Resucitation Today by Media Publishing Company

Volume 6 No. 1

Spring 2019

Resuscitation Today A Resource for all involved in the Teaching and Practice of Resuscitation

when every breath counts 9 Application proven: pre-hospital, emergency, critical care & resuscitation 9 Provides compliance to 2015 ERC/UK ALS waveform capnography guidelines

In this issue Risks and benefits of hypotensive resuscitation in patients The European Trauma Course: an introduction Identification and internal validation of models for predicting survival and ICU admission

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CONTENTS

CONTENTS 4

EDITORS COMMENT

CLINICAL PAPER R isks and benefits of hypotensive resuscitation in patients with traumatic hemorrhagic shock: a meta-analysis

EDUCATION The European Trauma Course: an introduction

CLINICAL PAPER I dentification and internal validation of models for predicting survival and ICU admission following a traumatic injury

Resuscitation Today This issue edited by: Russell D Metcalfe-Smith MSc. FRPSH NRP CHSE-A c/o Media Publishing Company Media House 48 High Street SWANLEY, Kent BR8 8BQ ADVERTISING & CIRCULATION: Media Publishing Company Media House, 48 High Street SWANLEY, Kent, BR8 8BQ Tel: 01322 660434 Fax: 01322 666539 E: info@mediapublishingcompany.com www.MediaPublishingCompany.com PUBLISHED: Spring, Summer and Autumn

COVER STORY EMMA Waveform Capnograph portable waveform capnography from MEDACX EMMA Waveform Capnograph is the second generation following the huge success of the EMMA Capnometer first introduced by MEDACX in 2006. With over 12 years of proven UK application experience EMMA Waveform Capnograph builds on its huge reputation, now with its waveform display and breath by breath EtC02 and Respiratory Rate values plus a ‘pulsing heart’, it’s the first choice in many hospitals, ambulance and emergency organisations in the United Kingdom, Europe and around the world. October 2015: European Resuscitation Council issued NEW 2015 ALS Guidelines1, with particular emphasis on the use of waveform capnography to confirm and continually monitor tracheal tube placement, quality of CPR and to provide an early indication of return of spontaneous circulation [ROSC].

‘when every breath counts’ You can find more information about the MEDACX capnography range at: www.medacx.co.uk/products/capnography [also see Outside back cover of this edition]. MEDACX Limited, Alexander House, 60-62 Station Road, Hayling Island, Hampshire, PO11 0EL, United Kingdom. Tel: +44 (0) 2392 469737 Email: info@medacx.co.uk Website: www.medacx.co.uk

PUBLISHERS STATEMENT: The views and opinions expressed in this issue are not necessarily those of the Publisher, the Editors or Media Publishing Company. Next Issue Summer 2019 Subscription Information – Spring 2019 Resuscitation Today is a tri-annual publication published in the months of March and September. The subscription rates are as follows:UK: Individuals - £12.00 inc. postage Commercial Organisations - £30.00 inc. postage Rest of the World: Individuals - £60.00 inc. postage Commercial Organisations - £72.00 inc. postage We are also able to process your subscriptions via most major credit cards. Please ask for details. Cheques should be made payable to MEDIA PUBLISHING. Designed in the UK by me&you creative

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EMMA Waveform Capnograph provides compliance to ALS guidelines and more… It is ideal for patient transfer and can be used with bags and face masks. With clear and precise EtC02 waveform display together with EtC02 and Respiratory rate values opens up its use for both intubated and non-intubated and for Adult/Paediatric through to Infant/Neonate patients. Confirming efficacy of endotracheal tube placement; providing early recognition of ROSC, instant feedback of effectiveness of CPR, indication of Hypercapnia & Hypocapnia states. Plus, alarm functionality; High/Low EtC02, Apnoea, Blocked Airway and Battery Status.

References: 1European Resuscitation Council [ERC] - ERC Guidelines 2015

EDITORS COMMENT

EDITORS COMMENT Welcome to the Spring Edition of Resuscitation Today.

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â&#x20AC;&#x153;The continued development of team based education and simulation enhances this technology to improve team cohesiveness and develop essential skills needed to competently and confidently manage complex clinical scenarios.â&#x20AC;?

The continued efforts of clinicians to improve care are pivotal to improving survivability from Cardiac Arrest. The availability of new technologies are increasing the ability of teams to enhance care, positively impacting patient outcomes. The cautious use of technology also offers the potential to not only impact direct patient care, but allow for enhanced flow in communication between clinicians. The continued development of team based education and simulation enhances this technology to improve team cohesiveness and develop essential skills needed to competently and confidently manage complex clinical scenarios. The well documented challenges associated with rapid reduction in effectiveness may additionally be enhanced by focusing the development of new educational curriculum, combined with technology to mitigate some of these challenges. We also can benefit from enhanced global collaboration by engaging with different systems and experts to learn and implement what is achieving outcomes. The Resuscitation community which includes all levels of care can, and will continue to search for the best ways to move the needle to improve survivability. Russell D Metcalfe-Smith FHEA MSc. BSc(Hons) MCPara CHSE-A

THURSDAY MARCH 28 2019 Pavilions of Harrogate HG2 8NZ For the benefit of Yorkshire medical staff, the following conference / individual workshops will be taking place on the above mentioned date which we hope will be of interest. First Responder Conference - start time 09.30, finish 12.45. Topics are currently being finalised but we hope to cover: Airway Management, Sepsis, Head Injuries, etc. Thanks to the generosity of Future Awards & Qualifications, a delegate rate of £24 will be offered. Only 15 places remain available Ultrasound Workshop - start time 09.30, finish 16.00. Supported by NEMUS Education & Training, this full day workshop is covering: The Common Uses of Ultrasound in Pre-Hospital and Hospital Practice and is suitable for all non doctor clinicians who want to see how point of care ultrasound can actually enhance your practice. Delegate rate £90. Limited places available Bariatric Workshop - start time 14.00, finish 16.00. This half day afternoon workshop run by Outreach Rescue is focusing on dealing with bariatric patients and the use of tripods, bipods and lifting systems that can be used for the extrication of bariatric patients from a wide range of locations, including RTC's. The workshop will include a 15 minute presentation being given by Hospitalaids. Delegate rate: £60 Trauma Management Workshop - start time 10.00, finish 12.30. Run by MedSkills Academy. This two hour morning workshop will be covering basic to advanced trauma skills and include: Trauma Patient Assessment, Catastrophic Bleeding, etc. Delegate rate £60 Airway Management Workshop - start time 14.00, finish 16.00. This two hour afternoon workshop which is also being run by MedSkills Academy will be covering: Basic to Advanced Airway Skills including Positioning, BVM, Video Laryngoscopy, Emergency Surgical Airway, etc. Delegate rate £60

All of the above rates include: lunch, tea/coffee and, as workshop places are limited, early registration is recommended. To secure your place please visit: www.lifeconnections.uk.com - combined discounted workshop rates are available, call The Organsiers on: 01322 660434. Media Publishing Co, Media House, 48 High Street, Swanley, Kent, BR8 8BQ. Tel: 01322 660434

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Pre Hospital Major Incident Workshop - start time 09.00, finish 17.00. Run by MedSkills Academy, this workshop will update and prepare those fulfilling healthcare and professional roles at the scene of a major incident including doctors and paramedics. Delegate rate £90

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CLINICAL PAPER

RISKS AND BENEFITS OF HYPOTENSIVE RESUSCITATION IN PATIENTS WITH TRAUMATIC HEMORRHAGIC SHOCK: A META-ANALYSIS Natthida Owattanapanich1, Kaweesak Chittawatanarat2, Thoetphum Benyakorn3 and Jatuporn Sirikun1* Reproduced with permission from the Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. (2018) 26:107 doi: 10.1186/s13049-018-0572-4

Abstract Background Damage control strategies play an important role in trauma patient management. One such strategy, hypotensive resuscitation, is being increasingly employed. Although several randomized controlled trials have reported its benefits, the mortality benefit of hypotensive resuscitation has not yet been systematically reviewed. Objectives To conduct a meta-analysis of the efficacy of hypotensive resuscitation in traumatic hemorrhagic shock patients relative to mortality as the primary outcome, with acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and multiple organ dysfunction as the secondary outcomes. Methods PubMed, Medline-Ovid, Scopus, Science Direct, EMBASE, and CNKI database searches were conducted. An additional search of relevant primary literature and review articles was also performed. Randomized controlled trials and cohort studies reporting the mortality rate associated with hypotensive resuscitation or limited fluid resuscitation were selected. The random-effects model was used to estimate mortality and onset of other complications.

Results Of 2114 studies, 30 were selected for this meta-analysis. A statistically significant decrease in mortality was observed in the hypotensive resuscitation group (risk ratio [RR]: 0.50; 95% confidence interval [CI]: 0.40–0.61). Heterogeneity was observed in the included literature (I2: 27%; degrees of freedom: 23; p = 0.11). Less usage of packed red cell transfusions and fluid resuscitations was also demonstrated. No significant difference between groups was observed for AKI; however, a protective effect was observed relative to both multiple organ dysfunction and ARDS. Conclusions This meta-analysis revealed significant benefits of hypotensive resuscitation relative to mortality in traumatic hemorrhagic shock patients. It not only reduced the need for blood transfusions and the incidences of ARDS and multiple organ dysfunction, but it caused a non-significant AKI incidence. Keywords Thailand, Hypotensive resuscitation, Traumatic hemorrhagic shock patients, Meta-analysis

Introduction

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Hemorrhagic shock is one of the most common causes of death

concluded that a more conservative hypotensive strategy—in which

in trauma or traumatized patients [1]. This is due to the fact that

minimal amounts of fluids are given until the severe bleeding has

hemorrhagic shock sets in motion a vicious cycle of outcomes,

been controlled—is a more efficacious resuscitation strategy [10–13].

consisting of hypothermia, acidosis, and coagulopathy—otherwise

Although the volume of data on hypotensive resuscitation continues to

known as the lethal triad. To mitigate these effects, damage control

grow, conflicting findings are being reported regarding the efficacy of

strategies have been proposed, including the early control of bleeding

this trauma-mitigating strategy. Accordingly, the aim of this study was to

and adequate fluid resuscitation. The aim of hypotensive resuscitation

conduct a meta-analysis of the efficacy and drawbacks of hypotensive

is to maintain systolic blood pressure (or mean arterial pressure) in order to sustain organ perfusion [2, 3]. It was believed that induced intraoperative hypotension could lead to reduced blood loss and fewer transfusions [4–6]. However, much recent data have shown that there is a significant relationship between hypotensive resuscitation and

resuscitation in traumatic hemorrhagic shock patients relative to mortality as the primary outcome, with acute respiratory distress syndrome, acute kidney injury, and multiple organ dysfunction as the secondary outcomes.

postoperative renal injuries [7–9]. Fluid resuscitation with the rapid administration of intravenous

Methods

fluids until the blood pressure is normalized is the traditional fluidresuscitation strategy. A number of randomized controlled trials have

Inclusion criteria

demonstrated some improvement in survival and mortality using a

This meta-analysis included only randomized controlled trials (RCTs)

liberal fluid hypotensive resuscitation. Nevertheless, other studies have

and cohort studies that evaluated adult patients aged older than

CLINICAL PAPER

Fig. 1 Flow diagram of the article selection procedure based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline

18 years who had traumatic hemorrhagic shock and a systolic blood

Data collection

pressure below 90 mmHg.

