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Multicenter Study
. 2020 Jun 19:2020:1219439.
doi: 10.1155/2020/1219439. eCollection 2020.

Demographic, Clinical Features and Outcome Determinants of Thoracic Trauma in Sri Lanka: A Multicentre Prospective Cohort Study

Affiliations
Multicenter Study

Demographic, Clinical Features and Outcome Determinants of Thoracic Trauma in Sri Lanka: A Multicentre Prospective Cohort Study

Yasith Mathangasinghe et al. Can Respir J. .

Abstract

Prognostic determinants in thoracic trauma are of major public health interest. We intended to describe patterns of thoracic trauma, demographic factors, clinical course, and predictors of outcome in selected tertiary care hospitals in Sri Lanka. A multicentre prospective cohort study was conducted in five leading teaching hospitals from June to September 2017. Patients with thoracic trauma were followed up during the hospital stay. A logistic regression analysis was conducted using in-hospital morbidity as the dichotomous outcome variable. One hundred seventy-one patients were included in the study yielding 1450 (median = 8.5) person-days of observation. Of them, 71.9% (n = 123) were males. The mean age was 45.8 ± 17.9 years. Majority (39.2%, n = 67) were recruited from the National Hospital of Sri Lanka. Automobile accidents were the commonest (62.6%, n = 107), followed by falls (26.9%, n = 46), assaults (8.8%, n = 15), and animal attacks (1.8%, n = 3). The ratio of blunt to penetrating trauma was 5.6 : 1. Injury patterns were rib fractures (80.7%, n = 138), haemothorax (44.4%, n = 76), pneumothorax (44.4%, n = 76), lung contusion (22.8%, n = 39), flail segment (15.8%, n = 27), tracheobronchial trauma (7.0%, n = 12), diaphragmatic injury (2.3%, n = 4), vascular injury (2.3%, n = 4), cardiac contusions (1.1%, n = 2), and oesophageal injury (0.6%, n = 1). Ninety nine (57.9%) had extrathoracic injuries. Majority (63.2%, n = 108) underwent operative management including intercostal tube insertion (60.8%, n = 104), wound exploration (6.4%, n = 11), thoracotomy (4.1%, n = 7), rib reconstruction (4.1%, n = 7), and video-assisted thoracoscopic surgery (2.9%, n = 5). Pneumonia (10.5%, n = 8), bronchopleural fistulae (2.3%, n = 4), tracheaoesophageal fistulae (1.8%, n = 3), empyema (1.2%, n = 2), and myocardial infarction (1.2%, n = 2) were the commonest postoperative complications. The mean hospital stay was 15.6 ± 18.0 days. The in-hospital mortality was 11 (6.4%). The binary logistic regression analysis with five predictors (age, gender, mechanism of injury (automobile/fall/assault), type of trauma (blunt/penetrating), and the presence of extrathoracic injuries) was statistically significant to predict in-hospital morbidity (X 2 (6, n = 168) = 13.1; p=0.041), explaining between 7.5% (Cox and Snell R 2) and 14.5% (Nagelkerke R 2) of variance. The automobile accidents (OR: 2.3, 95% CI = 0.2-26.2) and being males (OR: 2.3, 95% CI = 0.6-9.0) were the strongest predictors of morbidity.

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Conflict of interest statement

The authors declare that they have no conflicts of interest.

Figures

Figure 1
Figure 1
A bar chart illustrating the types of thoracic injuries diagnosed among the study participants (n = 171). Of those who had unilateral rib fractures, left hemithoracic fractures (n = 73) outnumbered right hemithoracic fractures (n = 49). Seventeen patients had bilateral rib fractures. All the tracheal injuries (n = 7) were located at the carinal level while all the bronchial injuries (n = 5) were lateralized to the left side. Vascular injuries were comprised of two subclavian arterial and two brachiocephalic arterial injuries. One patient had a mid-oesophageal level injury.
Figure 2
Figure 2
Factors associating with the length of the hospital stay. (a) A bar chart comparing the mean hospital stay in different types of injuries. The level of significance of the independent sample t-tests comparing the mean hospital stay depending on the presence or the absence of the individual injury type is denoted above each pair of columns. (b) A bar chart comparing the mean hospital stay in blunt and penetrating trauma. (c) A scatter plot illustrating a positive correlation between the length of the hospital stay and the number of body regions affected. Pearson's correlation coefficient r= 0.293, p=0.004. Note: the affected regions of the body were categorized as the head and neck, thorax, abdomen, pelvis, and extremities. Error bars indicate the standard error of the means (SEM). ns, not significant; p < 0.05; ∗∗p < 0.01.

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