determination of prognosis during neurointensive care in ... · determination of prognosis in...

QU A R T E R LY EV I D E N C E-B A S E D RE V I E W S O N CUR R E N T TO P I C S I N

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Acknowledgements:

Canadian Institutes of Health ResearchPublic Health Agency of Canada

John Granton, MDChair, Canadian Critical Care Society

John Marshall, MDChair, Canadian Critical Care Trials Group

Margaret Herridge, MDEditor, Critical Care Rounds

Determination of Prognosis DuringNeurointensive Care in Children andAdults with Traumatic Brain Injury: An UpdateBY ALEXIS F. TURGEON MD, MSC(EPID), FRCPC, AND JAMES S. HUTCHISON, MD, FRCPC

Several decades of research have advanced our understanding of factors in theprognosis of patients who have suffered a traumatic brain injury (TBI); however, testsor models that demonstrate high levels of accuracy remain elusive. This current issueof Critical Care Rounds presents the currently available early prognostic indicators inchildren and adults with TBI, and outlines the different scoring systems or modelsdeveloped in the ICU to determine prognosis after TBI.

Traumatic brain injury (TBI) is a common problem faced by critical care physicians. InCanada, more than 60% of all trauma cases are associated with brain injury and approximately2500 intensive care unit (ICU) admissions per year are related to severe TBI (Glasgow ComaScale [GCS] ≤8).1,2 It is the most common cause of death and acquired handicaps before the ageof 45 in Canada.3 TBI is most common in young males, but is seen in all ages. Causes of TBI inCanada include motor vehicle collisions, falls, inflicted injuries, and sports-related injuriesregardless of the patient’s age. It has also become one of the most common causes of death innations with emerging economies due to an increase in road traffic accidents.4

Despite improvements in the management of patients with TBI over the past fewdecades,5-8 mortality remains high for those with severe injury, ranging from 30%–50% inadults and 10%–30% in children.4,8-10 A significant proportion of survivors will be left withsevere neurological disabilities.11-13 Severe disability is less common in children and adoles-cents than adults, and persistent vegetative state is uncommon in pediatric cases.10,14 The earlydetermination of a patient’s prognosis is an important concern not only as it relates to mor-tality, but also for the patient’s global neurological and functional outcome. Indeed, there hasbeen an increased interest in recent years in long-term outcomes.15 In a recent multicentrecohort study, differences in both mortality and incidence of withdrawal of life-sustaining ther-apies were observed across Canadian centres9 in patients with severe TBI. These differencesmay be explained by variations in the evaluation of the neurological prognosis by medicalteams, and by the approach of physicians, families, or communities in terms of the level ofcare to provide. In a recent survey of Canadian Intensivists, Neurologists, and Neurosurgeons,there was important clinical equipoise observed concerning neuroprognostication amongrespondents for similar patients with severe TBI.16

The identification of evidence-based prognostic tools could help define realistic expecta-tions for physicians and relatives and assist with clinical decision-making. A better under-standing of prognosis during the ICU stay would also assist with hypothesis generation aboutbiological mechanisms of injury, risk stratification for quality assurance programs and clinicaltrials of medical and surgical therapies as well as early rehabilitation strategies.

Outcome Measures

Most clinical predictors and predictive models of prognosis focus on estimates of survival.Considering the important incidence of neurological disabilities following TBI, other out-comes also need to be prioritized to gain a better understanding of the burden of illness. TheGlasgow Outcome Scale (GOS)17 is the evaluation measure most often used to determine out-comes in prospective pediatric and adult studies. It consists of a 5-point scale that includesdeath, as well as different levels of neurological disability (1=death, 2=vegetative state, 3=severe

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The editorial content of Critical Care Rounds is determinedsolely by the Canadian CriticalCare Society.

