Open Access

Computed tomography during initial management and mortality among hemodynamically unstable blunt trauma patients: a nationwide retrospective cohort study

  • Yusuke Tsutsumi1, 3,
  • Shingo Fukuma1,
  • Asuka Tsuchiya2, 3,
  • Tatsuyoshi Ikenoue1,
  • Yosuke Yamamoto1,
  • Sayaka Shimizu1,
  • Miho Kimachi1 and
  • Shunichi Fukuhara1Email author
Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine201725:74

https://doi.org/10.1186/s13049-017-0396-7

Received: 23 October 2016

Accepted: 11 May 2017

Published: 19 July 2017

Abstract

Background

Although many hemodynamically unstable trauma patients undergo computed tomography (CT) to identify a source of bleeding, this practice is currently only recommended by a few guidelines. To clarify whether CT has harmful effects among these patients, we examined the association between CT during initial management and mortality among unstable blunt trauma patients.

Methods

This was a retrospective cohort study based on Japan Trauma Data Bank 2004–2014 registry data. Study population was adult blunt trauma patients with hypotension on arrival. The primary outcome was the in-hospital mortality. Two types of analyses were performed to adjust for confounding factors including propensity score inverse probability of treatment weighted (IPTW) and instrumental variable (IV) analysis.

Results

Among 5,809 patients who met inclusion criteria, 5,352 (92.1%) underwent CT. The No CT group was more likely to have severe physiological conditions and lower probability of survival than those of the CT group. In IPTW analysis adjusting for measured confounders, we found a significant protective effect of undergoing CT on in-hospital mortality (excess deaths: −20.6 per 100 patients, 95% CI −26.2 to −14.9). In IV analysis adjusting both for measured and unmeasured confounders, the association between CT and mortality was not statistically significant (excess deaths: −4.1 per 100 patients, 95% CI −23.1 to 14.8).

Discussion

We did not find clinically meaningful harmful effect of CT on survival for unstable blunt trauma patients even after adjusting both for measured and unmeasured confounders.

Conclusions

Our results did not support the recommendation of current guideline. We suggest physicians should consider CT as one of the diagnostic options even when patients are unstable.

Keywords

TomographyX-Ray computedMultiple traumaAdvanced trauma life support care/SNShockMortalityPrognosis

Background

Recently, computed tomography (CT) has become a standard initial diagnostic procedure in the management of severe trauma [14]. Accordingly, physicians sometimes perform CT on hemodynamically unstable patients, especially for blunt trauma cases, in order to identify a source of bleeding and assess for occult internal injury. However, CT has not been recommended for hemodynamically unstable trauma patients by most clinical guidelines [57]. Some have even called CT the “tunnel of death” for unstable patients [8].

Conventionally, examining these patients with CT has not been recommended according to the following reasons; 1) transporting patients to the CT scanner itself may compromise their condition, 2) resuscitation of patients in the CT room during a scan may be difficult, and 3) CT acquisition may delay definitive care.

However, evidence on the effectiveness of CT for unstable patients is inconsistent. Since 2010, one large-scale observational study has revealed the benefits of Whole-body CT (WBCT) for unstable patients [9]. In contrast, another study showed that CT was associated with a negative outcome among preoperative abdominal trauma patients [10], while other studies showed no significant association between CT and mortality [1113]. Therefore, whether CT is really harmful for hemodynamically unstable patients remains in question.

In this study, we examined the association between CT and mortality among unstable blunt trauma patients using nationwide Japanese registry data, to clarify whether CT has harmful effect among these patients after adjusting both for measured and unmeasured confounders.

