Glasgow Coma Scale Motor Component Research Articles

Effectiveness of and Adherence to Triage Algorithms during Prehospital Response to Mass Casualty Incidents

Introduction:At mass casualty incidents (MCIs) medical needs exceed available resources, requiring prioritization of response efforts and materials. Principles of triage have evolved since the 18th century into several modern-day algorithms that sort casualties into priority groups based on clinical parameters. It is unclear, however, if such algorithms are effective and practical during real-world MCIs. This analysis reviews the literature on use and efficacy of prehospital MCI triage algorithms.Method:The MEDLINE, Scopus, and Google Scholar databases were searched for peer-reviewed and grey literature on prehospital MCI medical response. Articles discussing MCI triage concepts, triage at MCIs, or algorithm efficacy were included. Articles were excluded if they described law enforcement, ethical, psychological or epidemiological perspectives without detailing the medical response.Results:Frequently-cited MCI triage algorithms include START (Simple Triage & Rapid Treatment); Triage Sieve; CareFlight; SALT (Sort, Assess, Lifesaving Interventions, Treatment/Transport); and RAMP (Rapid Assessment of Mentation & Pulse). They differ in the physiologic parameters assessed, inclusion of numerical measurements, and number of triage categories. Surveyed providers were less likely to have performed full triage at MCIs (16%) than in training (69%), and more likely to have performed no triage (29% vs. 1%). In retrospective trauma registry analyses, algorithms were generally poorly predictive of the need for life-saving interventions (13-58% sensitive, 72-97% specific) in one study, and variably predictive of critical injury (45-85% sensitive, 86-96% specific) in another. The Glasgow Coma Scale motor component was associated with critical injury (73% sensitive, 96% specific if <6); other physiologic variables had sensitivities under 40%. In prospective studies, algorithms were accurate for 36-52% of adults and 56-59% of children. Some suggest clinician judgment may be similarly effective.Conclusion:Multiple algorithms exist for MCI triage, but they are infrequently utilized and may be inaccurate. Simpler, more realistic, scalable, and widely accepted response systems need to be instituted.

New prehospital scoring system for traumatic brain injury to predict mortality and severe disability using motor Glasgow Coma Scale, hypotension, and hypoxia: a nationwide observational study.

ObjectiveAssessing the severity of injury and predicting outcomes are essential in traumatic brain injury (TBI). However, the respiratory rate and Glasgow Coma Scale (GCS) of the Revised Trauma Score (RTS) are difficult to use in the prehospital setting. This investigation aimed to develop a new prehospital trauma score for TBI (NTS-TBI) to predict mortality and disability.MethodsWe used a nationwide trauma database on severe trauma cases transported by fire departments across Korea in 2013 and 2015. NTS-TBI model 1 used systolic blood pressure <90 mmHg, peripheral capillary oxygen saturation <90% measured via pulse oximeter, and motor component of GCS. Model 2 comprised variables of model 1 and age >65 years. We assessed discriminative power via area under the curve (AUC) value for in-hospital mortality and disability defined according to the Glasgow Outcome Scale with scores of 2 or 3. We then compared AUC values of NTS-TBI with those of RTS.ResultsIn total, 3,642 patients were enrolled. AUC values of NTS-TBI models 1 and 2 for mortality were 0.833 (95% confidence interval [CI], 0.815 to 0.852) and 0.852 (95% CI, 0.835 to 0.869), respectively, while AUC values for disability were 0.772 (95% CI, 0.749 to 0.796) and 0.784 (95% CI, 0.761 to 0.807), respectively. AUC values of NTS-TBI model 2 for mortality and disability were higher than those of RTS (0.819 and 0.761, respectively) (P<0.01).ConclusionOur NTS-TBI model using systolic blood pressure, motor component of GCS, oxygen saturation, and age was feasible for prehospital care and showed outstanding discriminative power for mortality.

Nationwide cohort study of independent risk factors for acute respiratory distress syndrome after trauma

BackgroundThe primary objective of this study was to evaluate the effect of specific direct and indirect factors that accounted, in trauma patients, for the development of acute respiratory distress syndrome...

Study of Simplified Coma Scales: Acute Stroke Patients with Tracheal Intubation.