Two reviewers (N.O. and T.B.) independently inspected each article identified during the search, scanned the full text of relevant articles,

The intervention assessed was conventional fluid resuscitation

applied the inclusion and exclusion criteria, and extracted and recorded

with normotension (liberal fluid resuscitation) versus hypotensive

the data. Disagreements relating to any aspect of the data extraction

resuscitation (limited fluid resuscitation). Conventional fluid resuscitation

process were resolved by discussion with a third reviewer (K.C.), with

was defined as liberal fluid resuscitation until the systolic blood pressure

the final decision made by consensus.

exceeded 90 mmHg (normal blood pressure). Hypotensive resuscitation was defined as limited fluid resuscitation to maintain adequate organ perfusion, with a systolic blood pressure of ~ 70–80 mmHg or a mean arterial pressure of ~ 50 mmHg. Excluded were studies of patients who were pregnant or had traumatic brain injuries, research with insufficient mortality data, and investigations that had not received ethical approval. Outcomes assessed The primary outcome was all-cause mortality, as reported by the authors the following morbidities: acute respiratory distress syndrome (ARDS), acute kidney injury (AKI), and multiple organ dysfunction (MODS). Other secondary outcomes included the fluid resuscitation volume and the transfusion of packed red cells. Search methods

The quality of included studies was evaluated using the Jadad quality assessment scale for randomized controlled studies. Our subsequent analysis only included those studies that scored ≥2 on the scale (which indicated that their results were valid) [14]. To assess the quality of nonrandomized studies, the Newcastle–Ottawa Scale (NOS) was used. This 3-item scoring system evaluates the selection of the participants; the comparability between the groups; and the ascertainment of exposure for case-control studies, and the outcome of interest in the case of cohort studies [15]. Statistical analysis All statistical analyses were performed using Review Manager 5.3 software from the Cochrane Collaboration (London, United Kingdom). We extracted the proportions and 95% confidence intervals from each study and pooled them using the random effects model. Cochran’s Q

PubMed, Medline-Ovid, Scopus, Science Direct, EMBASE, and CNKI

test was performed and quantified using the I2 statistic to evaluate the

database searches were conducted for articles published before

statistical heterogeneity among the included studies. The I2-values were

January 31, 2018. An additional search of relevant primary literature

categorized as follows: 0–25% indicated insignificant heterogeneity;

and review articles was also performed. The references from identified

26–50%, low heterogeneity; > 50% to ≤75%, moderate heterogeneity;

studies that appeared to be germane to the topic of study were hand-

and > 75%, high heterogeneity [16]. The fixed effects model was used

searched. The medical subject headings (MeSHs) used in our searches

for analyses that evaluated data with no significant heterogeneity. Funnel

included “hypotensive resuscitation” or “limited fluid resuscitation” and

plots were used to evaluate for publication bias. P-values less than 0.05

“trauma” or “trauma*”. There was no language restriction.

were considered statistically significant.

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of the included studies. The secondary outcomes included the rates of

Quality assessment

CLINICAL PAPER

Table 1 Study characteristics

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Study

Country Study design

Jadad Quality score/ Participants Newcastle-Ottawa scale (NOS)

Bickell 1994

USA

Single-center, Three out of five prospective RCT -No double blind

Gunshot or stab wounds to the torso who had SBP<90 mmHg

Delayed resuscitation Immediate resuscitation with RLS 10ml/hr to maintain SBP at least until definitive 100 mmHg treatment

Dutton 2002

USA

Single-center, Three out of five prospective RCT -No double blind

Traumatic hemorrhagic shock with SBP <90 mmHg and evidence of ongoing bleeding

Low SBP of 70 mmHg

Conventional SBP > 100 mmHg

WANG Meitang 2007

China

Single-center, prospective cohort study

Traumatic hemorrhagic shock

Preoperative SBP approximately 70-80 mmHg

Preoperative SBP >90 mmHg

ZHENG Weihua 2007

China

Single-center, Two out of five prospective, RCT -No method of randomization -No double blind

Traumatic hemorrhagic shock patients

Limited fluid resuscitation (MAP 50-60 mmHg)

Aggressive fluid resuscitation (MAP 70 mmHg)

HUA Li-dain 2010

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Severe multiple hemorrhagic shock

Limited fluid resuscitation (SBP 70 mmHg)

Observational with MAP at least 90/60 mmHg

WANG Aitian 2010

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock

Limited fluid resuscitation to maintain SBP 70 mmHg

Conventional resuscitation to maintain SBP 100 mmHg

Fan Hai-Peng 2011

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Pelvic fracture with hemorrhagic Low MAP 50-60 shock mmHg or SBP 70-90 mmHg

Conventional MAP 60-80 mmHg or SBP >100 mmHg

Morrison 2011 China

Single-center, prospective, two-arm, intention to treat, RCT

Three out of five -No double blind

Patients undergoing laparotomy Experimental group or thoracotomy for blunt and with MAP 50 mmHg penetrating trauma who had SBP < 9o mmHg

Control group with MAP 65 mmHg

Fan Hai-Peng 2012

China

Single-center, RCT

Two out of five -No method of randomization -No double blind

Hepatic and splenic injury with hemorrhagic shock

Limited fluid resuscitation (MAP 50-60 mmHg)

Conventional resuscitation (SBP 100 mmHg or MAP 60-80 mmHg)

LI Wenhao 2012

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock without controlling bleeding

Limited fluid resuscitation (MAP 55 mmHg)

Adequate fluid resuscitation (MAP 75mm Hg)

Chen Mu-hu 2013

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock patients

Limited fluid resuscitation (SBP 70 mmHg)

Aggressive fluid resuscitation (SBP 90 mmHg)

ZHAO yonggang 2013

China

Retrospective cohort study

Traumatic hemorrhagic shock patients

Objective group (SBP 85 mmHg, limited fluid)

Control group (SBP >90 mmHg, rapid and full replenishment of fluid

WANG Xiaoguo 2014

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic liver and splenic injury

Limited fluid resuscitation (MAP 50-70 mmHg)

Conventional resuscitation (MAP 70-90 mmH)

ZENG Fanyuan 2014

China

Single-center, cohort study

Uncontrolled traumatic hemorrhagic shock patients

Experimental group (MAP 50 mmHg)

Control group (MAP 70 mmHg)

Chen Mianzhan 2015

China

Prospective, RCT Two out of five -No method of randomization

Traumatic hemorrhagic shock patients

Limited resuscitation Conventional resuscitation (SBP at least 90 mmHg) (SBP at least 80 mmHg)

Selection: 3 Comparability: 2 Outcome: 2

Selection: 4 Comparability: 2 Outcome: 2

Intervention

Control

CLINICAL PAPER Table 1 Study characteristics (Continued) Study

Country Study design

Jadad Quality score/ Participants Newcastle-Ottawa scale (NOS)

Intervention

Control

Chen Yuanbing, 2015

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock patients

Limited resuscitation Conventional resuscitation (SBP 70 mmHg) (SBP >90 mmHg)

Huang Ting 2015

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock

Control group with MAP 40-60 mmHg

Observation group with MAP 60-90 mmHg

Schreiber 2015

USA

Multi-center, RCT

Three out of five -No double blind

Blunt or penetrating trauma patients with SBP <90 mmHg

Administer 250 ml of fluid if SBP <70 mmHg or absent radial pulse

Administer 2 liters initially and additional fluid as needed to maintain SBP > 110 mmHg

Wen Zhen-jie 2015

China

Multi-center, prospective cohort studies

Selection: 4 Comparability: 2 Outcome: 2

Traumatic hemorrhagic shock

Limited fluid resuscitation (SBP 75 mmHg)

Conventional fluid resuscitation (SBP > 100 mmHg)

XU Guoping 2015

China

Single center, Two out of five prospective RCT -No method of randomization -No double blind

Traumatic hemorrhagic shock patients

Limited fluid resuscitation (MAP 40-60 mmHg or SBP 70 mmHg)

Conventional resuscitation (MAP 60-80 mmHg or SBP > 90 mmHg)

YAO Jian-hui 2015

China

Single center, Two out of five prospective, RCT -No method of randomization -No double blind

Multiple traumatic hemorrhagic shock patients

Limited fluid resuscitation (MAP 40-50 mmHg)

Active fluid resuscitation (MAP 60-80 mmHg)

Carrick 2016

USA

Single-center, prospective, two-arm, intention-totreat, RCT

Penetrating trauma patients with SBP < 90 mmHg who were brought emergently to OR for bleeding control

Keep low MAP (MAP Keep normotension 50 mmHg) (MAP at least 65 mmHg)

Dai Yulong, 2016

China

Prospective, RCT Two out of five -No method of randomization -No double blind

Traumatic hemorrhagic shock patients

Limited fluid resuscitation (SBP 65 mmHg)

Conventional resuscitation (SBP 90 mmHg)

Wang Fengyong 2016

China

Single center, Two out of five prospective RCT -No method of randomization -No double blind

Active hemorrhagic shock

Limited fluid resuscitation (maintain MAP 40-60 mmHg)

Conventional resuscitation (maintain MAP 60-90 mmHg)

-No double blind

Three out of five -No double blind

Results Search results and study characteristics Figure 1 illustrates a flow diagram describing the article selection Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Our review of the literature yielded 2114 publications up to January 31, 2018. For an assortment of reasons during the article selection process, 2090

[27]). These studies give the plot an asymmetrical appearance, with a gap at a bottom corner of the graph. In this setting, the effect calculated in a meta-analysis will tend to overestimate the intervention effect. However, after reviewing the study design and evaluating the outcomes, we still decided to include them in our analysis. The Egger test found a strong significance in publication bias

of those articles were excluded. The specific reasons for exclusion

(P = 0.000) Therefore, the trim and fill method was conducted to adjust

are given in Fig. 1. The remaining 24 studies were included in the final

the publication bias by removing the smaller studies causing asymmetry

analysis [2, 10–13, 17–35]. Of those 24 studies, 20 were randomized

and replacing the omitted studies. This method has been claimed to

controlled trials, while 4 were prospective cohort studies. The baseline

improve the effect size and confidence intervals [36]. As a result, the

characteristics described in Table 1 comprise country, article type, the

present study drew upon 11 hypothesized studies. The new RR was

quality assessment score for each study, and the intervention definition.

