- Email: [email protected]
Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke
European Journal of Paediatric Neurology xxx (xxxx) xxx
Contents lists available at ScienceDirect
European Journal of Paediatric Neurology
Original article
Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke Mahmoud Slim a, Robyn Westmacott b, Sandra Toutounji a, Jaspal Singh c, Indra Narang d, Shelly Weiss a, Pradeep Krishnan e, Elena Grbac a, Ann-Marie Surmava a, Kathleen Andres a, Daune MacGregor a, Gabrielle deVeber a, Mahendranath Moharir a, Nomazulu Dlamini a, * a
Division of Neurology, The Hospital for Sick Children, Toronto, Canada Department of Psychology, The Hospital for Sick Children, Toronto, Canada c Department of Neurology, University Hospital Southampton NHS Foundation Trust, Southampton, UK d Division of Respiratory Medicine, The Hospital for Sick Children, Toronto, Canada e Division of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 January 2019 Received in revised form 4 June 2019 Accepted 17 November 2019
Objectives: To assess the prevalence of obstructive sleep apnea syndrome (OSAS) in children with arterial ischemic stroke (AIS) and to evaluate its association with neuropsychological outcomes. Methods: We conducted a cross-sectional study of sleep health and neuropsychological outcome in children with AIS. A consecutive cohort of children attending a stroke clinic were assessed using a standardized pediatric sleep questionnaire (PSQ) and standardized measures of pediatric stroke outcome and intellectual, executive and adaptive function. High risk for OSAS was defined as PSQ score 0.33. Results: Overall, 102 children were included (55% males, median age: 9 years [interquartile-range [IQR]: 6e14]). The prevalence of OSAS in children with AIS was significantly higher compared to published normative prevalence rate (25.5% vs 5%, p < 0.001). Children with OSAS were more likely to have infarcts affecting both the anterior and posterior circulation (37.5% vs 9.5%, p ¼ 0.021). In addition, children with OSAS had significantly higher median Pediatric Stroke Outcome Measure (PSOM) scores (2 [IQR: 0e2] vs 1 [IQR: 1e3.5], p ¼ 0.01) and were more likely to be prescribed concomitant medications affecting sleep architecture (50% vs 22.4%, p ¼ 0.007). OSAS was associated with significantly lower scores on intellectual, memory, cognitive, behavioral, attention, executive and adaptive function scales. The association between PSQ and intellectual ability and working memory remained statistically significant upon controlling for potential confounding factors including stroke related characteristics (neurologic impairment and arterial territory). Conclusions: The prevalence of OSAS in children with AIS compared to healthy controls is significantly elevated and is associated with poor neuropsychological outcomes. We highlight the importance of regular screening for OSAS e a modifiable risk factor - in children with AIS. The specific risk factors for OSAS and the potential benefits of therapeutic interventions in this patient population warrant further investigation. © 2019 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.
Keywords: Obstructive sleep apnea syndrome Arterial ischemic stroke Neuropsychology Cognition Adaptive function
1. Introduction Sleep is essential for the psychosocial, physical and mental
* Corresponding author. Division of Neurology, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada. Fax: þ1 416 813 6334. E-mail address: [email protected] (N. Dlamini).
wellbeing of children. However, in the last 20 years, there has been an epidemic of sleep deprivation in children.1 Several factors have contributed to this epidemic including the underdiagnosis of sleep disorders such as obstructive sleep apnea syndrome (OSAS).2 OSAS represents a wide spectrum of sleep-related breathing disorders ranging from intermittent snoring to the more severe forms of obstructive sleep apnea and obstructive hypoventilation.3 The prevalence of OSAS in typically developing children ranges
https://doi.org/10.1016/j.ejpn.2019.11.006 1090-3798/© 2019 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
2
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
between 0.7% and 13%.4,5 Several medical conditions such as sickle cell disease, epilepsy, autism spectrum disorders, mood and anxiety disorders, and craniofacial abnormalities are known to have a high prevalence of OSAS in childhood.6 Untreated OSAS in healthy children is known to be associated with a range of adverse outcomes including daytime sleepiness, reduced quality of life, abnormal neurocognitive functioning, neurodevelopmental and long-term behavioral morbidities.6 These poor outcomes are not limited to the more severe forms of OSAS, but are also present with the milder forms including habitual snoring.7 In adults, OSAS is an established risk factor for stroke which contributes to worsening of cognitive and mood disorders such as depression and anxiety in adults with stroke.8,9 Several studies have demonstrated that stroke-related characteristics including age at stroke, lesion volume and location are important mediators of cognitive outcomes in pediatric stroke.10,11 However, the relationship between OSAS, stroke related outcomes, cognitive, executive, language and adaptive outcomes is relatively unexplored. To date, the prevalence rates of OSAS in children with AIS and their impact on neurocognitive and adaptive function in this population have not been investigated. We aimed to (1) estimate the prevalence of OSAS in children with AIS and (2) to assess the association between OSAS and intellectual and cognitive abilities, attention, executive function, language, and adaptive function. We hypothesized that the prevalence of OSAS in children with AIS is increased compared to healthy children and that comorbid OSAS is associated with poorer neuropsychological outcomes. 2. Methods 2.1. Patient population and procedures The patient population comprised of a consecutive cohort of children enrolled in the institutional Children's Stroke Registry at the Hospital for Sick Children, Toronto, Canada. Screening for OSAS was conducted using a validated pediatric sleep questionnaire (PSQ) in children attending the stroke clinic between July 2016 and October 2017.12 Inclusion criteria included: (1) age between 2 and 18 years and (2) a previous diagnosis of arterial ischemic stroke (AIS). Neurocognitive and behavioral assessments were available for eligible children who were co-enrolled in additional sub-studies conducted as part of the institutional Children's Stroke Registry. A maximum lag time of 2 years between the sleep and neurocognitive assessments was allowed. The study was approved by the Research Ethics Boards at the Hospital for Sick Children. 2.2. Measures 2.2.1. Demographic, clinical, and radiographic characteristics The Canadian Pediatric Ischemic Stroke Registry collects demographic, clinical and radiological data using standardized data collection forms. Details of the study protocol and procedures have been published elsewhere.13 Imaging studies conducted at the time of stroke onset were reviewed by study neuroradiologist (PK) to assess lesion location and affected artery size. Neurological deficits were evaluated by study stroke neurologists (JS, DM, GdV, MM, ND) using the Pediatric Stroke Outcome Measure (PSOM) which consists of five subscales: right sensorimotor, left sensorimotor, language production, language comprehension, and cognitive/ behavioral. Each child is assigned a score of 0 (no deficit), 0.5 (minimal/mild deficit, normal function), 1 (moderate deficit), or 2 (severe deficit) on each of the five subscales. Overall, children scoring 0 or 0.5 on any subscale or maximum of 1 on only 1 subscale were classified as having normal/mild neurologic impairment,
otherwise, children were considered to have moderate/severe neurologic impairment.14 Children were classified as obese or overweight using body mass index (BMI) z-scores which were calculated according to age- and sex-specific growth curves of the World Health Organization.15 Children with a BMI between 85th and 95th percentile were classified as overweight and those 95th were classified as obese. Based on known pharmacological effects, medications with known effects on sleep architecture (i.e. sleep aid or sleep disruption) were documented and reviewed including antiepileptic drugs, antihypertensives, antidepressants, central nervous system stimulant drugs, antipsychotics, hypnotics, and melatonin. 