A retrospective study on evaluating GAP, MGAP, RTS and ISS trauma scoring system for the prediction of mortality among multiple trauma patients

Development and validation of risk prediction model for adverse outcomes in trauma patients

BACKGROUND

The prognosis of trauma patients is highly dependent on early medical diagnosis. By constructing a nomogram model, the risk of adverse outcomes can be displayed intuitively and individually, which has important clinical implications for medical diagnosis.

OBJECTIVE

To develop and evaluate models for predicting patients with adverse outcomes of trauma that can be used in different data availability settings in China.

METHODS

This was a retrospective prognostic study using data from 8 public tertiary hospitals in China from 2018. The data were randomly divided into a development set and a validation set. Simple, improved and extended models predicting adverse outcomes were developed, with adverse outcomes defined as in-hospital death or ICU transfer, and patient clinical characteristics, vital signs, diagnoses, and laboratory test values as predictors. The results of the models were presented in the form of nomograms, and performance was evaluated using area under the receiver operating characteristic curve (ROC-AUC), precision-recall (PR) curves (PR-AUC), Hosmer-Lemeshow goodness-of-fit test, calibration curve, and decision curve analysis (DCA).

RESULTS

Our final dataset consisted of 18,629 patients (40.2% female, mean age of 52.3), 1,089 (5.85%) of whom resulted in adverse outcomes. In the external validation set, three models achieved ROC-AUC of 0.872, 0.881, and 0.903, and a PR-AUC of 0.339, 0.337, and 0.403, respectively. In terms of the calibration curves and DCA, the models also performed well.

CONCLUSIONS

This prognostic study found that three prediction models and nomograms including the patient clinical characteristics, vital signs, diagnoses, and laboratory test values can support clinicians in more accurately identifying patients who are at risk of adverse outcomes in different settings based on data availability.

Comparison of GAP, R-GAP, and new trauma score (NTS) systems in predicting mortality of traffic accidents that injure hospitals at Mashhad University of medical sciences

Background

There are several trauma scoring systems with varying levels of accuracy and reliability that have been developed to predict and classify mortality in trauma patients in the hospital admission. Considering the importance of the country's emergency organization and the World Health Organization in the category of traffic accidents, we used this information in the study. The objective of this study is to evaluate and compare the predictive power of three scoring systems (R-GAP, GAP, and NTS) on traffic accident injuries.

Methods

In an analytical cross-sectional study, all the data related to the mission of traffic accidents at the pre-hospital emergency management of Mashhad University of Medical Sciences in 2022 were extracted from the automation system, and the outcome of the patients in the hospital was recorded from the integrated hospital system. Then, GAP, R-GAP, and New Trauma Scores (NTS) were calculated, and their results were compared using ROC curve and logistic regression.

Results

In this study, 47,971 injuries from traffic accidents were evaluated. Their average age was 30.16 ± 10.93 years. R-GAP showed negligible difference than GAP and NTS scores (the area under the curve equals 0.904, 0.935, and 0.884, respectively), and the average scores of R-GAP, GAP, and NTS are equal to 22.45/45 ± 1/9, 22.25 ± 1.5, and 22.49 ± 1.3, respectively. Injury severity based on R-GAP, GAP, and NTS scores was mild in most patients. The effect of these models on the patient outcome based on OR values, R-GAP, GAP, and NTS models showed high values. All analysis was performed in SPSS 26.

Conclusion

According to the study results, it seems that R-GAP, GAP, and NTS, have the highest power to predict death in traffic accident injuries. It is recommended to include these points in the electronic file of the pre-hospital emergency for the injured. Also, the severity and outcome of the patient can be predicted by these scores, which play an important role in the triage of the injured and determining the appropriate treatment center.

Effect of Injury Patterns on the Development of Complications and Trauma-Induced Mortality in Patients Suffering Multiple Trauma

