Examining the impact of small bowel resection procedure timing in patients with blunt traumatic injury: a propensity-matched analysis
- 36 Downloads
The purpose of this study was to evaluate the impact of the timing of small bowel resection in small bowel injury on patients’ outcomes.
This study was performed using data from patients included in the National Trauma Data Bank (2007–2010) who sustained blunt injuries and underwent a small bowel resection (SBR) within 24 h of arrival to the hospital. The patients’ characteristics and outcomes were compared between two groups: SBR within 4 h (Group 1) and SBR between 4 and 24 h (Group 2) using Chi-square, Fisher exact, and Wilcoxon rank-sum tests. However, in an attempt to better balance the groups, propensity score matching was performed using baseline characteristics and a follow-up paired analysis was performed using McNemar, Stuart-Maxwell, and Wilcoxon signed-rank tests.
A total of 1774 patients qualified for the study. Of those, 1,292 (72.8%) patients underwent SBR within 4 h and 482 (27.2%) underwent SBR between 4 and 24 h after arrival. There were significant baseline differences between the two groups regarding Injury Severity Score (ISS) [Median (IQR)19 (10, 29) vs 14 (9, 25), P < 0.001], Glasgow Coma Scale (GCS) [15 (13, 15) vs 15 (15, 15), P < 0.001] and the proportion of patients with an initial systolic blood pressure (SBP) < 90 mmHg (18.3% vs 8.7%, P < 0.001). Given these clear differences, 482 patients from each group were pair-matched using propensity score matching on age, sex, race, ISS, GCS, and SBP. After matching, there were no significant differences observed in the matching variables, patient mortality rate (8.3% vs 7.9%, P = 0.90), or discharge disposition (home with no services: 63.1% vs 64.9%, P = 0.90); however, there was a significantly shorter hospital length of stay for those patients in Group 1 compared to Group 2 [9 (6, 15) vs 10 (7, 19), P = 0.03].
More than 70% of the patient cases examined underwent SBR within 4 h of hospital arrival. However, there were no significant differences identified in the mortality rate or the discharge disposition regardless of the timing of the SBR (≤ 4 vs > 4–24 h). However, the patients whose SBR was performed within 4 h of arrival had a lower hospital length of stay when compared with those whose procedure was delayed.
KeywordsBlunt trauma Small bowel injury Timing of small bowel resection Mortality
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
All procedures followed were in accordance with the ethical standards of the Institutional Review Board of Meridian Health and with the Helsinki Declaration of 1975, as revised in 2008. Since the study was done using a de-identified National database from the American College of Surgeons that is available to all researchers, this study was exempted from IRB review as per policy.
Given that this study was done using a de-identified National database from the American College of Surgeons that is available to all researchers, this study was exempted from IRB review as per policy and no informed consent was required.
- 1.Fakhry SM, Brownstein M, Watts DD, Baker CC, Oller D. Relatively short diagnostic delays (< 8 hours) produce morbidity and mortality in blunt small bowel injury: an analysis of time to operative intervention in 198 patients from a multicenter experience. J Trauma. 2000;48(3):408–15.CrossRefGoogle Scholar
- 14.Daniel E, Ho K, Imai G, King EA, Stuart. MatchIt: nonparametric preprocessing for parametric causal inference. J Stat Softw. 2011;42(8):1–28. http://www.jstatsoft.org/v42/i08/. Accessed 30 Sept 2015.
- 15.Hothorn T, Hornik K, Van De Wiel MA, Zeileis A. Implementing a class of permutation tests: the coin package. J Stat Softw. 2008;28(8):1–23. http://www.jstatsoft.org/v28/i08/>. Accessed 18 Sept 2015.
- 16.Terry Therneau. A package for survival analysis in R. R package version 2.38-3. 2015. http://CRAN.R-project.org/package=survival.
- 17.Terry M, Therneau, Patricia M, Grambsch. Modeling survival data: extending the cox model. New York: Springer; 2000. ISBN 0-387-98784-3.Google Scholar
- 18.R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 2014. http://www.R-project.org/.
- 19.StataCorp. Stata statistical software: release 13. College Station: StataCorp LP; 2013.Google Scholar