to use in casualty departments in the urban Indian setting, to predict early trauma mortality and improve triage.  相似文献   

2.
Abstract Background: The public health significance of injuries that occur in developing countries is now recognized. In 1996, as part of the injury surveillance registry in Kampala, Uganda, a new score, the Kampala Trauma Score (KTS) was instituted. The KTS, developed in light of the limited resource base of sub-Saharan Africa, is a simplified composite of the Revised Trauma Score (RTS) and the Injury Severity Score (ISS) and closely resembles the Trauma Score and Injury Severity Score (TRISS). Patients and Methods: The KTS was applied retrospectively to a cohort of prospectively accrued urban trauma patients with the RTS, ISS and TRISS calculated. Using ROC (receiver operating characteristics) analysis, logistic regression models and sensitivity and specificity cutoff analysis, the KTS was compared to these three scores. Results: Using logistic regression models and areas under the ROC curve, the RTS proved a more robust predictor of death at 2 weeks in comparison to the KTS. However, differences in screening performance were marginal (areas under the ROC curves were 87% for the RTS and 84% for the KTS) with statistical significance only reached for an improved specificity (67% vs. 47%; p < 0.001), at a fixed sensitivity of 90%. In addition, the KTS predicted hospitalization at 2 weeks more accurately. Conclusion: The KTS statistically performs comparably to the RTS and ISS alone as well as to the TRISS but has the added advantage of utility. Therefore, the KTS has potential as a triage tool in resource-poor and similar health care settings.  相似文献   

3.
《Injury》2023,54(1):93-99
BackgroundGlasgow Coma Scale (GCS) is one of the most commonly used trauma scores and is a good predictor of outcome in traumatic brain injury (TBI) patients. There are other more complex scores with additional physiological parameters. Whether they discriminate better than GCS in predicting mortality in TBI patients is debatable. The aim of this study was to compare the discrimination of GCS with that of MGAP, GAP, RTS and KTS for 24-hour and 30-day in-hospital mortality in adult TBI patients, in a resource limited LMIC setting.MethodWe analysed data from the multicentre, observational trauma cohort Towards Improved Trauma Care Outcome (TITCO) in India. We included all patients 18 years or older, admitted from the emergency department with TBI. The Area Under the Receiver Operating Characteristic (AUROC) curve was used to quantify and compare the discrimination of all scores: GCS; Revised Trauma Score (RTS); mechanism, GCS, age, systolic blood pressure (MGAP); GCS, age, systolic blood pressure (GAP) and Kampala Trauma Score (KTS) in the prediction of 24-hour and 30-day in-hospital mortality.ResultsA total of 3306 TBI patients were included in this study. The majority were within the GCS range 3-8. The commonest mechanism of injury was road traffic injuries [1907(58.0%)]. In-hospital mortality was 27.2% (899). There was no significant difference in discrimination in 24-hour in-hospital mortality when comparing GCS with MGAP and GAP. While GCS performed better than KTS, RTS performed better than GCS. For 30-day in-hospital mortality, GCS discriminated significantly better compared with KTS, but there was no significant difference when compared to MGAP and RTS. GAP discriminated significantly better when compared with GCS.ConclusionThis study shows that the discrimination of GCS is comparable to that of more complex trauma scores in predicting 24-hour and 30-day in-hospital mortality in adult TBI patients in a resource limited LMIC setting.  相似文献   