0.65 and CI (0.52–0.80), which showed significant difference in mortality benefit (Fig. 3).

Assessment of reporting bias A funnel plot of the reporting bias shows asymmetry on visual inspection

Synthesis of primary outcome

(Fig. 2). There were 3 studies with low statistically significant effects (risk

A pooled analysis was performed of the 24 studies using a random-

ratio [RR]: 0.11; 95% confidence interval [CI]: 0.01–0.75; Zhao Yong-

effects model, with findings reported as RR and 95% CI (n = 1473;

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process, which was based on the Preferred Reporting Items for

gang, 2013 [34], Dai Yulong, 2016 [20], and Wang Fengyong, 2016

CLINICAL PAPER

Fig. 2 Funnel plot of reporting bias (the dotted lines indicate the 95% confidence interval [CI]; SE, standard error; RR, risk ratio)

RR: 0.50; 95% CI: 0.40–0.61). A mild heterogeneity among these 24

red cell transfusion was 132 ml (95% CI: -203, -61).

studies was observed (Q test: 0.11, which is greater than 0.1; I2: 27%). Given the degree of homogeneity among the studies, a random-effects model was subsequently applied (Fig. 4). As described in Fig. 4, some overtime bias was observed among the studies. Although the first published study on this topic (by Bickell WH et al. [2]) was published in 1994, we still included it due to its sound methodology and overall high level of quality. Secondary outcomes The hypotensive resuscitation group had a lower amount of fluid

In terms of the possible risks of this hypotensive strategy, 7 studies [2, 13, 17, 18, 23, 28, 33] showed that the hypotensive resuscitation group had no significant difference in acute kidney injury (RR: 1.19; 95% CI: 0.65, 2.21; Fig. 7). This strategy also had lower incidences of both acute respiratory distress syndrome (RR: 0.44; 95% CI: 0.33, 0.59) and multiple organ dysfunction (RR: 0.40; 95% CI: 0.26, 0.61; Figs. 8 and 9).

Discussion

resuscitation and packed red cell transfusion than the normotensive resuscitation group (Figs. 5 and 6). The mean difference in fluid resuscitation between groups was 1233 ml (95% CI: -1576, -890) and

RESUSCITATION TODAY - SPRING 2019 Fig. 3 The funnel plot after trim and fill method

During the last decade, two differing approaches to damage control have been used for severe trauma patients. The traditional liberal fluid

CLINICAL PAPER

Fig. 4 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to mortality

approach has, however, come under increasing attention due to the

the first to study and publish the role of hypotensive resuscitation in

possible complications associated with administering more than 2â&#x20AC;&#x2030;l

penetrating trauma patients. They showed that hypotensive resuscitation

of fluid before surgery. In contrast, hypotensive resuscitation is being

before surgery could significantly decrease mortality. Not only did the

increasingly employed because many animal studies have found its use

fatality rate decrease, but the hypotensive resuscitation also appeared

is associated with reduced effects of the lethal triad. The concept of this

to correlate with less coagulopathy and other complications, including

strategy is to restrict the amount of fluid resuscitation to maintain a low

less cardiovascular failure, respiratory failure, and acute kidney injury

enough blood pressure for adequate cerebral perfusion. To avoid further

(AKI).

bleeding due to dilution coagulopathy and to dislodge hemostatic blood clots, hypotensive resuscitation has been adopted as a part of damage

Despite the sizeable number of studies on hypotensive resuscitation in

control resuscitation for trauma patients [37, 38]. Bickell WH et al. were

animal models and in humans, there is only one Cochrane-based review,

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Fig. 5 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to fluid resuscitation volume

CLINICAL PAPER

Fig. 6 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to transfusion of packed red cells

and that review pertains only to the timing and volume of fluid

Wei-zheng et al., whose studies both maintained low normal blood

administration in patients with bleeding. Moreover, in the present study,

pressure (SBP 90 mmHg or MAP 60–70 mmHg). Meanwhile, LIU Yu et al.

all types of hemorrhagic shock were included, including gastrointestinal

maintained SBP 70 mmHg, which truly met the definition of hypotensive

bleeding. The results of this meta-analysis showed that there is no

resuscitation. However, the data is not compelling enough to strongly

evidence for or against an early or larger volume of intravenous fluid

recommend hypotensive resuscitation in traumatic hemorrhagic shock

administration in cases of uncontrolled hemorrhage.

patients with traumatic brain injury, and there were no reported data on the functional outcomes after this strategy.

Given that there is no meta-analysis related to studies comparing hypotensive to liberal fluid resuscitation, we decided to perform such

This study supports the use of hypotensive resuscitation, not only in

an investigation. It is noteworthy that a large majority of the present

penetrating wound patients, but also in other types of traumatic injuries.

literature had to be excluded from further analysis. This was mainly due

This significant finding was based on low heterogeneity. However,

to either the presence of irrelevant data and/or the lack of sufficient data. This highlights and supports the validity of the Cochrane approach. Our analysis revealed that hypotensive resuscitation (i.e., limited fluid resuscitation) has beneficial effects on survival in traumatic hemorrhagic shock. Even in the blood product based resuscitation era, all the literature still shows significant survival benefits [10–13]. Hypotensive resuscitation is also associated with a significantly lower amount of fluid resuscitation and packed red cell transfusion, and a significantly lower incidence of acute respiratory distress syndrome and multiple organ

the limitations of this analysis include the fact that some clinical and methodological heterogeneities between the studies cannot be ruled out, and there may be some overtime bias. Despite significant publication bias shown by an asymmetrical funnel plot and Egger test, the trim and fill method also showed a statistically significant mortality benefit from the hypotensive strategy. Although a large, multi-center, randomized controlled trial should be conducted, the likelihood of such an approach succeeding given the present literature (including the present review) seems unlikely.

dysfunction. In contrast, no significant difference was observed between resuscitation methods relative to the incidence of acute kidney injury. Moreover, we were not able to identify any report of renal replacement

Conclusions

therapy and/or long-term dialysis in traumatic hemorrhagic shock patients.

The results of this meta-analysis revealed a significant benefit of hypotensive resuscitation relative to mortality in traumatic hemorrhagic

The subgroup analysis that we performed showed a mortality benefit

shock patients. Moreover, hypotensive resuscitation was found to be a

of hypotensive resuscitation in traumatic hemorrhagic shock with

significantly more effective strategy than traditional fluid resuscitation

coexisting traumatic brain injury. This might alert readers to carefully

in terms of acute respiratory distress syndrome and multiple organ

interpret the reported findings from Gong Hong-chang et al. and LIU

dysfunction.

RESUSCITATION TODAY - SPRING 2019 Fig. 7 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to acute kidney injury (AKI)

CLINICAL PAPER

Fig. 8 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to acute respiratory distress syndrome

Acknowledgements

Author details

The authors gratefully acknowledge Patompong Ungprasert of the

* Correspondence: j_sirikun@hotmail.com 1Division of Trauma Surgery,

Division of Clinical Epidemiology, Department of Research and

Department of Surgery, Faculty of Medicine, Siriraj hospital, Mahidol

Development, and Weerapat Owattanapanich of the Division of Hematology, Department of Medicine, both of the Faculty of Medicine, Siriraj Hospital, for assistance with the statistical analysis. Funding

University, 2 Wanglang Road, Bangkok Noi, Bangkok 10700, Thailand. Department of Surgery, Division of Surgical Critical Care and Trauma,

Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. Division of Vascular Surgery, Department of Surgery, Faculty of Medicine,

Thammasat University, Pathumthani, Bangkok, Thailand.

This was an unfunded study. Authors’ contributions NO and TB reviewed, extracted and recorded data. KC made consensus in final decision on selected literatures. JS processed manuscript. All authors read and approved the final manuscript. Competing interests All authors declare that there are no personal or professional conflicts of interest, and there has been no financial support from the companies that produce and/or distribute the drugs, devices, or materials described in this report. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References 1. Kauvar DS, Lefering R, Wade CE. Impact of hemorrhage on trauma outcome: an overview of epidemiology, clinical presentations, and therapeutic considerations. J Trauma. 2006;60(6 Suppl):S3–11. 2. Bickell WH, Wall MJ Jr, Pepe PE, Martin RR, Ginger VF, Allen MK, et al. Immediate versus delayed fluid resuscitation for hypotensive patients with penetrating torso injuries. N Engl J Med. 1994;331:17. 3. Bouglé A, Harrois A, Duranteau J. Resuscitative strategies in traumatic hemorrhagic shock. Ann Intensive Care. 2013;3:1. 4. Oh S-C, Bang SU, Kang B-G. The effect of induced hypotension on the perioperative bleeding and transfusion in the bipolar hemiarthroplasty of hip: retrospective study for four years. Korean J Anesthesiol. 2013;65(6 Suppl):S41–3. 5. Sharrock NE, Mineo R, Urquhart B, Salvati EA. The effect of two levels of hypotension on intraoperative blood loss during total hip arthroplasty performed under lumbar epidural anesthesia. Anesth Analg. 1993;76:3. RESUSCITATION TODAY - SPRING 2019

Fig. 9 Forest plot of association between hypotensive resuscitation and normal resuscitation, relative to multiple organ dysfunction

CLINICAL PAPER 6. Donald JR. Induced hypotension and blood loss during surgery. J R Soc Med. 1982;75:3. 7. Salmasi V, Maheshwari K, Yang D, Mascha EJ, Singh A, Sessler DI, et al. Relationship between intraoperative hypotension, defined by either reduction from baseline or absolute thresholds, and acute kidney and myocardial injury after noncardiac SurgeryA retrospective cohort analysis. Anesthesiology. 2017;126:1.

