Brain Advance Access originally published online on November 10, 2004
Brain 2004 127(12):2608-2620; doi:10.1093/brain/awh320
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Brain Vol. 127 No. 12 © Guarantors of Brain 2004; all rights reserved
Thirty month outcome from early childhood head injury: a prospective analysis of neurobehavioural recovery
1 University of Melbourne, 2 Royal Children's Hospital, 3 Murdoch Children's Research Institute, 4 Alfred Hospital and 5 Monash University, Melbourne, Australia
Correspondence to: Vicki Anderson, PhD, Department of Psychology, Royal Children's Hospital, Flemington Road, Parkville, Victoria 3052, Australia E-mail: vicki.anderson{at}rch.org.au
Received June 19, 2003. Revised January 13, 2004. Second revision on July 19, 2004. Accepted July 20, 2004.
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Summary |
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Traumatic brain injury (TBI) is a common cause of acquired disability during childhood. While much is now known about outcome following TBI in the school-aged population, recovery in infants and young children is less well documented. The aim of this study was to examine neurobehavioural function following TBI during early childhood, to plot recovery over the 30 months post-injury and to identify predictors of outcome. The study compared three groups of children, sustaining injuries of different severity (mild = 14, moderate = 46, severe = 24), aged 2.0–6.11 years at injury, with a healthy control group (n = 33). The groups were similar with respect to pre-injury adaptive and behavioural function, psychosocial characteristics, age and gender. Using a prospective, longitudinal design, intellectual, language and memory functions were investigated acutely post-injury and again at 12 and 30 months post-injury. Results suggested a strong association between injury severity across all neurobehavioural domains. Further, 30 month outcome was predicted by multiple factors including injury severity, socio-economic status, pre-injury adaptive abilities and age, with pre-injury child behaviour and specific lesion characteristics playing surprisingly little role. In conclusion, children with more severe injuries, lower pre-injury adaptive abilities and lower socio-economic status are at greatest risk of long-term neurobehavioural impairment, even several years post-injury.
Key Words: traumatic brain injury; children; IQ; language; memory
Abbreviations: BST = Bus Story Test; EOWPVT = Expressive One-Word Picture Vocabulary Test; FFQ = Family Functioning Questionnaire; FSIQ = full-scale IQ; GCS = Glasgow Coma Scale; MDI = Mental Development Index; NMI = Numerical Memory Test I; PIC = Personality Inventory for Children; PIQ = performance IQ; PPVT-R = Peabody Picture Vocabulary Test-Revised; RBMT = Rivermead Behavioural Memory Test; RTA = Road Traffic Accident; SES = socio-economic status; SRT = Story Recall Test; SLT = Spatial Learning Test; TACL-R = Test of Auditory Comprehension of Language—Revised; TBI = traumatic brain injury; TT = Tapping Test; VABS = Vineland Adaptive Behavior Scale; VFT = Verbal Fluency Test; VIQ = verbal IQ; WISC-III = Wechsler Intelligence Scale for Children—III; WPPSI-R = Wechsler Preschool and Primary Scale of Intelligence—Revised.
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Introduction |
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Traumatic brain injury (TBI) is a common cause of acquired disability during childhood. It is estimated that, in any one year, as many as 250 out of 100 000 children experience a head injury (Kraus, 1995
). While much is known about outcome following TBI in school-aged populations, recovery following insult in infants and young children is less well documented. A number of studies have investigated the nature of neuropsychological sequelae following paediatric TBI in school-aged children and adolescents. These studies suggest that, even years after injury, deficits are evident in attentional capacity (Kaufmann et al., 1993; Dennis et al., 1995; Anderson and Pentland, 1998; Catroppa and Anderson, 1999, 2003; Fenwick and Anderson, 1999), memory and learning (Levin et al., 1988; Anderson et al., 2000a; Catroppa and Anderson, 2002), psychomotor skills (Bawden et al., 1985), linguistic abilities (Ewing-Cobbs et al., 1989; Jordan and Murdoch, 1994; Catroppa and Anderson, 2004) and executive functions (Dennis et al., 1996a; Todd et al., 1996; Levin et al., 1997; Hanten et al., 1999, 2000). It is likely that, with fewer established skills, younger, pre-school children may experience even more severe and persistent impairments as a result of TBI. The aim of this study was to examine the nature of any neurobehavioural sequelae following TBI during early childhood, to plot recovery patterns over the 30 months post-injury and to identify significant predictors of outcome.