4.
《Injury》2017,48(9):1870-1877
BackgroundTrauma systems currently rely on imperfect and subjective tools to prioritize responses and resources, thus there is a critical need to develop a more accurate trauma severity score. Our objective was to modify the Rapid Emergency Medicine (REMS) Score for the trauma population and test its accuracy as a predictor of in-hospital mortality when compared to other currently used scores, including the Revised Trauma Score (RTS), the Injury Severity Score (ISS), the “Mechanism, Glasgow Coma Scale, Age and Arterial Pressure” (MGAP) score, and the Shock Index (SI) score.MethodsThe two-part study design involved both a modification step and a validation step. The first step incorporated a retrospective analysis of a local trauma database (3680 patients) where three components of REMS were modified to more accurately represent the trauma population. Using clinical judgment and goodness-of-fit tests, systolic blood pressure was substituted for mean arterial pressure, the weighting of age was reduced, and the weighting of Glasgow Coma Scale was increased. The second part comprised validating the new modified REMS (mREMS) score retrospectively on a U.S. National Trauma Databank (NTDB) that included 429,711 patients admitted with trauma in 2012. The discriminate power of mREMS was compared to other trauma scores using the area under the receiver operating characteristic (AUC) curve.ResultsOverall the mREMS score with an AUC of 0.967 (95% CI: 0.963–0.971) was demonstrated to be higher than RTS (AUC 0.959 [95% CI: 0.955–0.964]), ISS (AUC 0.780 [95% CI 0.770–0.791]), MGAP (AUC 0.964 [95% CI: 0.959–0.968]), and SI (AUC 0.670 [95% CI: 0.650–0.690]) in predicting in-hospital mortality on the NTDB.ConclusionIn the trauma population, mREMS is an accurate predictor of in-hospital mortality, outperforming other used scores. Simple and objective, mREMS may hold value in the pre-hospital and emergency department setting in order to guide trauma team responses.  相似文献   

5.
《Injury》2016,47(1):14-18
PurposeComputing trauma scores in the field allows immediate severity assessment for appropriate triage. Two pre-hospital scores can be useful in this context: the Triage-Revised Trauma Score (T-RTS) and the Mechanism, Glasgow, Age and arterial Pressure (MGAP) score. The Trauma Revised Injury Severity Score (TRISS), not applicable in the pre-hospital setting, is the reference score to predict in-hospital mortality after severe trauma. The aim of this study was to compare T-RTS, MGAP and TRISS in a cohort of consecutive patients admitted in the Trauma system of the Northern French Alps(TRENAU).Materials and methodsFrom 2009 to 2011, 3260 patients with suspected severe trauma according to the Vittel criteria were included in the TRENAU registry. All data necessary to compute T-RTS, MGAP and TRISS were collected in patients admitted to one level-I, two level-II and ten level-III trauma centers. The primary endpoint was death from any cause during hospital stay. Discriminative power of each score to predict mortality was measured using receiver operating curve (ROC) analysis. To test the relevancy of each score for triage, we also tested their sensitivity at usual cut-offs. We expected a sensitivity higher than 95% to limit undertriage.ResultsThe TRISS score showed the highest area under the ROC curve (0.95 [CI 95% 0.94–0.97], p < 0.01). Pre-hospital MGAP score had significantly higher AUC compared to T-RTS (0.93 [CI 95% 0.91–0.95] vs 0.86 [CI 95% 0.83–0.89], respectively, p < 0.01). MGAP score < 23 had a sensitivity of 88% to detect mortality. Sensitivities of T-RTS < 12 and TRISS < 0.91 were 79% and 87%, respectively.Discussion/conclusionPre-hospital calculation of the MGAP score appeared superior to T-RTS score in predicting intra-hospital mortality in a cohort of trauma patients. Although TRISS had the highest AUC, this score can only be available after hospital admission. These findings suggest that the MGAP score could be of interest in the pre-hospital setting to assess patients’ severity. However, its lack of sensitivity indicates that MGAP should not replace the decision scheme to direct the most severe patients to level-I trauma center.  相似文献   