26. Aitian WANG, Jingli GAO, Xiaolan LI, Shuohua CHEN, Hui ZHANG, Yujie MA, et al. The significance of APACHE II and IL-6 in patients with traumatic hemorrhagic shock by limited fluids resuscitation. Tianjin Med J. 2010;38:11.

8. Sun LY, Wijeysundera DN, Tait GA, Beattie WS. Association of intraoperative hypotension with acute kidney injury after elective noncardiac surgery. Anesthesiology. 2015;123(3).

27. Fengyong W. Efficacy of limited fluid resuscitation in the early treatment of patients with active hemorrhagic shock. Henan Meidcal Research. 2016;25:3.

9. Walsh M, Devereaux PJ, Garg AX, Kurz A, Turan A, Rodseth RN, et al. Relationship between intraoperative mean arterial pressure and clinical outcomes after noncardiac SurgeryToward an empirical definition of hypotension. Anesthesiology. 2013;119:3.

28. WANG M-t, MEI b, HE J, HUO Z-l. Effect of preoperative limited fluid resuscitation to the patients with traumatic shock. J Med Coll PLA. 2007;22(4).

10. Dutton RP, Mackenzie CF, Scalea TM. Hypotensive resuscitation during active hemorrhage: impact on in-hospital mortality. J Trauma. 2002;52(6). 11. Carrick MM, Morrison CA, Tapia NM, Leonard J, Suliburk JW, Norman MA, et al. Intraoperative hypotensive resuscitation for patients undergoing laparotomy or thoracotomy for trauma: early termination of a randomized prospective clinical trial. J Trauma Acute Care Surg. 2016;80:6. 12. Morrison CA, Carrick MM, Norman MA, Scott BG, Welsh FJ, Tsai P, et al. Hypotensive resuscitation strategy reduces transfusion requirements and severe postoperative coagulopathy in trauma patients with hemorrhagic shock: preliminary results of a randomized controlled trial. J Trauma. 2011;70(3):652–63.

29. Xiao-guo WANG, Zi-li L, Guo-feng WEI. Diagnosis and treatment of traumatic hemorrhagic shock caused by rupture of the liver and spleen on early fluid resuscitation. J Hepatobiliary Surg. 2014;22:4. 30. Zhen-jie WEN, Jian-ling LIU, Jun CHEN. Comparison of application effects by hypertonic saline fluid resuscitation, limited fluid resuscitation and conventional fluid resuscitation in traumatic hemorrhagic shock. China Prac Med. 2015;10:15. 31. Guoping XU. Clinical observation on limited fluid resuscitation in the treatment of uncontrolled hemorrhagic shock. Chinese Journal of Disaster Medicine. 2015;3:5. 32. Jian-hui YAO, Jiang-hong LU. A comparative study on the clinical effect of limited fluid resuscitation and active fluid resuscitation in the treatment of patients with mulitple trauma and hemorrhagic shock. Chinese Journal of Frontier Medicine. 2015;7:6.

13. Schreiber MA, Meier EN, Tisherman SA, Kerby JD, Newgard CD, Brasel K, et al. A controlled resuscitation strategy is feasible and safe in hypotensive trauma patients: results of a prospective randomized pilot trial. J Trauma Acute Care Surg. 2015;78:4.

33. Fan-yuan ZENG, Zeng-bin DENG, min-jian HU, Jian-xi YANG, Chaofan HE, Jiong-lin LIANG, et al. Clinical observation of limited fluid resuscitation on preoperative uncontrolled hemorrhagic shock. J Chin Pract Diagn Ther. 2014;28:1.

14. Jadad AR, Moore RA, Carroll D, Jenkinson C, Reynolds DJ, Gavaghan DJ, et al. Assessing the quality of reports of randomized clinical trials: is blinding necessary? Control Clin Trials. 1996;17(1):1–12.

34. Yong-gang ZHAO. The clinical effect analysis of limited fluids resuscitation in treatment of hemorrhagic shock. Medical Innovation of China. 2013;10:36.

15. Stang A. Critical evaluation of the Newcastle–Ottawa scale for the assessment of the quality of nonrandomized studies in metaanalyses. Eur J Epidemiol. 2010;25(9):603–5.

35. ZHENG Wei-hua, WANG Xin-liang, XU Hua. Effects of limited fluid resuscitation in treatment of hemorrhagic traumatic shock. China journal of emergency resuscitation and disaster Medicine 2007;2:9.

16. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:7414.

36. Duval S, Tweedie R. Trim and fill: a simple funnel-plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics. 2000;56(2):455–63.

17. Mianzhan CHEN. Analysis on the efficacy of limited fluid resuscitation of traumatic hemorrhagic shock. China Academic Journal. 2015;22:3.

37. Rezende-Neto JB, Rizoli SB, Andrade MV, Ribeiro DD, Lisboa TA, Camargos ER, et al. Permissive hypotension and desmopressin enhance clot formation. J Trauma. 2010;68(1):42–50.

18. Mu-hu CHEN, Wu ZHONG, Ying-chun HU. The study on limited fluid resuscitatin patients with traumatic shock. Sichuan Medical Journal. 2013;34:10.

38. Geeraedts LM Jr, Kaasjager HA, van Vugt AB, Frolke JP. Exsanguination in trauma: a review of diagnostics and treatment options. Injury. 2009;40(1).

19. Yuan-bing C, Bin L, Ai-guo Z, Qun-pei L, Yan-wen Y, Yan H. The application of limited fluid resuscitation in first aid of hemorrhagic traumatic shock. J Hunan Normal Univ. 2015;12:1. RESUSCITATION TODAY - SPRING 2019

20. Yulong DAI. Effect of limited fluid resuscitation on prognosis of patients with severe closed traumatic hemorrhagic shock. J Liaoning Medical University. 2016;37:1. 21. Hai-peng F, Yao-jian W, Zhi-hao Y. Clinical application of limited fluid resuscitation in treatment before operation of hepatic and splenic injury and haemorrhagic shock. Clin J Med Offic. 2012;40:4. 22. Hai-peng FAN, Mao-xing YUE, Yao-jian WU. Early therapeutic effects of limited fluid resuscitation on severe pelvic fracture combined with hemorrhagic shock. J Trauma Surg. 2011;13:5. 23. Li-dian HUA, Yan-yang TU, Jian-fang FU, Jian LIN, Hao WANG. Application of limited fluid resuscitation in patients with severe multiple trauma hemorrhagic shock. Progress in Modern Biomedicine. 2010;10:13. 24. Ting HUANG, Yincan ZHANG. Analysis of the therapeutic effect of limited fluid resuscitation in hemorrhagic shock patients. China Modern Doctor. 2015;53:11.

25. Wenhao LI, Hongfeng LIN, Xuebiao DENG. Clinical discussion of limited fluid resuscitation on hemorrhagic traumatic shock without controlling bleeding. China Academic Journal. 2012;19:9.

EDUCATION

THE EUROPEAN TRAUMA COURSE: AN INTRODUCTION Dr Mike Davis FAcadMEd The European Trauma Course (ETC) had its origins in some longstanding reservations about trauma training across Europe that, among other things, reflected concerns that the team contribution to trauma management was not being fully developed or enabled. The ETC, therefore, is depicted as “a team approach”, and the course is designed to maximise the team experience through its underlying philosophy and its design. The course is currently taught throughout Europe, in parts of North Africa and the Middle East. Aiming at psychological rather than physical reality, it has the capacity to be offered in settings ranging from sophisticated simulation suites or low fidelity environments. In practice, in UK and most of Europe, it runs in medium fidelity simulation facilities in major trauma centres. Courses are open to doctors, senior nursing staff involved in trauma settings and paramedics and offers observer status to others who can benefit from witnessing a structured team approach. Its aim is: Improving outcome of major trauma by offering state-of-the-art trauma training with a focus on the multi-specialty, multi-professional team approach and on developing non-technical skills as a team leader and a team member.1

Candidate performance is assessed formatively through the use of the Learning Conversation (see https://www.mededpublish.org/ manuscripts/1922 2) across of range of issues, both clinical and nonclinical; and summatively, as a team leader, on the final day. Potential instructors are identified on each course and they, along with existing instructors, take part in an instructor programme on the day before each course assembles. This is designed to address some of the educational issues associated with the course (e.g. managing information flow, feedback, assessment, group and team dynamics, workshop management), and to contribute towards a sense of effective group performance among faculty members. This latter element has the effect of translating itself into effective team performance by candidates, as they take on the productive norms demonstrated by faculty. For more information about the course, and how to apply to attend one, go to http://europeantraumacourse.com/how-to-book-a-place/ [accessed 9th February 2019] for further information Dr Mike Davis is a consultant in continuing medical education working mainly in life support communities. He has been an educator with the ETC since its inception. He can be contacted at DrMikeD36@gmail.com References

The ETC has led the way in moving life support courses away from presentation of information to practical exploration of the challenges associated with trauma in a variety of clinical contexts: there are 17 workshops over the initial two and a half days. Participants rotate between roles (always “playing” themselves) and take leadership and membership functions.

1. ETC (2018) Vision http://europeantraumacourse.com/vision/ [accessed 9th January 2019) 2. Davis & Denning 2018, Listening through the learning conversation: a thought provoking intervention. [accessed 9th February 2019]

WHY NOT WRITE FOR US? The publication is mailed to all resuscitation, A&E and anaesthetic departments plus all intensive care, critical care, coronary care and cardiology units. All submissions should be forwarded to info@mediapublishingcompany.com

If you have any queries please contact the publisher Terry Gardner via: info@mediapublishingcompany.com

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Resuscitation Today welcomes the submission of clinical papers, case reports and articles that you feel will be of interest to your colleagues.

