Trajectories of Motor Recovery in the First Year After Pediatric Arterial Ischemic Stroke
- Anna N. Cooper, BOTa,b,
- Vicki Anderson, PhDa,b,c,
- Stephen Hearps, PGDipBiostata,b,
- Mardee Greenham, MSca,b,
- Michael Ditchfield, PhDd,e,
- Lee Coleman, MDa,c,
- Rod W. Hunt, PhDa,b,c,
- Mark T. Mackay, PhDa,b,c,
- Paul Monagle, MDa,b,c, and
- Anne L. Gordon, PhDf,g
- aClinical Sciences, Murdoch Childrens Research Institute, Melbourne, Victoria, Australia;
- bUniversity of Melbourne, Melbourne, Victoria, Australia;
- cThe Royal Children’s Hospital, Melbourne, Victoria, Australia;
- dMonash Medical Centre, Southern Health, Melbourne, Victoria, Australia;
- eMonash University, Melbourne, Victoria, Australia;
- fEvelina London Children’s Hospital, Guy’s and St Thomas’ NHS Foundation Trust, London, United Kingdom; and
- gKings College London, London, United Kingdom
Ms Cooper assisted with data analysis and drafted the initial manuscript; Dr Gordon conceptualized and designed the study, coordinated and undertook recruitment, collected data and supervised data collection, designed the database, and critically reviewed the manuscript; Mr Hearps conducted initial analyses and reviewed and revised the manuscript; Ms Greenham assisted with data collection, recruitment, and project coordination and undertook and reviewed and revised the manuscript; Drs Ditchfield and Coleman contributed to the project design, codesigned the imaging capture protocol, and undertook imaging review; Dr Mackay supported identification of subjects for recruitment and contributed to the study design; Dr Hunt supported identification of subjects for recruitment, contributed to the study design, and critically reviewed the manuscript; Dr Monagle supported identification of subjects for recruitment, contributed to the study design and analysis, and critically reviewed the manuscript; Dr Anderson supported identification of subjects for recruitment, contributed to the study design and analysis, and critically reviewed the manuscript; and all authors approved the final manuscript as submitted.
BACKGROUND: Neuromotor impairments are common after pediatric stroke, but little is known about functional motor outcomes. We evaluated motor function and how it changed over the first 12 months after diagnosis. We also examined differences in outcome according to age at diagnosis and whether fine motor (FM) or gross motor (GM) function at 12 months was associated with adaptive behavior.
METHODS: This prospective, longitudinal study recruited children (N = 64) from The Royal Children’s Hospital, Melbourne who were diagnosed with acute arterial ischemic stroke (AIS) between December 2007 and November 2013. Motor assessments were completed at 3 time points after the diagnosis of AIS (1, 6, and 12 months). Children were grouped as follows: neonates (n = 27), preschool-aged (n = 19), and school-aged (n = 18).
RESULTS: A larger lesion size was associated with poorer GM outcomes at 12 months (P = .016). Neonatal AIS was associated with better FM and GM function initially but with a reduction in z scores over time. For the preschool- and school-aged groups, FM remained relatively stable over time. For GM outcomes, the preschool- and the school-aged age groups displayed similar profiles, with gradual recovery over time. Overall, poor FM and GM outcomes at 12 months were associated with poorer adaptive behavior scores.
CONCLUSIONS: Motor outcomes and the trajectory of recovery post-AIS differed according to a child’s age at stroke onset. These findings indicate that an individualized approach to surveillance and intervention may be needed that is informed in part by age at diagnosis.
- AIS —
- arterial ischemic stroke
- BOT-2 —
- Bruininks-Oseretsky Test of Motor Proficiency, Second Edition
- BSID-III —
- Bayley Scales of Infant and Toddler Development, Third Edition
- FM —
- fine motor
- GM —
- gross motor
- PSOM —
- Pediatric Stroke Outcome Measure
- VABS2 —
- The Vineland Adaptive Behavior Scales, Second Edition
What’s Known on This Subject:
Neuromotor impairment is a common presenting feature of pediatric stroke and is also a frequent long-term sequela. Children may have a more protracted recovery after stroke than adults, and recovery may differ depending on age at stroke onset.