Background:Whether the Glasgow Coma Scale (GCS) can assess intubated patients is still a topic of controversy. We compared the test performance of the GCS motor component (GCS-M)/Simplified Motor Score (SMS) to the total of the GCS in predicting the outcomes of intubated acute severe cerebral vascular disease patients.Methods:A retrospective analysis of prospectively collected observational data was performed. Between January 2012 and October 2015, 106 consecutive acute severe cerebral vascular disease patients with intubation were included in the study. GCS, GCS-M, GCS eye-opening component, and SMS were documented on admission and at 24, 48, and 72 h after admission to Neurointensive Care Unit (NCU). Outcomes were death and unfavorable prognosis (modified Rankin Scale: 5–6) at NCU discharge. The receiver operating characteristic (ROC) curve was obtained to determine the prognostic performance and best cutoff value for each scoring system. Comparison of the area under the ROC curves (AUCs) was performed using the Z-test.Results:Of 106 patients included in the study, 41 (38.7%) patients died, and 69 (65.1%) patients had poor prognosis when discharged from NCU. The four time points within 72 h of admission to the NCU were equivalent for each scale's predictive power, except that 0 h was the best for each scale in predicting outcomes of patients with right-hemisphere lesions. Nonsignificant difference was found between GCS-M AUCs and GCS AUCs in predicting death at 0 h (0.721 vs. 0.717, Z = 0.135, P = 0.893) and 72 h (0.730 vs. 0.765, Z = 1.887, P = 0.060), in predicting poor prognosis at 0 h (0.827 vs. 0.819, Z = 0.395, P = 0.693), 24 h (0.771 vs. 0.760, Z = 0.944, P = 0.345), 48 h (0.732 vs. 0.741, Z = 0.593, P = 0.590), and 72 h (0.775 vs. 0.780, Z = 0.302, P = 0.763). AUCs in predicting death for patients with left-hemisphere lesions ranged from 0.700 to 0.804 for GCS-M and from 0.700 to 0.824 for GCS, in predicting poor prognosis ranged from 0.841 to 0.969 for GCS-M and from 0.875 to 0.969 for GCS, with no significant difference between GCS-M AUCs and GCS AUCs within 72 h (P > 0.05). No significant difference between GCS-M AUCs and GCS AUCs was found in predicting death (0.964 vs. 0.964, P = 1.000) and poor prognosis (1.000 vs. 1.000, P = 1.000) for patients with right-hemisphere lesions at 0 h. AUCs in predicting death for patients with brainstem or cerebella were poor for GCS-M (<0.700), in predicting poor prognosis ranged from 0.727 to 0.801 for GCS-M and from 0.704 to 0.820 for GCS, with no significant difference between GCS-M AUCs and GCS AUCs within 72 h (P > 0.05). The SMS AUCs (<0.700) in predicting outcomes were poor.Conclusions:The GCS-M approaches the same test performance as the GCS in assessing the prognosis of intubated acute severe cerebral vascular disease patients. The GCS-M could be accurately and reliably applied in patients with hemisphere lesions, but caution must be taken for patients with brainstem or cerebella lesions.

Inclusion of Highest Glasgow Coma Scale Motor Component Score in Mortality Risk Adjustment for Benchmarking of Trauma Center Performance

The Glasgow Coma Scale (GCS) is the most widely used measure of traumatic brain injury (TBI) severity. Currently, the arrival GCS motor component (mGCS) score is used in risk-adjustment models for external benchmarking of mortality. However, there is evidence that the highest mGCS score in the first 24 hours after injury might be a better predictor of death. Our objective was to evaluate the impact of including the highest mGCS score on the performance of risk-adjustment models and subsequent external benchmarking results. Data were derived from the Trauma Quality Improvement Program analytic dataset (January 2014 through March 2015) and were limited to the severe TBI cohort (16 years or older, isolated head injury, GCS ≤8). Risk-adjustment models were created that varied in the mGCS covariates only (initial score, highest score, or both initial and highest mGCS scores). Model performance and fit, as well as external benchmarking results, were compared. There were 6,553 patients with severe TBI across 231 trauma centers included. Initial and highest mGCS scores were different in 47% of patients (n= 3,097). Model performance and fit improved when both initial and highest mGCS scores were included, as evidenced by improved C-statistic, Akaike Information Criterion, and adjusted R-squared values. Three-quarters of centers changed their adjusted odds ratio decile, 2.6% of centers changed outlier status, and 45% of centers exhibited a ≥0.5-SD change in the odds ratio of death after including highest mGCS score in the model. This study supports the concept that additional clinical information has the potential to not only improve the performance of current risk-adjustment models, but can also have a meaningful impact on external benchmarking strategies. Highest mGCS score is a good potential candidate for inclusion in additional models.

