Distribution of shock index and age shock index score among trauma patients in India

Shock Index for the Prediction of Interventions and Mortality in Patients With Blunt Thoracic Trauma

INTRODUCTION

Shock index (SI) is a bedside simple scoring tool; however, it has not yet been tested in blunt thorax trauma (BTT). We sought to evaluate the prognostic value of SI for chest interventions (thoracostomy tube or thoracotomy), blood transfusion, and mortality in patients with BTT. We hypothesized that high SI is associated with worse outcomes in patients with BTT.

METHODS

We conducted a retrospective analysis of all BTT patients (chest Abbreviated Injury Score [AIS] > 1) hospitalized in a level 1 trauma center between 2011 and 2020. Patients with AIS >1 for head or abdominal injuries and patients undergoing open reduction and internal fixation surgery or penetrating injuries were excluded. Patients were categorized into two groups (low SI <0.80 versus high SI ≥0.80) based on the receiver operating characteristic curve analysis. Multivariable regression analysis was performed to identify the predictors of mortality.

RESULTS

A total of 1645 patients were admitted with BTT; of them, 24.5% had high SI. The mean age was 39.2 ± 15.2 y, and most were males (91%). Patients with high SI were younger, had sustained severer injuries, and required more chest interventions (P = 0.001), blood transfusion (P = 0.001), and massive transfusion protocol activation (P = 0.001) compared with low SI group. The overall in-hospital mortality rate was 2.6%, which was more in the high SI group (8.2% versus 0.8%; P = 0.001). SI significantly correlated with age (r = -0.281), injury severity score (r = 0.418), Glasgow Come Score on arrival (r = -0.377), Trauma and Injury Severity Score (r = -0.144), Revised Trauma Score (r = -0.219), serum lactate (r = 0.434), blood transfusion units (r = 0.418), and chest AIS (r = 0.066). SI was an independent predictor of mortality (odds ratio 3.506; 95% confidence interval 1.389-8.848; P = 0.008), and this effect persisted after adjustment for chest intervention (odds ratio 2.923; 95% confidence interval 1.146-7.455; P = 0.02).

CONCLUSIONS

The present study highlights the prognostic value of SI as a rapid bedside tool to predict the use of interventions and the risk of mortality in patients with BTT. The study findings help the emergency physicians for early and appropriate risk stratification and triaging of patients with BTT.

An Analysis of 30-Day in-Hospital Trauma Mortality in Four Urban University Hospitals Using the Australia India Trauma Registry

Background

India has one-sixth (16%) of the world’s population but more than one-fifth (21%) of the world’s injury mortality. A trauma registry established by the Australia India Trauma Systems Collaboration (AITSC) Project was utilized to study 30-day in-hospital trauma mortality at high-volume Indian hospitals.

Methods

The AITSC Project collected data prospectively between April 2016 and March 2018 at four Indian university hospitals in New Delhi, Mumbai, and Ahmedabad. Patients admitted with an injury mechanism of road or rail-related injury, fall, assault, or burns were included. The associations between demographic, physiological on-admission vitals, and process-of-care parameters with early (0–24 h), delayed (1–7 days), and late (8–30 days) in-hospital trauma mortality were analyzed.

Results

Of 9354 patients in the AITSC registry, 8606 were subjected to analysis. The 30-day mortality was 12.4% among all trauma victims. Early (24-h) mortality was 1.9%, delayed (1–7 days) mortality was 7.3%, and late (8–30 days) mortality was 3.2%. Abnormal physiological parameters such as a low SBP, SpO2, and GCS and high HR and RR were observed among non-survivors. Early initiation of trauma assessment and monitoring on arrival was an important process of care indicator for predicting 30-day survival.

Conclusions

One in ten admitted trauma patients (12.4%) died in urban trauma centers in India. More than half of the trauma deaths were delayed, beyond 24 h but within one week following injury. On-admission physiological vital signs remain a valid predictor of early 24-h trauma mortality.

Pattern and Distribution of Shock Index and Age Shock Index Score Among Trauma Patients in Towards Improved Trauma Care Outcomes (TITCO) Dataset

OBJECTIVE

To compare the shock index (SI - which is the ratio of heart rate to systolic blood pressure) and Age SI (Age in years multiplied by SI) with survival outcome of the patients across multicenter trauma registry in India.

METHODS

Study is based on Towards Improved Trauma Care Outcomes (TITCO) project. Records with valid details of age, heart rate, systolic blood pressure, Injury Severity Scale (ISS) and Glasgow Coma Scale (GCS) score was considered. SI was categorized into four groups; Group I (SI<0.6) as no shock, group II (SI ≥0.6 to <1.0) as mild shock, group III (SI ≥1.0 to <1.4) as moderate shock and group IV (SI ≥1.4) as severe shock. Age SI was categorized decade wise into six groups. Mortality was dependent variable. GCS and ISS were considered as secondary variables.

RESULTS

10843 participants from TITCO registry satisfying inclusion-exclusion criteria were considered for study. Mean SI score in group I to IV was increasing with 0.53 to 1.72 respectively. Age SI was seen to be increasing across its six groups. Gender wise no difference was found among SI group. For severe ISS and critical ISS, mortality in SI group IV was 50% and 56 % respectively. Mortality was increasing across mild to severe GCS among all SI groups.

CONCLUSION

The categorized SI and Age SI had shown increase in death percentages from mild to severe severity of injuries. Similar to GCS and ISS, SI and Age SI should also be calculated and categorized in all health care and further plan for management aspects.