What This Study Adds:
This is the first prospective, longitudinal cohort study to systematically evaluate motor outcome over time after the diagnosis of AIS. Functional motor limitations vary according to age at diagnosis. Poorer motor outcomes are associated with reduced adaptive abilities.
Long-term neurodevelopmental disability occurs in 50% of childhood strokes1,2 and 30% to 60% of symptomatic neonatal strokes.3–5 Arterial ischemic stroke (AIS) occurs more frequently in neonates (≤28 days old), with an incidence of 1 in 4000 live births,6 when compared with 2 to 8 per 100 000 in childhood (29 days–18 years old).3,4 Acute presentation differs between the 2 groups; hemiplegia is the most common acute clinical sign of childhood AIS and is present in 72% to 90% of cases,2,3,7–10 with estimates of the prevalence of chronic hemiplegia varying from 25% to 56%.7,8 In contrast, neonates typically present with seizures2,5,11 and have lower rates of chronic hemiplegia (ranging from 20% to 28%).7,9,12,13
After an adult stroke, rapid motor recovery occurs in the first few months postdiagnosis with less improvement thereafter.14,15 In contrast, brain injury researchers suggest that the trajectory of motor recovery in children may be more protracted.16
Lesion characteristics may play an important role in motor outcomes after a pediatric stroke,7,9,12,17–19 with studies revealing poorer outcomes in children who have more than 10% intracranial volume infarction.20 Authors of other studies (primarily of neonates) have noted poorer outcomes for cortical (as opposed to subcortical) infarct location21 and for cortical lesions with corticospinal tract involvement.22–24 Clinical experience suggests a wide variation in the nature and severity of functional motor difficulties. Researchers have conducted several cross-sectional studies that describe motor function outcomes in children after AIS, but these assessments are mainly descriptive and usually confined to identifying a presence or absence of motor impairments.19,25–28 To date, most studies in which the researchers measure motor function in children have been limited to clinical judgments using qualitative tools. More specific characterization of gross motor (GM) and fine motor (FM) function after pediatric AIS and how they change over time is lacking in the literature,1,19,26,29–31 which limits the ability to develop targeted rehabilitation strategies to optimize motor outcomes.
We aimed to examine changes in motor function in the first year after acute presentation of AIS across 3 age groups (neonates, preschool-aged, and school-aged children) by using robust, age-appropriate measurement tools. We also investigated the relationship between FM and GM function at 12 months post-AIS with adaptive behavior.
This is a single site, prospective, longitudinal observational cohort study. Participants were assessed at 3 time points: 1, 6, and 12 months after an acute diagnosis of AIS. The first time point was selected based on clinical experience of the earliest likely time point at which all children would be likely to undertake the study protocol. The subsequent time points were selected to capture changes over time. Ethics approval was obtained through the Human Research Ethics Committee of The Royal Children’s Hospital, Melbourne.
Participants aged between term newborn and 18 years with acute AIS were consecutively recruited from a single tertiary-level children’s hospital between December 2007 and November 2013, as detailed in a previous article.32 Children were included if their brain MRIs confirmed an acute parenchymal ischemic infarction on diffusion-weighted imaging that corresponded to 1 or more arterial territories. Children with previously diagnosed AIS, coexisting diffuse brain injury caused by a traumatic or hypoxic ischemic event, and preterm infants (born <36 weeks’ gestation) were excluded.
One hundred and seven children met the eligibility criteria for the study. Thirty-three were not approached (of which 12 died acutely, 6 resided interstate, and 15 were missed and/or not referred in time), and 7 declined participation (1 because of employment, 3 were too busy and/or stressed, and 3 gave no reason). Sixty-seven children were recruited between December 2007 and November 2013. Two participants were unable to be contacted for follow-up appointments, and 1 child died (of non-stroke–related issues) before the 12-month assessment. A total of 64 children completed the assessments for the current study.
Infarct laterality, lesion location, and the vascular territory affected were rated by 2 neuroradiologists (M.D. and L.C.) on the basis of visual inspection of images obtained at the time of diagnosis (as described in Gordon et al32). Lesion size was dichotomized as “small or medium” or “large” according to the degree of vascular territory impacted. Lesion location was categorized as cortical, subcortical, both, or infratentorial. All clinical assessments were conducted by experienced pediatric clinicians (A.L.G. and M.G.). The presence of a hemiplegia was determined after a clinical examination, which is indicated by a score of ≥0.5 on the sensorimotor domain of the Pediatric Stroke Outcome Measure (PSOM).