It is now well established that injury severity, as measured by parameters such as the Glasgow Coma Scale (GCS) or post-traumatic amnesia, represent reliable predictors of outcome across all ages, with more severe TBI related to greater impairments of neurobehavioural function (Winogron et al., 1984; Fletcher et al., 1990; Michaud et al., 1992; Jaffe et al., 1993; Dennis et al., 1996a). However, no single factor can account for the wide variability in recovery patterns observed in paediatric populations (Fletcher et al., 1995). It is likely that several mechanisms may act, both independently and interactively, to determine prognosis. For example, pre-injury abilities and environmental factors, such as socio-economic status (SES) and family functioning, have been reported to contribute to long-term outcome (Donders, 1992; Rivara et al., 1993, 1994; Taylor et al., 1995; Yeates et al., 1997; Anderson et al., 2001). Several studies have indicated that low levels of maternal education and lower SES may be associated with increased risk of accident (Bijur et al., 1988; Larson and Pless, 1988; Coster et al., 1994), suggesting that victims of childhood TBI represent a specifically disadvantaged subset of the population. However, a number of recent studies conducted outside the USA have questioned this view, arguing that pre-morbid psychosocial disturbances are no more common in children with TBI than in the general population (Donders, 1992; Prior et al., 1994). Regardless of pre-injury characteristics, there is growing evidence that, for children with psychosocial disadvantage, there is an increased risk of post-injury behavioural disturbance (Brown et al., 1981; Taylor et al., 2002), with recent research also identifying associated deficits in cognitive and educational function in this group (Kinsella et al., 1995, 1997; Yeates et al., 1997).
A critical predictor of outcome following child TBI is the child's age, or developmental level, at time of injury. Despite the acknowledged importance of developmental factors, only a small number of studies have examined the consequences of TBI in very young children. The earliest studies, employing cross-sectional designs and summary outcome measures, detected no association between injury age and outcome (Klonoff et al., 1977; Chadwick et al., 1981; Dennis, 1985; Tompkins et al., 1990). More recent, longitudinal investigations have reported that, while children sustaining early injuries present with similar patterns of acute impairment, they may demonstrate poorer recovery than children sustaining TBI later in childhood (Lange-Cosack et al., 1979; Ewing-Cobbs et al., 1989; Kriel et al., 1989; Anderson and Moore, 1995; Anderson et al., 1997, 2000b; Gronwall et al., 1997). In support of this argument, Thompson et al. (1994) have shown that younger children with severe injuries exhibited slower development of motor and visuo-spatial skills than older children or younger children with mild head injuries, while Kaufmann et al. (1993) described similar impairments for attentional skills following early TBI. Research from our laboratory has demonstrated increasing developmental lag with time since injury, across verbal and non-verbal skills, in young children with severe TBI (Anderson and Moore, 1995; Anderson et al., 2000).
Traditionally, it has been argued that the young child's brain is ‘plastic’, and may sustain substantial insult with little or no observable loss of function (Lenneberg, 1967; Smith, 1983). Proponents of this ‘brain plasticity’ model argue that young children show less severe injuries and experience less substantive residual effects from brain insult (Teuber, 1962; Lenneberg, 1967; Tompkins et al., 1990) than older children and adults. Such theories are based largely on the surprisingly good outcomes observed in very young children with focal or unilateral cerebral pathology (Dennis, 1980; Aram and Enklemen, 1986). These findings have been interpreted as evidence that brain physiology and structure are more modifiable early in life, with healthy tissue subsuming the function of damaged tissue, resulting in few, if any, residual impairments.
Contrary to this well-established view, recent research suggests that, while there may be a degree of neuronal plasticity, this does not necessarily translate to ‘functional’ plasticity, particularly where cerebral pathology is widespread, such as is the case for TBI (Ewing-Cobbs et al., 1987; Taylor et al., 1993; Anderson et al., 1994, 1997; Dennis et al., 1995; Taylor and Alden, 1997). Rather, serious residual neurobehavioural impairments have been reported, providing evidence that the young child's brain may in fact be particularly vulnerable to early trauma. Further, some researchers have suggested that, in this young age group, residual deficits are not static, but that young children ‘grow into’ these deficits gradually through childhood, with new impairments emerging as expected developmental milestones fail to be attained (Anderson, 1988; Dennis, 1989; Anderson et al., 1994, 2000c; Anderson and Moore, 1995; Dennis et al., 1996b; Taylor and Alden, 1997). These findings argue that younger children may require more substantial clinical follow-up and intervention post-TBI.
A range of factors may account for the increased susceptibility of the young child to ongoing neurobehavioural deficits following generalized cerebral insult. For example, structural factors may influence the nature of injuries sustained by young children. Young children possess a relatively larger head supported by a smaller neck compared with older children and adults, placing them at greater risk for diffuse injuries (Amacher, 1988). Greater flexibility of cranial bones in young children may increase the capacity of the skull to absorb traumatic forces, thus minimizing focal brain injury (Craft et al., 1972; Begali, 1992). As a result, young children are more likely to experience diffuse injury. Such diffuse damage may interrupt ongoing cerebral development, including neuronal myelination and frontal lobe maturation, both processes which are thought to be particularly rapid during the first 5 years of life (Hudspeth and Pribram, 1990; Thatcher, 1991). The neuropsychological literature suggests that these cerebral substrates may subsume information processing activities and executive skills, and thus damage or disruption may have implications for future learning and skill acquisition.