CLINICAL PAPER

IDENTIFICATION AND INTERNAL VALIDATION OF MODELS FOR PREDICTING SURVIVAL AND ICU ADMISSION FOLLOWING A TRAUMATIC INJURY Rebecca J. Mitchell1*, Hsuen P. Ting1, Tim Driscoll2 and Jeffrey Braithwaite1 Reproduced with permission from the Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine. (2018) 26:95 doi: 10.1186/s13049-018-0563-5

Abstract Background Measures to improve the accuracy of determining survival and intensive care unit (ICU) admission using the International Classification of Injury Severity Score (ICISS) are not often conducted on a population-wide basis. The aim is to determine if the predictive ability of survival and ICU admission using ICISS can be improved depending on the method used to derive ICISS and incremental inclusion of covariates. Method A retrospective analysis of linked injury hospitalisation and mortality data during 1 January 2010 to 30 June 2014 in New South Wales, Australia was conducted. Both multiplicative-injury and single-worst-injury ICISS were calculated. Logistic regression examined 90-day mortality and ICU admission with a range of predictor variables. The models were assessed in terms of their ability to discriminate survivors and nonsurvivors, model fit, and variation explained. Results There were 735,961 index injury admissions, 13,744 (1.9%) deaths within 90-days and 23,054 (3.1%) ICU admissions. The best predictive

model for 90-day mortality was single-worst-injury ICISS including age group, gender, all comorbidities, trauma centre type, injury mechanism, and nature of injury as covariates. The multiplicative-injury ICISS with age group, gender, all comorbidities, injury mechanism, and nature of injury was the best predictive model for ICU admission. Conclusions The inclusion of comorbid conditions, injury mechanism and nature of injury, improved discrimination for both 90-day mortality and ICU admission. Moves to routinely use ICD-based injury severity measures, such as ICISS, should be considered for hospitalisation data replacing more resource-intensive injury severity classification measures. Electronic supplementary material The online version of this article (10.1186/s13049-018-0563-5) contains supplementary material, which is available to authorized users. Keywords: Trauma, Trauma severity, 90-day mortality, International classification of diseases

Background

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The International Classification of Injury Severity Score (ICISS) is one of

factors that may impact on survival, such as age, gender, pre-injury

a number of indices that can be used to estimate injury severity [1–4].

comorbid conditions, and mechanism of injury. None have considered

The ICISS has previously been shown to provide good estimates of

whether including type of trauma service improves predictive ability

survival following injury [1, 5]. It also has a practical advantage [6] as

[1–3, 7, 8, 10]. Previous research has indicated that treatment at a major

it is relatively easily derived by calculating Survival Risk Ratios (SRRs)

trauma service can provide a survival advantage [12, 13], but it is unclear

for injury diagnosis classifications using hospital administrative data

whether the accuracy of ICISS to indicate post-discharge survival could

and an indicator of mortality. Both in-hospital [5, 7] and post-discharge

be improved by including type of trauma service as a covariate.

mortality up to 90-days post-admission [8] have been used to indicate survival. The ICISS has largely been derived using data from trauma

Various factors are associated with an injured individual being admitted

centre registries [2, 3] which generally record information on more

to an Intensive Care Unit (ICU), including age, gender, comorbid

severely injured individuals, and have higher mortality rates (around

health conditions, and injury mechanism [14–16]. However, there has

5%) compared to all injury admissions (around 1–2%) [7, 8]. In addition,

been limited examination of ICISS as a tool to assist in predicting ICU

the ICISS has been estimated using pooled diagnosis-specific survival

admission [5]. Predicting which patients may require admission to ICU

probabilities from hospitalisation data across several high-income

based on their injury severity will assist in determining resource use

countries using in-hospital mortality to indicate survival [9].

and is an additional health outcome indicator. Assessment of whether multiplicative-injury or worst-injury ICISS is a better predictor of ICU

Assessments of the predictive ability of ICISS values to determine survival

admission for trauma patients on a population-wide basis is needed.

have found that the SRR of the worst-injury is often a better predictor of survival than a multiplicative combination of SRRs for all injury diagnoses

Different approaches have previously been used to internally validate

[10, 11]. Previous studies have also examined the inclusion of other

SRRs estimated from in-hospital records. These have largely involved

CLINICAL PAPER using the split-sample approach, where the data are randomly spilt

Comorbidity identification

into two (or more) parts, with one dataset acting as the training dataset

The Charlson Comorbidity Index [31] was used to identify 17

where the model is developed, and the other dataset(s) acting as the

comorbidities using up to 50 diagnosis classifications in the

testing dataset(s) where predictive accuracy is assessed [6, 10], or

hospitalisation data and a 12-month look-back period to 1 January

using a bootstrapping approach where the model is developed on the

2009. Each comorbid condition was assigned a weight between 1

full dataset and bootstrapping is applied to assess performance [7, 8].

and 6 based on the risk of mortality and/or resource use and the sum

Limitations of the split-sample approach include creation of imprecise

of weights was used to generate a comorbidity score. A higher score

models [17–19], underestimated performance of the full model [17],

is indicative of a higher likelihood of mortality and/or resource use. In

non-efficient use of all data [17, 20], adverse effects on calibration [4,

addition, specific health conditions that are associated with injury risk

21], and that validation only occurs on a sample of the full-dataset [20].

and poor recovery [32, 33] including mental health conditions (ICD-10-

As a result of the limitations with the spilt-sample approach for internal

AM: F20-F50), alcohol misuse and dependence (ICD-10-AM: F10, Y90,

validation of prognostic models, bootstrapping has been recommended

Y91, Z50.2, Z71.4, Z72.1), and drug-related dependence (ICD-10-AM:

as the preferred approach for assessing the internal validation of

F11-F16, F19, Z50.3, Z71.5, Z72.2) were also identified using diagnosis

predictive models [17, 18, 20–24]. The bootstrapping approach is

classifications.

able to provide optimism-corrected estimates of the fit statistics. A previous comparison of the bootstrapping approach using a split-

Calculation of the international classification of injury severity

sample to predict 30-day mortality following acute myocardial infarction

score

identified that internal validity was best estimated with bootstrapping as

For all of the index injury hospital admissions, a SRR was calculated

it provided the most stable estimates with low bias [17]. This research

for each injury diagnosis. A SRR represents the ratio of the number

aims to determine if the predictive ability of survival and ICU admission

of individuals with each injury diagnosis who did not die to the total

using ICISS can be improved depending on the method used to derive

number of individuals with the injury diagnosis. The mean number of

ICISS and incremental inclusion of covariates.

diagnoses recorded per injured individual was 1.74 (SD = 1.46; range 1–43). For each injury admission, two ICISS values were calculated:

Method

(i) multiplicative-injury ICISS where ICISS is the product of all SRRs for each of the individual’s injuries; and (ii) single worst-injury, where ICISS only includes the worst-injury (i.e. the injury diagnosis with the

Linked hospitalisation and mortality data

lowest SRR) as the single worst-injury has been shown to have good

Hospitalisation data included information on all inpatient admissions

discriminatory ability for survival [10].

for all public and private hospitals in New South Wales (NSW), Australia during the period 1 January 2010 to 30 June 2014. Diagnoses

Data analysis

and external cause codes were classified using the International

All analyses were performed using SAS version 9.4 [34]. Logistic

Classification of Diseases, 10th Revision, Australian Modification (ICD-

regression was used to examine both 90-day mortality and ICU

10-AM) [25]. Injury-related admissions were identified using a principal

admission as outcomes with varying predictor variables: ICISS

diagnosis of injury (ICD-10-AM: S00-T89). Mortality data from 1 January

(i.e. multiplicative or worst-injury), age group (i.e. 0–16, 17–24, 25–44,

2010 to 31 March 2015 from the NSW Registry of Births, Deaths and

45–64, 65–79, ≥80 years), sex, Charlson Comorbidity Index group

Marriages was probabilistically linked to the hospitalisation records by

(i.e. 0, 1–2, 3–4, ≥5 on the comorbidity index score), mental health

the Centre for Health Record Linkage.

conditions (i.e. Y/N), alcohol misuse and dependence (i.e. Y/N), drug related dependence (i.e. Y/N), trauma service level (i.e. major trauma,

The state of NSW, Australia covers an area of 800,628 km2 [26], with

regional trauma, other hospital), injury mechanism, and nature of injury.

a population of 7.7 million [27]. NSW has had a trauma management The models were assessed in terms of their ability to discriminate

treatment of an injured individual at the most appropriate hospital [28].

survivors and non-survivors using the ROC curve and the

A major, level 1 trauma service is able to provide the full spectrum of

concordance statistic (c-statistic), with better discrimination scores

care for severely injured patients from resuscitation to discharge and a

having more area under the ROC curve. A ROC of ≥0.7 and < 0.8

regional trauma service is capable of providing care to individuals with

as a general indication was considered to provide acceptable

minor to moderate injuries [29]. Regional trauma services often provide

discrimination, a ROC of ≥0.8 and < 0.9 was considered to indicate

initial assessment and stabilisation of a seriously injured patient, before

excellent discrimination, and a ROC ≥0.9 was considered to indicate

transfer to a major trauma service. Within NSW there are ten major

outstanding discrimination [35]. Model fit was examined using

trauma centres (including three paediatric) and ten regional trauma

the Akaike information criterion (AIC) that indicates how close a

centres [30].

statistical model approaches the true distribution, with lower values indicating a better fit. Goodness-of-fit was examined using the

All hospital episodes of care related to the one injury event were linked

Hosmer-Lemeshow (H-L) statistic that compared predicted mortality

to form a period of care (i.e. all episodes of care related to the injury until

with actual mortality, with lower values indicating better calibration.

discharge from the health system). Ninety-day mortality was calculated

Nagelkerke’s R2 was used as a pseudo R-squared to provide

from the date of admission of the index injury hospital admission. Where

additional information regarding goodness-of-fit of the models by

an individual was treated at more than one hospital for their injury,

indicating the proportion of outcome variance explained, ranging

trauma care was considered to be delivered at the hospital where the

from 0 to 1, with values closer to one indicating higher variance

majority of patient care was provided as defined by length of stay (LOS).

explained by the model.

