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
8
CLINICAL PAPER R isks and benefits of hypotensive resuscitation in patients with traumatic hemorrhagic shock: a meta-analysis
17
EDUCATION The European Trauma Course: an introduction
18
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.
COPYRIGHT: Media Publishing Company Media House 48 High Street SWANLEY, Kent, BR8 8BQ
References: 1European Resuscitation Council [ERC] - ERC Guidelines 2015
3
EDITORS COMMENT
EDITORS COMMENT Welcome to the Spring Edition of Resuscitation Today.
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4
“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 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
RESUSCITATION TODAY - SPRING 2019
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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7
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
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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
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
11
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
12
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
13
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)
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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,
2
Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand. Division of Vascular Surgery, Department of Surgery, Faculty of Medicine,
3
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
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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.
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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
RESUSCITATION TODAY - SPRING 2019
Resuscitation Today welcomes the submission of clinical papers, case reports and articles that you feel will be of interest to your colleagues.
17
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
19
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
0
586,878
79.7
1–2
96,062
13.1
Gendera
b
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
a
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
21
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22
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 (0.916, 0.919)
0.917 (0.915, 0.919)
0.917 (0.915, 0.919)
0.912 (0.910, 0.914)
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 (0.322, 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)
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)
0.922 (0.920, 0.923)
0.921 (0.920, 0.923)
0.921 (0.920, 0.923)
0.918 (0.916, 0.920)
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
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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
23
RESUSCITATION TODAY - SPRING 2019
24
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
a
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
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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
25
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:
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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.
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