2.2.2. The pediatric sleep questionnaire (PSQ) The PSQ, a parent-report questionnaire, was developed and validated for the screening of OSAS in children aged between 2 and 18 years old.12 The OSAS component of the PSQ consists of 22 closed-ended questions. A total score >0.33 has been shown to be a reliable cut-off point for detection of OSAS. This criterion has been shown to correctly classify 86.4% of subjects with sleep related breathing disorders, displaying high sensitivity and specificity (85% and 87%, respectively).12 The prevalence of OSAS in our study was compared to that reported in a cohort of healthy children seen in clinic for well-child development assessment or undergoing immunization in the study conducted by Archbold et al.; 5% (10 out of 201) of these children were found to have OSAS.4 2.2.3. Intellectual abilities We used Wechsler cognitive index scores to assess the intellectual abilities of our patient population. Outcomes were evaluated using: Wechsler Intelligence Scale for Children e 4th or 5th Edition (WISC-IV/V), Weschsler Adult Intelligence Scale e 4th Edition (WAIS-IV), and Wechsler Preschool and Primary Scale of Intelligence e 4th Edition (WPSSI-IV). Index scores included overall intellectual ability (Full-scale IQ [FSIQ]), verbal reasoning ability (Verbal Comprehension Index [VCI]), non-verbal and fluid reasoning (Perceptual Reasoning Index [PRI]), mental manipulation (Working Memory Index [WMI]), and visualemotor speed (Processing Speed Index [PSI]).16e19 To ensure homogeneity across the index scores between the different tests, the PRI scores for WISC-V and WPPSIIV tests were obtained by calculating the arithmetic mean of the visualespatial ability and Fluid Reasoning Index scores. 2.2.4. Behavior and cognitive abilities The Adaptive Behavior Assessment System e 2nd edition (ABAS-2) was used to assess adaptive skills in daily life.20 Three composite scores are derived from the sum of the scaled scores: conceptual (e.g. functional communication, self-direction), social (e.g. leisure activities, social interaction), and practical (e.g. self-care, community use, health and safety). A Global Adaptive Composite (GAC) is obtained from all 11 skill areas. Two distinct questionnaire forms are completed, one by the parent/caregiver and another by the teacher/daycare provider. 2.2.5. Attention and executive function The Behavior Rating Inventory Executive Function (BRIEF) is a widely used standardized instrument for the assessment of executive function of school-age children which includes both parent and teacher forms. It consists of three summary scores: Behavioral Regulation Index (BRI), Metacognition Index (MCI), and Global Executive Composite (GEC).21 2.2.6. Verbal learning and memory We used California Verbal Learning Test for Children (CVLT-C) for the assessment of verbal learning and memory.22 CVLT-C examines
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
the child's verbal learning and memory in children and adolescents through assessing their ability to recall meaningful information from day to day. We examined three measures: List A total Trials 1e5 (total number of words recalled across five trials), List B (total number of words recalled from the second interference list), and Long Delay Free Recall (total number of words freely recalled after a 20-min delay). 2.3. Statistical analysis Descriptive statistics were presented as mean ± standard deviation, median and interquartile ranges (IQR) or percentages, as appropriate. We compared the demographic and clinical characteristics between children with and those without OSAS using Chisquare or Fisher's exact test for qualitative variables and Student's t or ManneWhitney U tests for quantitative variables, as appropriate. For children who underwent neuropsychological evaluation, we compared neuropsychological outcomes based on OSAS status, gender, obesity, and history of seizure using Student's t or MannWhitney U tests. Differences based on the affected artery size and arterial territory were conducted using one-way Analysis of Variance (ANOVA) or Kruskal-Wallis, as appropriate. For the arterial territory, only differences in intellectual ability were conducted due to the small sample sizes obtained with the remaining neuropsychological outcomes. We used Pearson correlation analysis to investigate the relationship between neuropsychological outcomes and age at stroke onset, age at PSQ assessment, time since stroke, and total PSOM scores. We conducted exploratory analysis of index scores of intellectual outcomes that correlated significantly with more than one predictor using stepwise multiple linear regression. We used the Akaike's information criterion corrected for small-sample bias to select the most important predictors of the outcomes. All relevant assumptions for the regression analyses were examined. P-values <0.05 were considered to be statistically significant. Statistical analyses were conducted using SAS University Edition (SAS Institute, Inc, Cary, NC). 3. Results A total of 260 children were screened, 102 of whom were eligible to participate and were assessed for the presence of OSAS. Of the 158 excluded children: 50 children were <2 years of age at the time of assessment and 108 did not have AIS diagnosis. The median age of children at the time of inclusion was 9 (IQR: 6e14) years with almost equal proportions of males and females (Table 1). The median age at stroke onset was 2 years with a neonatal stroke incidence of 22%. Eleven children (11%) were overweight and 19 (18.6%) were obese. One-third of participants were prescribed a concomitant medication that had effects on sleep architecture. Concomitant medications included antiepileptics (17.4%), antihypertensives (8.7%), and central nervous system stimulants (4.4%). 3.1. Prevalence of OSAS: clinical and demographic determinants The prevalence of OSAS in our study cohort was 25.5% (N ¼ 26), which was significantly higher than the normative prevalence rate (5%) reported by Archbold et al. (p < 0.001).4 Differences in demographic and clinical characteristics between children with OSAS and those without OSAS are presented in Table 1. At the time of stroke onset, patients with OSAS were more likely to have anterior and posterior circulation territory infarcts compared to children without OSAS (37.5% vs 9.5%, p ¼ 0.021). No differences were found in age at stroke onset, gender, artery size, infarct location, presence
3
of fever, respiratory difficulties, and seizure at the time of stroke onset. At the time of sleep study assessment, no differences in age, time since stroke, or obesity/overweight prevalence were found between children with and without OSAS. On the other hand, children with OSAS had significantly higher median PSOM scores (2 [IQR: 0e2] vs 1 [IQR: 1e3.5], p ¼ 0.01) and were more likely to be prescribed concomitant medications that affect sleep architecture (50% vs 22.4%, p ¼ 0.007) (Table 1). Specifically, children with AIS and OSAS were more likely to have received medications that could potentially disrupt sleep architecture (42.3% vs 17.1%, p ¼ 0.01) (Table 1). 3.2. Effects of OSAS on neuropsychological outcomes Forty-three children were assessed for their intellectual ability. AIS patients with OSAS had lower scores on all indices but differences were statistically significant for FSIQ and WMI at 73.5 ± 18.2 vs 88.4 ± 19.5 (p ¼ 0.026) and 78.2 ± 16.7 vs 94.7 ± 20.2 (p ¼ 0.015), respectively. A trend toward statistical significance was seen with verbal comprehension index (79.1 ± 16.3 in OSAS-positive vs 90.8 ± 19.6 in OSAS-negative, p ¼ 0.06) (Fig. 1). ABAS-2 parent and teacher forms were evaluated in 26 and 18 children, respectively; children with OSAS performed lower on all composite scales with differences reaching statistical significance for the conceptual and practical composite scores of the parent form (71 ± 13.3 vs 94.3 ± 19.5, p ¼ 0.005 and 71.3 ± 15 vs 84.8 ± 19.3, p ¼ 0.04, respectively) and for the general adaptive composite scores for both the parent and teacher forms (Table 2). BRIEF parent and teacher forms were administered in 32 and 22 children with AIS, respectively; children with OSAS had more pronounced deficits on all executive summary scores of both the parent and teacher forms. With respect to CVLT-C assessment which was conducted in 23 children, those with OSAS scored significantly lower on the T1-5 t score only (37.9 ± 13 vs 47.1 ± 7.4, p ¼ 0.04). 3.3. Effects of other demographic and clinical characteristics on neuropsychological outcomes Comparisons of neuropsychological outcomes based on gender, obesity, arterial size and territory, and history of seizure are summarized in Supplementary Table 1. No differences were found in any of the neuropsychological outcomes between males and females, whereas children classified as overweight/obese had significantly lower scores on the WMI index of the intellectual ability and on the different measures of the CVLT-C compared to those with normal BMI scores. We did not find any differences in neuropsychological outcomes based on the size of the affected artery or history of seizure. However, children with AIS in which both the anterior and posterior circulation were affected had significantly lower scores on the different indices of intellectual ability. As shown in Supplementary Table 2, there were no significant correlations between the age at stroke onset and the different neuropsychological outcomes. Significant negative correlations were demonstrated between age at PSQ assessment and WMI (Pearson's r ¼ 0.36, p ¼ 0.021) and time since stroke onset and PRI (Pearson's r ¼ 0.36, p ¼ 0.03). We also found significant negative correlations between the total PSOM scores at the time of sleep assessment with most of the neuropsychological outcomes. 3.4. Predictors of impaired intellectual function We fitted three stepwise multiple linear regression models to assess the impact of OSAS, obesity/overweight, severity of neurologic impairment (using PSOM) and arterial territory on FSIQ, VCI and WMI index scores (Table 3).
