Association between the Japan Coma Scale scores at the scene of injury and in-hospital outcomes in trauma patients: an analysis from the nationwide trauma database in Japan.
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ABSTRACT: Objective
Japan Coma Scale (JCS) is a grading system used to evaluate disturbed consciousness in prehospital care settings. We aimed to identify the association between the JCS levels at the scene with in-hospital mortality, as well as the discrimination ability for the outcomes.Design
A retrospective cohort study based on the nationwide trauma database in Japan.Setting
Multicentre cohort study using data from the Japan Trauma Data Bank, which is a nationwide, prospective, observational trauma registry derived from 235 hospitals.Participants
Adult trauma victims transferred directly from the scene of injury to the hospital from January 2004 to December 2017 were eligible for inclusion.Primary and secondary outcomes
Primary outcome was the association between the JCS levels at the scene with in-hospital mortality. We conducted a multivariate logistic regression analysis to calculate the adjusted ORs of JCS levels with 95% CIs for in-hospital mortality. We also calculated the c-statistics for in-hospital mortality.Results
164 723 patients were included in the analysis. In a multivariate logistic regression analysis, the corresponding adjusted ORs of JCS levels 2 and 3 referred to level 1 for in-hospital mortality were 4.1 (95% CI 3.8 to 4.4) and 26.0 (95% CI 24.8 to 27.2). The c-statistics of the JCS level for in-hospital mortality was 0.845 (95% CI 0.842 to 0.849).Conclusions
Data from large multicentre prospective registry revealed strong associations of the JCS level at the scene of injury with in-hospital mortality as well as the good discriminatory performance for this outcome.
SUBMITTER: Okada Y
PROVIDER: S-EPMC6677991 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:The Japan Coma Scale (JCS) score has been widely used to assess patients' consciousness level in Japan. JCS scores are divided into four main categories: alert (0) and one-, two-, and three-digit codes based on an eye response test, each of which has three subcategories. The purpose of this study was to investigate the utility of the JCS score on hospital arrival in predicting outcomes among adult trauma patients. METHODS:Using the Japan Trauma Data Bank, we conducted a nationwide registry-based retrospective cohort study. Patients 16 years old or older directly transported from the trauma scene between January 2004 and December 2017 were included. Our primary outcome was in-hospital mortality. We examined outcome prediction accuracy based on area under the receiver operating characteristic curve (AUROC) and multiple logistic regression analysis with multiple imputation. RESULTS:A total of 222,540 subjects were included; their in-hospital mortality rate was 7.1% (n = 15,860). The 10-point scale JCS and the total sum of Glasgow Coma Scale (GCS) scores demonstrated similar performance, in which the AUROC (95% CIs) showed 0.874 (0.871-0.878) and 0.878 (0.874-0.881), respectively. Multiple logistic regression analysis revealed that the higher the JCS score, the higher the predictability of in-hospital death. When we focused on the simple four-point scale JCS score, the adjusted odds ratio (95% confidence intervals [CIs]) were 2.31 (2.12-2.45), 4.81 (4.42-5.24), and 27.88 (25.74-30.20) in the groups with one-digit, two-digit, and three-digit scores, respectively, with JCS of 0 as a reference category. CONCLUSIONS:JCS score on hospital arrival after trauma would be useful for predicting in-hospital mortality, similar to the GCS score.
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Project description:ObjectivesTo examine the association between body temperature (BT) on hospital arrival and in-hospital mortality among paediatric trauma patients.DesignA retrospective cohort study.SettingJapan Trauma Data Bank (JTDB, which is a nationwide, prospective, observational trauma registry with data from 235 hospitals).ParticipantsPaediatric trauma patients <16 years old who were transferred directly from the scene of injury to the hospital and registered in the JTDB from January 2004 to December 2017 were included. We excluded patients >16 years old and those who developed cardiac arrest before or on hospital arrival.Primary outcomeThe association between BT on hospital arrival and in-hospital mortality. We conducted multivariate logistic regression analyses to calculate the adjusted ORs, with their 95% CIs, of the association between BT and in-hospital mortality.ResultsA total of 9012 patients were included (median age: 9 years (IQR, 6.0-13.0 years), mortality: 2.5% (mortality number was 226 in total 9012 patients)). In the multivariate logistic regression analysis, the corresponding adjusted ORs of BT <36.0°C and BT ≥37.0°C, relative to a BT of 36°C-36.9°C, for in-hospital mortality were 2.83 (95% CI: 1.85 to 4.33) and 0.93 (95% CI: 0.53 to 1.63), respectively.ConclusionsIn paediatric patients with hypothermia (BT <36.0°C) on hospital arrival, a clear association with in-hospital mortality was observed; no such association was observed between higher BT values (≥37.0°C) and outcomes.