Glasgow Coma Scale Motor Component (“Patient Does Not Follow Commands”) Performs Similarly to Total Glasgow Coma Scale in Predicting Severe Injury in Trauma Patients

Trauma victims are frequently triaged to a trauma center according to the patient's calculated Glasgow Coma Scale (GCS) score despite its known inconsistencies. The substitution of a simpler binary assessment of GCS-motor (GCS-m) score less than 6 (ie, "patient does not follow commands") would simplify field triage. We compare total GCS score to this binary assessment for predicting trauma outcomes. This retrospective analysis of a statewide trauma registry includes records from 393,877 patients from 1999 to 2013. Patients with initial GCS score less than or equal to 13 were compared with those with GCS-m score less than 6 for outcomes of Injury Severity Score (ISS) greater than 15, ISS greater than 24, death, ICU admission, need for surgery, or need for craniotomy. We judged a priori that differences less than 5% lack clinical importance. The relative differences between GCS and GCS-m scores less than 6 were less than 5% and thus clinically unimportant for all outcomes tested, even when statistically significant. For the 6 outcomes, the differences in areas under receiver operating characteristic curves ranged from 0.014 to 0.048. Total GCS score less than or equal to 13 was slightly more sensitive (difference 3.3%; 95% confidence interval 3.2% to 3.4%) and slightly less specific (difference -1.5%; 95% confidence interval -1.6% to -1.5%) than GCS-m score less than 6 for predicting ISS greater than 15, with similar overall accuracy (74.1% versus 74.2%). Replacement of the total GCS score with a simple binary decision point of GCS-m score less than 6, or a patient who "does not follow commands," predicts serious injury, as well as the total GCS score, and would simplify out-of-hospital trauma triage.

The Severity of Disparity: Increasing Injury Intensity Accentuates Disparate Outcomes Following Trauma

Studies have shown disparities in mortality among racial groups and among those with differing insurance coverage. Our goal was to determine if injury severity affects these disparities. We classified patients from the 2003-2008 National Trauma Data Banks suffering moderate to severe injuries into six groups based on race/ethnicity and insurance, stratifying by injury severity. Logistic regression compared odds of death between races-ethnicities/insurance groups within these strata. We adjusted for age, gender, Injury Severity Score, Glasgow Coma Scale motor component, hypotension, and mechanism of injury. Patients meeting inclusion criteria numbered 760,598. Disparities between races-ethnicities/insurance groups increased as injury severity worsened. Odds of death for uninsured Black patients compared with insured Whites increased from 1.82 among moderately injured patients to 3.14 among severely injured, hypotensive patients. A similar pattern was seen among uninsured Hispanic patients. Disparities in trauma mortality suffered by minority and uninsured patients, when compared with non-minority and insured patients, worsen with increasing injury.

Pupil evaluation in addition to Glasgow Coma Scale components in prediction of traumatic brain injury and mortality