From a cognitive perspective, young children possess few established skills, and are just beginning to consolidate skills and knowledge. The younger the age at injury, the fewer mature cognitive skills available to the child. Future acquisition of skills may be compromised, depending on the nature and severity of the cerebral damage (Dennis, 1989). If this is the case, then young children may appear to have few observable deficits in the early stages of recovery from cerebral trauma. However, future development may lag behind that of healthy peers or, alternatively, impairments may ‘emerge’ as the impact of poor skill acquisition results in increasing discrepancies between the child with TBI and peers over time. As the child moves through childhood, and is required to function independently, information processing skills and executive functions, subsumed by areas of the brain which are immature during early childhood, especially those vulnerable to the impact of TBI, may fail to mature (Kennard, 1940; Finger and Stein, 1982; Dennis, 1989; Dennis et al., 1996a; Anderson et al., 2001b).
Such findings, while largely based on retrospective studies, provide initial support for the vulnerability of the young child's brain to the generalized effects of head injury. We were interested to determine whether such vulnerability, and consequent poor functional outcome following early TBI, was universal and whether we could identify additional risk factors predictive of outcome in this age group (e.g. injury severity, pre-injury ability or psychosocial factors). While individual predictors of outcome can be evaluated in isolation, it is most likely that these factors will interact to determine long-term outcome. Some researchers have begun to address this possibility, suggesting a double hazard hypothesis where psychosocial, developmental and injury variables interact to determine prognosis (Breslau, 1990; Taylor and Alden, 1997).
The present study aimed to address the impact of TBI during early childhood on neurobehavioural functions, by plotting recovery patterns over 30 months post-injury. The design of the study was prospective and longitudinal, with children recruited at the time of injury and followed over 30 months. Measures of pre-injury status, psychosocial characteristics and injury parameters were collected to provide a baseline on which to determine injury effects. We predicted that children with early childhood TBI would experience residual neurobehavioural impairments, even after the traditional 2 year recovery period. We also hypothesized that a number of injury-related, developmental and psychosocial factors would impact on 30 month outcome. The results presented here represent an extension of an earlier study, which followed children to 12 months post-injury (Anderson et al., 1997).
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Methods |
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Participants
One hundred and seventeen children participated in the study. Eighty-four children with a diagnosis of closed head injury were recruited from consecutive admissions to the neurosurgical ward of the Royal Children's Hospital, Melbourne, between 1993 and 1997. Inclusion criteria were: (i) age at injury 2.0–7.0 years; (ii) documented evidence of TBI, including a period of altered consciousness; (iii) medical records sufficiently detailed to determine injury severity; (iv) able to complete evaluations; (v) completed acute, 12 and 30 month evaluations; (vi) English as a first language; and (v) parents competent with English. Exclusion criteria were: (i) TBI as a result of abuse; (ii) penetrating injury; (iii) history of previous TBI; and (iv) evidence of pre-existing neurological, psychiatric or developmental disorder.
During recruitment, 109 children were admitted to hospital with TBI. Seven were ineligible due to pre-existing neurological, psychiatric or developmental problems (n = 2), previous TBI (n = 1) or had sustained injury due to abuse (n = 4). One child had sustained such severe injuries that he was unable to participate in the assessment at any time point. Initial approaches were made to 101 children, and their families, with 17 declining to participate. Reasons for refusal included inconvenience of time requirements (n = 6), residing outside the state of Victoria (n = 6) and lack of interest (n = 5). Comparison of the demographic and injury characteristics of participating and non-participating groups identified no significant group differences.
The remaining 33 children comprised the non-injured control group and were identified via pre-schools and childcare centres within the injured participants' communities, to match the TBI groups as closely as possible for age, gender, SES and pre-injury characteristics. Inclusion criteria (i), (iv), (v) and (vi) and exclusion criteria (iii) and (iv), described above, also applied to this group. Table 1 provides the demographic characteristics of the sample.
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Children with TBI were divided into groups, based on the following criteria: (i) mild TBI (n = 14): GCS (Teasdale and Jennett, 1974
) on admission 13–15, indicating alteration of conscious level (e.g. drowsiness, disorientation), no evidence of mass lesion on CT/MRI, and no neurological deficits; (ii) moderate TBI (n = 46): GCS on admission 9–12, indicating significantly altered consciousness, with reduced responsiveness; and/or mass lesion or other evidence of specific injury on CT/MRI; and (iii) severe TBI (n = 24): GCS on admission 3–8, representing coma, and mass lesion or other evidence of specific injury on CT/MRI. Implementation of this categorization procedure for severity successfully classified all children. GCS scores (on admission) were recorded by the admitting medical officer. Following admission, half-hourly neurosurgical observations were recorded by neurosurgical staff, and these gradually increased to 4-hourly observations, continuing until the child had regained consciousness. CT/MRI scans were reported and classified by an experienced neuroradiologist and neurosurgeon. Where there was radiological evidence of only frontal pathology or extrafrontal pathology, children were classified into one of those groups. Where pathology was diffuse, or multifocal, children were included in the ‘diffuse’ group. All children with mild TBI recorded normal CT/MRI results. Abnormalities (non-linear fractures, bleeds, oedema, axonal damage and mass effects) were detected in 34 (73.9%) of the moderate TBI group and 22 (91.7%) of the severe group, with lesion sites described in Table 2. TBI due to motor vehicle accidents was relatively uncommon in this sample (n = 26, 22.2%), with most injuries occurring as a result of falls or blows to the head (n = 48, 41.0%).