Primary Motor Outcomes
GM and FM capacity were assessed by using standardized motor assessments at all time points either in an outpatient clinic or at home, according to child or parent preferences.
For infants and children aged ≤42 months, the motor domains of the Bayley Scales of Infant and Toddler Development, Third Edition (BSID-III) were administered.33 The BSID-III provides comprehensive assessment of infant and toddler development. Scaled scores were generated for the FM and GM subscales of the motor function domain (mean = 10, SD = 3).
For children aged >42 months, the Bruininks-Oseretsky Test of Motor Proficiency, Second Edition (BOT-2) was conducted.34 The BOT-2 is a standardized, norm-referenced, comprehensive motor assessment for children aged 4 to 21 years.34,35 It assesses motor function across 4 domains: fine manual control, manual coordination, body coordination, and speed and agility. Standard scores were generated across the 4 subdomains (mean = 50, SD = 10), and an overall motor composite score was also generated (mean = 50, SD = 10). Thirty-eight children were assessed with the BSID-III at all time points, 23 children were assessed with the BOT-2 at all time points, and 3 children were assessed with both the BSID-III and the BOT-2.
Scores from subdomains of fine manual control and manual coordination were combined and averaged to generate an FM score, and body coordination and strength and agility were combined and averaged for a GM score. These were converted into z scores for both FM and GM function.
Descriptors and Predictors
The PSOM is a detailed neurologic assessment that measures impairments across 5 domains: left sensorimotor, right sensorimotor, language production, language comprehension, cognition, and behavior.2 When it was not possible to examine a child, the Recovery and Recurrence Questionnaire36 was administered, which is a parent-administered version of the PSOM that has been demonstrated to correlate strongly with the clinician-administered PSOM.36
The Vineland Adaptive Behavior Scales, Second Edition (VABS2)37 is a parent-rated questionnaire that measures a child’s activity and participation across 4 domains: communication, daily living, motor skills and socialization subscales, and total adaptive behavior. These were employed in analyses (mean = 100, SD = 15).37 The motor subscale is only administered to children <6 years old, so scores for this subdomain were not entered into analyses.
Descriptive analyses were reported for patient demographic and lesion characteristics between stratified age groups: neonatal (≤30 days old at diagnosis), preschool-aged (>30 days–5 years old), and school-aged (≥5 years old). Means and SDs were reported for continuous variables and compared between groups with an analysis of variance. Frequencies and proportions were reported for categorical variables and compared by using Fisher’s exact tests (because of low cell counts).
Motor z scores were entered into analysis, with functional impairment indicated as a z score of ≤−1. Linear growth curve models were undertaken to explore changes in FM and GM outcomes over the time points of 1, 6, and 12 months for the whole population and were stratified by age group. This method of analysis utilizes all available information without the requirement of participant data at all time points (with data missing at random).38 Participant identification was entered as a random variable, time (in months) was entered as a random slope, and an unstructured covariance matrix was applied. Model estimates were plotted for each outcome, including 95% confidence intervals.
Multiple-regression models explored the prediction of FM and GM z scores at 12 months by using dichotomized demographic and lesion characteristics. For age dummy variables, a linear joint test was conducted to determine the overall effect of age categories. Unstandardized β coefficients and significances were reported in addition to model effect sizes (R2) and P values.
Finally, Pearson correlations were calculated to explore the relationship between total adaptive behavior scores and both FM and GM z scores. A strong correlation was indicated by a correlation coefficient of >0.7, moderate was between 0.5 and 0.7, and low was <0.5.39
Sample demographics and lesion characteristics are presented in Table 1. There was a higher proportion of neonates (40%) than older children, more neonates had combined cortical and subcortical involvement (P = .001), and nearly double the number of neonates had left-sided lesions when compared with other age groups; however, this was not statistically significant (P = .06).