Dr. Turgeon is an adult critical care physicianand Assistant Professor of Anesthesiology andCritical Care Medicine, Université Laval,Québec City, Québec. Dr. Hutchison is apediatric critical care physician and Professor ofPediatrics, University of Toronto, Toronto,Ontario. Both are clinician-scientists leadingresearch programs within the Canadian CriticalCare Trials Group (CCCTG) on thedetermination of prognosis in patients with TBIin adults and children, respectively. Dr. Turgeonis the principal investigator of 2 multicentreprospective studies on prognosis and on thewithdrawal of life-sustaining therapies in adultswith severe TBI, respectively funded by theCanadian Institutes of Health Research (CIHR#275553) (TBI-Prognosis Study) and by theFonds de Recherche du Québec – Santé (FRQS#24792) (TBI-QualE Study). Dr. Hutchison isthe co-principal investigator of a multicentreprospective study on prognosis in children withTBI (B-TBI Study), funded by the OntarioNeurotrauma Foundation (ONF #2010-VINI-DCP08-817) and the Victorian NeurotraumaInitiatives, and the co-principal investigator of aprospective study on long-term outcome inchildren with TBI (A-TBI Study), funded bythe Ontario Neurotrauma Foundation (ONF#2006-ABI-COMOR-440).

neurological disability, 4=moderate neurological disability,and 5=good recovery). An extended version of this toolusing an 8-point scale was recently proposed (GOSe) andhas recently replaced the standard GOS as an outcomemeasure in adult studies.18-20 In pediatric studies, the 6-point Pediatric Cerebral Performance Category (PCPC)score is also used more frequently.21,22 This was developedfrom the GOS and includes a category for mild disabilitygiven the important impact on education and learningduring development. More recently, the GOS extended forpediatrics (GOSe Peds) has been recommended by theNational Institutes of Health common data elements groupas the preferred functional outcome measure for pediatricTBI research.23 In most studies in both children and adults,the GOS or the GOSe are presented in a dichotomousfashion (ie, an unfavourable prognosis is defined as a GOSscore of 1–3, and/or a GOSe of 1–4.)

More detailed outcome measures, including cognitiveand neuropsychological tests and quality of life, have notbeen used to evaluate the ICU population despite theircommon use for evaluation after rehabilitation. Thus, mostprognostic models for outcomes in critically ill traumaticbrain-injured patients are designed to determine mortality,GOS, GOSe (in children and adults), and GOSe Peds orPCPC (in children).

Prognostic Indicators

Several independent prognostic indicators for TBIhave been identified and relate to preinjury neurologicalstatus, etiology of the trauma, clinical signs, neuroimaging,and electrophysiological and biochemical data. In a sys-tematic review of adults with severe TBI, the BrainTrauma Foundation and the American Association of Neu-rological Surgeons24 identified 4 significant clinical criteriaindependently associated with an unfavourable prognosis:the GCS, the patient’s age, pupil diameter and light reflex,and hypotension. Other important prognostic indicatorshave been identified in previous studies (Table 1).25-36

Clinical Signs and DemographicsGCS

The GCS is a simple, well-established tool for esti-mating the severity of the brain injury and has a linear rela-tionship with prognosis.1 The sum score and the motorcomponent subscore are both predictors of mortality andneurological function (GOS score) in children andadults.37,38 However, interobserver variability and differ-ence in assessment of the initial GCS can significantlymodify the estimation of morbidity and mortality.39 Forexample, the mortality associated with a GCS of 3–5 onadmission was reported to be 88% when the score was cal-culated prior to intubation and 66% when a score of 1 wasgiven for the verbal component in intubated adults withTBI.5,40 The optimal timing of assessment of the GCS isalso debatable, but the consensus is to evaluate it after non-surgical resuscitation.41 However, the timing of evaluationis not always reported in studies and often neglected. Moreimportantly, a significant proportion of patients survivewith a favourable neurological outcome (GOS 4-5) despitea low GCS score on admission. The GCS therefore, will

be useful as a primary risk evaluation but not for accurateprediction of mid or long-term prognosis.