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Measures
Pre-injury screening
Families agreeing to participate completed the following questionnaires, based on pre-injury behaviours.
Injury and demographic variables. These were recorded via children's medical record and a demographic/medical questionnaire completed by parents. Data were collected on medical and developmental history, parental education and occupation, and family constellation. During in-patient stay, medical records were reviewed daily and details of GCS, length of coma, neurological abnormalities and surgical interventions were recorded. SES was coded using Daniel's Scale of Occupational Prestige (Daniel, 1983) which rates parent occupation on a 7-point scale, where a high score represents a low SES.
Adaptive functioning. The Vineland Adaptive Behavior Scale (VABS; Sparrow et al., 1984) was completed by parents, based on pre-injury child functioning. Total adaptive behaviour score was employed in analyses (mean = 100, SD = 15).
Behavioural functioning. The revised format version of the Personality Inventory for Children (PIC; Lachar, 1992) was employed, which included 131 items for which parents respond either true or false. Parents completed this questionnaire based on their child's pre-injury functioning. Four factors (mean = 50, SD = 10) are derived from the scale: factor I, undisciplined/poor self-control; factor II, social incompetence; factor III, internalization/somatic symptoms; and factor IV, cognitive development. Higher scores indicate greater behavioural disturbance, and scores >70 represent behavioural difficulties of clinical significance.
Family Functioning Questionnaire (FFQ; Noller, 1988). This 68 item questionnaire was employed to measure family function. Items are rated on a 6-point scale (1 = totally agree, 6 = totally disagree). Three factors are derived: conflict (scored out of 60 points); intimacy (72 points); and parenting style (30 points), with a higher score reflecting more of that characteristic. The intimacy factor was employed in statistical analyses, due to its high correlation with both other factors.
Child evaluations: acute, 12 and 30 months
Initial evaluation occurred within the first 3 months post-injury, as soon as the child was able to participate in test procedures. Follow-ups were conducted at 12 and 30 months post-injury.
Intellectual evaluation
The Bayley Scales of Infant Development (Bayley, 1969), Wechsler Preschool and Primary Intelligence Scale—Revised (WPPSI-R; Wechsler, 1989) and Wechsler Intelligence Scale for Children—III (WISC-III; Wechsler, 1991) were administered at each evaluation, dependent on the child's age at testing. Full-scale IQ (FSIQ), verbal IQ (VIQ) and performance IQ (PIQ) scores were calculated (mean = 100, SD = 15).
Expressive language measures
Expressive One-Word Picture Vocabulary Test (EOWPVT; Gardner, 1979). This is a measure of expressive language, specifically the ability to name pictorial stimuli. Standard scores (mean = 100, SD = 15) were employed in analyses.
Renfrew Bus Story Test (BST; Renfrew, 1995). The BST requires the child to retell a story told by the examiner in response to a picture. Raw scores were derived for story content (information) and length.
Verbal Fluency Test (VFT; McCarthy, 1972). This test taps fluency skills and requires the child to generate items in a number of categories: animals, things to eat, things to wear, things to ride. Each category has a time limit of 20 s. Raw scores were used in analyses.
Receptive language measures
Peabody Picture Vocabulary Test—Revised (PPVT-R; Dunn and Dunn, 1981). The PPVT-R assesses receptive vocabulary for single words, with items graded in order of difficulty. Standard scores (mean = 100, SD = 15) were derived from the test.
Test of Auditory Comprehension of Language—Revised (TACL-R; Carrow-Woolfolk, 1985). This measures components of language comprehension. Deviation quotients, based on total scores (mean = 100, SD = 15), were used in analyses.
Memory assessment
Numerical Memory I (NMI; McCarthy, 1972). The NMI assesses auditory span, requiring the child to repeat strings of digits of increasing length. Raw scores were used in analyses.
Tapping Test (TT; McCarthy, 1972). The TT taps visual span and involves the child tapping visual sequences of increasing length. Raw scores were used in analyses.
Story Recall Test (SRT; Anderson et al., 1995, from Christensen, 1979). This is a verbal learning task in which children must repeat two stories, each containing 21 content items. Recall was summed across the two trials, with a maximum score of 42.
Spatial Learning Test (SLT; Anderson et al., 1995, from Lhermitte and Signoret, 1972). This test evaluates spatial memory by requiring the child to learn an array of nine stimuli. The resultant score reflected the number of trials taken to learn placements of all nine items.