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system since 1991. This system facilitates transfer to and optimal

CLINICAL PAPER Table 1 Demographic characteristics of individuals with an injury-related hospitalisation, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014 Number

Percent

Male

409,148

55.6

Female

326,804

44.4

0–16

107,833

14.7

17–24

80,908

11.0

25–44

158,514

21.5

45–64

152,913

20.8

65–79

111,351

15.1

≥ 80

124,438

16.9

586,878

79.7

1–2

96,062

13.1

Gendera

Age group

Charlson Comorbidity Index group

3–4

29,312

4.0

≥5

23,709

3.2

Mental health diagnosesc

69,923

9.5

Alcohol misuse and dependence

53,280

7.2

Drug-related dependence

26,479

3.6

Trauma service level Level 1 trauma centre

204,530

27.8

Regional trauma centre

131,987

17.9

Other hospital

399,444

54.3

Injury mechanism Land transport incidents

73,977

10.1

Falls

262,196

35.6

Inanimate mechanical forces

88,323

12.0

Drowning and submersion and other threats to breathing

1558

0.2

Smoke, fire and flames, heat and hot substances

7497

1.0

Poisoning

11,563

1.6

Intentional self-harm

35,204

4.8

Assault

22,600

3.1

Other and unspecified injury mechanism

233,043

31.7

Superficial injuries

36,518

5.0

Open wound

89,321

12.1

Fracture

250,697

34.1

Dislocations, sprains & strains

34,367

4.7

Principal nature of injury

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Injury to nerves and spinal cord

7334

1.0

Injury to blood vessels

3057

0.4

Injury to muscle, fascia and tendon

28,424

3.9

Injury to internal organs

28,744

3.9

Foreign body entering through natural orifice

10,019

1.4

Burns

9274

1.3

CLINICAL PAPER Table 1 Demographic characteristics of individuals with an injury-related hospitalisation, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014 (Continued) Poisoning by drugs, medicaments and biological substances

Number

Percent

40,425

5.5

Toxic effects of substances chiefly nonmedicinal as to source

6868

0.9

Other and unspecified injuries

190,913

25.9

Intensive care unit admission

23,054

3.1

90-day mortality

13,744

1.9

Gender was missing 9 injury hospitalisations Age was missing for 4 injury hospitalisations Includes depression, schizophrenia, bipolar and anxiety disorders

b c

The full hospital-mortality data extract was used to calculate the SRRs

ICU admission

in order to include the widest possible range of injury diagnosis codes.

There were 23,054 (3.1%) ICU admissions for the injured patients. Of

Therefore, to account for possible bias caused by using a single data

those who were admitted to ICU, 58.8% were male, 46.7% were aged

extract for both development and testing, non-parametric bootstrapping

25–64 years, 37.7% had one or more Charlson comorbidities, 27.0%

with 200 replications was used to correct for optimism for calculating the

were injured following a fall, 17.2% following self-harm, and 15.9% after

fit statistics and 95% confidence intervals [21]. Bootstrapping involved

a land transport incident. Fractures (24.1%), poisoning (19.5%), and

fitting the full model and then deriving the parameter estimates which

injury to internal organs (18.3%) were the most common nature of the

were applied to the full dataset to obtain the apparent fit statistics. A

principal injury.

bootstrap data sample was then generated to derive fit statistics on the sample using the fitted value from the bootstrapped dataset. The fitted

The inclusion of comorbidities, injury mechanism and nature of injury

value was applied to the original full dataset to derive another set of fit

saw improvement in model assessment criteria for multiplicative-injury

statistics, which were used to calculate the optimism estimates. This

and single worst-injury ICISS for ICU admission, with concordance

process was replicated 200 times and then the average of the optimism

improving from 0.763 to 0.856 for multiplicative-injury ICISS and from

estimates were subtracted from the apparent fit statistics [21].

0.745 to 0.841 for single worst-injury ICISS. The multiplicative-injury ICISS was identified as a better predictor of ICU admission compared to the single worst-injury ICISS. The best discriminatory model was

Results During the study timeframe, there were 735,961 index injury admissions and 13,744 (1.9%) deaths within 90-days of hospital admission. Over half (55.6%) the injury hospitalisations were of males, with 68.0% aged

generated using multiplicative-injury ICISS, age group, gender, all comorbidities, injury mechanism, and nature of injury which explained 25% of variation (model 7, Table 3). Calibration was better for lower ICU admission and was very good below estimated ICU admission of 40% (Fig. 2).

< 65 years. For over three-quarters (79.7%) of hospitalisations there were no Charlson comorbidities identified. However, for individuals ≥65 years, 106,805 (45.3%) had at least one Charlson comorbidity identified.

Discussion

Just over one-quarter (27.8%) of hospital treatment was provided at a level 1 trauma centre. Falls and land transport crashes accounted for

The ability to provide an indication of injury severity for injury hospital

45.7% of all injury mechanisms and fractures (34.1%) were the most

admissions is useful to enable surveillance of injury severity for

common principal nature of injury (Table 1).

different injury mechanisms, to clinically evaluate injured patient health and to inform clinical resource use [7, 8]. This study demonstrated

The inclusion of additional predictor variables saw improvement in model

that the single-worst-injury ICISS was a better predictor of 90-day

assessment criteria for both multiplicative-injury and single worst-injury

mortality compared to multiplicative-injury ICISS, with the best model

ICISS for 90-day mortality. As predictor variables were added, concordance

incorporating age group, gender, all comorbidities, trauma centre

improved from 0.886 to 0.917 for multiplicative-injury ICISS and from 0.894 to

type, injury mechanism, and nature of injury. While the single-worst-

0.922 for single worst-injury ICISS. The single worst-injury ICISS was identified

injury ICISS provided the best model of 90-day mortality risk, clinical

as a better predictor of 90-day mortality than the multiplicative-injury ICISS.

significance of this model compared to the multiplicative ICISS is not

The best discriminatory model was generated using single-worst-injury ICISS,

expected. However, this does confirm other research which found that

age group, gender, all comorbidities, trauma centre type, injury mechanism,

an individual’s worst-injury is most influential in predicting mortality risk

and nature of injury that explained 33% of variation (i.e. model 8). Generally,

[10], rather than a combination of multiple injuries.

inclusion of type of trauma centre did not improve concordance over the inclusion of comorbid conditions (Table 2). The calibration curves for 90-day

Discrimination for 90-day mortality was indicated to range from

mortality for all models were similar. Calibration was better for lower mortality

excellent to outstanding, with concordance ranging from 0.886 to

and was very good below estimated mortality of 30% (Fig. 1).

0.922 for all models. These estimates are higher than previous studies

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outcomes, to provide an indication of injury burden in the population, 90-day mortality

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0.301 (0.296, 0.306)

0.304 (0.299, 0.309)

0.312 (0.308, 0.317)

98,219 (96,972, 99,362)

98,187 (96,932, 99,334)

96,513 (95,269, 97,631)

96,335 (95,099, 97,481)

96,335 (95,092, 97,472)

Model 3: Age group, gender, CCI group, mental health, drug, alcohol

Model 4: Age group, 97,792 (96,515, 98,917) gender, CCI group, mental health, drug, alcohol, trauma centre

96,731 (95,506, 97,865)

Model 2: Age group, gender, CCI group

Model 5: Age group, gender, CCI group, mechanism, nature

Model 6: Age group, gender, CCI group, mechanism, trauma centre

Model 7: Age group, gender, CCI group, mechanism, nature, trauma centre

Model 8: Age group, gender, CCI group, mental health, drug, alcohol, mechanism, nature, trauma centre

Single worst-injury ICISS

275 (221, 323)

273 (214, 323)

281 (222, 337)

315 (244, 370)

235 (186, 280)

392 (332, 451)

346 (291, 402)

196 (153, 235)

0.917 (0.916, 0.919)

0.917 (0.915, 0.919)

0.912 (0.910, 0.914)

0.911 (0.909, 0.914)

0.886 (0.884, 0.889)

Bootstrap-adjusted R2 (95% CI)

94,904 (93,684, 96,044)

94,899 (93,679, 96,040)

94,941 (93,717, 96,108)

95,263 (94,046, 96,449)

95,847 (94,601, 97,061)

96,202 (94,981, 97,447)

96,245 (95,034, 97,475)

0.326 (0.322, 0.331)

0.326 (0.321, 0.331)

0.324 (0.319, 0.328)

0.319 (0.314, 0.324)

0.316 (0.311, 0.321)

102,256 (100,846, 103,599) 0.270 (0.265, 0.274)

Bootstrap-adjusted Bootstrap-adjusted Bootstrap-adjusted H-L statistic (95% CI) concordance (95% CI) AIC (95% CI)

273 (229, 317)

268 (222, 314)

266 (213, 309)

304 (248, 356)

272 (223, 319)

347 (287, 393)

325 (267, 371)

134 (100, 170)

0.922 (0.920, 0.923)

0.921 (0.920, 0.923)

0.918 (0.916, 0.920)

0.917 (0.915, 0.919)

0.894 (0.892, 0.897)

Bootstrap-adjusted Bootstrap-adjusted H-L statistic (95% CI) concordance (95% CI)

a CCI group Charlson Comorbidity Index, mental health mental health conditions, alcohol alcohol misuse and dependence, drug drug-related dependence, mechanism injury mechanism, nature nature of injury

0.316 (0.311, 0.320)

0.315 (0.311, 0.320)

0.314 (0.309, 0.319)

0.301 (0.296, 0.306)

104,572 (103,114, 105,888) 0.252 (0.247, 0.257)

Model 1: Age group, gender

Bootstrap-adjusted R2 (95% CI)

Bootstrap-adjusted AIC (95% CI)

90-day mortalitya

Multiplicative-injury ICISS

Table 2 Model performance for ICISS to predict 90-day mortality, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014

CLINICAL PAPER

Fig. 1 Calibration curve for best fit for single worst-injury ICISS to predict 90-day mortality, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014. Model includes: age group, gender, Charlson comorbidities, mental health conditions, alcohol misuse and dependence, drug-related dependence, injury mechanism, nature of injury and trauma centre type

that examined the calculation of ICISS using in-hospital mortality for

individual would need to be alive when they reached the higher level of

Australian and New Zealand injury hospitalisations using ICD-10-AM [7]

care, otherwise there is potential to introduce immortal time bias [37].

and for the United States (US) using National Trauma Data Bank records and ICD-9-CM [10]. Differences in concordance scores are likely

Calibration results for 90-day mortality were better at lower levels

between the current study and previous Australian/New Zealand and US

of mortality (i.e. â&#x2030;¤30%). This is likely to be due to the majority of

studies as only in-hospital mortality was considered in the previous work

hospitalisations having low mortality (i.e. ICISS values near 1). The ICISS

compared to 90-day mortality in the current study, with survival post-

generated in this study indicating probability of death was overestimated

discharge likely to provide a better indicator of overall survival. Also,

for higher levels of mortality (i.e. â&#x2030;Ľ60%). Other studies have also found

differences in the classification structure between ICD-10-AM and ICD-

calibration to be better at lower levels of mortality [7, 8].