Early diagnosis and prediction of traumatic brain injury (TBI) is essential for determining treatment strategies and allocating resources. This study evaluated the predictive accuracy of Glasgow Coma Scale (GCS) verbal, motor and eye components alone, or in addition to pupil size and reactivity, for TBI. A retrospective cohort analysis of data from 51 425 severely injured patients registered in the Trauma Registry of the German Society for Trauma Surgery from 1993 to 2009 was undertaken. Only directly admitted patients alive on admission and with complete data on GCS, pupil size and pupil reactivity were included. The unadjusted predictive roles of GCS components and pupil parameters, alone or in combination, were modelled using area under the receiver operating characteristic (AUROC) curve analyses and multivariable logistic regression regarding presence of TBI and death. Some 24 115 patients fulfilled the study inclusion criteria. Best accuracy for outcome prediction was found for pupil reactivity (AUROC 0.770, 95 per cent confidence interval 0.761 to 0.779) and GCS motor component (AUROC 0.797, 0.788 to 0.805), with less accuracy for GCS eye and verbal components. The combination of pupil reactivity and GCS motor component (AUROC 0.822, 0.814 to 0.830) outmatched the predictive accuracy of GCS alone (AUROC 0.808, 0.800 to 0.815). Pupil reactivity and size were significantly correlated (r(s) = 0.56, P < 0.001). Patients displaying both unequal pupils and fixed pupils were most likely to have TBI (95.1 per cent of 283 patients). Good outcome (Glasgow Outcome Scale score 4 or more) was documented for only 1929 patients (8.0 per cent) showing fixed and bilateral dilated pupils. The best predictive accuracy for presence of TBI was obtained using the GCS components. Pupil reactivity together with the GCS motor component performed best in predicting death.

Good Mortality Prediction by Glasgow Coma Scale for Neurosurgical Patients

How to effectively use the finite resources of an intensive care unit (ICU) for neurosurgical patients is a critical decision-making process. Mortality prediction models are effective tools for allocating facilities. This study intended to distinguish the prediction power of the Acute Physiology and Chronic Health Evaluation II (APACHE II), the Simplified Acute Physiology Score II (SAPS II), and the Glasgow Coma Scale (GCS) for neurosurgical patients. According to the definitions of the APACHE II, this study recorded both APACHE II and SAPS II scores of 154 neurosurgical patients in the ICU of a 600-bed general hospital. Linear regression models of GCS (GCS-mr) were constructed. The t test, receiver operating characteristic (ROC) curve and Wilcoxon signed rank test were used as the statistical evaluation methods. There were 50 (32.5%) females and 104 (67.5%) males in this study. Among them, 108 patients survived and 46 patients died. The areas under the ROC curves (AUC) of SAPS II and APACHE II were 0.872 and 0.846, respectively. The AUC of GCS-mr was 0.866, and the R(2) was 0.389. The evaluation powers of SAPS II, GCS-mr and APACHE II were the same (p > 0.05). Patients with GCS <or= 5 or motor component of GCS (GCS-M) <or= 3 had a higher probability of mortality than patients with GCS > 5 or GCS-M > 3 (p < 0.01). The predictive powers of SAPS II, APACHE II and GCS-mr were the same. The GCS-mr is more convenient for predicting mortality in neurosurgical patients. Both GCS <or= 5 and GCS-M <or= 3 are good indicators of mortality in these patients.

Pediatric Trauma Patients Have Excellent Outcomes Even if They Suffer an Adverse In-Hospital Complication: Another Example of How Kids Are Not Little Adults

Introduction: In-hospital complications after admission for trauma is known to be associated with worse clinical outcomes including increased mortality among Adults. Trauma remains the leading cause of death and disability among children above the age of one year. However the impact of in-hospital complications amongst children is unknown. Objective: To determine the relationship between different in-hospital complications and in-hospital mortality after injury among pediatric trauma patients. Methods: Pediatric trauma patients (age <18 years) from hospitals known to contribute complication data to the National Trauma Data Bank (NTDB) and who had at least a 3 day long hospital stay were included in the study. The most common complications among pediatric trauma patients: pneumonia, acute respiratory distress syndrome (ARDS), acute renal failure (ARF), Deep Venous Thrombosis (DVT), Pulmonary Embolism (PE), intra-abdominal abscess (IAA), wound infection and urinary tract infection (UTI) were analyzed. Initially, bivariate analysis was used to determine the unadjusted association of each complication with in hospital mortality. Multiple logistic regression was then used to determine the independent association between developing a complication and the risk of mortality. To adequately control for case mix and injury severity the following patient level co-variates were adjusted: age, ethnicity, gender, insurance status, injury severity score (ISS), presence (or absence) of shock (using age adjusted Systolic Blood Pressure), presence of head injury, Glasgow Coma Scale-Motor component and presence of severe extremity injury. Results: A total of 90,160 records were included in this analysis with males accounting for two-thirds of the entire study population. Mean age of the population was 11 years (SD=5.5 years). Children between ages 13-17 years made up 51.6% of the population followed by ages 5 through 12 at 29.8%. Majority were Whites (57.6%), with Blacks and Hispanics at 16.9% and 12.1% respectively. Overall in-hospital mortality in the study population was 4.0%. On unadjusted analysis, patients with ARF, ARDS, Pneumonia and Compartment Syndrome all had an increased mortality (please see table). However after adjusting for covariates, only those with ARF (OR 2.88, 95% CI=1.29-6.43) and ARDS (OR 3.00, 95% CI=2.00-4.52) were found to have an increased odds of in-hospital death when compared with patients who had no known complications. The presence of pneumonia, PE, DVT or other complications did not significantly increase the odds of death among equivalently injured children.