Motor Outcomes Across the First Year After AIS Onset
At 12 months after AIS onset, 19 (30%) children exhibited hemiplegia, with similar percentages of children in each age group (33% neonates, 21% preschool-aged, and 33% school-aged). Six (9%) children had a bilateral motor impairment (no neonates, 19% preschool-aged, and 14% school-aged) (see Fig 1). For FM outcomes, the neonatal and school-aged groups demonstrated a gradual emergence of impairments over time, whereas the preschool-aged group tended to improve. For GM outcomes, impairments again emerged over time in the neonatal group and for both the preschool-aged group and the school-aged group. GM impairments were greatest at 1 month and then steadily improved (see Fig 2). At 12 months, FM impairments tended to be more common in children with bilateral (36.4%) or infratentorial (35.5%) lesions than those with unilateral lesions (22%). At the same time, GM impairments tended to be more frequent in children with unilateral (42%) or bilateral (63%) lesions than in those with infratentorial lesions (25%). Nevertheless, injury location was not a significant predictor of motor outcomes at 12 months in our regression analysis.
Linear growth curve models plotted FM and GM z scores over time. For FM scores, significant main effects of age at AIS onset were identified (P < .001), and time post-AIS was detected (P < .001). A significant interaction between age group and time was found (P = .004), which supported the differences in recovery trajectories across age groups. Overall, a younger age at AIS onset was associated with better FM function initially with reduced scores over time. For the preschool- and school-aged groups, z scores remained relatively stable over time, as illustrated in Fig 3A.
The GM z score model also found a significant main effect of age at AIS onset and time (both P < .001) and a significant interaction effect (P = .001). The neonates performed best overall at 1 month, but they showed a trend toward poorer scores over time. The preschool- and school-aged groups displayed similar profiles: initially ≤1 SD below the mean with gradual recovery over time (Fig 3B). FM and GM z scores at each time point, as well as VABS2 standard scores at 12 months, are summarized in Table 2.
Factors Associated With 12-Month Outcomes
Multiple-regression analyses explored the combination of demographic and clinical characteristics with 12-month FM and GM z scores (Table 3). A large lesion size was associated with poorer GM outcomes but not FM outcomes. When exploring the effect of age at injury, the school-aged group exhibited poorer FM outcomes (β = −.91, P = .02) when compared with neonates; however, the linear age category joint test was not significant. There were no significant relationships between sex, lesion laterality, or lesion location and 12-month GM and FM outcomes.
The Relationship Between Motor Scores and Adaptive Behavior, Activity, and Participation
Finally, a low-strength correlation was found between GM scores and total adaptive behavior scores (r = 0.27, P < .001), and a moderate relationship was found between FM scores and total adaptive behavior scores (r = 0.51, P = .03), with poorer adaptive behavior scores being associated with poorer GM and FM scores.
Examination of the relationship between children’s direct motor outcomes (BOT-2 and BSID-III) and parental ratings (VABS-2) identified significant correlations between the VABS-2 communication and both FM (r = 0.30, P = .019) and GM (r = 0.43, P = .001) z scores. Daily-living scores were also associated with FM (r = 0.34, P = .008) and GM (r = 0.42, P = .001) z scores, but there were no significant relationships between socialization and motor outcomes (Table 4).
Motor impairments are the most commonly reported long-term sequelae of pediatric AIS.4,5,8 In this prospective longitudinal study, we investigated age-related trajectories of motor recovery over time. At 1 month, poor FM and GM outcomes were associated with younger age at AIS onset. Over time, impairments emerged in the neonatal group for FM and GM function. This finding is consistent with previous research in which motor impairments have been reported to emerge in the neonatal population at ∼4 to 5 months of age, when infants typically develop voluntary hand use.40 In contrast, the preschool- and school-aged groups met criteria for “impairment,” with gradual recovery over time. Both groups had similar overall recovery trajectories, but the preschool-aged group performed better in both FM and GM domains at all time points, which suggests that these groups demonstrate a similar magnitude of recovery. The finding that the preschool-aged group had better motor outcomes is consistent with findings reported by researchers who have explored cognitive outcomes after pediatric AIS onset, and this finding also suggests a protective period, meaning the poorest outcomes occur when AIS onset is before age 1 or after age 6.41,42
Twelve months after AIS onset, the percentage of children with GM impairments was higher than those with FM impairments across all age groups. The neonatal group had 3 times as many GM impairments (50%) when compared with FM outcomes (15%). The development of hand functioning in children is refined over many years with skills such as regulation of grip force and in-hand manipulation that develop well beyond the first year of life. Thus, a neonate’s FM impairments may become more evident in the subsequent years that these skills typically develop.43
Despite significant age-related differences in the trajectories of motor recovery, none of the 3 groups were significantly impaired in FM or GM function at 12 months after AIS onset. This could be because sensorimotor skills are considered by some investigators to be “lower-order” skills that have possibly less complex neural networks, and as a consequence, they could be less vulnerable to early brain injury than more complex, higher-order skills (such as attention or social cognition), which may rely on more diffuse neural networks.16 It is also important to acknowledge the involvement of cognitive skills in motor function testing, which adds complexity to assessing outcomes in children.