9-CM will account for some differences in concordance scores between the Australian and US research.

In the current study, the best model to predict ICU admission was generated using multiplicative-injury ICISS, age group, gender, all comorbidities, injury mechanism, and nature of injury. The multiplicative-

from excellent to outstanding for both the single worst-injury and the

injury method to calculate ICISS assumes that each injury independently

multiplicative-injury ICISS. Pre-existing health conditions have previously

affects the outcome, which may not necessarily be so when an individual

been demonstrated to increase mortality following injury, even for minor-

sustains multiple injuries [7]. However, it is possible that the superiority of

moderate severity injuries [36]. As all hospitals in one Australian state

the multiplicative-injury method to predict ICU admission could be due to

were included in the current study, the impact of including trauma centre

individuals requiring ICU admission being more likely to sustain multiple

type as a covariate in the assessment of predictors of 90-day mortality

injuries. Gagne and colleagues [38] have also found that the multiplicative-

was able to be examined. However, the inclusion of type of trauma

injury ICISS had the best discriminatory ability for ICU admission for

centre did not improve concordance, model fit or variation for 90-day

individuals hospitalised with traumatic brain injury. Further improvements

mortality. This seems counterintuitive and could be due to selection

in the predictive ability of ICU admission are likely to be gained with the

bias, with severely injured individuals more likely to be admitted and/or

addition of physiologic covariates. In particular, the inclusion of covariates

transferred to level 1 trauma centres for treatment and severely injured

was able to improve the model fit for the prediction of ICU admission.

individuals less likely to survive their injuries irrespective of where they are treated. While an individual who is transferred to a level 1 trauma

Compared to previous Abbreviated Injury Scale (AIS)-based estimates

centre may provide an indicator of injury severity, the severely injured

of injury severity, injury severity scoring using the ICISS is easier and

RESUSCITATION TODAY - SPRING 2019

The inclusion of information on comorbidities improved concordance

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0.161 (0.156, 0.164)

0.175 (0.170, 0.179)

0.195 (0.190, 0.199)

0.232 (0.228, 0.237)

0.241 (0.237, 0.246)

0.250 (0.246, 0.255)

0.252 (0.248, 0.257)

Model 1: Age group, 175,710 gender (173,800, 177,367)

Model 2: Age group, 173,093 gender, CCI group (171,178, 174,762)

Model 3: Age group, 169,268 gender, CCI group, (167,500, 170,857) mental health, drug, alcohol

Model 4: Age group, 162,265 gender, CCI group, (160,406, 163,818) mechanism

Model 5: Age group, 160,529 gender, CCI group, (158,753, 162,033) nature

Model 6: Age group, 158,863 gender, CCI group, (157,039, 160,357) mechanism, nature

Model 7: Age group, 158,474 gender, CCI group, (156,669, 159,970) mental health, drug, alcohol, mechanism, nature 572 (489, 650)

555 (468, 632)

589 (512, 661)

809 (707, 897)

1083 (959, 1210)

560 (468, 652)

1267 (1134, 1391)

0.856 (0.854, 0.859)

0.855 (0.852, 0.857)

0.849 (0.847, 0.852)

0.841 (0.839, 0.844)

0.809 (0.806, 0.812)

0.777 (0.773, 0.780)

0.763 (0.759, 0.766)

165,988 (164,216, 167,490)

166,481 (164,735, 168,032)

168,908 (167,072, 170,450)

171,083 (169,292, 172,649)

177,355 (175,605, 178,961)

181,083 (179,267, 182,822)

183,437 (181,589, 185,142)

0.213 (0.209, 0.217)

0.210 (0.206, 0.214)

0.197 (0.193, 0.201)

0.185 (0.182, 0.190)

0.152 (0.147, 0.156)

0.132 (0.127, 0.135)

0.119 (0.115, 0.123)

Bootstrap-adjusted R2 (95% CI)

Single worst-injury ICISS Bootstrap-adjusted Bootstrap-adjusted Bootstrap-adjusted H-L statistic (95% CI) concordance (95% CI) AIC (95% CI)

421 (356, 492)

366 (301, 436)

617 (538, 698)

619 (541, 699)

1333 (1170, 1495)

520 (427, 605)

1007 (892, 1121)

0.841 (0.839, 0.844)

0.839 (0.837, 0.842)

0.833 (0.830, 0.835)

0.824 (0.822, 0.826)

0.793 (0.790, 0.796)

0.759 (0.756, 0.763)

0.745 (0.741, 0.748)

Bootstrap-adjusted Bootstrap-adjusted H-L statistic (95% CI) concordance (95% CI)

CCI group Charlson Comorbidity Index, mental health mental health conditions, alcohol alcohol misuse and dependence, drug drug-related dependence, mechanism injury mechanism, nature nature of injury

Bootstrap-adjusted R2 (95% CI)

Multiplicative-injury ICISS

Bootstrap-adjusted AIC (95% CI)

ICU admission1

Table 3 Model performance for ICISS to predict ICU admission, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014

CLINICAL PAPER

Fig. 2 Calibration curve for best fit for multiplicative-injury ICISS to predict ICU admission, linked hospitalisation and mortality data, NSW, 1 January 2010 to 30 June 2014. Model includes: age group, gender, Charlson comorbidities, mental health conditions, alcohol misuse and dependence, drug-related dependence, injury mechanism, and nature of injury

Additionally, no validation of the diagnosis classifications in the hospital

hospital administrative data, but is reliant on accurate classification of

administrative records was able to be conducted. This study did not use

the worst-injury. Other indices of severity, such as the Injury Severity

a split-sample approach on hospital-mortality data extract to develop

Score (ISS), are more resource intensive, and are used by major trauma

the SRRs, instead the SRRs were developed on the original dataset to

centres in NSW. The ISS is based on an assessment of all injuries

maximise the injury diagnosis classifications available to develop the

sustained and is generated using AIS scores. It is calculated as the sum

SRRs, and bootstrapping was applied. The authors did investigate and

of squares of the single highest AIS score in each of the three most severely injured body regions out of nine body regions [39]. Calculation

perform a midpoint time-based split-sample approach for modelling and testing, with little difference in R2 or concordance values for ICISS

of ISS requires specialist training of data coders and specialist

to predict 90-day mortality (Additional file 1: Table S1), or to predict

resources. Moving to the routine clinical use of ICISS to estimate injury

ICU admission (Additional file 2: Table S2). Only health conditions

severity would seem to be a preferential option as comparisons of ICISS

relevant to the hospitalisation are recorded, so it is possible that the

and ISS have indicated that ICISS performs as well or better than ISS [1,

number of health conditions experienced are under-enumerated, even

5, 40].

with the 1-year look-back period. A longer lookback period may have been able to provide a better indication of long-term comorbid health

There are several limitations of the current study. No information was

conditions [41]. Deaths that occurred prior to hospital admission were

available on pre-hospital treatment and care and/or use of emergency

not considered. External validation of the SRRs generated in the current

transport services that may have aided survival. There was also no

study is recommended to ascertain if differences in model performance

information available on physiologic responses, such as Glasgow Coma Score, respiratory rate or systolic blood pressure. There were modest numbers for some injury diagnosis classifications and there is a low proportion of ICU admissions and deaths in the current study, so SRRs

for 90-day mortality and ICU admission are replicated using the same predictor variables in other jurisdictions. Lastly, ICISS is an indicator of threat-to-life, so does not consider threat to on-going disability following injury.

were based on small counts. The low proportion of deaths would have influenced the SRRs, as a higher proportion of diagnoses classifications would have survived. Likewise, for ICU admissions, with injured

Conclusion

individuals being less likely to be admitted to ICU. However, balancing these limitations, these injuries represented all the hospital admissions

This study has demonstrated that the worst-injury ICISS was a better

and 90-day mortality in the state.

predictor of 90-day mortality and that multiplicative-injury ICISS was a

RESUSCITATION TODAY - SPRING 2019

more accessible [10], able to be generated using routinely collected

CLINICAL PAPER better predictor of ICU admission. It also demonstrated better calibration

Author details

and explained variance for both outcomes with inclusion of covariates,

particularly comorbid conditions, injury mechanism and nature of injury.

Innovation, Macquarie University, Level 6, 75 Talavera Road, Sydney,

Moves to routinely use ICD-based injury severity measures, such as

NSW 2109, Australia. 2Sydney Medical School, The University of Sydney,

ICISS, should be considered for hospitalisation data.

Sydney, Australia.

Abbreviations

References

AIC:Akaike information criterion; AIS: Abbreviated Injury Scale; H-L:

1. Stephenson S, Langley J, Civil I. Comparing measures of injury severity for use with large databases. J Trauma Inj Inf Crit Care. 2002;53:326–332. doi: 10.1097/00005373-200208000-00023.