Rivermead Behavioural Memory Test for Children (RBMT; Wilson et al., 1991). The RBMT is a test tapping everyday memory in young children, comprising 10 subtests measuring verbal and visual memory. Total scores were employed in analyses. Classification scores (normal, borderline, impaired) were also derived.
Procedure
Children were enrolled in the study during initial hospital admission. Families were given a detailed description of the study and asked to provide written consent, in keeping with ethics requirements of the Royal Children's Hospital Human Ethics Committee. Once they had agreed to participate, parents were requested to complete the demographic questionnaire, the VABS (Sparrow et al., 1984), PIC (Lachar, 1992) and FFQ (Noller, 1988), based on the child's pre-injury abilities.
Children were evaluated at three data points: acute (0–3 months post-injury), 12 and 30 months post-injury. Initial assessment was conducted once acute neurological dysfunction/post-traumatic amnesia had resolved, with some variability in the timing of this assessment (time lapse between injury and acute assessment: range: 0–3 months). Each assessment occurred over four 45 min sessions, to ensure optimal performance in this young age group. Assessments were conducted on an individual basis, by a qualified child psychologist. Order of test presentation was fixed within each session.
For intellectual evaluations, the breakdown of specific tests conducted was as follows: (i) acute, Bayley, n = 22; WPPSI-R, n = 64; WISC-III, n = 31. (ii) 12 months, Bayley, n = 11; WPPSI-R, n = 56; WISC-III, n = 50; and (iii) 30 months, WPPSI-R, n = 44; WISC-III, n = 73. For 37% of participants, the same test was conducted at all time points. For the remainder of the sample, tests changed from Bayley to WPPSI-R, or from WPPSI-R to WISC-III. To evaluate the possible impact of inclusion of multiple tests for the measurement of intellectual ability, preliminary analyses were conducted. Comparisons were made for mean performances of children tested with the same versus different tests over time points. Using the total sample, and analysing FSIQ scores (or MDI for Bayley Scales), no group differences were detected at any of the three time points. These results suggest that change in FSIQ scores over time cannot be explained on the basis of change in test administered.
Statistical analysis
Initially the four groups (mild, moderate, severe TBI and controls) were compared on pre-injury and psychosocial measures to identify any differences that might influence post-injury performance. Repeated measures univariate analysis of variance (severity x time) was employed to examine associations between injury severity and time since injury. Planned contrasts were conducted and reported only where a significant omnibus main effect was found, as follows: for severity (i) controls versus mild TBI; (ii) mild versus moderate TBI; and (iii) moderate versus severe TBI, and for time (i) acute versus 12 months; and (ii) 12 months versus 30 months. For measures where no age-adjusted scores were available (BST, VFT, NMI, TT, SRT and SLT), age at testing was employed as a time-varying covariate in analyses. Separate analyses were conducted for each domain, i.e. intellectual ability, language skills and memory functioning.
Hierarchical regression was performed within the TBI sample to investigate predictors of outcome at 30 months. Only outcome variables for which age-adjusted scores were available were included in these analyses. Predictor variables used in the analyses were injury-related variables (severity; 24 h GCS; lesion site; frontal, extra-frontal or diffuse), developmental factors (test age), pre-injury child factors (VABS, PIC, factor I, undisciplined/poor self-control) and environment (SES). While of significant interest, age at injury was not employed as a predictor due to its high correlation with age at testing (r = 0.998).
There were 15 cases who did not complete a number of tests at the acute assessment, due to their young age. There was no association between severity and whether or not children were too young to be tested, 
2 (n = 117) = 5.60, P = 0.13. These 15 cases were excluded from the repeated analysis of variance (ANOVA) reported here, but were included in regression analyses.
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Results |
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Demographic and pre-injury screening variables
As illustrated in Table 1, there were no significant group differences for gender or age at initial testing, SES or family structure. However, a smaller number of children in the severe TBI group came from intact family units.
Pre-injury VABS scores were consistent across groups, indicating no significant differences with respect to pre-morbid adaptive abilities. On the family function measures (FFQ), all groups recorded similar scores, indicating no pre-injury differences for parenting style, intimacy or conflict. Finally, PIC scores showed no pre-injury group differences for any of the factor scores.
Intellectual recovery
Figure 1 provides results for IQ measures at acute, 12 and 30 month evaluations. As expected, analyses identified a consistent effect for injury severity. No main effect of time and no interaction effects were identified on IQ variables, suggesting no differences in patterns of change over time across groups. Repeated measures ANOVA (severity x time) identified a significant main effect of severity for FSIQ [F(3,98) = 11.13, P < 0.001], with planned contrasts detecting a significant difference between moderate and severe TBI groups only [t(98) = 3.71, P < 0.001]. For the subset of the total sample completing the WPPSI-R and WISC-III, a breakdown of verbal and non-verbal skills was possible. These data are presented in Figure 1B and C. Analysis detected severity effects for both VIQ [F(3,97) = 11.67, P < 0.001] and PIQ [F(3,97) = 7.02, P < 0.001]. Once again, planned contrasts were conducted and identified significant group differences between moderate and severe TBI groups only [VIQ, t(98) = 3.79, P < 0.001; PIQ, t(98) s = 3.09, P = 0.003], with severe TBI associated with poorer performance in each instance.