The age for optimal motor recovery from brain injury remains unclear. Motor plasticity is likely to be greatest in early childhood, when the young brain is rapidly reorganizing and myelinating. In contrast, older children may have less plasticity, but functional outcome may be improved by the possession of a wider set of learned skills and behaviors at the time of injury, which creates a greater potential for true rehabilitation. This study suggests that preschool-aged children may have the best motor outcomes and recovery trajectory, and therefore, they may be the age group in which there is an optimal balance between greater brain plasticity and lower vulnerability.44
There were no significant relationships found between motor outcomes and lesion laterality or location (using dichotomized variables); however, as has been reported by others, larger lesions tended to be associated with poorer outcomes, particularly in GM function.
A significant relationship was identified between communication skills and activities of daily living with GM and FM outcomes at 12 months, which suggests that AIS in children has broad-reaching implications in daily life.
This is the first published study to use a prospective longitudinal design to measure trajectories of motor recovery over 12 months after AIS onset in children. The focus on individual outcomes (specifically the proportion of children with persisting functional limitations) was a strength of the current study and contrasts it to previous literature that is limited to interpretation of group mean data, which can be misleading because it can mask underlying difficulties. Most participants’ scores fell within 1 SD of the mean (suggesting normal function), but analyses of FM and GM impairment rates revealed a high percentage of children who continued to have both FM and GM impairments.
A challenge of measuring motor function in this population is that the PSOM is the only standardized neurologic impairment outcome measure that is validated to the pediatric stroke population. The PSOM is, however, a neurologic screening tool, which may miss the finer details of motor function. It is also difficult to measure change over time in a pediatric population because standardized assessments are designed for specific age ranges. Different assessments are therefore needed at different ages, which adds complexity to this analysis. A strength of this study is that we used sensitive and comprehensive measures of motor function and so were able to link these assessments to adaptive function. Of note, handedness was not reported in our sample because approximately three-quarters of participants were younger than 4 years old at the time of AIS onset. Less than two-thirds of eligible children were enrolled in the study. Because of government regulations, we were unable to assess whether there were differences between participants and nonparticipants, which may influence interpretations of the findings.
Sample size was large for the field, but age at AIS onset subgroups were small, which limited the breadth of possible analyses. In addition, overrepresentation of bilateral and infratentorial AIS in the consecutively recruited sample may have impacted our results.
Westmacott et al45 recently described the emergence of cognitive impairments after a unilateral stroke beyond the first year. Given that the trajectory of recovery from pediatric strokes in other domains is unclear and that recovery may continue beyond the first year, a long-term observational study is warranted.
FM and GM outcomes after pediatric AIS are variable. Factors that influence the recovery trajectory and long-term motor outcomes include age at AIS onset and lesion size. Neonates have a different recovery trajectory from older-onset age groups and appear to grow into their motor impairments over time. At 12 months after AIS onset, children with FM and GM difficulties also have difficulties with functional activities, which is evidenced by lower adaptive behavior scores. These findings support the need for long-term neurodevelopmental surveillance in the pediatric AIS population so that as developmental needs change or impairments emerge, needs can be addressed to optimize outcomes.
- Accepted April 28, 2017.
- Address correspondence to Anne Gordon, PhD, Evelina London Children’s Hospital, Westminster Bridge Rd, London SE1 7EH, UK. E-mail:
FINANCIAL DISCLOSURE: The authors have indicated they have no financial relationships relevant to this article to disclose.
FUNDING: Dr Cooper was supported by a Murdoch Childrens Research Institute graduate research scholarship, and Dr Anderson was supported by a National Health and Medical Research Council senior practitioner fellowship. This study was also supported by the Victorian government’s operational initiative scheme.
POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose.
- Copyright © 2017 by the American Academy of Pediatrics