Hosmer-Lemeshow; ICD: International Classification of Diseases; ICISS: International Classification of Injury Severity Score; ICU: Intensive Care Unit; LOS: Length of Stay; NSW: New South Wales; ROC: Receiver Operator Characteristic; SRR: Survival Risk Ratio; Acknowledgements The authors wish to thank the NSW Ministry of Health for providing access to the Admitted Patient Data Collection, the NSW Registry of Births Deaths and Marriages for providing access to mortality data, the Australian Coordinating Registry for providing access to the cause of death unit record file and the CHeReL for conducting the record linkage. RM is supported by a career fellowship from the New South Wales Ministry of Health under the New South Wales Health Early-Mid Career Fellowships Scheme. JB’s research is funded by various NHMRC grants. Funding The research was supported by the New South Wales Health Early-Mid Career Fellowships Scheme. Availability of data and materials The data that support the findings of this study are available from the NSW Ministry of Health and the NSW Registry of Births, Deaths and Marriages, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission of all data custodians supplying the original data and with approval from the ethics committee. Authors’ contributions All authors were all involved in study concept and design. RM acquired the data, HT conducted the analysis and RM wrote the first draft of the manuscript. All authors were all involved in interpretation of data and critical revision of the manuscript. All authors read and approved the final manuscript. RESUSCITATION TODAY - SPRING 2019

Ethics approval and consent to participate Ethical approval was provided by the NSW Population and Health Services Research Ethics Committee (2015/08/599). A waiver of consent was granted by the ethics committees. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Correspondence: r.mitchell@mq.edu.au 1Australian Institute of Health

2. Glance L, Osler T, Maukamel D, Meredith W, Wagner J, Dick A. TMPM-ICD9 a trauma mortality prediction model based on ICD9-CM codes. Ann Surg. 2009;249(6):1032–1039. doi: 10.1097/ SLA.0b013e3181a38f28. 3. Willis C, Gabbe B, Jolley D, Harrison J, Cameron P. Predicting trauma patient mortality: ICD [or ICD 10 AM] versus AIS based approaches. ANZ J Surg. 2010;80(11):802. doi: 10.1111/j.14452197.2010.05432.x. 4. Sacco W, MacKenzie E, Champion H, Davis E, Buckman R. Comparison of alternative methods for assessing injury severity based on anatomic descriptors. J Trauma Inj Infect Crit Care. 1999;47(3):441–446. doi: 10.1097/00005373-199909000-00001. 5. Gagne M, Moore L, Beaudoin C, Kuimi B, Sirois M. Performance of international classification of diseases-based injury severity measures used to predict in-hospital mortality: a systematic review and meta-analysis. J Trauma Acute Care Surg. 2016;80(3):419–426. doi: 10.1097/TA.0000000000000944. 6. Meredith J, Kilgo P, Osler T. A fresh set of survival risk ratios derived from incidents in the National Trauma Data Bank from which the ICISS may be calculated. J Trauma Acute Care Surg. 2003;55(5):924–932. doi: 10.1097/01.TA.0000085645.62482.87. 7. Stephenson S, Henley G, Harrison J, Langley J. Diagnosis based injury severity scaling: investigation of a method using Australian and New Zealand hospitalisations. Injury Prev. 2004;10:379–383. doi: 10.1136/ip.2004.005561. 8. Davie G, Cryer C, Langley J. Improving the predictive ability of the ICD-based injury severity score. Injury Prev. 2008;14:250–255. doi: 10.1136/ip.2007.017640. 9. Gedeborg R, Warner M, Chen L, Gulliver P, Cryer C, Robitaille Y, Bauer R, Ubeda C, Lauritsen J, Harrison J. Internationally comparable diagnosis-specific survival probabilities for calculation of the ICD-10–based injury severity score. J Trauma Acute Care Surg. 2014;76(2):358–365. doi: 10.1097/TA.0b013e3182a9cd31. 10. Kilgo P, Osler T, Meredith J. The worst injury predict mortality outcome the best: rethinking the role of multiple injuries in trauma outcome scoring. J Trauma. 2003;55(4):599–607. doi: 10.1097/01. TA.0000085721.47738.BD. 11. Tepas J, Leaphart C, Celso b, Tuten J, Pieper P, Ramenosfky M. Risk stratification simplified: the worst injury predicts mortality for the injured children. J Trauma. 2008;65:1258–1263. doi: 10.1097/ TA.0b013e31818cac29. 12. Pracht E, Tepas J, Celso B, Langland-Orban B, Flint L. Survival advantage associated with treatment of injury at designated trauma centers. Med Care Res Rev. 2007;64(1):83–97. doi: 10.1177/1077558706296241. 13. Pracht E, Tepas J, Langland-Orban B, Simpson L, Pieper P, Flint L. Do pediatric patients with trauma in Florida have reduced mortality rates when treated in designated trauma centres? J Pediatr Surg. 2008;43:212–221. doi: 10.1016/j.jpedsurg.2007.09.047. 14. Balogh Z, Varga E, Tomka J, Süveges G, Tóth L, Simonka J. The new injury severity score is a better predictor of extended hospitalization and intensive care unit admission than the injury severity score in patients with multiple orthopaedic injuries. J Orthop Trauma. 2003;17(7):508–512. doi: 10.1097/00005131-20030800000006.

CLINICAL PAPER 15. Lavoie A, Moore L, LeSage N, Liberman M, Sampalis J. The injury severity score or the new injury severity score for predicting intensive care unit admission and hospital length of stay? Injury. 2005;36(4):477–483. doi: 10.1016/j.injury.2004.09.039.

33. Wan J, Morabito D, Khaw L, Knudson M, Dicker R. Mental illness as an independent risk factor for unintentional injury and injury recidivism. J Trauma Acute Care Surg. 2006;61(6):1299–1304. doi: 10.1097/01.ta.0000240460.35245.1a.

16. Tamim H, Al Hazzouri A, Mahfoud Z, Atoui M, El-Chemaly S. The injury severity score or the new injury severity score for predicting mortality, intensive care unit admission and length of hospital stay: experience from a university hospital in a developing country. Injury. 2008;39(1):115–120. doi: 10.1016/j.injury.2007.06.007.

34. SAS Institute . SAS: statistical software, version 9.4. Cary: SAS Institute; 2014.

17. Steyerberg Ewout W, Harrell Frank E, Borsboom Gerard J.J.M, Eijkemans M.J.C, Vergouwe Yvonne, Habbema J.Dik F. Internal validation of predictive models. Journal of Clinical Epidemiology. 2001;54(8):774–781. doi: 10.1016/S0895-4356(01)00341-9. 18. Steyerberg E, Harrell F. Prediction models need appropriate internal, internal–external, and external validation. J Clin Epidemiol. 2016;69:245–247. doi: 10.1016/j.jclinepi.2015.04.005. 19. Altman D, Royston P. What do we mean by validating a prognostic model? Stat Med. 2000;19(4):453–473. doi: 10.1002/(SICI)10970258(20000229)19:4<453::AID-SIM350>3.0.CO;2-5. 20. Kononen D, Flannagan C, Wang S. Identification and validation of a logistic regression model for predicting serious injuries associated with motor vehicle crashes. Accid Anal Prev. 2011;43(1):112–122. doi: 10.1016/j.aap.2010.07.018. 21. Harrell F, Lee K, Mark D. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–387. doi: 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4. 22. Bleeker S, Moll H, Steyerberg E, Donders A, Derksen-Lubsen G, Grobbee D, Moons K. External validation is necessary in prediction research: a clinical example. J Clin Epidemiol. 2003;56(9):826–832. doi: 10.1016/S0895-4356(03)00207-5. 23. Steyerberg E, Bleeker S, Moll H, Grobbee D, Moons K. Internal and external validation of predictive models: a simulation study of bias and precision in small samples. J Clin Epidemiol. 2003;56(5):441– 447. doi: 10.1016/S0895-4356(03)00047-7. 24. Harrell F. Springer Series in Statistics. Springer: New York; 2001. Regression modeling strategies with application sto linear models, logistic and original regression, and survival analysis.

35. Hosmer D, Lemeshow S. Applied logistic regression. Second. New York: John Wiley & Sons; 2000. 36. Hollis S, Lecky F, Yates D, Woodford M. The effect of pre-existing medical conditions and age on mortality after injury. J Trauma Acute Care Surg. 2006;61(5):1255–1260. doi: 10.1097/01. ta.0000243889.07090.da. 37. Hernán M, Sauer B, Hernández-Díaz S, Platt R, Shrier I. Specifying a target trial prevents immortal time bias and other self-inflicted injuries in observational analyses. J Clin Epidemiol. 2016;79:70–75. doi: 10.1016/j.jclinepi.2016.04.014. 38. Gagné M, Moore L, Sirois M, Simard M, Beaudoin C, Kuimi B. Performance of international classification of diseases–based injury severity measures used to predict in-hospital mortality and intensive care admission among traumatic brain-injured patients. J Trauma Acute Care Surg. 2017;82(2):374–382. doi: 10.1097/ TA.0000000000001319. 39. Baker S, O’Neil B, Haddon W, Long W. The injury severity score: a method for describing patients with multiple injuries and evaluating emergency care. J Trauma Injury Infect Crit Care. 1974;14:187–196. doi: 10.1097/00005373-197403000-00001. 40. Meredith J, Evans G, Kilgo P, MacKenzie E, Osler T, McGwin G, Cohn S, Esposito T, Gennarelli T, Hawkins M, Lucas C, Mock C, Rotondo M, Rue L, Champion H. A comparison of the abilities of nine scoring algorithms in predicting mortality. J Trauma Injury Infect Crit Care. 2002;53(4):621–629. doi: 10.1097/00005373-20021000000001. 41. Preen D, Holman CD, Spilsbury K, Semmens J, Brameld K. Length of comorbidity lookback period affected regression model performance of administrative health data. J Clin Epidemiol. 2006;59(9):940–946. doi: 10.1016/j.jclinepi.2005.12.013.

25. National Centre for Classification in Health . ICD-10-AM. Fifth. Sydney: National Centre for Classification in Health; 2006. 26. Australian Government. Area of Australia - States and Territories. 2017 [cited 2017 24/3/2017]; Available from: http://www.ga.gov.au/ scientific-topics/national-location-information/dimensions/area-ofaustralia-states-and-territories. 27. Australian Bureau of Statistics . Australian demographic Statistics Cat. no. 3101.0. Canberra: ABS; 2016. 28. NSW Health Department . NSW Trauma Services. North Sydney: NSW Health Department; 2009. Selected Specialty And Statewide Services Plans Number Six.

30. NSW Institute of Trauma and Injury Management. NSW Trauma Services. 2017 [cited 2017 24/3/2017]; Available from: https:// www.aci.health.nsw.gov.au/get-involved/institute-of-trauma-andinjury-management/clinical/trauma_system/nsw_trauma_system/ nsw_trauma_services. 31. Quan H, Li B, Couris C, Fushimi K, Graham P, Hider P, Januel J, Sundararajan V. Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676–682. doi: 10.1093/aje/kwq433.

RESUSCITATION TODAY - SPRING 2019

29. Royal Australasian College of Surgeons . The Australasian trauma verification program manual. Melbourne: Royal Australasian College of Surgeons; 2009.

32. Miller T, Lestina D, Smith GS. Injury risk among medically identified alcohol and drug abusers. Alcohol Clin Exp Res. 2001;25(1):54–59. doi: 10.1111/j.1530-0277.2001.tb02127.x.

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