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
4
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Table 1 Demographic and clinical characteristics in the overall sample and among children with and without OSAS. p<0.05: statistically significant (appearing in bold).
Demographic, clinical and radiographic characteristics at stroke onset Age at stroke, years Male, n (%) Age group at stroke, n (%) Childhood Neonatal Fever, n (%) Respiratory difficulties, n (%) Seizure, n (%) Artery size, n (%) Small Large None Arterial territory, n (%) Anterior circulation Posterior circulation Both None Infarct location, n (%) Infratentorial Supratentorial Both None Demographic and clinical characteristics at the time of PSQ assessment Age at PSQ assessment, years Time lag between stroke onset and PSQ assessment, years Total PSOM score Normal/mild neurologic outcome, n (%) Moderate/severe neurologic outcome, n (%) BMI, n (%) Overweight Obese Use of concomitant medications affecting sleep architecture, n (%) Sleep aida Sleep disrupta
Total sample N ¼ 102
OSAS-negative N ¼ 76
OSAS-positive N ¼ 26
P-value
2 (1e6) 56/101 (55.5)
2 (1e6) 45 (60)
2 (0.02e6) 11 (42.3)
0.986 0.118 0.828
80 (78.4) 22 (21.6) 3/98 (3.1) 7/98 (7.1) 34/102 (33.3)
60 (79) 16 (21) 1 (1.4) 4 (5.4) 24 (31.6)
20 (76.9) 6 (23.1) 2 (8.3) 3 (12.5) 10 (38.5)
15/98 (15.3) 43/98 (43.9) 40/98 (40.8)
12 (16.2) 30 (40.5) 32 (43.2)
3 (12.5) 13 (54.2) 8 (33.3)
34/98 (34.7) 9/98 (9.2) 16/98 (16.3) 39/98 (39.8)
28 (37.8) 8 (10.8) 7 (9.5) 31 (41.9)
6 1 9 8
3/98 (3.1) 50/98 (51) 5/98 (5.1) 40/98 (40.8)
2 (2.7) 39 (52.7) 2 (2.7) 31 (41.9)
1 (4.2) 11 (45.8) 3 (12.5) 9 (37.5)
9 (6e14) 5 (3e8) 1 (0e2.5) 76 (74.5) 26 (25.5)
9 (6e14.5) 4 (3e9) 1 (0e2) 60 (79) 16 (21)
9 (6e14) 5 (3e8) 2 (1e3.5) 16 (61.5) 10 (38.5)
0.611 0.847 0.010 0.078
11/102 (10.8) 19/102 (18.6) 30/102 (29.4) 8/102 (7.8) 24/102 (23.5)
7 (9.2) 14 (18.4) 17 (22.4) 5 (6.6) 13 (17.1)
4 (15.4) 5 (19.2) 13 (50) 3 (11.5) 11 (42.3)
0.465 1 0.007 0.417 0.01
0.147 0.357 0.631 0.505
0.021 (25) (4.2) (37.5) (33.3) 0.261
Continuous variables are expressed as median (25e75 Interquartile range). AIS: arterial ischemic stroke; BMI: body mass index; PSOM: pediatric stroke outcome measure; PSQ: pediatric stroke questionnaire; OSAS: obstructive sleep apnea syndrome. a Two children had concomitant prescription of sleep aid and sleep disrupt medications.
Regression analysis revealed that PSQ score, obesity and arterial territory were the strongest predictors of FSIQ accounting for 38% of its total variance, F (5, 36) ¼ 5.43, p ¼ 0.001 and of the WMI accounting for 44.9% of its total variance, F (5, 37) ¼ 7.04, p < 0.001. At the level of VCI scores, moderate/severe neurologic disability and PSQ scores were the only significant predictors of poor verbal and comprehension explaining a total of 28.9% of its variance, F (2, 38) ¼ 8.7, p < 0.001. Of interest, the contribution of the total PSQ to the variance in FSIQ and WMI scores remained statistically significant when accounting for other predictors. 4. Discussion To our knowledge, this is the first study to investigate the prevalence of OSAS in children with AIS and its association with neuropsychological outcomes. In our current study, we found significantly elevated prevalence rates of OSAS in children with AIS compared with published rates in healthy children. The presence of OSAS correlated significantly with poor neurocognitive and adaptive function. OSAS represents a continuum of breathing abnormalities during sleep that affect both adults and children.23 In children with AIS, the prevalence of OSAS (25.5%) was significantly higher than the prevalence rates described in the scientific literature for the general pediatric population. However, it is comparable to prevalence rates
of OSAS documented in other disease conditions such as hypertension and non-infectious respiratory conditions.4,24 A reciprocal relationship is thought to exist between OSAS and general health in childhood.25 While OSAS is known for its detrimental health outcomes, the risk of OSAS occurrence in childhood increases remarkably in the presence of certain acute or chronic disease conditions.6 Hence, OSAS can be the consequence of underlying disease-related mechanisms or medication-related adverse reaction or the cause of disease conditions.6,26e28 Specifically, multiple studies demonstrated the presence of a bidirectional relationship between OSAS as a risk factor for stroke and as a potential consequence of stroke.9,28e30 In a meta-analysis of adult stroke survivors, Johnson and Johnson30 demonstrated that sleep apnea is significantly elevated reaching 72% in patients with ischemic or hemorrhagic stroke and TIA. The development of respiratory disturbances following stroke is highly dependent on the affected brain region.31e35 Supra or infratentorial stroke lesions favor the development of obstructive sleep apnea by inducing disturbed coordination of upper airways, intercostal and diaphragmatic muscles.28 Damage to the brainstem respiratory control following medullary brain lesions leads to decreased ventilatory sensitivity to carbon dioxide and increased predisposition to sleep apnea.36 In addition, it has been postulated that stroke may disrupt breathing through the disturbance of central rhythm generation, interruption of descending respiratory pathways or by causing bulbar weakness/aspiration.37 Other
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
5
Fig. 1. Differences in intellectual ability between children with and without OSAS. *p < 0.05. FSIQ: full scale IQ; OSAS: obstructive sleep apnea syndrome; PRI: Perceptual Reasoning Index; PSI: processing speed index; WMI: working memory index; VCI: verbal comprehension index.