6.
《Injury》2022,53(9):3059-3064
Trauma scoring systems were created to predict mortality and enhance triage capabilities. However, efficacy of scoring systems to predict mortality and accuracy of originally reported severity thresholds remains uncertain. A single-center, retrospective study was conducted at University of Virginia (UVA), an American College of Surgeons verified Level I trauma center. We compared four scoring systems: MGAP (Mechanism, Glasgow Coma Scale, Age, and arterial pressure), Injury Severity Score (ISS), New Injury Severity Score (NISS), and Trauma Related Injury Severity Score (TRISS) to predict in-hospital mortality and disposition from the emergency department to higher acuity level of care including mortality (i.e. operating room, intensive care unit, morgue) versus standard floor admission using area under the curve (AUC) for receiver operating characteristic analysis. Second, we examined sensitivity of these scores at standard thresholds to determine if adjustments were needed to minimize under-triage (sensitivity ≥95%). TRISS was the best predictor of mortality in a cohort of n = 16,265 with AUC of 0.920 (95% CI: 0.911–0.929, p<0.0001), followed by MGAP with AUC of 0.900 (95% CI: 0.889–0.911, p<0.0001), and finally ISS and NISS (0.830 (95% CI: 0.814–0.847) and 0.827 (95% CI: 0.809–0.844) respectively). NISS was the best predictor of high acuity disposition with an AUC of 0.729 (95% CI: 0.721–0.736, p<0.0001), followed by ISS with AUC of 0.714 (95% CI: 0.707–0.722, p<0.0001), and finally TRISS and MGAP (0.673 (95% CI: 0.665–0.682) and 0.613 (95% CI: 0.604–0.621) respectively (p<0.0001). At historic thresholds, no scoring system displayed adequate sensitivity to predict mortality, with values ranging from 73% for ISS to 80% for NISS. In conclusion, in the reported study cohort, TRISS was the best predictor of mortality while NISS was the best predictor of high acuity disposition. We also stress updating scoring system thresholds to achieve ideal sensitivity, and investigating how scoring systems derived to predict mortality perform when predicting indicators of morbidity such as disposition from the emergency department.  相似文献   

7.
Kilgo PD  Meredith JW  Osler TM 《The Journal of trauma》2006,60(5):1002-8; discussion 1008-9
BACKGROUND: The Trauma and Injury Severity Score (TRISS), used to garner predictions of survival from the Injury Severity Score (ISS), the Revised Trauma Score (RTS, for physiologic reserve), and age is difficult for many trauma facilities to compute because it requires 8 to 10 variables and ISS depends on the specialized Abbreviated Injury Scale (AIS) scale rather than the International Classification of Diseases scale (ICD-9). It has been shown that metrics describing a patient's worst injury (WORSTSRR) are a powerful predictor of survival (regardless of coding type, AIS versus ICD-9) and that the Glasgow Coma Scale (GCS) motor component contains the majority of the information found in the full GCS score. This study hypothesized that the TRISS approach could be made more predictive and efficient with fewer variables by incorporating these advances. METHODS: A total of 310,958 patients with nonmissing TRISS variables were subset from the National Trauma Data Bank (NTDB). Logistic regression was used to model mortality as a function of anatomic, physiologic and age variables. A traditional TRISS model was computed (with NTDB-derived coefficients) that uses ISS, RTS, age index, and mechanism to predict survival. Four smaller three- or four-variable models employed the ICD-9 WORSTSRR, the GCS motor component, and age (both continuously and dichotomously). Two of the four models also use mechanism. These models were compared using the concordance index (c-index, a measure of model discrimination) and the pseudo-R statistic (estimates proportion of variance explained). RESULTS: Each experimental model (two models with 3 variables and two models with 4 variables) have superior discrimination and explain more variance than the traditional TRISS model that employs 8-10 variables. CONCLUSIONS: Recent advances in anatomic and physiologic scoring markedly simplify TRISS-type models at no cost to prediction. This approach uses routinely available data, requires up to seven fewer terms, and predicts at least as well as the original TRISS. These findings could increase the availability of accurate trauma scoring tools to smaller trauma facilities.  相似文献   