Age

The likelihood of unfavourable neurological outcomeis closely associated with the patient’s age.27,42 In the case ofchildren, the age thresholds associated with increased riskof mortality or unfavourable functional outcome are belowthe ages of 3 and 7, respectively. In patients younger than3 years of age, the risk of death is 30%.43 For adults, thethreshold for increased mortality risk or unfavourablefunctional outcome is approximately >55–60 years.44 Therisk of death or persistent vegetative state in those above60 years of age ranges from 75%–90% 3 to 6 months afterinjury.45-47

Pupillary light reflex and pupil diameter

The bilateral absence of pupillary light reflex onadmission – part of the clinical diagnosis of brain death inCanada and several other countries – is correlated with a70%–95% chance of unfavourable prognosis (GOS 1–2) inadults with severe TBI5 and with mortality in children withsevere TBI.4 However, up to 5% of these patients still havea positive outlook (GOS 3–5) despite nonreactive pupilsafter resuscitation.48 Compared to other features of theneurological examination, pupillary reaction was found tobe a robust measurement for prognosis according to asmall cohort study even in the presence of medication.49

Hypotension

Hypotension in the prehospital setting, in the ICU, orin the operating room is associated with an increased risk ofdeath. A systolic blood pressure (SBP) ≤90 mm Hg is asso-ciated with 2-fold and 4-fold increases in adult and child

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Table 1: Most important early prognostic indicators*of mortality or unfavourable outcome at 6 or12 months

• Initial post-resuscitation GCS5

• Motor score25,26

• Age ≥55–60 years27,28

• Absence of pupillary light reflex5,25

• Systolic blood pressure ≤90 mm Hg26,29

• CT scan findings5

– Intracrbanial diagnosis30

– Presence of subarachnoid hemorrhage30,31

– Midline shift ≥5 mm32

– Status of basal cisterns5

• Mechanism of injury (penetrating > blunt trauma)28

• Increased intracranial pressure33,34

• Hypoxemia (PaO2 < 60 mm Hg)29,35

• Blood glucose level on admission28,36

* Admission data or from within the first 24 hours

GCS = Glasgow Coma Scale; CT = computed tomography; PaO2 = partial pressure of arterial oxygen

mortality with severe TBI, respectively.29,50 Hypotension onadmission and late hypotension each contributed to a 66%chance of unfavourable neurological outcome (GOS 1–2)compared to 17% in normotensive adults with TBI.29 Oneor more episodes of hypotension were also associated withworse neurological outcome in children with TBI.51,52

Although the duration of hypotension corresponding tounfavourable outcome is unknown, it should be treatedaggressively to prevent secondary brain injury. Currentguidelines recommend avoiding SBP ≤90 mm Hg.7,53

Furthermore, high SBP on admission has also beenassociated with an unfavourable outcome.54 It is likely anearly marker of increased intracranial pressure and thus ofthe severity of the TBI. As opposed to hypotension,aggressive treatment of high SBP is not a recommendedoption.

Hypoxemia

Low oxygen saturation, mainly during prehospitalcare, may occur more frequently than initially appreciatedin those with severe TBI.55 Even one hypoxemic event ofpartial pressure of oxygen (PaO2) <60 mm Hg (adjustedodds ratio 1.65; [1.37-2.00]) has been noted to increasemortality.29,56 Current recommendations are to avoid anyepisodes of oxygen saturation <90% or PaO2 <60 mm Hg.5

Intracranial pressure (ICP) and cerebral perfusion pressure (CPP)

Increased ICP and low CPP are associated withunfavourable outcomes in severe TBI in both children andadults.13,57,58 In one study of continuous CPP monitoring,the combination of duration and amplitude of low CPPwas highly predictive of outcomes of TBI.59 The treatmentof increased ICP and low CPP has been the key feature ofthe management of patients with severe TBI.5

Radiological ImagingComputed tomography (CT) scan

The etiology, localization, and extent of the lesion onCT imaging provide important prognostic information inadults. Four important predictors were closely linked withprognosis in the review of the American Association ofNeurological Surgeons: the absence of basal cisterns, presence of subarachnoid hemorrhage, presence of amidline shift, and the type of lesion.5 The absence of basalcisterns had a positive predictive value of 73%–87% forunfavourable outcomes at 6 and 12 months,60-62 while thepresence of a subarachnoid hemorrhage doubled the mor-tality.30,31 In a large prospective cohort study, a midlineshift >5 mm in patients ≥45 years of age was associatedwith a positive predictive value for unfavourable outcome(GOS 1–2) of 78%, and the positive predictive value was79% for a lesion with a volume >15 mL.32 The samelesions observed on the CT scan are also associated withunfavourable prognoses in children with TBI.4,63,64 Dif-ferent scoring systems were also proposed for risk stratifi-cation in adult patients.34,65-67 The most frequently usedclassification was created by Marshall and colleagues67

(Marshall score). This was based on the Traumatic ComaData Bank and originally developed to determine prog-

nosis at hospital discharge. The classification has a strongcorrelation with the GOS at discharge. The Marshallscore is not validated for use in children.