predisposing factors include the incidence of respiratory infections, decreased voluntary chest movements on the paralyzed side, prolonged supine position, and increased sleep fragmentation due to stroke complications.28 In our current study, although statistical significance was not reached, children with stroke who were OSASpositive were more likely to have infarcts in both supra and infratentorial regions. These findings were comparable to those reported in adults by Kaneko et al.38 Furthermore, children with stroke and OSAS-positive were more likely to have their stroke affecting both anterior and posterior circulations. A recently published nationwide cohort study in children and adolescents showed that the risk of major adverse cardiovascular events is doubled in the presence of obstructive sleep apnea.27 Similarly, a significant association between OSAS and cerebrovascular events including stroke is found in the adult population. In their cross-sectional study, Shahar et al. reported significantly elevated relative odds for disordered apnea-hypopnea index (1.58;
95% CI: 1.02e2.46) in stroke patients.39 Causal association between obstructive sleep apnea and stroke in adults was confirmed in the large cohort study conducted by Yaggi et al. in which a two-fold increase in the risk of stroke in patients with obstructive sleep apnea was found.9 Several mechanisms have been postulated to be responsible for the increased risk of stroke in patients with OSAS. Acute apneic episodes are associated with hemodynamic changes that cause significant decline in cerebral blood flow due to reduction in cardiac output predisposing subjects to cerebrovascular accidents.40 OSAS has also been shown to be associated with systemic hypertension and endothelial dysfunction following sympathetic nervous system activation in addition to increased platelet aggregability, and paradoxical embolization.41 In children with stroke, there is mounting evidence which points toward the potential involvement of hypertension, arteriosclerosis and endothelial dysfunction, in the underlying pathogenesis of stroke.42e44 However, the potential contribution of OSAS to these underlying
Table 2 Differences in neuropsychological function between children with and without OSAS. p<0.05: statistically significant (appearing in bold).
ABAS-2 parent form composite scores Conceptual composite (n ¼ 26) Social composite (n ¼ 25) Practical composite (n ¼ 25) General adaptive composite (n ¼ 25) ABAS-2 teacher form composite scores Conceptual composite (n ¼ 18) Social composite (n ¼ 18) Practical composite (n ¼ 17) General adaptive composite (n ¼ 17) BRIEF (T scores) e parent form BRI (n ¼ 32) MCI (n ¼ 31) GEC (n ¼ 33) BRIEF (T scores) e teacher form BRI (n ¼ 22) MCI (n ¼ 22) GEC (n ¼ 22) CVLT-C T1-5 t score (n ¼ 23) Long Del. Free Recall Z (n ¼ 23) List B Z (n ¼ 23) a
Total sample
OSAS-negative
OSAS-positive
N ¼ 26 87.1 ± 20.7 90.6 ± 19.6 80.5 ± 18.9 83.3 ± 20.4 N ¼ 18 88.3 ± 28.3 88.5 ± 26.7 88.6 ± 21.4 90.5 ± 20.6 N ¼ 34 59.7 ± 11.7 59.8 ± 11 59.5 ± 11.9 N ¼ 22 58.3 ± 14.9 61.7 ± 12.5 61.1 ± 13.1 N ¼ 23 43.9 ± 10.4 0.66 ± 1.3 0.59 ± 0.9
N ¼ 18 94.3 ± 19.5 93.5 ± 21.2 84.8 ± 19.3 89.3 ± 20.6 N ¼ 13 92.4 ± 29.6 90.7 ± 30.2 94.7 ± 16.8 96.9 ± 17.1 N ¼ 21 55.6 ± 11.4 55.7 ± 9.9 55 ± 10.5 N ¼ 13 51.3 ± 7.7 57.1 ± 13.7 55 ± 11 N ¼ 15 47.1 ± 7.4 0.3 ± 1.1 0.6 ± 0.8
N¼8 71 ± 13.3 84.4 ± 15 71.3 ± 15 70.5 ± 13.5 N¼5 77.8 ± 24.3 82.8 ± 15.7 74 ± 26 75.2 ± 21.8 N ¼ 13 65.5 ± 10 66.2 ± 9.8 67.3 ± 10.3 N¼9 68.5 ± 17.2 68.4 ± 6.8 69.9 ± 10.9 N¼8 37.9 ± 13 1.3 ± 1.5 0.6 ± 1.3
P-value 0.005 0.285 0.035a 0.028 0.183a 0.590 0.068 0.044 0.008 0.008 0.003 0.001 0.033 0.005 0.039 0.106 0.891
ManneWhitney U test.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
6
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Table 3 Stepwise multiple linear regression modelsa for predictors of intellectual ability index scores. Slope (B) FSIQ Constant Total PSQ score Overweight/obesity Arterial territory Ref ¼ “None” Anterior Posterior Both VCI Constant Total PSQ score Moderate/Severe neurologic impairmentb Ref ¼ “Normal/Mild” WMI Constant Total PSQ score Overweight/obesity Arterial territory Ref ¼ “None” Anterior Posterior Both
95% CI
Adjusted R2
t
P-value
0.38 92.3 45.9 16.6
81.1, 103.5 83.9, 8.1 29.9, 3.3
16.8 2.48 2.55
<0.001 0.019 0.016
14.5 19.9 10.7
2.1, 26.8 5.1, 44.9 26.5, 5.2
2.4 1.6 1.4
0.023 0.115 0.178
101.2 32.7 17.5
91.3, 111.1 70.8, 5.3 28.8, 6.3
20.8 1.75 3.2
<0.001 0.089 0.0031
97.1 43.2 21.2
86.6, 107.6 79.5, 6.8 34.1, 8.2
18.9 2.42 3.33
<0.001 0.022 0.002
19.8 20.6 8
7.9, 31.8 3.73, 44.9 23.4, 7.4
3.4 1.72 1.1
0.002 0.094 0.298
0.289
0.44
CI: confidence interval; FSIQ: full scale IQ; PSQ: pediatric stroke questionnaire; WMI: working memory index; VCI: verbal comprehension index. a For each of the models, total PSQ scores, overweight/obesity status, arterial territory, and severity of neurologic important were incorporated as predictor variables. b Neurologic impairment severity was classified based on the Pediatric Stroke Outcome Measure subscale scores.