Methods

Study population

We performed a retrospective cohort study using Japan Trauma Data Bank (JTDB) for the years 2004–2014. The JTDB is a nationwide database of trauma patients maintained since 2004 by the Japanese Association of Trauma Surgery and the Japanese Association for Acute Medicine [14], and is one of the largest trauma registries in the world [15]. By 2014, 244 emergency hospitals voluntarily participated in this registry, most of which (81.1%) are emergency and critical centers that have equivalent role to level 1 trauma centers in the USA. These participating facilities use a Web system to collect patient data, including age and sex; vital signs on arrival, including systolic blood pressure (SBP), diastolic blood pressure (DBP), respiratory rate (RR), heart rate (HR) and Glasgow Coma Scale (GCS); type of trauma (blunt or penetrating); severity of injury using the Injury Severity Score (ISS), Revised Trauma Score (RTS) and Probability of Survival using Trauma and the Injury Severity Score (TRISS Ps) methods; CT data; and the status at discharge of each patient. Each physician enters these data without any personal information to achieve anonymization. Because we used anonymous registry data, the requirement for informed consent was waived. This study was fully approved by the ethics committee of Kyoto University School of Medicine.

Patient selection and definitions

We included all blunt trauma patients with hypotension (SBP < 90 mmHg) on arrival. We excluded pediatric patients aged < 16 years, patients who were transferred from other facilities, and patients who suffered cardiac arrest (no heart rate; no respiratory rate; and no palpable pulse) or near-arrest (SBP ≤ 40 mmHg; based on the JTDB registration criteria that blood pressure cannot be measured at 40 mmHg SBP but a pulse is palpable) on arrival. We also excluded patients with missing data on items such as prognosis, CT information, and date of admission, as well as patients treated in facilities that had small volumes of eligible patients (<10 patients) during the study period, because we used a facility’s likelihood of performing CT as a potential instrument for instrumental variable (IV) analysis.

The primary predictor

The primary predictor was use of CT during initial management of trauma. We defined patients undergoing CT of at least one body region as the “CT group” and patients not undergoing CT as the “No CT group.” Therefore, patients undergoing whole-body CT and those undergoing selective CT were all included in the “CT group”.

Primary and secondary outcomes

The primary outcome of interest was in-hospital mortality. The secondary outcome was mortality within 24 h of arrival (24-h mortality). The outcome data of each patient was registered at the time of discharge or death.

Covariates

Factors considered clinically important to the prognosis of trauma patients that can be obtained from the National Trauma Data Bank include age, ISS, gender, SBP, mechanism or type of injury, GCS, head abbreviated injury scale (AIS), abdomen AIS, race, and insurance status [16]. Among these variables, we chose age, ISS, gender, SBP, and GCS as covariates in our models. We included heart rate on hospital arrival as a covariate because it is also known to predict mortality and is commonly used as a covariate [16, 17]. We also included year of injury because the mortality of trauma patients has decreased year by year in Japan [18].

We excluded mechanisms or types of injury because our study population was restricted to blunt trauma only. We also excluded head and abdomen AIS and because these variables are difficult to measure without CT. In Japan, the public health insurance system covers all citizens and the vast majority of citizens are Asian, so we did not consider race or insurance status.

Statistical analysis

First, we conducted a descriptive analysis of patients’ demographic data to compare the CT group to the No CT group. Continuous covariates were shown as mean (SD) and categorical covariates were expressed as numbers with percentage (%). We used Student’s t-test for continuous data and Pearson’s chi-squared test for categorical data for comparison. We also compared the distribution of clinically relevant covariates between the two groups.

Second, we estimated the number of excess deaths per 100 patients in the CT group compared to the No CT group as a reference by estimating the absolute risk differences of in-hospital and 24-h mortality between these two groups. We performed univariate analysis using a generalized linear model with identity link function for binomial outcomes. We also performed multivariate analysis using the inverse probability of treatment weighted (IPTW) estimator based on propensity score (PS) and IV analysis. We excluded patients with missing data for any covariate included in the model.

IPTW method

We used the IPTW method to adjust for measured confounders [19]. We estimated PS based on clinically important variables including age, sex, vital signs at hospital arrival (SBP, HR, GCS), ISS, and year of injury. We used a logistic regression model conditionally on these variables to calculate PS. Next, we calculated the inverse probability of treatment, i.e. 1/PS for the CT group and 1/(1-PS) for the No CT group, and used these inverse probabilities of treatment as weighting factors to produce a pseudo-population where the probability of undergoing CT was equivalent. Then, we estimated the effect of CT on in-hospital and 24-h mortality using a generalized linear model with an identity link function for a binomial outcome weighted by IPTW.