The recent technology of CT perfusion has been avail-able in many centres.68 This technology estimates thequantity of blood flowing to specific areas of the brain,allowing extrapolation for determining underperfused andoligemic areas. Its potential and properties as a futureprognostic tool require further study.69

Magnetic resonance imaging (MRI)

In adults, the sensitivity of the MRI is generally betterthan CT at detecting structural damage.70 ConventionalMRI provides useful information on vascular and axonaldamage while diffusion MRI allows a better appreciationof secondary lesions such as edema.71 Detailed imagingtechniques are vital since the location of an injury is alsoprognostic. In a prospective study of 57 patients, lesions ofthe corpus callosum, the basal ganglia, and the midbrainwere closely associated with unfavourable outcome (GOS1–3).72 In children and adults with severe TBI, bilateralbrainstem injury had positive and negative predictivevalues of 0.86 and 0.88, respectively, for unfavourableoutcome at 12 months post-injury.73

Newer MRI techniques, including diffusion-tensionimaging (DTI), susceptibility-weighted imaging (SWI),and functional MRI (fMRI), suggest enhanced detection ofmicrohemorrhages and subtle axonal injuries.68,74-76

However, although these new techniques are promising forprognostic assessment, very few studies have been con-ducted linking these findings to outcome and routine rec-ommendations for its use cannot be made.

Nuclear MedicineSingle-photon emission CT (SPECT) and positron emission tomography (PET)

Newer nuclear medicine imaging technologies haveshown promise in their abilities to correlate findings tolong-term prognosis.70,77 Among these, SPECT and PETare used to assess regional brain metabolism.68 However,as with other new technologies, they require further eval-uation prior to gaining acceptance as routine prognosticindicators.

Electrophysiological TestsSomatosensory evoked potential (SSEP) and brainstem auditory evoked potential (BAEP)

In systematic reviews evaluating the use of SSEP inadults and children with TBI, a bilateral absence of poten-tials at the median nerve was associated with a 95% positivepredictive value of unfavourable neurological prognosis at3–12 months (GOS 1–2).78,79 All SSEPs were performedwithin the first 2 weeks in the ICU. These findings wereconsistent with a previous systematic review.80 However,unilateral absence or abnormal evoked potentials were dif-ficult to interpret since most of these patients experiencedawakening from coma (GOS 3–5). In a recent study byHoulden and colleagues,81 a scoring system that proposeddifferent combinations of normal, abnormal or absentSSEP unilaterally or bilaterally showed promising prog-


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nostic value. SSEP has the highest specificity forunfavourable prognosis after TBI and should be used inclinical practice.

BAEPs were evaluated in small cohort studies earlyafter experiencing TBI. In pooled results from 7 studies(N=389), all but 1 patient showing unilateral or bilateralabsence of BAEP experienced a suboptimal outcome (GOS1–2) at 3–12 months.80 BAEPs are not used often in clinicalpractice.

Electroencephalography (EEG)

Many studies have evaluated the prognostic value ofEEG for long-term outcome in TBI. With the advent ofmore affordable and user-friendly technology, the use ofEEG is expanding in the ICU. Continuous EEG moni-toring is more often used to diagnose seizures and/ormonitor treatment. Although the technology is used exten-sively by neurologists, the information provided by an iso-lated EEG is unlikely to provide relevant long-term prog-nostic information. Beyond isoelectric patterns which areclearly associated with an unfavourable outcome, theabsence of EEG reactivity has a positive predictive value of93% for an unfavourable outcome (GOS 1–3).82,83 Addi-tionally, lack of alpha variability, representative of thalamicdamage, is associated with unfavourable prognosis at6 months.84 As opposed to SSEP, sedation produces somevariation in EEG evaluation. The advent of variabilityanalysis and more recently of synchronicity has brought arenewed interest in the prognostic value of the EEG.85,86

However, considering the complexity of data interpreta-tion for assessing EEG reactivity and synchrony, theseEEG patterns are not yet used in clinical practice.