processes requires further investigation. Children with AIS and OSAS had greater neurologic deficits at the time of sleep assessment as indicated by the significantly higher PSOM scores. This is in keeping with the adult literature in which OSAS in patients with stroke was shown to be associated with poorer functional outcomes.31,45 This could also explain the higher frequency of prescription drugs used among these children that are potentially linked to the disruption of sleep architecture. However, the specific effects of the concomitant medications on the sleep cycle in our study cannot be elucidated using the PSQ. Improved understanding of this requires larger prospective studies with objective polysomnographic evaluation. Neuropsychological impairments secondary to pediatric stroke have been documented in several short and long-term studies that reported reductions in various domains including intellectual function, attention, verbal learning and memory, visual-spatial processing, processing speed, and executive function.46 Demographic and clinical determinants including age at stroke, time since stroke, laterality, and lesion characteristics are wellestablished risk factors for impaired neuropsychological function in children with stroke.47 In addition to these factors, our current study attempted to assess the potential role for OSAS as a contributing factor to neuropsychological impairments following pediatric AIS. Pediatric OSAS can negatively influence children's development, resulting in significant cognitive and behavioral deficits.48,49 In our study, the presence of OSAS was associated with significantly worse performance across the different neuropsychological domains assessed. Full scale IQ and working memory were the most affected, though non-significant trends were observed for the other scales from the intellectual battery. OSAS in children is independently linked with adverse neurocognition and increased severity of OSAS was associated with worse neurocognitive performance.50 Adenoidectomy and/or tonsillectomy are typically the first line of therapy for children with sleep apnea who have adenoidal or tonsillar hypertrophy. These surgical interventions are associated with improvements in neurobehavioral and cognitive performance especially where there is complete resolution of sleep apnea.51 In children with persistent OSA post-
adenotonsillectomy, continuous positive airway pressure (CPAP) is typically prescribed. In one study evaluating the effects of CPAP in 52 children with sleep apnea, significant improvements in neurobehavioral parameters were found after 3 months of treatment despite the fact that the average use of CPAP was approximately 3 h per night.52 However, it must be considered that the effects of OSAS on neuropsychological function in children with stroke may not be independent of stroke-related factors. Interestingly, in the randomized clinical trial conducted by Ryan et al.53 in adult stroke survivors with obstructive sleep apnea, CPAP therapy led to improved functional and motor outcomes but not neurocognitive outcomes. Since these studies may not necessarily be extrapolated to children with OSAS in the absence of stroke, future studies should focus on evaluating neurocognition, behavior and functional outcomes in children with stroke pre and post therapeutic interventions for OSAS. Such information will facilitate knowledge for advanced therapeutics to improve outcomes following stroke in children. Our findings of abnormal behavioral and adaptive functioning in children with stroke and OSAS as demonstrated using ABAS-2 composite scores are comparable to results reported in previous studies in which significantly increased risk of hyperactivity, lower social competency, diminished adaptive skills, and aggressive and inattentive behavior in children with OSAS were found.54,55 A plausible negative association between OSAS and executive function was also evident in our study, which is consistent with findings from a previous study showing significant association between sleep-disordered breathing and executive function in children.56 The exact mechanism through which OSAS induces cognitive and adaptive impairments remains unclear. It has been hypothesized that sleep fragmentation, arousals and intermittent hypoxemia interfere with restorative sleep processes and cellular homeostasis of the prefrontal cortex, inducing systemic inflammatory and vascular changes in the brain, as observed in children with OSAS.57e59 The use of a subjective sleep measure represents a limitation in our study. Nevertheless, the PSQ has displayed adequate validity
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
and reliability as a screen for polysomnographically defined OSAS.12 In addition, PSQ has been shown to be of important utility in epidemiological studies as a screening tool for OSAS and it has been shown to correctly classify 86.4% of subjects with sleep related breathing disorders.60 Assuming misclassification rates of 14%, prevalence rates of OSAS in pediatric stroke remain significantly elevated at 22%. The absence of clinical assessment for other known risk factors of OSAS, such as adenotonsillar hypertrophy is a limitation in our current study. Conducting the correlation analyses between OSAS and neuropsychological function in subsets of the total sample could have increased the potential of selection bias. Finally, the lag time between sleep and neuropsychological testing is another drawback in the design of our study; however, despite the tendency for OSAS to improve with time in some children, significant negative correlations between OSAS and neuropsychological outcomes were obtained. Our study highlights the relatively increased prevalence of OSAS in children with AIS and its association with poor neurocognitive and adaptive function. Poor neurological outcomes, infarcts affecting both the anterior and posterior circulation, and increased use of medications affecting sleep architecture correlated significantly with OSAS in children with AIS. Our current study highlights the importance of regular screening for OSAS among children with stroke. We suggest consideration of referral for polysomnography and respiratory consultation for assessment and confirmation of diagnosis if a validated screening threshold is reached, i.e. total PSQ scores0.33. Implementation of this approach is likely to lead to the identification of children with an added modifiable risk of poor neuropsychological outcome. The beneficial effects of therapeutic interventions targeting OSAS on the neurological and neuropsychological outcomes warrant further investigation. Declaration of Competing Interest The authors have indicated they have no potential conflicts of interest to disclose. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ejpn.2019.11.006. Funding source All phases of this study were supported by The Auxilium Foundation. ABAS-2: Adaptive Behavior Assessment System, 2nd edition; BRI: Behavioral Regulation Index; BRIEF: Behavior Rating Inventory Executive Function; CVLT-C: California Verbal Learning Test for Children; FSIQ: full scale IQ; GEC: Global Executive Composite; Long Del. Free Recall: Long Delay Free Recall; MCI: Metacognition Index; PRI: Perceptual Reasoning Index; OSAS: obstructive sleep apnea syndrome; PSI: processing speed index; WMI: working memory index; VCI: verbal comprehension index. References 1 V.K. Chattu, S.M. Sakhamuri, R. Kumar, et al., Insufficient Sleep Syndrome: is it time to classify it as a major noncommunicable disease? Sleep Sci 11 (2018) 56e64. 2 V. Kapur, K.P. Strohl, S. Redline, et al., Underdiagnosis of sleep apnea syndrome in U.S. communities, Sleep Breath 6 (2002) 49e54. 3 M. Anstead, B. Phillips, The spectrum of sleep-disordered breathing, Respir Care Clin N Am 5 (1999) 363e377 [viii]. 4 K.H. Archbold, K.J. Pituch, P. Panahi, R.D. Chervin, Symptoms of sleep disturbances among children at two general pediatric clinics, J Pediatr 140 (2002) 97e102.