IV method

The IV method was also used to adjust for unmeasured confounders [20, 21]. An eligible instrument is a variable that is significantly associated with treatment selection and only affects patient outcome through this association (CT in this study). We chose the institutional preference of performing CT as a potential instrument. Practically, we defined our instrument as the number of the previous three admitted patients who underwent CT. This approach for defining preference by previous patients’ workup has been described previously [21, 22].

We confirmed the validity of the instrument by testing its association with our main predictor of the actual likelihood of performing CT using partial F-statistics. Partial F-statistics > 10 were regarded as valid instruments [23]. We also assumed that this instrument had no direct relation on our outcome.

We performed two-stage least squares estimation for the IV analysis. In the first-stage model, we estimated the probability of undergoing CT using least squares estimation conditional on IV and covariates including age, sex, SBP, HR, GCS on arrival, ISS, and year of injury. In the second-stage model, we estimated the effect of CT on in-hospital and 24-h mortality using a least squares estimation conditional on the probability of undergoing CT and the same covariates.

We performed sensitivity analysis using different definitions of instruments to confirm the robustness of our main analyses. Practically, we redefined our instruments as the total number of patients undergoing CT among the previous one, five, and seven patients as instruments.

Analyses were conducted using commercial software (STATA MP4 version 13.0®, StataCorp, College Station TX, USA).

Results

Characteristics of study subjects

A total of 198,744 patients were registered in the JTDB between January 2004 and December 2014. Of these, 6,915 patients were eligible adult blunt trauma patients with hypotension who were directly transported from the trauma site. Of these 6,915 patients, 1,106 were excluded because of missing data or ineligibility for IV analysis due to being treated in a small volume facility (<10). Eventually, 5,809 met our inclusion criteria (Fig. 1). Summary statistics of patient baseline demographics are shown in Table 1 and Table 2. Mean age of the whole population was 56.4 years old and 65.7% were male. At hospital arrival, mean SBP was 75.6 mmHg, HR was 93.4 beats/min and GCS was 11.3. Mean ISS was 26.0 and TRISS Ps was 0.67. Overall, 5352 patients (92.1%) underwent CT (CT group). Their crude in-hospital mortality was 25.5% (Table 1). A total of 1,239 (22.4%) patients showed positive Focused Assessment Sonography for Trauma (FAST) findings. The CT group showed higher SBP, RTS, TRISS Ps, a lower proportion of positive FAST results, and a lower HR than the No CT group (Table 2). There was sufficient overlap in the distribution of these covariates and propensity scores, indicating the validity of comparing these two groups (Additional file 1: Figure S1, Additional file 2: Figure S2).
Fig. 1

Flow chart reveals the reason for, and number of, patient exclusions

Table 1

Baseline characteristics of overall study population

Characteristics

Total

Missing

(n = 5,809)

n (%)

Age, mean (SD), years

56.4 (20.7)

 

Gender, male (%)

3,813 (65.7)

1 (0.02)

Year of the injury (%)

 2004

164 (2.8)

 

 2005

197 (3.4)

 

 2006

160 (2.8)

 

 2007

339 (5.8)

 

 2008

493 (8.5)

 

 2009

550 (9.5)

 

 2010

674 (11.6)

 

 2011

765 (13.2)

 

 2012

907 (15.6)

 

 2013

862 (14.8)

 

 2014

698 (12.0)

 

Arrival vital signs, mean (SD)

 SBP a , mmHg

75.6 (10.1)

 

 DBP b , mmHg

47.0 (12.2)

952 (16.4)

 RR c , breaths/min

24.0 (8.2)

563 (9.7)

 HR d , beats/min

93.4 (28.0)

81 (1.4)

 GCS e

11.3 (4.3)

269 (4.6)

Severity, mean (SD)

 ISS f

26.0 (15.2)

146 (2.5)

 RTS g

5.87 (1.41)

740 (12.7)

 TRISS Ps h

0.67 (0.31)

899 (15.5)

 Underwent CT (%)

5,352 (92.1)

 

 FAST i , positive (%)