8.
PurposeAmongst the ASEAN countries, Malaysia has the highest road fatality risk (>15 fatalities per 100 000 population) with 50% of these fatalities involving motorcyclist. This contributes greatly to ward admissions and poses a significant burden to the general surgery services. From mild rib fractures to severe intra-abdominal exsanguinations, the spectrum of cases managed by surgeons resulting from motorcycle accidents is extensive. The objective of this study is to report the clinical characteristics and identify predictors of death in motorcycle traumatic injuries from a Malaysian trauma surgery centre.MethodsThis is a prospective cross-sectional study of all injured motorcyclists and pillion riders that were admitted to Hospital Sultanah Aminah and treated by the trauma surgery team from May 2011 to February 2015. Only injured motorcyclists and pillion riders were included in this study. Patient demography and predictors leading to mortality were identified. Significant predictors on univariate analysis were further analysed with multivariate analysis.ResultsWe included 1653 patients with a mean age of (35 ± 16.17) years that were treated for traumatic injuries due to motorcycle accidents. The mortality rate was 8.6% (142) with equal amount of motorcycle riders (788) and pillion riders (865) that were injured. Amongst the injured were male predominant (1 537) and majority of ethnic groups were the Malays (897) and Chinese (350). Severity of injury was reflected with a mean Revised Trauma Score (RTS) of 7.31 ± 1.29, New Injury Severity Score (NISS) of 19.84 ± 13.84 and Trauma and Injury Severity Score (TRISS) of 0.91 ± 0.15. Univariate and multivariate analysis revealed that age≥35, lower GCS, head injuries, chest injuries, liver injuries, and small bowel injuries were significant predictors of motorcycle trauma related deaths with p < 0.05. Higher trauma severity represented by NISS, RTS and TRISS scores was also significant for death with p < 0.05.ConclusionAge, lower GCS, presence of head, chest, liver, small bowel injuries and higher severity on NISS, RTS and TRISS scores are predictive of death in patients involved with motorcycle accidents. This information is important for prognostic mortality risk prevention and counselling.  相似文献   

9.
Validity of applying adult TRISS analysis to injured children   总被引:2,自引:0,他引:2  
Injury severity measures are becoming increasingly important for quality assurance and injury research. TRISS analysis, which uses the Revised Trauma Score (RTS) and Injury Severity Score (ISS) to predict survival, is an effective tool for comparing outcomes between trauma centers. It has been argued that blunt trauma outcome differs between children and adults, yet the Major Trauma Outcome Study (MTOS) adult data base (ages 15-54 years) regression weights have been used by others to calculate TRISS scores for injured children. This study appears to be the first to perform TRISS analysis on groups of children and adults treated by the same surgeons using the same treatment protocols to assess the validity of applying "adult" TRISS analysis to children. The charts of 346 consecutive children (ages 0-14) and 346 random adults (ages 15-54) admitted to a regional trauma center for isolated blunt trauma over a 30-month period were reviewed for demographics, mechanism of injury, RTS, ISS, and survival. Statistical evaluation included TRISS survival analysis and calculation of the Z statistic. The median ISS was 10 for both children and adults. The Z statistics for children and adults were similar (1.85 and 1.81). Analysis demonstrated the groups to be statistically identical with a nonsignificant trend toward improved survival compared with the MTOS baseline group. These data support the use of existing TRISS analysis for evaluation of pediatric trauma care.  相似文献   