7
5 K.A. Bonuck, R.D. Chervin, T.J. Cole, et al., Prevalence and persistence of sleep disordered breathing symptoms in young children: a 6-year population-based cohort study, Sleep 34 (2011) 875e884. 6 A.S. Lewandowski, T.M. Ward, T.M. Palermo, Sleep problems in children and adolescents with common medical conditions, Pediatr Clin N Am 58 (2011) 699e713. 7 R.D. Chervin, K.H. Archbold, J.E. Dillon, et al., Inattention, hyperactivity, and symptoms of sleep-disordered breathing, Pediatrics 109 (2002) 449e456. 8 N. Glozier, T.J. Moullaali, B. Sivertsen, et al., The course and impact of poststroke insomnia in stroke survivors aged 18 to 65 Years: results from the psychosocial outcomes in StrokE (POISE) study, Cerebrovasc Dis Extra 7 (2017) 9e20. 9 H.K. Yaggi, J. Concato, W.N. Kernan, et al., Obstructive sleep apnea as a risk factor for stroke and death, N Engl J Med 353 (2005) 2034e2041. 10 M. Studer, E. Boltshauser, A. Capone Mori, et al., Factors affecting cognitive outcome in early pediatric stroke, Neurology 82 (2014) 784e792. 11 R. Westmacott, R. Askalan, D. MacGregor, P. Anderson, G. Deveber, Cognitive outcome following unilateral arterial ischaemic stroke in childhood: effects of age at stroke and lesion location, Dev Med Child Neurol 52 (2010) 386e393. 12 R.D. Chervin, K. Hedger, J.E. Dillon, K.J. Pituch, Pediatric sleep questionnaire (PSQ): validity and reliability of scales for sleep-disordered breathing, snoring, sleepiness, and behavioral problems, Sleep Med 1 (2000) 21e32. 13 G.A. deVeber, A. Kirton, F.A. Booth, et al., Epidemiology and outcomes of arterial ischemic stroke in children: the Canadian pediatric ischemic stroke registry, Pediatr Neurol 69 (2017) 58e70. 14 M. Slim, N. Dlamini, C. Fox, et al., Outcome severity assessment with the pediatric stroke outcome measure (PSOM): validation of a novel classification system. 47th Annual Meeting of the Child Neurology Society, Ann Neurol. 84 (2018) S281eS428. 15 WHO Multicentre Growth Reference Study Group, WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-for-length, weight-forheight and body mass index-for-age: methods and development, World Health Organization, Geneva, 2006. 16 D. Wechsler, Wechsler intelligence scale for children, 5th ed., Pearson Education, Inc., & Psychological Corporation., San Antonio, TX, 2014. 17 D. Wechsler, Wechsler intelligence scale for children - fourth edition technical and interpretive manual, The Psychological Corporation, San Antonio, TX, 2003. 18 D. Wechsler, Wechsler adult intelligence scale, 4th ed., Pearson, San Antonio, TX, 2008. 19 D. Wechsler, Wechsler Preschool and primary scale of intelligence, 4th ed., NCS Pearson, San Antonio, TX, 2012. 20 P.L. Harrison, T. Oakland, ABAS II : adaptive behavior assessment system, Western Psychological Services, Los Angeles, Calif., 2008. 21 G.A. Gioia, P.K. Isquith, S.C. Guy, L. Kenworthy, TEST REVIEW behavior rating inventory of executive function, Child Neuropsychol 6 (2000) 235e238. 22 D.C. Delis, CVLT-C : California verbal learning test, Psychological Corporation, Harcourt Brace Corporation, San Antonio, TX, 1994. 23 R. Downey 3rd, R.M. Perkin, J. MacQuarrie, Upper airway resistance syndrome: sick, symptomatic but underrecognized, Sleep 16 (1993) 620e623. 24 M.B. Lande, S.R. Hooper, D.L. Batisky, et al., Sleep disordered breathing as measured by SRBD-PSQ and neurocognition in children with hypertension, Am J Hypertens 28 (2015) 552e558. 25 M.R. Irwin, Why sleep is important for health: a psychoneuroimmunology perspective, Annu Rev Psychol 66 (2015) 143e172. 26 R. Arens, C.L. Marcus, Pathophysiology of upper airway obstruction: a developmental perspective, Sleep 27 (2004) 997e1019. 27 N.S. Tzeng, C.H. Chung, H.A. Chang, et al., Obstructive sleep apnea in children and adolescents and the risk of major adverse cardiovascular events: a nationwide cohort study in Taiwan, J Clin Sleep Med 15 (2019) 275e283. 28 F. Alexiev, A.K. Brill, S.R. Ott, et al., Sleep-disordered breathing and stroke: chicken or egg? J Thorac Dis 10 (2018) S4244eS4252. 29 S. Jehan, M. Farag, F. Zizi, et al., Obstructive sleep apnea and stroke, Sleep Med Disord 2 (2018) 120e125. 30 K.G. Johnson, D.C. Johnson, Frequency of sleep apnea in stroke and TIA patients: a meta-analysis, J Clin Sleep Med 6 (2010) 131e137. 31 D.C. Good, J.Q. Henkle, D. Gelber, J. Welsh, S. Verhulst, Sleep-disordered breathing and poor functional outcome after stroke, Stroke 27 (1996) 252e259. 32 M. Bonnin-Vilaplana, A. Arboix, O. Parra, et al., Sleep-related breathing disorders in acute lacunar stroke, J Neurol 256 (2009) 2036e2042. 33 D.L. Brown, M. McDermott, A. Mowla, et al., Brainstem infarction and sleepdisordered breathing in the BASIC sleep apnea study, Sleep Med 15 (2014) 887e891. 34 S.M. Stahl, H.K. Yaggi, S. Taylor, et al., Infarct location and sleep apnea: evaluating the potential association in acute ischemic stroke, Sleep Med 16 (2015) 1198e1203. 35 A.L. Fisse, A. Kemmling, A. Teuber, et al., The association of lesion location and sleep related breathing disorder in patients with acute ischemic stroke, PLoS One 12 (2017), e0171243. 36 M.J. Morrell, P. Heywood, S.H. Moosavi, A. Guz, J. Stevens, Unilateral focal lesions in the rostrolateral medulla influence chemosensitivity and breathing measured during wakefulness, sleep, and exercise, J Neurol Neurosurg Psychiatry 67 (1999) 637e645. 37 R.S. Howard, A.G. Rudd, C.D. Wolfe, A.J. Williams, Pathophysiological and clinical aspects of breathing after stroke, Postgrad Med J 77 (2001) 700e702. 38 Y. Kaneko, V.E. Hajek, V. Zivanovic, J. Raboud, T.D. Bradley, Relationship of sleep apnea to functional capacity and length of hospitalization following stroke,
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
8