1,239 (22.4)

284 (4.9)

Death (%)

 In-hospital

1,483 (25.5)

 

 Death within 24 h

802 (14.5)j

 

a SBP, systolic blood pressure; b DBP, diastolic blood pressure; c RR, respiratory rate; d HR, heart rate; e GCS, Glasgow Coma Scale; f ISS, Injury Severity Score; g RTS, Revised Trauma Score; h TRISS Ps, Trauma Revised Injury Severity Score Probability of Survival; i FAST, Focused Assessment Sonography for Trauma

j280 dead patients with missing time of death data were excluded from the numerator

Table 2

Baseline characteristics of the CT group and No CT group

Characteristics

CT group

No CT group

 

(n = 5,352)

(n = 457)

p value

Age, mean (SD), year

56.2 (21.8)

58.7 (20.6)

0.013

Gender, male (%)

3,535 (66.1)

278 (60.8)

0.024

Year of injury

 2004

148 (2.8)

16 (3.5)

<0.001

 2005

172 (3.2)

25 (5.5)

 2006

140 (2.6)

20 (4.4)

 2007

301 (5.6)

38 (8.3)

 2008

437 (8.2)

56 (12.3)

 2009

516 (9.6)

34 (7.4)

 2010

622 (11.6)

52 (11.4)

 2011

712 (13.3)

53 (11.6)

 2012

852 (15.9)

55 (12.0)

 2013

802 (15.0)

60 (13.1)

 2014

650 (12.1)

48 (10.5)

Arrival vital signs, mean (SD)

 SBP a , mmHg

75.8 (10.0)

73.6 (11.1)

<0.001

 DBP b , mmHg

47.1 (12.1)

45.1 (13.7)

0.003

 RR c , breaths/min

23.9 (8.2)

24.6 (8.6)

0.079

 HR d , beats/min

92.9 (27.7)

99.2 (31.2)

<0.001

 GCS e

11.4 (4.3)

10.9 (4.8)

0.008

Severity, mean (SD)

 ISS f

26.2 (15.1)

23.9 (16.8)

0.002

 RTS g

5.89 (1.40)

5.54 (1.57)

<0.001

 TRISS Ps h

0.68 (0.31)

0.64 (0.34)

0.047

 FAST i , positive (%)

1,088 (21.4)j

151 (35.2)j

<0.001

Death (%)

 In-hospital

1,276 (23.8)

207 (45.3)

<0.001

 Death within 24 h

655 (12.8)k

147 (34.9)k

<0.001

a SBP, systolic blood pressure; b DBP, diastolic blood pressure; c RR, respiratory rate; d HR, heart rate; e GCS, Glasgow Coma Scale; f ISS, Injury Severity Score; g RTS, Revised Trauma Score; h TRISS Ps, Trauma Revised Injury Severity Score Probability of Survival; i FAST, Focused Assessment Sonography for Trauma

j256 patients in the CT group and 28 patients in the No CT group with missing FAST data were excluded from the numerator

k244 dead patients in CT group and 36 dead patients in No CT group with missing data of death time were excluded from the numerator

Main results

We performed complete case analysis, which means we excluded patients with missing covariates from the analysis. As a results, total 5,345 patients were included in IPTW analysis and 5,008 patients were included in IV analysis. Figure 2 compares the number of excess deaths per 100 patients of the two groups. Unadjusted comparison revealed that the CT group had significantly lower mortality than the No CT group. Multivariate analysis using IPTW methods also showed that the CT group had significantly lower in-hospital and 24-h mortality than the No CT group (excess deaths: −20.6 per 100 patients, 95% CI −26.2 to −14.9 for in-hospital mortality; and −20.9 per 100 patients, 95% CI −26.4 to −15.5 for 24-h mortality, respectively)
Fig. 2

a Number of excess deaths per 100 patients for in-hospital mortality by non-adjusted, inverse probability of treatment weighted analysis and instrumental variable analysis. b Number of excess deaths per 100 patients for 24 h mortality by non-adjusted, inverse probability of treatment weighted (IPTW) analysis and instrumental variable (IV) analysis. We included age, gender, vital signs on arrival (systolic blood pressure, heart rate and Glasgow Coma Scale), Injury Severity Score and year of injury as covariate in both analyses