Biomarkers

Biomarkers from blood, spinal fluid, or from brainmicrodialysis are emerging prognostic tools. Serum bio-markers such as S-100B protein, neuron-specific enolase,glial fibrillary acidic protein, and interleukin-8 were cor-related with unfavourable outcome at 12 months in bothchildren and adults with TBI (GOS 1–3 and PCPC 4–6).83,87-90 Protein S-100ß is the most studied biomarker inneurocritical care populations. Changes in the expressionof this protein are associated with the severity of braindamage and survival.91 Combining brain-specific bio-markers with inflammatory proteins improves the prog-nostic accuracy of serum biomarkers in TBI.92 Mass spec-trometry has recently been used for the discovery of novelbrain-specific prognostic biomarkers in TBI.93 Alactate/pyruvate ratio >25 obtained from brain dialysis wasfound to correlate with unfavourable outcome (GOS 1–3)at 6 months.94 Brain glucose level, glycerol, and glutamatemight also be associated with prognosis as much as brainpH.95,96 Clinical research on biomarkers is growing andtheir use as a prognostic determination tool is promising.

Predictive Models

Over the last decades, severity-of-illness models topredict mortality or morbidity in the ICU were developedin the absence of clinically significant accuracy from solepredictors. Having been developed in a general ICU pop-

ulation or in a specific TBI population, these models arelabeled as generic or specific.

Generic models

Generic models were developed for risk stratification,outcome research and quality assurance. However, theAcute Physiology And Chronic Health Evaluation(APACHE) scoring,97-99 the Simplified Acute PhysiologyScore (SAPS),100,101 and the Mortality Probability Model(MPM)102,103 were validated in the adult TBI population asprognostic tools.104-106 The 3 main generic models – theAPACHE II score, the SAPS II score and the MPM II(admission and 24 hours) to the GCS score – were com-pared using a subgroup of adult patients with head injury(n=401) from a large, multicentre cohort study.106 Allmodels predicted mortality at hospital discharge with gooddiscrimination (area under the receiver operating charac-teristic curve >0.9). Albeit, both the SAPS II and APACHEII slightly underestimated mortality compared to theMPM II. In a single-centre study of 200 patients, theAPACHE III score was found to be superior to theAPACHE II and the GCS in prediction of hospital mor-tality, with a sensitivity of 87% specificity of 81%.107 TheIndex of Independence in Activities of Daily Living (Indexof ADL), classifying functional outcomes in 7 grades, wasalso assessed as a long-term outcome. Again, the APACHEIII score provided the better estimate with a sensitivity of73% and a specificity of 82% for unfavourable functionalstatus measured by the Index of ADL (score of ≤4). Corre-lation with other long-term functional outcomes, such asthe GOS at 1 year, was only validated in a small, retrospec-tive cohort study with 70 patients.105

To specifically address the broader trauma population,other generic models were developed. The AbbreviatedInjury Scale (AIS), the Injury Severity Score (ISS), theRevised Trauma Score (RTS) and the Trauma InjurySeverity Score (TRISS) are the most often used scoringsystems for estimating mortality in this population.108-112

Using a large cohort from an American trauma registry(≥7700 patients) with different degrees of head injuryseverity, the Head component of the AIS (score from 1–6;6 = fatal injury) predicted hospital mortality in all cases(23/23) when the score was 6.28 However, the maximumscore of 6 is infrequent and might predict hospital deathsthat would be obvious without the help of a scoringsystem. A Head AIS of 5 also predicted hospital mortality,albeit with a low positive predictive value of 65%. Overall,the prognostic value of the Head AIS was not significantlybetter than the GCS. In a previous cohort study of 109patients, values from 0–3 of the Head AIS had shown apositive predictive value of 95% for favourable outcomesat 6 months (GOS 4–5).113