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Sleep 26 (2003) 293e297. 39 E. Shahar, C.W. Whitney, S. Redline, et al., Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the sleep heart health study, Am J Respir Crit Care Med 163 (2001) 19e25. 40 N. Netzer, P. Werner, I. Jochums, M. Lehmann, K.P. Strohl, Blood flow of the middle cerebral artery with sleep-disordered breathing: correlation with obstructive hypopneas, Stroke 29 (1998) 87e93. 41 R.S. Leung, T.D. Bradley, Sleep apnea and cardiovascular disease, Am J Respir Crit Care Med 164 (2001) 2147e2165. 42 J.C. Kupferman, D.I. Zafeiriou, M.B. Lande, F.J. Kirkham, S.G. Pavlakis, Stroke and hypertension in children and adolescents, J Child Neurol 32 (2017) 408e417. 43 S. Sultan, M. Dowling, A. Kirton, et al., Dyslipidemia in children with arterial ischemic stroke: prevalence and risk factors, Pediatr Neurol 78 (2018) 46e54. 44 D. Eleftheriou, V. Ganesan, Y. Hong, N.J. Klein, P.A. Brogan, Endothelial repair in childhood arterial ischaemic stroke with cerebral arteriopathy, Cerebrovasc Dis Extra 5 (2015) 68e74. 45 S. Yan-fang, W. Yu-ping, Sleep-disordered breathing: impact on functional outcome of ischemic stroke patients, Sleep Med 10 (2009) 717e719. 46 M. Greenham, V. Anderson, A. Cooper, et al., Early predictors of psychosocial functioning 5 years after paediatric stroke, Dev Med Child Neurol 59 (2017) 1034e1041. 47 A. Fuentes, A. Deotto, M. Desrocher, G. deVeber, R. Westmacott, Determinants of cognitive outcomes of perinatal and childhood stroke: a review, Child Neuropsychol 22 (2016) 1e38. 48 D.W. Beebe, Cognitive, behavioral, and functional consequences of inadequate sleep in children and adolescents, Pediatr Clin N Am 58 (2011) 649e665. 49 B. Galland, K. Spruyt, P. Dawes, et al., Sleep disordered breathing and academic performance: a meta-analysis, Pediatrics 136 (2015) e934e946. 50 S.J. Hunter, D. Gozal, D.L. Smith, et al., Effect of sleep-disordered breathing severity on cognitive performance measures in a large community cohort of
young school-aged children, Am J Respir Crit Care Med 194 (2016) 739e747. 51 C.L. Marcus, R.H. Moore, C.L. Rosen, et al., A randomized trial of adenotonsillectomy for childhood sleep apnea, N Engl J Med 368 (2013) 2366e2376. 52 C.L. Marcus, J. Radcliffe, S. Konstantinopoulou, et al., Effects of positive airway pressure therapy on neurobehavioral outcomes in children with obstructive sleep apnea, Am J Respir Crit Care Med 185 (2012) 998e1003. 53 C.M. Ryan, M. Bayley, R. Green, B.J. Murray, T.D. Bradley, Influence of continuous positive airway pressure on outcomes of rehabilitation in stroke patients with obstructive sleep apnea, Stroke 42 (2011) 1062e1067. 54 D.J. Gottlieb, R.M. Vezina, C. Chase, et al., Symptoms of sleep-disordered breathing in 5-year-old children are associated with sleepiness and problem behaviors, Pediatrics 112 (2003) 870e877. 55 M.M. Perfect, K. Archbold, J.L. Goodwin, D. Levine-Donnerstein, S.F. Quan, Risk of behavioral and adaptive functioning difficulties in youth with previous and current sleep disordered breathing, Sleep 36 (2013) 517e525B. 56 J.J. Mietchen, D.P. Bennett, T. Huff, D.W. Hedges, S.D. Gale, Executive function in pediatric sleep-disordered breathing: a meta-analysis, J Int Neuropsychol Soc 22 (2016) 839e850. 57 I. Trosman, S.J. Trosman, Cognitive and behavioral consequences of sleep disordered breathing in children, Med Sci 5 (2017). 58 C.S. Tam, M. Wong, R. McBain, S. Bailey, K.A. Waters, Inflammatory measures in children with obstructive sleep apnoea, J Paediatr Child Health 42 (2006) 277e282. 59 D. Gozal, L.D. Serpero, O. Sans Capdevila, L. Kheirandish-Gozal, Systemic inflammation in non-obese children with obstructive sleep apnea, Sleep Med 9 (2008) 254e259. 60 K. Spruyt, D. Gozal, Pediatric sleep questionnaires as diagnostic or epidemiological tools: a review of currently available instruments, Sleep Med Rev 15 (2011) 19e32.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
Contents lists available at ScienceDirect
European Journal of Paediatric Neurology
Original article
Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke Mahmoud Slim a, Robyn Westmacott b, Sandra Toutounji a, Jaspal Singh c, Indra Narang d, Shelly Weiss a, Pradeep Krishnan e, Elena Grbac a, Ann-Marie Surmava a, Kathleen Andres a, Daune MacGregor a, Gabrielle deVeber a, Mahendranath Moharir a, Nomazulu Dlamini a, * a
Division of Neurology, The Hospital for Sick Children, Toronto, Canada Department of Psychology, The Hospital for Sick Children, Toronto, Canada c Department of Neurology, University Hospital Southampton NHS Foundation Trust, Southampton, UK d Division of Respiratory Medicine, The Hospital for Sick Children, Toronto, Canada e Division of Diagnostic Imaging, The Hospital for Sick Children, Toronto, Canada b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 7 January 2019 Received in revised form 4 June 2019 Accepted 17 November 2019
Objectives: To assess the prevalence of obstructive sleep apnea syndrome (OSAS) in children with arterial ischemic stroke (AIS) and to evaluate its association with neuropsychological outcomes. Methods: We conducted a cross-sectional study of sleep health and neuropsychological outcome in children with AIS. A consecutive cohort of children attending a stroke clinic were assessed using a standardized pediatric sleep questionnaire (PSQ) and standardized measures of pediatric stroke outcome and intellectual, executive and adaptive function. High risk for OSAS was defined as PSQ score 0.33. Results: Overall, 102 children were included (55% males, median age: 9 years [interquartile-range [IQR]: 6e14]). The prevalence of OSAS in children with AIS was significantly higher compared to published normative prevalence rate (25.5% vs 5%, p < 0.001). Children with OSAS were more likely to have infarcts affecting both the anterior and posterior circulation (37.5% vs 9.5%, p ¼ 0.021). In addition, children with OSAS had significantly higher median Pediatric Stroke Outcome Measure (PSOM) scores (2 [IQR: 0e2] vs 1 [IQR: 1e3.5], p ¼ 0.01) and were more likely to be prescribed concomitant medications affecting sleep architecture (50% vs 22.4%, p ¼ 0.007). OSAS was associated with significantly lower scores on intellectual, memory, cognitive, behavioral, attention, executive and adaptive function scales. The association between PSQ and intellectual ability and working memory remained statistically significant upon controlling for potential confounding factors including stroke related characteristics (neurologic impairment and arterial territory). Conclusions: The prevalence of OSAS in children with AIS compared to healthy controls is significantly elevated and is associated with poor neuropsychological outcomes. We highlight the importance of regular screening for OSAS e a modifiable risk factor - in children with AIS. The specific risk factors for OSAS and the potential benefits of therapeutic interventions in this patient population warrant further investigation. © 2019 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.
Keywords: Obstructive sleep apnea syndrome Arterial ischemic stroke Neuropsychology Cognition Adaptive function
1. Introduction Sleep is essential for the psychosocial, physical and mental
* Corresponding author. Division of Neurology, The Hospital for Sick Children, 555 University Avenue, Toronto, Ontario, M5G 1X8, Canada. Fax: þ1 416 813 6334. E-mail address: [email protected] (N. Dlamini).