Our instruments showed a strong association with the actual performance of CT (partial F statistics 99.1 for in-hospital mortality; and 101.7 for 24-h mortality). After adjusting unmeasured confounders using the IV method, there was no significant difference between the two groups in in-hospital or 24-h mortality (excess deaths: −4.1 per 100 patients, 95% CI −23.1 to 14.8 for in-hospital mortality; and −13.6 per 100 patients, 95% CI −30.6 to 3.4 for 24-h mortality, respectively) (Fig. 2).

In sensitivity analyses, we found similar associations to the main analysis after changing the definition of our instruments (Table 3).
Table 3

Sensitivity analysis using differently defined instrumental variables

Instrumental Variable

Excess deaths per 100 patients

95% confidence interval

No. of patients

F statistics

In-hospital mortality

 Previous patient’s CT performance

−13.5

−40.2 to 13.3

5,230

48.8

 Previous 5 patients’ CT performance

−2.4

−18.7 to 13.8

4,783

151

 Previous 7 patients’ CT performance

−3.9

−19.3 to 11.4

4,548

187.5

24-h mortality

 Previous patient’s CT performance

−13.7

−37.3 to 9.9

5,000

48.6

 Previous 5 patients’ CT performance

−10.2

−25.1 to 4.6

4,572

155.1

 Previous 7 patients’ CT performance

−14

−28.3 to 0.0

4,349

188.5

Discussion

In Japan, more than 90% of unstable blunt trauma patients received CT during initial management, which is not recommended in most of the current clinical guidelines. However, we did not find a clinically meaningful harmful effect of CT on survival after adjusting both for measured and unmeasured confounders by IV method. Our results do not support the recommendation of current guidelines that indicates CT should be used only for hemodynamically stable patients. We suggest physicians should consider CT as one of the diagnostic options even when patients are unstable.

Most guidelines do not recommend CT for hemodynamically unstable patients [57]. In Japan, the ATLS-equivalent guidelines, Japan Advanced Trauma Evaluation and Care (JATEC) [24], have been widely adopted. Physicians predominantly treat patients according to the “no CT for unstable patients” policy, similar to that indicated in the ATLS. However, in almost all hospitals in this database, multidetector CT scanners were located near or in the emergency room, allowing rapid CT for unstable patients depending on patients’ status and physicians’ preferences. In this study, 92.1% of patients underwent CT. Further, 76.1% of the CT group had negative FAST findings, which may lead physicians to avoid CT. However, some studies have suggested the low sensitivity of FAST [25, 26]: a negative FAST finding does not always indicate the absence of severe abdominal injury. For example, a patient with no abdominal complaints may have a head or chest injury characterized by a change in mental status or chest pain. In such situations, head or chest but not abdominal CT may be conducted. As a result, many patients with negative FAST findings underwent CT. Recently, the number of CT scans for trauma patients has been substantially increasing globally [27, 28]. And radiation exposure due to excessive CT use has been discussed recently [29]. Therefore, appropriate CT use for trauma patients has become important issue globally.

There has been no definitive evidence to show harmful effect of CT for unstable trauma patients. Among preoperative abdominal trauma patients, one previous study reported harmful effect of CT [10]. Another previous study reported that there was no significant difference of mortality between patients underwent CT and those not underwent CT in different population of unstable trauma patients including abdominal and non-abdominal trauma patients [13]. Those previous studies have critical limitations to examine the effect of CT in observational studies, due to unmeasured confounders.

Randomized controlled trials (RCTs) are considered the ideal method to estimate treatment effects, except for the possible effects of confounding factors. However, it is difficult to conduct RCTs among unstable trauma patients because of ethical concerns and the difficulty of recruitment of those patients. Further, observational studies have some advantages over RCTs. In this study, we could include participants who reflected the exact population irrespective of whether physicians ordered CT or not and were able to reveal the practice patterns and effect of CT in the real-world.