10.
PurposeMajor liver trauma in polytraumatic patients accounts for significant morbidity and mortality. We aimed to assess prognostic factors for morbidity and mortality in patients with severe liver trauma undergoing perihepatic packing.MethodsProspectively collected records of 293 consecutive polytrauma patients with liver injury admitted at a level I trauma centre between 1996 and 2008 were reviewed. 39 patients with grade IV–V AAST liver injury and treated with peri-hepatic packing were identified and included for analysis. Univariate and multivariate analyses were performed to assess prognostic factors for morbidity and mortality.ResultsMean age of patients was 41 years. 34 patients were haemodynamically unstable at initial presentation. Ten of 39 patients were treated with angiographic embolization in addition to perihepatic packing. The overall mortality rate was 51.3%. Liver-related death occurred in 23.1%. Overall and liver-related morbidity rates were 90% and 28%, respectively. Glasgow Coma Scale (GCS), respiratory rate, packed red blood cells (PRBC) transfusion, pH and Base Excess (BE), Revised Trauma Score (RTS) and Trauma Injury Severity Score (TRISS), need for angiographic embolization as well as early OR and ICU admission were associated with significant decrease of early mortality.ConclusionsRevised Trauma Score, haemodynamic instability, blood pH and BE are important prognostic factors influencing morbidity and mortality in polytrauma patients with grade IV/V liver injury. Furthermore, fast and effective surgical damage control procedure with perihepatic packing, followed by early ICU admission is associated with lower complication rate and shorter ICU stays in this patient population.  相似文献   

11.
PURPOSE: The aim of this study was to identify significant independent predictors of inpatient mortality rates for pediatric victims of blunt trauma and to develop a formula for predicting the probability of inpatient mortality for these patients. METHODS: Emergency department and inpatient data from 2,923 pediatric victims of blunt injury in the New York State Trauma Registry in 1994 and 1995 were used to explore the relationship between patient risk factors and mortality rate. A stepwise logistic regression model with P<.05 was developed using survival status asthe dependent variable. Independent variables included are elements of the Pediatric Trauma Score (PTS), additional elements from the Revised Trauma Score (RTS), the motor response and eye opening components of the Glasgow Coma Scale (GCS), age-specific systolic blood pressure, the AVPU score, and 2 measures of anatomic injury severity (the Injury Severity Score [ISS] and the International Classification of Disease, Ninth Revision-based Injury Severity Score [ICISS]). RESULTS: The only significant independent predictors of severity that emerged were the ICISS, no motor response (best motor response = 1) from the GCS, and the unresponsive component from the AVPU score. The statistical model exhibited an excellent fit (C statistic = .964). The specificity associated with the prediction of inpatient mortality rate based on the presence of 1 or more of these risk factors was .926, and the sensitivity was .944. CONCLUSION: The best independent predictors of inpatient mortality rate for pediatric trauma patients with blunt injuries include variables not specifically contained in the PTS or the RTS: ICISS, no motor response (best motor response = 1) from the GCS, and the unresponsive component of the AVPU score.  相似文献   

12.
BACKGROUND: Prediction of survival chances for trauma patients is a basic requirement for evaluation of trauma care. The current methods are the Trauma and Injury Severity Score (TRISS) and A Severity Characterization of Trauma (ASCOT). Scales for scoring injury severity are part of these methods. This study compared three injury scales, the Injury Severity Score (ISS), the New ISS (NISS), and the Anatomic Profile (AP), in three otherwise identical predictive models. METHODS: Records of the Rotterdam Trauma Center were analyzed using logistic regression. The variables used in the models were age (as a linear variable), the corrected Revised Trauma Score (RTS), a denominator for blunt or penetrating trauma, and one of the three injury scales. The original TRISS and ASCOT models also were evaluated. The resulting models were compared in terms of their discriminative power, as indicated by the receiver-operator characteristic (ROC), and calibration (Hosmer-Lemeshow [HL]) for the entire range of injury severity. RESULTS: For this study, 1,102 patients, with an average ISS of 15, met the inclusion criteria. The TRISS and ASCOT models, using original coefficients, showed excellent discriminative power (ROC, 0.94 and 0.96, respectively), but insufficient fits (HL, p = 0.001 and p = 0.03, respectively). The three fitted models also had excellent discriminative abilities (ROC, 0.95, 0.97, and 0.96, respectively). The custom ISS model was unable to fit the entire range of survival chances sufficiently (p = 0.01). Models using the NISS and AP scales provided adequate fits to the actual survival chances of the population (HL, 0.32 and 0.12, respectively). CONCLUSIONS: The AP and NISS scores particularly both managed to outperform the ISS score in correctly predicting survival chances among a Dutch trauma population. Trauma registries stratifying injuries by the ISS score should evaluate the use of the NISS and AP scores.  相似文献   