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Project description:BackgroundThe Japan Coma Scale (JCS) is the most frequently adopted method for evaluating level of consciousness in Japan. However, no validated method for converting the JCS to the Glasgow Coma Scale (GCS) exists. The aims of the present study were to develop and validate a method to convert the JCS to GCS.MethodsThis is a multicenter retrospective analysis involving three emergency departments (EDs) in Japan. We included all adult patients who visited the ED between 2017 and 2020. The participating facilities were divided into two cohorts-one cohort to develop a table to convert the JCS to GCS (development cohort), and the other cohort to validate the conversion table (validation cohort). The conversion table of the JCS to GCS was developed based on the median values of the GCS. The outcome was the concordance rate between the JCS and GCS.ResultsWe identified 8,194 eligible patients. The development cohort included 7,373 patients and the validation cohort included 821 patients. In the validation cohort, the absolute and relative concordance rates were 80.3% (95% confidence interval, 77.4-82.9%) and 93.2% (95% confidence interval, 91.2-94.8%), respectively.ConclusionThis study developed and validated a novel method for converting the JCS to GCS. Assuming the offset by a single category between the JCS and GCS is acceptable, the concordance rate was over 90% in the general adult patient population visiting the ED. The conversion method may assist researchers to convert JCS scores into GCS scores, which are more commonly recognized among global audiences.
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Project description:Geriatric trauma is a major socio-economic problem, especially among the aging Japanese society. Geriatric people are more vulnerable to trauma than younger people; thus, their outcomes are often severe. This study evaluates the characteristics of geriatric trauma divided by age in the Japanese population. We evaluated trauma characteristics in patients (n = 131,088) aged ≥ 65 years by segregating them into 2 age-based cohorts: age 65-79 years (65-79 age group; n = 70,707) and age ≥ 80 years (≥ 80 age group; n = 60,381). Clinical characteristics such as patient background, injury mechanism, injury site and severity, treatment, and outcome were examined. Injuries among men were more frequent in the 65-79 age group (58.6%) than in the ≥ 80 age group (36.3%). Falls were the leading cause of trauma among the 65-79 age group (56.7%) and the ≥ 80 age group (78.9%). In-hospital mortality was 7.7% in the 65-79 age group and 6.6% in the ≥ 80 age group. High fall in the ≥ 80 age group showed 30.5% mortality. The overall in-hospital mortality was 11.8% (the 65-79 age group, 12.3%; the ≥ 80 age group, 11.2%). Most hospitalized patients were transferred to another hospital (the 65-79 age group, 52.5%; the ≥ 80 age group, 66.2%). We demonstrated the epidemiological characteristics of Japanese geriatric trauma patients. The overall in-hospital mortality was 11.8%, and fall injury in the ≥ 80 age group required caution of trauma care.
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Project description:The reverse shock index (rSI), a ratio of systolic blood pressure (SBP) to heart rate (HR), is used to identify prognosis in trauma patients. Multiplying rSI by Glasgow Coma Scale (rSIG) can possibly predict better in-hospital mortality in patients with trauma. However, rSIG has never been used to evaluate the mortality risk in adult severe trauma patients (Injury Severity Score [ISS]???16) with head injury (head Abbreviated Injury Scale [AIS]???2) in the emergency department (ED). This retrospective case control study recruited adult severe trauma patients (ISS???16) with head injury (head AIS???2) who presented to the ED of two major trauma centers between January 01, 2014 and May 31, 2017. Demographic data, vital signs, ISS scores, injury mechanisms, laboratory data, managements, and outcomes were included for the analysis. Logistic regression and receiver operating characteristic analysis were used to evaluate the accuracy of rSIG score in predicting in-hospital mortality. In total, 438 patients (mean age: 56.48 years; 68.5% were males) were included in this study. In-hospital mortality occurred in 24.7% patients. The median (interquartile range) ISS score was 20 (17-26). Patients with rSIG???14 had seven-fold increased risks of mortality than those without rSIG???14 (odds ratio: 7.64; 95% confidence interval: 4.69-12.42). Hosmer-Lemeshow goodness-of-fit test and area under the curve values for rSIG score were 0.29 and 0.76, respectively. The sensitivity, specificity, positive predictive value, and negative predictive values of rSIG???14 were 0.71, 0.75, 0.49, and 0.89, respectively. The rSIG score is a prompt and simple tool to predict in-hospital mortality among adult severe trauma patients with head injury.