In a large retrospective cohort study, the APACHE IIIscore was observed to be more sensitive and specific thanthe APACHE II, the TRISS and the 24-hour ICU pointsystem (based on the GCS, the ratio of partial pressure ofarterial oxygen to fraction of inspired oxygen [PaO2/FiO2],and the fluid balance within the first 24 hours afterinjury)114 to estimate hospital mortality in a subgroup ofpatients with TBI.115 The performance was globally better


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in nonoperative head injury. In a small cohort study from adifferent American trauma registry, the Head AIS was notshown to be a significant predictor at 1 year for 2 measuresof function and independence: the Disability Rating Scaleand the Community Integration Questionnaire (CIQ).116-118

In the same study, the RTS – a score combining the GCSwith the heart and respiratory rates – did show a significantcorrelation with these functional long-term outcomes whenassociated with other demographic variables.118

Recently, the accuracy of the Pediatric Index of Mor-tality (PIM) was evaluated in 2575 children with head injuryadmitted to pediatric ICUs in England and Wales.8 Overall,the model performed well; however, mortality was lowest inthe mid-volume units. The Pediatric Risk of Mortality(PRISM) Score and the Pediatric Trauma Score (PTS) havealso been examined in children with TBI. A PRISM IIscore >17.5 had a sensitivity of 80% and a specificity of88% in predicting mortality in nonaccidental TBI in chil-dren.119 In another study, using multivariate analysis in 222children with severe TBI, both PRISM II >20 and bilateralmydriasis were associated with unfavourable outcome.4

Thus, generic models are well correlated with short-term outcomes such as hospital mortality, but very fewstudies attempted to validate these models for long-termfunctional outcomes. Moreover, none of these models hasa sufficiently high positive predictive value to be usedoutside of risk stratification and quality assurance.

Specific models

Most prognostic models for patients with severe TBIwere developed in an attempt to estimate the occurrence ofunfavourable neurological prognosis using different out-comes. These so-called prediction rules are normallydeveloped to determine the probability of a specificoutcome and then help physicians interpret clinical infor-mation.120 However, depending of the outcome of interestand further decisions associated with this outcome, theprediction rule has to be very sensitive or very specific.Many specific models using different statistical methodolo-gies were developed over the years with variable success(Table 2).25,26,30,46,121-125

The first prediction rule to have been developed wasthe GCS. This score has been so well implemented in clin-ical practice as part of the standard clinical examinationthat we tend to forget it is a specific prediction modeldeveloped in the TBI population.1 Considering the limita-tions of the GCS previously discussed, other models wereproposed for predicting short-, mid-, and long-term out-comes of mortality or neurological functions.

The first prediction trees for severe head injury wereproposed 20 years ago using clinical and demographic vari-ables of 555 patients on admission (pupillary response, age,motor response, and intracerebral lesions) to predict theGOS at 12 months.25 The predictive accuracy of the modelwas greater for good recovery (GOS 4–5) or death(GOS 1), with a positive predictive value of 82%, than forintermediate neurological outcomes. In another study, 5admission variables – age, GCS, ISS, pupillary reactivity,and hematoma on CT scan – were used to derive a predic-tion rule that showed 85% accuracy to predict mortality at