13.
BACKGROUND: For the quantification of multiple injuries in children, a range of different trauma scores are available, the actual prognostic value of which has, however, not so far been investigated and compared in a group of patients. METHODS: In 261 polytraumatized children and adolescents, 11 trauma scores (Abbreviated Injury Scale [AIS], Injury Severity Score [ISS], Glasgow Coma Scale [GCS], Acute Trauma Index [ATI], Shock Index [SI], Trauma Score [TS], Revised Trauma Score [RTS], Modified Injury Severity Score [MISS], Trauma and Injury Severity Score [TRISS]-Scan, Hannover Polytrauma Score [HPTS], and Pediatric Trauma Score [PTS]) were calculated, and their prognostic relevance in terms of survival, duration of intensive care treatment, hospital stay, and long-term outcome analyzed. RESULTS: With a specificity of 80%, physiologic scores (TS, RTS, GCS, ATI) showed a greater accuracy (79-86% vs. 73-79%) with regard to survival prediction than did the anatomic scores (AIS, HPTS, ISS, PTS); combined forms of these two types of score (TRISS-Scan, MISS) did not provide any additional information (76-80%). Overall, the TRISS-Scan was the score that showed the highest correlation with duration of treatment and long-term outcome. Trauma scores specially conceived for use with children (PTS, MISS) failed to show any superiority vis-à-vis trauma scores in general. CONCLUSION: With regard to prognostic quality and ease of use in the practical setting, TS and the TRISS-Scan are recommended for polytrauma in children and adolescents. Special pediatric scores are not necessary.  相似文献   

14.
A simple reproducible and sensitive prognostic trauma tool is still needed. In this article we have introduced modified GCS motor response (MGMR) and evaluated the performance of logistic models based on this variable. The records of 8452 trauma patients admitted to major hospitals of Tehran from 1999 to 2000 were analysed. 7226 records with known outcome were included in our study. Logistic models based on outcome (death versus survival) as a dependent variable and Injury Severity Score (ISS), Revised Trauma Score (RTS), Glasgow Coma Scale (GCS), GCS motor component (GMR) and MGMR (following command [=2], movement but not following [=1] command and without movement [=0]) were compared based on their accuracy and area under the Receiver Operating Characteristic (ROC) curve. The accuracy of the Trauma and Injury Severity Score (TRISS), RTS, GCS, GMR and MGMR models were almost the same. Considering both the area under the ROC curve and accuracy, the age included MGMR model was also comparable with other age included models (RTS+age, GCS+age, GMR+age). We concluded that although in some situations we need more sophisticated models, should our results be reproducible in other populations, MGMR (with or without age added) model may be of considerable practical value.  相似文献   

15.

Background

In the developed world, multiple injury severity scores have been used for trauma patient evaluation and study. However, few studies have supported the effectiveness of different trauma scoring methods in the developing world. The Kampala Trauma Score (KTS) was developed for use in resource-limited settings and has been shown to be a robust predictor of death. This study evaluates the ability of KTS to predict the mortality of trauma patients compared to other trauma scoring systems.

Methods

Data were collected on injured patients presenting to Central Hospital of Yaoundé, Cameroon from April 15 to October 15, 2009. The KTS, Injury Severity Score, Revised Trauma Score, Glasgow Coma Scale, and Trauma Injury Severity Score were calculated for each patient. Scores were evaluated as predictors of mortality using logistic regression models. Areas under receiver operating characteristic (ROC) curves were compared.

Results

Altogether, 2855 patients were evaluated with a mortality rate of 6 per 1000. Each score analyzed was a statistically significant predictor of mortality. The area under the ROC for KTS as a predictor of mortality was 0.7748 (95 % CI 0.6285–0.9212). There were no statistically significant pairwise differences between ROC areas of KTS and other scores. Similar results were found when the analysis was limited to severe injuries.

