To Study Prediction of Outcome of Chest Trauma Using Chest Trauma Scoring System at Tertiary Care Centre
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Abstract
Background: Aim of this study is to investigate CTS-based prognostic and predictive outcomes in individuals with chest injuries following chest trauma. Methods: This prospective observational study conducted at a tertiary care center in India involved 70 patients with thoracic trauma. Upon admission to the emergency department or trauma unit, a comprehensive clinical evaluation was carried out, which included a detailed history, vital signs, and necessary investigations such as chest radiographs and computed tomography (CT) or high-resolution CT (HRCT) of the chest, provided the patient's hemodynamics were stable. The study utilized four key factors—age, pulmonary contusion identified via HRCT, the total number of rib fractures, and the presence of bilateral rib fractures—to calculate the chest trauma score. Results: Seventy cases were analyzed, revealing 50 survivors and 20 non-survivors. Survivors had an average age of 45.52 years, compared to 35.45 years for non-survivors. The gender ratio was 60% male among survivors and 70% among non-survivors. Notable physiological factors for non-survivors included higher pulse rates (130.66 bpm vs. 113.48 bpm), lower blood pressures (SBP 93.33 mmHg, DBP 59 mmHg), and increased respiratory rates (29/min vs. 23.86/min). Key mortality predictors were chest symmetry, subcutaneous emphysema, and a need for intubation, with 75% of non-survivors requiring airway intervention. Pneumonia was present in 75% of non-survivors. A correlation between GCS scores showed survivors averaged 15.60 compared to 12.20 for non-survivors. Bilateral fractures linked to higher pain and reduced quality of life, whereas fewer or unilateral fractures supported recovery. Conclusion: The chest trauma scoring system effectively predicts outcomes in thoracic injury patients, correlating higher scores with increased severity, intervention needs, and mortality rates. Key clinical parameters, including vital signs and complications like pneumonia, improve its predictive accuracy, enabling early identification of high-risk patients and facilitating timely management for better outcomes.
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Copyright (c) 2026 Dr. Brijesh Kumar Shukla, Dr. Rahul Agarwal, Dr. Sayiad Alim Hussan
This work is licensed under a Creative Commons Attribution 4.0 International License.
Creative Commons License All articles published in Annals of Medicine and Medical Sciences are licensed under a Creative Commons Attribution 4.0 International License.
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