1 year after moderate and severe TBI.46 The rule wasderived from a prospective cohort of 372 patients and vali-dated in a subsequent cohort of 520 patients from the samecentre. Using data from a large epidemiologic study per-formed in Taiwan, Hsu and colleagues121 derived and vali-dated a rule to estimate the GOS assessed within 12 monthsafter injury. This neural network model was developedusing 10 admission variables and obtained a global accuracyof 75.8% to predict the GOS. Despite a good specificity forworst outcomes on the GOS, this accuracy is lower thanthe one observed in previous studies. As well as for the 3rules previously described, most specific models were devel-oped using nonmodifiable variables. However, 2 prognosticstudies included potentially modifiable variables to generatetheir prediction rules.25,125 Hukkelhoven and colleaguesused data from 2 multicentre clinical trials26,35 previouslyperformed in Europe and North America. Among 7 predic-tive admission characteristics, hypoxia and hypotensionwere included along with age, motor score, pupillary reac-tivity, CT scan classification, and presence of subarachnoidhemorrhage. This rule, developed to determine mortalityand unfavourable outcomes (GOS 1–3) at 6 months,showed accuracy advantageously comparable to the rulespreviously cited. The use of potentially modifiable predic-tors such as hypoxia and hypotension means inclusion ofsecondary brain injury components. In a small prospectivestudy (N=124) conducted by Andrews and colleagues,122 theinfluence of variables leading to secondary brain injury todetermine functional outcomes (GOS) at 12 months wasevaluated. In that study, 3 main prediction trees werecreated: one using only demographic data, a second oneusing only injury data and a last combining both types ofvariables. The tests accuracy ranged from 61%–64% in thevalidation phase. A longer duration of insult correlated withunfavourable GOS for most of the injury data.

In a recent study of 315 children with TBI,126 it wasobserved that age <2 years, GCS ≤5, accidental hypo -thermia, hyperglycemia, and coagulopathy on admissionwere significantly associated with mortality using a logisticregression analysis. These variables were used to develop aprediction score ranging from 0–6 for mortality. A score of0 was associated with 100% mortality. A recent small study(N=28) in children showed that combining postresuscita-tion GCS scores with a day-1 serum biomarker (inter-leukin-8) level produced a sensitivity of 100% and a speci-ficity of 96% for prediction of unfavourable outcome(GOS 1–2).127 These studies need to be validated in largeprospective cohorts of pediatric patients.

More recently, 2 prognostic models using largedatasets from previous prospective studies in adults weredeveloped.124,125 Using admission data from a large-scale,randomized, controlled trial on steroids in moderate andsevere TBI (N=10 008 patients), the Medical ResearchCouncil (MRC) CRASH Trial Collaborators124 developed4 prognostic models using age, GCS, pupillary reactivity,presence or absence of major extracranial injury and selectfindings on CT scan (when available) with 14-day mor-tality and the 6-month GOS (best area under the curve[AUC]: 0.88). These prognostic models at 6 months wereexternally validated using a large dataset from the Interna-


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Table 2: Important specific prognostic models

Author,period of

datacollection

No. ofpatients Data

Patientselection Outcome Predictors Model Validation Performance

Choi et al,25

1976-1989555 Retrospective,

single centreGCS < 9 GOS at

1 year4 admission variables: age, pupillary reactivity,motor response,intracerebral lesion

Tree model Limited Accuracy: 78%(60-82%)

Signorini et al,46

1989-1991

372 Prospective,single centre

GCS ≤ 12 or> 12 withISS > 16

Mortalityat 1 year

5 admission variables: age, GCS, ISS, pupillaryreactivity, hematoma on

CT

Logisticregression

Limited Accuracy: 85%

Hsu et al,121

1995-19983345 Database,

multicentreGCS ≤ 12 GOS in first

12 months10 variables: age, number of

nonreactive pupils, motorresponse, verbal response,eye opening, use of

helmet, hematoma on CT,subdural hematoma on CT,craniotomy, alcohol-

related

Neuralnetwork

Yes Accuracy: 76%Sensitivity: 48%–92%Specificity:89%–99%(depending onthe GOS score)

Andrews et al,122

1989-1991


GCS ≤ 12 or> 12 withISS > 15

GOS at 12 months

4 variables (time notreported): age, GCS, typeof accident, referral,

isolated head injury, CPP,hypotension, hypocarbia,sex, type of hematoma,evacuation of hematoma

Tree model No Accuracy: 60%–64%

Rovlias et al,30

1993-2000


GCS < 9 GOS at 6 months

6 variables (time notreported): age, GCS,pupillary response,Intracranial diagnosis,glucose level on Day 2,SAH, WBC on admission)