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Language skills
Results on language tests were also found to be consistently related to severity, and results are provided in Table 3. There was a significant relationship between injury severity and both expressive skills, EOWPVT [F(3,98) = 4.61, P = 0.005], BST (information) [F(3,97) = 4.54, P = 0.005], BST (length) [F(3,97) = 3.02, P = 0.034], and receptive skills, PPVT-R [F(3,98) = 4.60, P = 0.005] and TACL-R [F(3,98) = 4.60, P = 0.005]. A main effect of time was found for all expressive language measures, but on none of the receptive language tasks: EOWPVT [F(2,196) = 19.30, P < 0.001], VFT [F(2,196) = 68.42, P < 0.0001], BST (information) [F(2,195) = 9.62, P < 0.001] and BST (length) [F(2,195) = 3.18, P = 0.044], suggesting improvement of all groups over 30 months on these measures, and probably reflecting a combination of recovery and expected developmental progression. No time x severity interactions were detected, suggesting similar patterns of performance over time for the groups, and no evidence for any additional ‘recovery’ of skills for any of the TBI groups.
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Planned contrasts for severity detected differences between moderate and severe TBI groups for all language measures, with the exception of the VFT: EOWPVT [t(98) = –2.70, P = 0.009]; BST (information) [t(98) = 3.24, P = 0.002], BST (length) [t(98) = 2.61, P = 0.011], PPVT-R [t(98) = –2.73, P = 0.003] and TACL-R [t(98) = –4.12, P < 0.001], and between mild and moderate TBI groups for EOWPVT [t(98) = 3.23, P = 0.002], PPVT-R [t(98) = 3.36, P = 0.001] and TACL-R [t(98) = 3.46, P = 0.001]. These analyses also identified differences between acute and 12 month and between 12 and 30 month assessments for EOWPVT [t(98) = 3.35, P = 0.001, t(98) = 3.96, P < 0.001, respectively] and VFT [t(98) = 3.70, P < 0.001, t(98) = 8.57, P < 0.001, respectively].
Memory tests
For memory tests, raw scores were employed in analyses, as age-standardized scores were not available for all measures across the age range under study. Repeated measures analysis of covariance (ANCOVA), covarying for age, was conducted on these data. Scores are presented in Table 4. For traditional memory measures, severity had a significant impact on performance on all tasks with the exception of NMI [TT, F(3.97) = 4.49, P = 0.005; SRT, F(3,97) = 4.41, P = 0.006; SLT, F(3,97) = 7.42, P < 0.001]. Planned contrasts demonstrated significant differences between the moderate and severe groups [TT, t(97) = 2.78, P = 0.006; SRT, t(97) =–3.03, P = 0.003; SLT, t(97) = 3.53, P = 0.001]. On each measure, the trend was for the predicted dose–response, with children with more severe injuries tending to record lower scores. A main effect of time was also identified for TT [F(2,195) = 4.30, P = 0.015] and SLT [F(2,195) = 14.75, P < 0.0001], probably reflecting the ongoing development in these skills throughout the 2.5 years of follow-up. No time x severity interactions arose.
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For the RBMT, purported to provide a better indication of day-to-day memory skills than traditional memory measures, a similar pattern of results was documented. A significant main effect of severity was recorded for raw scores on the test [F(3,97) = 9.96, P < 0.001], with differences existing between the moderate and severe groups [t(97) = 4.84, P < 0.001]. To illustrate this finding further, RBMT classification scores are plotted across severity groups and over time in Fig. 2. Of note, over half of the children in the severe TBI group demonstrated borderline or impaired memory performances even 30 months post-injury.
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Predicting outcome following head injury
To investigate predictors of long-term outcome (30 months post-injury), a series of multiple regressions was conducted, within the TBI sample, on major outcome variables including IQ scores, EOWPVT, TACL and RBMT, using 24 h GCS score, site of lesion, test age, pre-injury adaptive and behavioural scores, and SES as predictors. Results from these analyses are reported in Table 5. Within all domains, injury severity (as measured by 24 h GCS), pre-injury adaptive abilities (VABS) and SES were significant predictors of 30 month outcomes, with regression models accounting for between 42 and 64% of variance. For intellectual ability and memory test, age also contributed significantly to regression equations. Location of cerebral pathology and pre-injury child behavioural function did not significantly predict any of the outcome variables tested.
