Prognostic analysis of patients with blunt chest trauma admitted to an intensive care unit

Which criteria is a better predictor of ICU admission in trauma patients? An artificial neural network approach

PURPOSE

One of the most critical concerns in the intensive care unit (ICU) section is identifying the best criteria for entering patients to this part. This study aimed to predict the best compatible criteria for entering trauma patients in the ICU section.

METHOD

The present study was a historical cohort study. The data were collected from 2448 trauma patients referring to Shahid Rajaee Hospital between January 2015 and January 2017 in Shiraz, Iran. The artificial neural network (ANN) models with cross-validation and logistic regression (LR) with a backward method was used for data analysis. The final analysis was performed on a total of 958 patients who were transferred to the ICU section.

RESULTS

Based on the present results, the motor component of the GCS score at each cutoff point had the highest importance. The results also showed better performance for the AUC and accuracy rate for ANN compared with LR.

CONCLUSION

The most critical indicators in predicting the optimal use of ICU services in this study were the Motor component of the GCS. Results revealed that the ANN had a better performance than the LR in predicting the main outcomes of the traumatic patients in both the accuracy and AUC index. Trauma section surgeons and ICU specialists will benefit from this study's results and can assist them in making decisions to predict the patient outcomes before entering the ICU.

Thoracic Trauma Severity score on admission allows to determine the risk of delayed ARDS in trauma patients with pulmonary contusion

BACKGROUND

Pulmonary contusion is a major risk factor of acute respiratory distress syndrome (ARDS) in trauma patients. As this complication may appear after a free interval of 24-48 h, detection of patients at risk is essential. The main objective of this study was to assess the performance of the Thoracic Trauma Severity (TTS) score upon admission in predicting delayed ARDS in blunt trauma patients with pulmonary contusion.

METHODS

All blunt thoracic trauma patients admitted consecutively to our trauma centre between January 2005 and December 2009 were retrospectively included if they presented a pulmonary contusion on the admission chest computed tomography scan. Main outcome measure was the presence of moderate or severe ARDS (PaO2/FiO2 ratio≤200) for 48 h or more. The global ability of the TTS score to predict ARDS was studied by ROC curves with a threshold analysis using a grey zone approach.

RESULTS

Of 329 patients studied (75% men, mean age 36.9 years [SD 17.8 years], mean Injury Severity Score 21.7 [SD 16.0]), 82 (25%) presented with ARDS (mean lowest PaO2/FiO2 ratio of 131 [SD 34]). The area under the ROC curves for the TTS score in predicting ARDS was 0.82 (95% CI 0.78-0.86) in the overall population. TTS scores between 8 and 12 belonged to the inconclusive grey zone. A TTS score of 13-25 was found to be independent risk factors of ARDS (OR 25.8 [95% CI 6.7-99.6] P<0.001).

CONCLUSIONS

An extreme TTS score on admission accurately predicts the occurrence of delayed ARDS in blunt thoracic trauma patients affected by pulmonary contusion. This simple score could guide early decision making and management for a non-negligible proportion of this specific population.

Risk Score for Predicting Mortality in Flail Chest

BACKGROUND

Flail chest injuries are associated with high mortality and morbidity. Despite evidence that operative repair of flail chest is beneficial, it is rarely done. We sought to create a simple risk score using available preoperative covariates to calculate individual risk of mortality in flail chest.

METHODS

A logistic regression model was trained on Ontario Trauma Registry data to generate a mortality risk score. The final model was validated for calibration and discrimination and corrected for optimism.

RESULTS

The model uses five risk factors that are readily obtained during the initial assessment of the trauma patient: age, Glasgow Coma Score, ventilation, cardiopulmonary resuscitation, and number of comorbidities. It was determined that less than 6 points is consistent with 1% observed mortality, 6 to 10 points predicts 5% mortality, 11 to 15 points predicts 22% mortality, and 16 or more points predicts 46% mortality.

CONCLUSIONS

We have developed a simple model that can be easily applied at bedside to predict mortality in patients with flail chest by accessing a spreadsheet program in an application or other handheld computer device. This model has the potential to be a useful tool for surgeons considering operative repair of flail chest.

Comparison of different thoracic trauma scoring systems in regards to prediction of post-traumatic complications and outcome in blunt chest trauma

BACKGROUND

As accurate assessment of thoracic injury severity in the early phase after trauma is difficult, we compared different thoracic trauma scores regarding their predictive ability for the development of post-traumatic complications and mortality.

MATERIALS AND METHODS

Two hundred seventy-eight multiple trauma patients (ISS ≥ 16) age > 16 y with severe blunt chest trauma (AIS(chest) ≥ 3) admitted between 2000 and 2009 to Level I Trauma center were included. Exclusion criteria were severe traumatic brain injury (AIS(head) ≥ 3) and penetrating thoracic trauma. The association between AIS(chest), Pulmonary Contusion score (PCS), Wagner-score and Thoracic Trauma Severity score (TTS), and duration of ventilation, length of ICU stay, development of post-traumatic complications, and mortality was investigated. Statistical analysis was performed with χ(2)-test, ANOVA, logistic regression, and receiver operating characteristic (ROC) curve.

RESULTS

Patients' mean age was 42.7 ± 17.0 y, the mean injury severity score was 28.7 ± 9.3 points. Overall, 60 patients (21.6%) developed ARDS, 143 patients (51.4%) SIRS, 110 patients (39.6%) sepsis, and 36 patients (13.0%) MODS. Twenty-two patients (7.9%) died. Among the examined thoracic trauma scores only the TTS was an independent predictor of mortality. With the TTS showing the best prediction power, the TTS, PCS, and Wagner-score were independent predictors of ventilation time, length of ICU stay, and the development of post-traumatic ARDS and MODS.

CONCLUSIONS

Thoracic trauma scores combining anatomical and physiologic parameters like the TTS seem to be most suitable for severity assessment and prediction of outcome in multiple trauma patients with concomitant blunt chest trauma.

Epidemiology of Sternal Fractures

The epidemiology of sternal fractures has been poorly described. The objective of this study was to examine the demographics, outcomes and injuries associated with sternal fractures. The trauma registry at a level I trauma center was retrospectively reviewed to identify all patients with sternal fractures over a 10 year period. Demographic data collected included age, gender, mechanism of injury and injury severity score. Patients were analyzed according to age ≤ 55 or > 55 years. During the 10-year study period, a total of 37,087 patients were admitted to the emergency department. Of these, 125 (0.33%) had a sternal fracture. The average age was 44 ± 17 years, with 76.0 per cent being male. The most common mechanism of injury was motor vehicle collision (68%) followed by auto vs. pedestrian (18%). Associated rib fractures occurred in 49.6% of the population, cardiac contusions in 8.0%, thoracic aortic injuries in 4.0 per cent and heart lacerations in 2.4 per cent of patients. Associated rib fractures were more likely to occur in patients over the age of 55 (66.7% vs 44.2%, P = 0.032) as well as a traumatic hemothorax (15.8% vs 40.0%, P = 0.005). However, no significant difference in mortality was observed between the two age groups (16.8% vs. 26.7%, OR: 0.56, 95% CI, 0.21 to 1.47; P = 0.234). Sternal fractures are a rare sequela of blunt trauma. Associated injuries are common, including rib fractures and soft tissue contusions. Associated cardiac and aortic injuries are rare but highly lethal and should be screened for on the initial chest CT scan. After appropriate exclusion of associated injuries, the majority of patients diagnosed with a sternal fracture following blunt trauma can be safely discharged to home.