Conclusions

This comparison of KTS to other trauma scores supports the adoption of KTS for injury surveillance and triage in resource-limited settings. We show that the KTS is as effective as other scoring systems for predicting patient mortality.  相似文献   

16.
《Injury》2016,47(1):125-129
BackgroundMortality prediction in trauma patients has relied upon injury severity scoring tools focused on anatomical injury. This study sought to examine whether an injury severity scoring system which includes physiologic data performs as well as anatomic injury scores in mortality prediction.MethodsUsing data collected from 18 Level I trauma centers and 51 non-trauma center hospitals in the US, anatomy based injury severity scores (ISS), new injury severity scores (NISS) were calculated as were scores based on a modified version of the physiology-based Kampala trauma score (KTS). Because pre-hospital intubation, when required, is standard of care in the US, a modified KTS was calculated excluding respiratory rate. The predictive ability of the modified KTS for mortality was compared with the ISS and NISS using receiver operating characteristic (ROC) curves.ResultsA total of 4716 individuals were eligible for study. Each of the three scores was a statistically significant predictor of mortality. In this sample, the modified KTS significantly outperformed the ISS (AUC = 0.83, 95% CI 0.81–0.84 vs. 0.77, 95% CI 0.76–0.79, respectively) and demonstrated similar predictive ability compared to the NISS (AUC = 0.83, 95% CI 0.81–0.84 vs. 0.82, 95% CI 0.80–0.83, respectively).ConclusionsThe modified KTS may represent a useful tool for assessing trauma mortality risk in real time, as well as in administrative data where physiologic measures are available. Further research is warranted and these findings suggest that the collection of physiologic measures in large databases may improve outcome prediction.  相似文献   

17.
Pediatric trauma centers often do not meet the guidelines requiring a trauma team as recommended by the American Academy of Pediatrics (AAP). We reviewed our experience with a team consisting of a pediatric emergency physician, resident, nurse, and respiratory therapist. The surgical and pediatric critical care residents and staff were available within 5 minutes. We conducted a retrospective chart review of 146 patients (aged 8.1 +/- 4.8 years) between 1987 and 1989, with Injury Severity Scores (ISS) greater than or equal to 16 or admitted to the pediatric critical care unit. The time of presentation, surgical services consulted, and the nature of the injury were obtained from chart review. The Pediatric Trauma Score (PTS), the Revised Trauma Score (RTS), the Injury Severity Score (ISS), Glasgow Coma Scale (GCS) score, and Pediatric Risk of Mortality (PRISM) were used to determine the severity of insult and physiologic derangement on admission. The Modified Injury Severity Score (MISS) was determined and the Delta score for Disability Assessment was assigned at discharge. The Delta score was also determined at 3-month intervals up to one year. The probability of survival (Ps) was calculated, using the ISS and RTS. The Z statistic for this group of patients was then determined, using the Major Trauma Outcome Study (MTOS) methodology. The percentages of patients who were normal, disabled, and dead were 61%, 31.5%, and 7.5%, respectively, at 6 months follow-up. Eleven deaths were expected based on PRISM and TRISS analysis. Our mortality and morbidity figures were comparable with those of centers with teams based on AAP guidelines.(ABSTRACT TRUNCATED AT 250 WORDS)  相似文献   