The Development of a Simple Risk Score to Predict Early Outcome in Severe Acute Acidotic Cardiogenic Pulmonary Edema

Background— Acute cardiogenic pulmonary edema is a common medical emergency with high early mortality. Initial clinical assessment would benefit from accurate mortality prediction. We aimed to develop a simple clinical score based on presenting characteristics that would predict 7-day mortality in patients with acute cardiogenic pulmonary edema. Methods and Results— We used data from patients recruited to the 3CPO trial (a pragmatic multicenter trial comparing continuous positive airway pressure, noninvasive positive pressure ventilation, and standard oxygen therapy in emergency department patients with acute cardiogenic pulmonary edema) to investigate the association between baseline characteristics and 7-day mortality. Factors associated with mortality ( P &lt;0.1) were entered into a multivariable model. Independent predictors of mortality from the multivariable model ( P &lt;0.05) were assigned integer weights based on their coefficients and incorporated into a risk score. The discriminant ability of the score was tested by receiver operator characteristic analysis. Data from 1069 patients (78±10 years; 43% men; 7-day mortality, 9.6%) were analyzed. Multivariable analysis identified age ( P =0.003), systolic blood pressure ( P &lt;0.001), and Glasgow Coma Scale motor component dichotomized and simplified to the ability to obey commands or not ( P =0.02) as the only independent predictors of 7-day mortality. These were weighted and used to develop a risk score ranging from 0 (7-day mortality, 1.9%; 95% CI, 0.8 to 4.5) to 7 (7-day mortality, 100%; 95% CI, 34.2 to 100). Receiver operator characteristic analysis demonstrated good risk prediction with a c-statistic of 0.794 (95% CI, 0.745 to 0.843). A simplified 3-point score with no weighting had a c-statistic of 0.754 (95% CI, 0.701 to 0.807). Conclusions— A simple clinical score based on age, systolic blood pressure, and the ability to obey commands predicts early mortality in patients with acute cardiogenic pulmonary edema. Clinical Trial Registration— clinicaltrials.gov Identifier: ISRCTN077448447.

Incorporating Recent Advances To Make the TRISS Approach Universally Available

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. 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). 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. 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.

Comparing logistic models based on modified GCS motor component with other prognostic tools in prediction of mortality: Results of study in 7226 trauma patients

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.

Monitoring Hospital Trauma Mortality Using Statistical Process Control Methods

Background: We sought to develop a simple and effective way to monitor trends in trauma mortality, using objective clinical categories and methods of statistical process control. Study Design: Control charts and Pareto analysis were applied to trauma mortality data at the Maine Medical Center. We collected data prospectively on patients who died in our hospital after acute injury during 1985–1996 (and retrospectively for 1975–1984) to identify cases requiring medical quality review. We excluded from this study patients older than 80 years, those whose Glasgow Coma Scale motor component was never >3 at any time after admission, and those with pathologic fractures, carcinomatosis, high quadriplegia, or severe burns. The remaining deaths were classified as resulting from inability to resuscitate (mostly hemorrhage), neurologic deterioration, or organ failure. The annual numbers in each of these categories were evaluated under the hypothesis of stationary Poisson processes with mean values equal to those seen from 1975–1984. Results: After the exclusions, annual mortality from trauma has remained within control limits consistent with the Poisson model. Death from neurologic deterioration has shown a trend consistent with significant improvement in the process mean. Transient peaks in the other categories did not exceed control limits, but Pareto analysis prompted detailed studies of aortic and liver trauma. Conclusions: Process control methodology is easy to apply and potentially useful in monitoring hospital trauma mortality.