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Project description:ObjectiveTo determine the frequency with which specific Coma Recovery Scale-Revised (CRS-R) subscale scores co-occur as a means of providing clinicians and researchers with an empirical method of assessing CRS-R data quality.DesignWe retrospectively analyzed CRS-R subscale scores in hospital inpatients diagnosed with disorders of consciousness (DOCs) to identify impossible and improbable subscore combinations as a means of detecting inaccurate and unusual scores. Impossible subscore combinations were based on violations of CRS-R scoring guidelines. To determine improbable subscore combinations, we relied on the Mahalanobis distance, which detects outliers within a distribution of scores. Subscore pairs that were not observed at all in the database (ie, frequency of occurrence=0%) were also considered improbable.SettingSpecialized DOC program and university hospital.ParticipantsPatients diagnosed with DOCs (N=1190; coma: n=76, vegetative state: n=464, minimally conscious state: n=586, emerged from minimally conscious state: n=64; 794 men; mean age, 43±20y; traumatic etiology: n=747; time postinjury, 162±568d).InterventionsNot applicable.Main outcome measureImpossible and improbable CRS-R subscore combinations.ResultsOf the 1190 CRS-R profiles analyzed, 4.7% were excluded because they met scoring criteria for impossible co-occurrence. Among the 1137 remaining profiles, 12.2% (41/336) of possible subscore combinations were classified as improbable.ConclusionsClinicians and researchers should take steps to ensure the accuracy of CRS-R scores. To minimize the risk of diagnostic error and erroneous research findings, we have identified 9 impossible and 36 improbable CRS-R subscore combinations. The presence of any one of these subscore combinations should trigger additional data quality review.
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Project description:PurposeEarly diagnosis of traumatic brain injury (TBI) is important for improving survival and neurologic outcome in trauma victims. The purpose of this study was to assess whether Glasgow Coma Scale (GCS) of 12 or less can predict the presence of TBI and the severity of associated injuries in blunt trauma patients.MethodsA retrospective cohort study including 303,435 blunt trauma patients who were transferred from the scene to hospital from 1998 to 2013. The data was obtained from the records of the National Trauma Registry maintained by Israel's National Center for Trauma and Emergency Medicine Research, in the Gertner Institute for Epidemiology and Health Policy Research. All blunt trauma patients with GCS 12 or less were included in this study. Data collected in the registry include age, gender, mechanism of injury, GCS, initial blood pressure, presence of TBI and incidence of associated injuries. Patients younger than 14 years old and trauma victims with GCS 13-15 were excluded from the study. Statistical analysis was performed by using Statistical Analysis Software Version 9.2. Statistical tests performed included Chi-square tests. A p-value less than 0.05 was considered statistically significant.ResultsThere were 303,435 blunt trauma patients, 8731 (2.9%) of them with GCS of 3-12 that including 6351 (72%) patients with GCS of 3-8 and 2380 (28%) patient with GCS of 9-12. In these 8731 patients with GCS of 3-12, 5372 (61.5%) patients had TBI. There were total 1404 unstable patients in all the blunt trauma patients with GCS of 3-12, 1256 (89%) patients with GCS 3-8, 148 (11%) patients with GCS 9-12. In the 5095 stable blunt trauma patients with GCS 3-8, 32.4% of them had no TBI. The rate in the 2232 stable blunt trauma patients with GCS 9-12 was 50.1%. In the unstable patients with GCS 3-8, 60.5% of them had TBI, and in subgroup of patients with GCS 9-12, only 37.2% suffered from TBI.ConclusionThe utility of a GCS 12 and less is limited in prediction of brain injury in multiple trauma patients. Significant proportion of trauma victims with low GCS had no TBI and their impaired neurological status is related to severe extra-cranial injuries. The findings of this study showed that using of GCS in initial triage and decision making processes in blunt trauma patients needs to be re-evaluated.