18.
Abstract Background: A central component to the statistical analysis of trauma care is the probability of survival model, which predicts outcome of the trauma event taking into account various anatomical and physiological factors. One of the key input information to the survival model is the injury score which forms the cornerstone of trauma epidemiology. There are many scoring systems currently in use, and the Injury Severity Score (ISS) as the anatomical component of the injury in the probability of survival model is a widely used one. This paper examines the possibility of representing the anatomical component of the trauma using different injury severity scoring methods described in the literature. Material and methods: The dataset used consists of 75,371 cases from the Trauma Audit and Research Network (TARN). TARN regroups 110 hospitals in the UK and it is the largest European trauma registry. Various limitations of ISS have been described in the literature and an investigation into other scoring methods, which could be calculated from the available data, was proposed. Using the available database, the alternative injury scoring methods can be calculated and their use within a Trauma score and Injury Severity Score (TRISS) probability of survival model is assessed. Results: The current score performs reasonably well, but there is some improvement in calibration associated with introducing a score, which takes into account body-region locations of all injuries.  相似文献   

19.

Background

The Trauma and Injury Severity Score (TRISS) remains the most commonly used tool for benchmarking trauma fatality outcome. Recently, it was demonstrated that the predictive power of TRISS could be substantially improved by re-classifying the component variables and treating the variable categories nominally. This study aims to develop revised TRISS models using re-classified variables, to assess these models’ predictive performances against existing TRISS models, and to identify and recommend a preferred TRISS model.

Materials and methods

Revised TRISS models for blunt and penetrating injury mechanism were developed on an adult (aged ≥15 years) sample from the National Trauma Data Bank National Sample Project (NSP), using 5-category variable classifications and weighted logistic regression. Their predictive performances were then assessed against existing TRISS models on the unweighted NSP, National Trauma Data Bank (NTDB), and New Zealand Database (NZDB) samples using area under the Receiver Operating Characteristic curve (AUC) and Bayesian Information Criterion (BIC) statistics.

Results

The weighted NSP sample included 1,124,001 adults with blunt or penetrating injury mechanism events and known discharge status, of whom 1,061,709 (94.5%) survived to discharge. Complete information for all TRISS variables was available for 896,212 (79.7%). Revised TRISS models that included main-effects and two-factor interaction terms had superior AUC and BIC statistics to main-effects models and existing TRISS models for patients with complete data in NSP, NTDB and NZDB samples. Predictive performance decreased as the number of variables with missing values included within revised TRISS models increased, but model performances generally remained superior to existing TRISS models.

Discussion

Revised TRISS models had importantly improved predictive capacities over existing TRISS models. Additionally, they were easily computed, utilised only those variables already collected for existing TRISS models, and could be applied and produce meaningful survival probabilities when one or more of the predictor variables contained missing values. The preferred revised TRISS model included main-effects and two-factor interaction terms and allowed for missing values in all predictor variables. A strong case exists for replacing existing TRISS models in trauma scoring systems benchmarking software with this preferred revised TRISS model.  相似文献   

20.
Developmental changes in the anatomy and physiology of growing children are thought to improve the survivability of older children to significant injury. The effect of age upon survival, however, is poorly defined. Data for 4,615 patients less than 15 years old from a statewide trauma center registry were analyzed. Injury and survival were characterized by Abbreviated Injury Scale (AIS, 1985 revision), Injury Severity Score (ISS), Revised Trauma Score (RTS), and probability of survival [P(s)] and Z by TRISS. Patients were separated into age groups of 0 through 4, 5 through 9, and 10 through 14 years. The survival rate for patients with a maximum AIS 3 for any region was significantly higher in the 10-14-year age group. There were no significant differences in survival rates from head, thoracic, and abdominal injuries stratified by AIS among the three age groups. Survival rates for ISS cohorts were consistently lowest in the 0-4-year age group, but differences failed to reach significance. Survival for RTS and P(s) intervals were similar for all ages. The Z statistic reached significance for all children (Z = 4.717, W = 1.049), and for each group (Z = 2.203-3.029). Corresponding values of the W statistic suggest approximately one additional unexpected survivor per 100 admitted children when compared with the Major Trauma Outcome Study. Logistic regression for patients with all data required for TRISS showed no significant effect for any of the three age groups. We conclude that for this patient set, survival after childhood injury is independent of the age groups used in this study, after controlling for injury severity.  相似文献   

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