Discussion
Compared with national data, our cohort has less SAE and lower rates of additional intervention, and had lower risk-adjusted mortality. This is consistent with our hypothesis that performing SAE less frequently does not result in increased failure or mortality. This is in contrast to suggestions that SAE reduces the need for later interventions.23–25 32 36–38 The differences in initial SAE strategy may reflect a difference in patient populations as reflected in table 1. Although grading changes by the AAST may have changed the distribution of III–V injuries, we did not find a difference in our cohort when compared with the NTDB. Our grading criteria has stayed consistent with the guidelines as required. However, multivariate analysis verified increased utilization of SAE in the NTDB cohort (2.79 OR, 95% CI 1.68 to 4.66, p=0.000, online supplemental file 1) despite higher rates of ISS 25+ on univariate analysis in our cohort (table 1). Unmeasured variables may also contribute to this finding.
The failure of NOM and/or SAE may contribute to improving practice management in our clinical practices and nationally. Other than NTDB status, failure of NOM was associated with age 65+ years, more than one comorbidity, mechanism of injury, grade V spleen injury, and ISS 25+ while plasma transfusion was not significant (p=0.063) (table 3). Thus, patients with grade V spleen injury, increased comorbidities, age 65+ years, and complex injuries may be candidates for SAE and/or surgery. Many of these variables are non-modifiable factors related to older patients with comorbidities and complex injuries and thus may constitute a population of patients that may have poorer response to bleeding injuries or coagulopathy and require earlier risk stratification. In addition, older patients have an altered hemodynamic response that may underestimate the extent of their injuries and may reflect other institutional or cultural factors such as permissive hypotension, threshold for intervention (surgery or SAE), and other unmeasured confounders. Defining failure can be challenging, because in this case the definition of ‘failure’ is based the decision to make another intervention. The threshold to perform a procedure may vary center-by-center or surgeon-by-surgeon. Furthermore, there are likely interactions and associations within a center around decisions to perform SAE versus splenectomy. For example, a center that more frequently uses SAE may also have a lower threshold to operate. Therefore, interpreting any splenic injury data that uses failure should be interpreted with this nuance in mind. Compared with the Splenic Arterial Embolization to Avoid Splenectomy (SPLASH) trial where 35% of III–IV injuries require SAE after observation, we have rates of 8.9% in our cohort vs 23% in the NTDB.37 Given the structure of the trial when compared with our analytic methods which include some potentially unstable patients that may have received surgery and/or SAE and unclear end points determined for failure, our results are not directly comparable. However, we did find that in a real-world cohort a higher rate of NOM did not consequently result in a need for additional SAE, although our cohort patients do appear to be older than the SPLASH trial, for example, 41 (28–56) vs 30 (22–42).37 Thus, our results support the conclusion that delayed SAE does not necessarily result in increased failure rates of SAE.
Failure of SAE was associated with Shock Index >0.9 and 10+ units of blood in 24 hours (table 3). Thus, these two clinical variables may pose a viable stratification for early surgical intervention, especially for patients that may not meet the massive transfusion protocol early and continue to bleed at a slower rate in the first 24 hours. Although Shock Index has previously been validated as predictive for SAE failure, these two clinical variables have not been validated in combination.21 Further evaluation with a coagulopathy-based measurement such as TEG may allow for additional information on bleeding and failure risk.
Compared with national data, our cohort had lower risk-adjusted mortality (table 4). Although there was a higher rate of SAE in the NTDB, there was no difference in the utilization of surgery in multivariable analysis between cohorts (online supplemental file 2). Thus, our cohort had a higher rate of NOM and still had risk-adjusted lower mortality. Mortality was significantly associated with NTDB cohort (vs Stanford/SCVMC), age 65 years or older, non-private insurance, more than one comorbidity, mechanism of injury, ISS 25+, grade V injury, Shock Index >0.9, 10 or more units blood transfused in 24 hours, NOM, hospital complications, anticoagulant history, and the presence of any other severe abdominal injury as defined by abdominal AIS of 3 or more (table 4). Although abdominal injuries AIS ≥3 were associated with mortality, this variable was not associated with NOM failure, SAE failure, surgery utilization, or NOM utilization. However, patients with SAE were less likely to have AIS of 3 or more injuries (0.69, p=0.000) (online supplemental file 1). Although the effect of this variable on surgical intervention was not significant (online supplemental file 2), it is our opinion that other significant injuries in the abdomen may play a role in the choice of splenectomy. The association between mortality and the decision to forgo operative management for splenic injury is likely complicated by unmeasured confounders. For example, it may have been that those with severe traumatic brain injury (TBI) or those with Do not resuscitate/do not intubate (DNR/DNI) status were in the process of discussing goals of care. This would be difficult to discern from the data. Other confounding variables may have included other relevant factors such as perceived futility from other injuries. SAE and surgery appear to decrease the rate of mortality on multivariate analysis (table 4). However, we do not believe that intervention alone is the cause for this effect. For example, in our sensitivity analyses we found that our cohort has higher rates of NOM, lower rates of SAE, and no difference in surgery when accounting for confounding clinical variables (online supplemental file 1). However, our cohort still does appear to have lower mortality when compared with the NTDB, again accounting for confounding clinical variables (table 4). Thus, it appears there may be unmeasured confounders in NOM that may result in improved outcomes in addition to using intervention on appropriate risk stratified patients. Due to the limitations of the study, we are unable to recommend or state that more conservative approach may be warranted in certain cases and should be considered alongside clinical and patient factors. One of the three risk factors for mortality are shared with the risk of SAE failure, thus, these patients may be early candidates for surgical intervention rather than SAE. Further validation of a coagulopathy or bleeding risk-related early surgical intervention model may provide further evidence on preventing early mortality after non-penetrating injury in trauma with BSI.
Limitations of this study include inability to measure coagulopathy directly, between-cohort differences, differing time period of patient management, for example, 2010–2020 (Stanford/SCVMC) vs 2018 (NTDB), and inability to account for management after index discharge. Stevens et al did find that TEG-directed management of blunt organ injury in pediatric patients may improve outcomes.34 However, this finding has not been replicated in adult patients and we lacked the data to validate this finding. The differences between cohorts were accounted for by using multivariate analyses conducted in this study to validate our findings on initial management, failure, and mortality. However, unmeasured confounders such as differences in medical management could not be accounted for based on the design of this study. In addition, our study was not designed with the intent of understanding the causes of mortality in BSI and this finding requires further study in an appropriately designed cohort. For example, unmeasured confounders include TBI, DNR/DNI status, futility, and other factors that may have resulted in low rates of surgery in the non-operative cohort. Finally, the time period of data collection was different and may reflect a difference in practice. Although this may influence the overall rates of utilization of practices such as SAE, it would not explain differences in mortality or failure of initial management strategy. Furthermore, the predictors of failure of SAE primarily used data from the NTDB cohort due to the requirements of multivariable logistic regression and sample size. Although additional interventions or treatments may have occurred after initial discharge, the data analyzed from both cohorts are similarly reported and neither included data for follow-up in our analysis. However, this clinical question was assessed with the clinical trial conducted by Arvieux et al with 1-month follow-up of treatment and injury.37