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Project description:BackgroundPrevious studies have reported conflicting results regarding fresh frozen plasma (FFP)-to-red blood cell (RBC) ratio and platelet-to-RBC ratio on outcomes for massive transfusion for trauma. Moreover, nationwide data on massive transfusion practices for trauma in the real-world clinical setting are scarce. This study aimed to examine the nationwide practice patterns and trends in massive transfusion for trauma in Japan using a national administrative, inpatient database.MethodWe identified patients who underwent emergency hospitalization for trauma and received massive transfusion, defined as administration of at least 20 units of RBC within the first 2 days of admission, using the nationwide inpatient database, which covers approximately 90% of all tertiary emergency hospitals in Japan, between 2011 and 2020. Trends in the incidence and practice patterns of massive transfusion were described by calendar year. The association of practice patterns with mortality or adverse events was tested.ResultsA total of 3,530,846 trauma hospitalizations were identified, of which 5247 (0.15%) received massive transfusion. A significant declining trend was observed in the incidence of massive transfusion in trauma hospitalizations from 0.24% in 2011 to 0.10% in 2020 (P for trend < 0.001). The FFP-to-RBC ratio rose significantly from 0.77 in 2011 to 1.08 in 2020 (P for trend < 0.001), while the platelet-to-RBC ratio remained virtually unchanged from 0.71 in 2011 to 0.78 in 2020 (P for trend 0.060). Massive transfusion with lower FFP-to-RBC (< 0.75) and platelets-to-RBC ratio (< 1.00) were associated with increased in-hospital mortality compared with those ≥ 1.00, while there were linear increases in adverse events with increasing FFP and platelets ratios.ConclusionsThis study demonstrated a declining trend in the incidence and a rise in higher FFP-to-RBC ratios in massive transfusion in association with patient outcomes for trauma from 2011 to 2020 in Japan.
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Project description:BackgroundProviding optimal care for trauma, the leading cause of death for young adults, remains a challenge e.g., due to field triage limitations in assessing a patient's condition and deciding on transport destination. Data-driven On Scene Injury Severity Prediction (OSISP) models for motor vehicle crashes have shown potential for providing real-time decision support. The objective of this study is therefore to evaluate if an Artificial Intelligence (AI) based clinical decision support system can identify severely injured trauma patients in the prehospital setting.MethodsThe Swedish Trauma Registry was used to train and validate five models - Logistic Regression, Random Forest, XGBoost, Support Vector Machine and Artificial Neural Network - in a stratified 10-fold cross validation setting and hold-out analysis. The models performed binary classification of the New Injury Severity Score and were evaluated using accuracy metrics, area under the receiver operating characteristic curve (AUC) and Precision-Recall curve (AUCPR), and under- and overtriage rates.ResultsThere were 75,602 registrations between 2013-2020 and 47,357 (62.6%) remained after eligibility criteria were applied. Models were based on 21 predictors, including injury location. From the clinical outcome, about 40% of patients were undertriaged and 46% were overtriaged. Models demonstrated potential for improved triaging and yielded AUC between 0.80-0.89 and AUCPR between 0.43-0.62.ConclusionsAI based OSISP models have potential to provide support during assessment of injury severity. The findings may be used for developing tools to complement field triage protocols, with potential to improve prehospital trauma care and thereby reduce morbidity and mortality for a large patient population.
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Project description:BackgroundThe Kampala Trauma Score (KTS) has been proposed as a triage tool for use in low- and middle-income countries (LMICs). This study aimed to examine the diagnostic accuracy of KTS in predicting emergency department outcomes using timely injury estimation with Abbreviated Injury Scale (AIS) score and physician opinion to calculate KTS scores.MethodsThis was a diagnostic accuracy study of KTS among injured patients presenting to Komfo Anokye Teaching Hospital A&E, Ghana. South African Triage Scale (SATS); KTS component variables, including AIS scores and physician opinion for serious injury quantification; and ED disposition were collected. Agreement between estimated AIS score and physician opinion were analyzed with normal, linear weighted, and maximum kappa. Receiver operating characteristic (ROC) analysis of KTS-AIS and KTS-physician opinion was performed to evaluate each measure's ability to predict A&E mortality and need for hospital admission to the ward or theatre.ResultsA total of 1053 patients were sampled. There was moderate agreement between AIS criteria and physician opinion by normal (κ=0.41), weighted (κlin=0.47), and maximum (κmax=0.53) kappa. A&E mortality ROC area for KTS-AIS was 0.93, KTS-physician opinion 0.89, and SATS 0.88 with overlapping 95% confidence intervals (95%CI). Hospital admission ROC area for KTS-AIS was 0.73, KTS-physician opinion 0.79, and SATS 0.71 with statistical similarity. When evaluating only patients with serious injuries, KTS-AIS (ROC 0.88) and KTS-physician opinion (ROC 0.88) performed similarly to SATS (ROC 0.78) in predicting A&E mortality. The ROC area for KTS-AIS (ROC 0.71; 95%CI 0.66-0.75) and KTS-physician opinion (ROC 0.74; 95%CI 0.69-0.79) was significantly greater than SATS (ROC 0.57; 0.53-0.60) with regard to need for admission.ConclusionsKTS predicted mortality and need for admission from the ED well when early estimation of the number of serious injuries was used, regardless of method (i.e. AIS criteria or physician opinion). This study provides evidence for KTS to be used as a practical and valid triage tool to predict patient prognosis, ED outcomes and inform referral decision-making from first- or second-level hospitals in LMICs.
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