One of the most important problems in estimating a treatment effect in observational studies is confounding by indication, which is sometimes difficult to measure directly [30]. Clearly, the indication for CT in unstable patients is not based on random allocation but is dependent on individual patient condition and facility-level restrictions. For example, physicians tend not to order a CT if the patient is considered too unstable to tolerate the scan procedure. Physicians also cannot order CT if his or her facility does not have a CT scanner. Thus, these factors are potential confounders between CT and mortality. To resolve this problem, the IV method is a popular approach to cope with unmeasured confounders and enables the estimation of more unbiased results [2133]. On the other hand, it has the disadvantage of a tendency towards wide 95% confidence intervals [31, 34, 35]. In our database, some clinically important predictors such as response to initial fluid resuscitation and change in vital signs after hospital arrival were not measured. We assumed the results of the IPTW method were implausible because of the likely effect of these unmeasured confounders on both CT ordering and mortality that could not be ignored. We therefore focused on the results of the IV method. Previous study supported this idea to implicate the results of the IPTW method and IV method [36].

Our study had some limitations. First, only 7.9% of participants did not undergo CT and might have represented a different population from the other 92.1%. For example, patients in the No CT group may have been more likely to have severe physiological conditions and lower probability of survival than those in the CT group. To consider this issue, we compared the distribution of major measured confounders and found that there was sufficient overlap of measured characteristics between the two groups. We therefore considered the two groups to be comparable. Second, we could not elucidate whether our instrument variable meet the criteria of an IV method based on measured data. Although it is impossible to prove there was no direct relation between our instrument and outcomes, we consider our instrument to be acceptable because most facilities included in this study were tertiary care hospitals which have no restriction on the performance of CT. Therefore, the preference to order CT was not likely related to the hospital’s quality of care. Moreover, patient-level confounders might have had a greater influence on the physician’s choice to order CT. Additionally, physicians may have underestimated the ISS in the No CT group, which had a significantly higher mortality rate. This underestimation might have had an influence on the results.

Conclusion

In summary, most unstable blunt trauma patients undergo CT as part of initial management in Japan. We did not find clinically meaningful harmful effect of CT on survival for unstable blunt trauma patients after adjusting both for measured and unmeasured confounders. Our results do not support the current guidelines, of which only a few recommend CT for unstable patients. Continued discussion and more studies of this issue are necessary to improve the quality of care of blunt trauma patients.

Abbreviations

AIS: 

Abbreviated injury scale

CT: 

Computed tomography

DBP: 

Diastolic blood pressure

GCS: 

Glasgow coma scale

HR: 

Heart rate

IPTW: 

Inverse probability of treatment weighted

ISS: 

Injury severity score

IV: 

Instrumental variable

JTDB: 

Japan trauma data bank

PS: 

Propensity score

RR: 

Respiratory rate

RTS: 

Revised trauma score

SBP: 

Systolic blood pressure

TRISS Ps: 

Trauma revised injury severity score probability of survival

Declarations

Acknowledgements

We would like to thank all members and personnel of the JTDB, the Japanese Association for Trauma Surgery, the Japanese Association for Acute Medicine, and Japan Trauma Care and Research.

Funding

All authors none were declared.

Availability of data and materials

The data will not be shared, because of restrictions to its use.

Authors’ contributions

YT and SF conceived and designed the study, analyzed and interpreted the data. SF supervised the conduct of the study. YT drafted the manuscript and all authors contributed substantially to its revision. SF take responsibility for the paper as a whole. All authors read and approved the final manuscript.

Competing interests

The authors declare that they have no competing interests.

Consent for publication

Not applicable.

Ethics approval and consent to participate

This study was fully approved by the ethics committee of Kyoto University School of Medicine, which waived the requirement for informed patient consent because of the anonymous nature of the data (reference number: R0208).

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Authors’ Affiliations

(1)
Department of Healthcare Epidemiology, Graduate School of Medicine and Public Health, Kyoto University
(2)
Department of Clinical Epidemiology and Health Economics, School of Public Health, Graduate School of Medicine, The University of Tokyo
(3)
Department of Emergency Medicine, National Hospital Organization Mito Medical Center

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