Patients that suffer from severe multiple trauma are highly vulnerable to the development of complications that influence their outcomes. Therefore, this study aimed to evaluate the risk factors that can facilitate an early recognition of adult patients at risk. The inclusion criteria were as follows: admission to a level 1 trauma center, injury severity score (ISS) ≥ 16 (severe injury was defined by an abbreviated injury score (AIS) ≥ 3) and ≥18 years of age. Injury- and patient-associated factors were correlated with the development of four complication clusters (surgery-related, infection, thromboembolic events and organ failure) and three mortality time points (immediate (6 h after admission), early (>6 h-72 h) and late (>72 h) mortality). Statistical analysis was performed using a Chi-square, Mann-Whitney U test, Cox hazard regression analysis and binominal logistic regression analysis. In total, 383 patients with a median ISS of 24 (interquartile range (IQR) 17-27) were included. The overall mortality rate (27.4%) peaked in the early mortality group. Lactate on admission significantly correlated with immediate and early mortality. Late mortality was significantly influenced by severe head injuries in patients with a moderate ISS (ISS 16-24). In patients with a high ISS (≥25), late mortality was influenced by a higher ISS, older age and higher rates of organ failure. Complications were observed in 47.5% of all patients, with infections being seen most often. The development of complications was significantly influenced by severe extremity injuries, the duration of mechanical ventilation and length of ICU stay. Infection remains the predominant posttraumatic complication. While immediate and early mortality is mainly influenced by the severity of the initial trauma, the rates of severe head injuries influence late mortality in moderate trauma severity, while organ failure remains a relevant factor in patients with a high injury severity.

Prehospital Trauma Scoring Systems for Evaluation of Trauma Severity and Prediction of Outcomes

INTRODUCTION

Trauma scoring systems in prehospital settings are supposed to ensure the most appropriate in-hospital treatment of the injured.

AIM OF THE STUDY

To determine the sensitivity and specificity of the CRAMS scale (circulation, respiration, abdomen, motor and speech), RTS score (revised trauma score), MGAP (mechanism, Glasgow Coma Scale, age, arterial pressure) and GAP (Glasgow Coma Scale, age, arterial pressure) scoring systems in prehospital settings in order to evaluate trauma severity and to predict the outcome.

MATERIALS AND METHODS

A prospective, observational study was conducted. For every trauma patient, a questionnaire was initially filled in by a prehospital doctor and these data were subsequently collected by the hospital.

RESULTS

The study included 307 trauma patients with an average age of 51.7 ± 20.9. Based on the ISS (injury severity score), severe trauma was diagnosed in 50 (16.3%) patients. MGAP had the best sensitivity/specificity ratio when the obtained values indicated severe trauma. The sensitivity and specificity were 93.4 and 62.0%, respectively, for an MGAP value of 22. MGAP and GAP were strongly correlated with each other and were statistically significant in predicting the outcome of treatment (OR 2.23; 95% Cl 1.06-4.70; p = 0.035). With a rise of one in the MGAP score value, the probability of survival increases 2.2 times.

CONCLUSION

MGAP and GAP, in prehospital settings, had higher sensitivity and specificity when identifying patients with a severe trauma and predicting an unfavorable outcome than other scoring systems.

Comparison the Ability of Quantitative Trauma Severity Assessment Methods Based On GAP, RTS, and ISS Criteria in Determining the Prognosis of Accidental Patients

Objective

To compare the ability of quantitative trauma severity assessment methods based on Glasgow coma scale, age, and arterial pressure (GAP), revised trauma score (RTS), and injury severity score (ISS) criteria in determining the prognosis of accidental patients.

Methods

This cross-sectional study was performed on random patients referred to Imam Khomeini Hospital in Urmia from March 20, 2020 to September 21, 2020. The data were obtained by using a checklist includes items such as age, sex, respiration rate, oxygen saturation level, pulse rate, primary blood pressure, initial Glascow coma scale (GCS), patient outcome and injury to different parts of body. After collecting the data, it was entered into SPSS 18 and analyzed with the descriptive and analytical statistics include an independent t-test and receiver operating characteristic curve (ROC) curves.

Results

Out of 1930 studied patients, 365 (18.9%) were women and 1565 (81.1%) were men. The mean age of patients was 37.05±17.11 years and women were significantly older than men. The mortality rate was 4.8% and was significantly more in men compared to women. The mean blood pressure, GCS and oxygen saturation level were lower in deceased patients. The mean GAP, ISS and RTS values were 23.13±2.69, 4.07±3.82, 7.72±0.52, respectively. The mean values of GAP and RTS were significantly low in deceased patients whereas the mean ISS value was significantly high in the deceased patients. The Area under the curve (AUS) for ISS was greater than the other two scoring systems.

Conclusion

The findings of the current study showed that all three systems were adequately efficient to prognoses the final outcome in multi-trauma patients but the ISS measure was better than the other two criteria.