Tree model No Accuracy: 87%PPV for

unfavourableoutcome: 85%

Hukkelhovenet al,26

1991-1994

2269 2 RCTs,multicentre

GCS ≤ 12 GOS at 6 months

7 admission variables: age, gender, cause ofinjury, motor score,pupillary reactivity,

hypotension, hypoxia, CTclassification, SAH

Logisticregression

Yes AUC*: 0.83–0.89

Combes et al,123

1989-1992


GCS < 9 GOS(uncleartimeperiod)

3 admission variables: age, motor response,

hypoxia

Logisticregression

No Accuracy: 73%Sensitivity: 93%Specificity: 57%

Perel et al(MRC CRASHdatabase),124

1999-2004

10 008 Prospectivemulticentre

GCS ≤ 14 GOS at 6 months,14-daymortality

7 admission variables: age,GCS, pupillary reactivity,major extracranial injury,petechial hemorrhages,obliteration of thirdventricle, SAH, midlineshift, nonevacuated

hematoma

Logisticregression

Yes AUC: 0.83–0.88

Steyerberg et al

(IMPACTdatabase),125

1984-1997

8509 Prospectivemulticentre

GCS ≤ 12 GOS at 6 months,mortality

10 admission variables:age, GCS motor score,pupillary reactivity,hypoxia, hypotension,Marshall score, SAH,

epidural hematoma, bloodsugar, hemoglobin level

Logisticregression

Yes AUC: 0.78–0.80

GOS = Glasgow Outcome Scale; ISS = Injury Severity Score; CPP = cerebral perfusion pressure; SAH = subarachnoid hemorrhage; WBC = white blood cell count; PPV = positive pressure ventilation; RCT = randomized, controlled trial; AUC = area under the curve; MRC = Medical Research Council; IMPACT = International Mission for Prognosis And Clinical Trial* Area under the operating curve in the validation dataset.

tional Mission for Prognosis And Clinical Trial(IMPACT) database.128 These prognostic models usedmixed data, from low-, middle-, and high-income coun-tries and are available on the Internet. During the sameperiod, 6 different prognostic models using the IMPACTdatabase (data from 11 prospective studies in patients withmoderate or severe TBI conducted from 1984–1997) weredeveloped.125 These prognostic models were developedusing the following admission data from 8509 patients:age, GCS motor score, pupillary reactivity, hypoxia,hypotension, Marshall score, and select CT scan featuresto predict mortality and the GOS at 6 months. Thesemodels proposing a scoring system were externally validated using the MRC CRASH dataset (bestAUC 0.80). The prognostic models developed using theMRC CRASH and the IMPACT databases are the largestand the most accurate using admission data to date.

Limitations

A number of limitations to these prognostic modelsmust be considered. First, many models predate advances inCT scan as part of bedside care, monitoring, and consensusrecommendations for TBI management.5 Additionally veryfew models accounted for secondary cerebral injuries,which are not always avoidable despite the application ofappropriate prevention measures.5,26,122 Most prognosticmodels use admission variables which could be prematureto show high accuracy.129 Other prognostic models usedcomplex formulas requiring computer software assistancemaking their utilization less convenient in clinical prac-tice.121 More importantly, many models were derived fromsingle centres,25,46 small cohorts,122,123 retrospective data,25,126

or were never externally validated in a distinct dataset,35,40,122

thus precluding generalizability of the findings.

Conclusion

Over the past decades, there has been an importantinterest in the understanding of prognosis in critically illpatients with TBI. Yet, long-term neurological outcomesare challenging to determine early after the event despitethe identification of many prognostic indicators. There areseveral promising innovative technologies, but none areyet appropriate for use in current clinical practice. There isno current prognostic test that is able to reliably delineatefavourable versus unfavourable outcome. Many prognosticmodels have been developed to improve this level ofuncertainty and address these limitations. However, nomodel is sufficiently precise to be standard of care forprognostic evaluation of an adult TBI population. Further-more, few models have been developed and validated forthe pediatric population.

Considering that most deaths in critically patients withTBI occur following the withdrawal of life-sustaining ther-apies,9 more precise prognostic instruments with long-term neurological functional outcome measures in bothchildren and adults are urgently required. These instru-ments could not only provide better evidence-based expec-tations for physicians, family and relatives, but also a betterrisk stratification of patients with TBI for evaluatingsystem performance and standardize future research.

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