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Discussion |
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TopSummaryIntroductionMethodsResultsDiscussionReferences |
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The aim of this study was to examine the nature of neurobehavioural deficits following TBI during early childhood, to plot recovery patterns over the 30 months post-injury and to identify significant predictors of outcome. To do this, the performances of three groups of children, sustaining injuries of different severity, were compared with those of a healthy control group. The groups were similar with respect to pre-injury adaptive and behavioural function, psychosocial characteristics, age and gender. Using a prospective, longitudinal design, intellectual abilities, language capacity and memory functions were investigated over 30 months post-injury. Findings from the study were generally in keeping with initial predictions. There was a strong association between injury severity and children's level of function across all neurobehavioural domains. Further, neurobehavioural outcome was influenced by multiple factors including injury severity, pre-injury function, SES and age. In contrast, the nature and location of brain pathology and pre-injury child behaviour were unrelated to neurobehavioural outcomes.
Intellectual skills
For overall intellectual function, the impact of TBI was evident in the acute stages post-injury, consistent with previous literature (Jaffe et al., 1993; Prior et al., 1994; Yeates et al., 1997; Catroppa and Anderson, 1999). Children with severe TBI performed significantly poorer than all other groups, with mean scores falling below the average range, despite pre-injury measures indicating prior age-appropriate development. In contrast, while there was a trend for the expected injury effect, for mild and moderate TBI groups, mean results were within the average range, and not significantly different from controls. Recovery over time was minimal and certainly less than predicted from studies of adults and older children (Chadwick et al., 1981; Finger and Stein, 1982), with increments in FSIQ of between 0.9 and 1.2 IQ points recorded across the three TBI groups from acute to 30 month assessments. Consistent with these summary results, for VIQ, while the mild TBI group showed a three IQ point improvement during this period, moderate and severe groups recorded a small decline (–2.1 and –2.3 IQ points, respectively), again finding no support for ‘recovery’ of function in the 30 months post-TBI in young children. Of note, VIQ is a measure heavily dependent on well-learned verbal knowledge such as word knowledge, general knowledge and social knowledge. Thus, these findings provide indirect support for the hypothesis that young children sustaining significant TBI may be unable to acquire skills and knowledge from their environment at age-appropriate rates, perhaps due to reductions in memory and information processing abilities.
Patterns of recovery for non-verbal skills are largely consistent with those described for verbal skills. For PIQ, significant severity effects were again documented, with the severe TBI group recording the poorest performances at all time points. Of note, these results are contrary to previous research findings from adults and school-aged children, which have frequently reported significant improvements in PIQ in the months post-injury. Such improvements have generally been interpreted as evidence of recovering psychomotor skills and executive abilities (Chadwick et al., 1981; Jaffe et al., 1992; Anderson et al., 2001). The findings in this study suggest that such recovery is largely absent for children sustaining their injuries in early childhood.
Language functions
Consistent with previous research (Ewing-Cobbs et al., 1987, 1989, 1998; Chapman et al., 1998), severity effects were identified for expressive and receptive language, and these persisted over the duration of the study. On standardized language measures (e.g. EOWPVT, TACL-R and PPVT-R), children with mild and moderate TBI performed consistently within the average range, across all test points. In contrast, children with severe TBI demonstrated mild to moderate impairments of language function. Improvements over the 30 months post-injury were evident for all four groups on all measures of expressive language, from simple naming tasks, to more complex fluency and story telling measures. Given that many test scores in this domain were not standardized for age, the results suggest the potential presence of some practice effect, but are more likely to represent expected developmental gains across the 30 months of the study. For receptive language measures, minimal improvements were evident over time, and there was no evidence of the expected recovery in skills for TBI groups. Rather, the significant effect of TBI identified acutely was maintained over time, indicating an ongoing deficit in receptive language for children with severe TBI.
Memory function
Memory and learning impairments are commonly implicated following TBI, both in adults and in school-aged children (Levin et al., 1988; Yeates et al., 1995; Anderson et al., 2000b; Catroppa and Anderson, 2002). Findings from this study provide support for similar deficits following TBI in early childhood, with severity effects identified on both standardized and functional memory measures.
For immediate memory measures (NMI and TT), all groups showed a trend to increased immediate memory capacity over time, but only for TT was there a significant effect of injury severity, with the severe TBI group demonstrating a shorter spatial span at all time points. On tasks tapping new learning (SRT and SLT), results were more in line with study expectations, with severity effects identified for each measure. At 12 and 30 months post-injury, children with severe TBI exhibited reduced verbal learning skills, showing greater difficulty retaining the elements of two short stories. They also took a greater number of trials to learn a spatial array. In contrast, mild and moderate TBI groups performed similarly to healthy controls. The persisting nature of memory difficulties following more severe TBI was best illustrated by findings from the RBMT, purported to measure everyday memory skills. On this task, children with severe TBI performed significantly worse than all other groups, with no evidence of improvement over time since injury. By 30 months post-injury, more than 50% of children with severe TBI continued to demonstrate borderline to impaired memory performances (see Fig. 2). Thus, despite the possibility of recovery from injury, these children did not achieve the expected level of progress, and fell further behind with respect to developmental expectations.
Predictors of outcome
In keeping with previous research, and the results obtained for this sample at earlier follow-up (acute and 12 months) (Anderson et al., 1997, 2001), the substantive predictor of long-term neurobehavioural recovery following early TBI was injury severity. Specifically, more severe injury (as measured by the GCS) was related to poorer recovery and outcome across intellectual, memory and receptive language domains. Of note, while greater depth of coma (GCS at 24 h post-injury) was related to poorer recovery, lesion site was not identified as a significant predictor. This lack of association may simply reflect the generalized pathology often described following TBI, the reported lack of reliability of acute brain scan data or the particular indices employed in this study. Alternatively, late changes in brain structure following early TBI (Anderson et al., 2001) may also confound results. Future research reporting serial brain scans, and providing more detailed analysis, is needed to clarify these issues.
Also in keeping with initial study expectations, and with recent paediatric literature (Taylor and Alden, 1997; Yeates et al., 1997; Anderson et al., 2001), a number of non-injury factors were found to be important for determining 30 month neurobehavioural outcomes. Environmental factors, specifically parental occupation, and pre-injury child adaptive abilities contributed substantively to intellectual, language and memory outcomes. Age (at testing and at injury) contributed to intellectual and memory performances, but was less influential for language variables. In contrast, pre-injury child behaviour characteristics were not predictive of outcome at the 30 month follow-up, supporting the view that cognitive and behavioural recovery post-injury may be determined by different factors (Anderson et al., 2001, 2004). These results emphasize the potential for complex interactions across a range of domains relevant to the child's experience post-injury. Further, they point to a series of parameters that need to be identified in order to determine each child's risk of long-term neurobehavioural impairment post-injury, and consequent rehabilitation requirements.
A number of design limitations must be considered when interpreting the results from this study. First, control group selection: the issue of appropriate control groups for TBI studies is a vexed one. We did consider the argument that children with TBI are ‘different’ from the normal population with respect to social, behavioural and ability factors. In response to this, we chose to exclude children with pre-existing behavioural and developmental difficulties, and, in addition, to select a control sample from pre-schools and child care centres within the injured child's community. The choice of this group, rather than a sample of orthopaedic controls, was based on a number of factors. First, for this age group we could not ensure reliable reports from children regarding any simultaneous head injury, nor accurate coma scores in the mild TBI range for very young children. Thus there was a risk of including children with mild TBI in the control sample. To support the success of this strategy, we note that the TBI group (total) and controls did not differ with respect to pre-injury behaviour, adaptive ability or family function (see Table 1). Further, there were no significant differences between the TBI group (total) and controls for SES (TBI = 4.2, controls = 3.7) or family structure (TBI = 78.2% intact families, controls = 80.9% intact families). Only a subset of the TBI group, the severe TBI group, were less likely to come from intact families, suggesting that it may be that significant head injuries are specifically associated with social disadvantage and pre-injury problems. Secondly, the inclusion of serial testing may lead to the presence of confounding factors such as practice effects, which may need to be considered in interpretations of ‘recovery’. We suggest that the inclusion of a control group allows for the identification of such effects. In the present study, while normal developmental gains and practice effects may be difficult to differentiate, ‘recovery’ effects specific to certain severity groups were more easily recognized. Further, future research interested in measuring the impact of both age at injury, age at testing and time since injury would need to consider alternative study designs where these variables are not intrinsically confounded, as is the case in prospective, longitudinal designs. Finally, future research more carefully detailing the nature, focus and extent of brain pathology may be better suited to careful evaluation of the contribution of such factors.
In conclusion, findings from this study demonstrate a consistent and substantive effect of severe TBI on recovery and ongoing development in a range of neurobehavioural domains, including intelligence, language and memory, for children sustaining early injury. By 30 months post-injury, these children continue to function at below average levels in all domains. Further, plotting performances from acute to 30 months post-injury provides evidence of a flatter recovery/developmental curve for all TBI groups. This pattern is most evident following severe TBI, and suggests, at minimum, a failure to develop at age-expected rates, but also questions the presence of any ongoing recovery of function following severe brain injury in early childhood. On a positive note, children with mild and moderate TBI tend to exhibit some improvements, suggesting that they may be experiencing additional recovery as well as expected developmental gains. Thirty month outcomes in the areas of intellectual functioning, memory and language are determined by a range of injury and non-injury variables, including injury severity, as measured by conscious state, SES, operationalized by parent occupation, and child factors, specifically, pre-injury child ability levels and age. Each of these factors needs to be taken into consideration when determining long-term prognosis and intervention needs for young children post-TBI.
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This research was supported by the Australian National Health and Medical Research Council and the Royal Children's Hospital Research Foundation. The authors are indebted to Paul Dudgeon for his statistical advice and support in the preparation of this manuscript.
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