wellbeing of children. However, in the last 20 years, there has been an epidemic of sleep deprivation in children.1 Several factors have contributed to this epidemic including the underdiagnosis of sleep disorders such as obstructive sleep apnea syndrome (OSAS).2 OSAS represents a wide spectrum of sleep-related breathing disorders ranging from intermittent snoring to the more severe forms of obstructive sleep apnea and obstructive hypoventilation.3 The prevalence of OSAS in typically developing children ranges
https://doi.org/10.1016/j.ejpn.2019.11.006 1090-3798/© 2019 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
2
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
between 0.7% and 13%.4,5 Several medical conditions such as sickle cell disease, epilepsy, autism spectrum disorders, mood and anxiety disorders, and craniofacial abnormalities are known to have a high prevalence of OSAS in childhood.6 Untreated OSAS in healthy children is known to be associated with a range of adverse outcomes including daytime sleepiness, reduced quality of life, abnormal neurocognitive functioning, neurodevelopmental and long-term behavioral morbidities.6 These poor outcomes are not limited to the more severe forms of OSAS, but are also present with the milder forms including habitual snoring.7 In adults, OSAS is an established risk factor for stroke which contributes to worsening of cognitive and mood disorders such as depression and anxiety in adults with stroke.8,9 Several studies have demonstrated that stroke-related characteristics including age at stroke, lesion volume and location are important mediators of cognitive outcomes in pediatric stroke.10,11 However, the relationship between OSAS, stroke related outcomes, cognitive, executive, language and adaptive outcomes is relatively unexplored. To date, the prevalence rates of OSAS in children with AIS and their impact on neurocognitive and adaptive function in this population have not been investigated. We aimed to (1) estimate the prevalence of OSAS in children with AIS and (2) to assess the association between OSAS and intellectual and cognitive abilities, attention, executive function, language, and adaptive function. We hypothesized that the prevalence of OSAS in children with AIS is increased compared to healthy children and that comorbid OSAS is associated with poorer neuropsychological outcomes. 2. Methods 2.1. Patient population and procedures The patient population comprised of a consecutive cohort of children enrolled in the institutional Children's Stroke Registry at the Hospital for Sick Children, Toronto, Canada. Screening for OSAS was conducted using a validated pediatric sleep questionnaire (PSQ) in children attending the stroke clinic between July 2016 and October 2017.12 Inclusion criteria included: (1) age between 2 and 18 years and (2) a previous diagnosis of arterial ischemic stroke (AIS). Neurocognitive and behavioral assessments were available for eligible children who were co-enrolled in additional sub-studies conducted as part of the institutional Children's Stroke Registry. A maximum lag time of 2 years between the sleep and neurocognitive assessments was allowed. The study was approved by the Research Ethics Boards at the Hospital for Sick Children. 2.2. Measures 2.2.1. Demographic, clinical, and radiographic characteristics The Canadian Pediatric Ischemic Stroke Registry collects demographic, clinical and radiological data using standardized data collection forms. Details of the study protocol and procedures have been published elsewhere.13 Imaging studies conducted at the time of stroke onset were reviewed by study neuroradiologist (PK) to assess lesion location and affected artery size. Neurological deficits were evaluated by study stroke neurologists (JS, DM, GdV, MM, ND) using the Pediatric Stroke Outcome Measure (PSOM) which consists of five subscales: right sensorimotor, left sensorimotor, language production, language comprehension, and cognitive/ behavioral. Each child is assigned a score of 0 (no deficit), 0.5 (minimal/mild deficit, normal function), 1 (moderate deficit), or 2 (severe deficit) on each of the five subscales. Overall, children scoring 0 or 0.5 on any subscale or maximum of 1 on only 1 subscale were classified as having normal/mild neurologic impairment,
otherwise, children were considered to have moderate/severe neurologic impairment.14 Children were classified as obese or overweight using body mass index (BMI) z-scores which were calculated according to age- and sex-specific growth curves of the World Health Organization.15 Children with a BMI between 85th and 95th percentile were classified as overweight and those 95th were classified as obese. Based on known pharmacological effects, medications with known effects on sleep architecture (i.e. sleep aid or sleep disruption) were documented and reviewed including antiepileptic drugs, antihypertensives, antidepressants, central nervous system stimulant drugs, antipsychotics, hypnotics, and melatonin. 2.2.2. The pediatric sleep questionnaire (PSQ) The PSQ, a parent-report questionnaire, was developed and validated for the screening of OSAS in children aged between 2 and 18 years old.12 The OSAS component of the PSQ consists of 22 closed-ended questions. A total score >0.33 has been shown to be a reliable cut-off point for detection of OSAS. This criterion has been shown to correctly classify 86.4% of subjects with sleep related breathing disorders, displaying high sensitivity and specificity (85% and 87%, respectively).12 The prevalence of OSAS in our study was compared to that reported in a cohort of healthy children seen in clinic for well-child development assessment or undergoing immunization in the study conducted by Archbold et al.; 5% (10 out of 201) of these children were found to have OSAS.4 2.2.3. Intellectual abilities We used Wechsler cognitive index scores to assess the intellectual abilities of our patient population. Outcomes were evaluated using: Wechsler Intelligence Scale for Children e 4th or 5th Edition (WISC-IV/V), Weschsler Adult Intelligence Scale e 4th Edition (WAIS-IV), and Wechsler Preschool and Primary Scale of Intelligence e 4th Edition (WPSSI-IV). Index scores included overall intellectual ability (Full-scale IQ [FSIQ]), verbal reasoning ability (Verbal Comprehension Index [VCI]), non-verbal and fluid reasoning (Perceptual Reasoning Index [PRI]), mental manipulation (Working Memory Index [WMI]), and visualemotor speed (Processing Speed Index [PSI]).16e19 To ensure homogeneity across the index scores between the different tests, the PRI scores for WISC-V and WPPSIIV tests were obtained by calculating the arithmetic mean of the visualespatial ability and Fluid Reasoning Index scores. 2.2.4. Behavior and cognitive abilities The Adaptive Behavior Assessment System e 2nd edition (ABAS-2) was used to assess adaptive skills in daily life.20 Three composite scores are derived from the sum of the scaled scores: conceptual (e.g. functional communication, self-direction), social (e.g. leisure activities, social interaction), and practical (e.g. self-care, community use, health and safety). A Global Adaptive Composite (GAC) is obtained from all 11 skill areas. Two distinct questionnaire forms are completed, one by the parent/caregiver and another by the teacher/daycare provider. 2.2.5. Attention and executive function The Behavior Rating Inventory Executive Function (BRIEF) is a widely used standardized instrument for the assessment of executive function of school-age children which includes both parent and teacher forms. It consists of three summary scores: Behavioral Regulation Index (BRI), Metacognition Index (MCI), and Global Executive Composite (GEC).21 2.2.6. Verbal learning and memory We used California Verbal Learning Test for Children (CVLT-C) for the assessment of verbal learning and memory.22 CVLT-C examines
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
the child's verbal learning and memory in children and adolescents through assessing their ability to recall meaningful information from day to day. We examined three measures: List A total Trials 1e5 (total number of words recalled across five trials), List B (total number of words recalled from the second interference list), and Long Delay Free Recall (total number of words freely recalled after a 20-min delay). 2.3. Statistical analysis Descriptive statistics were presented as mean ± standard deviation, median and interquartile ranges (IQR) or percentages, as appropriate. We compared the demographic and clinical characteristics between children with and those without OSAS using Chisquare or Fisher's exact test for qualitative variables and Student's t or ManneWhitney U tests for quantitative variables, as appropriate. For children who underwent neuropsychological evaluation, we compared neuropsychological outcomes based on OSAS status, gender, obesity, and history of seizure using Student's t or MannWhitney U tests. Differences based on the affected artery size and arterial territory were conducted using one-way Analysis of Variance (ANOVA) or Kruskal-Wallis, as appropriate. For the arterial territory, only differences in intellectual ability were conducted due to the small sample sizes obtained with the remaining neuropsychological outcomes. We used Pearson correlation analysis to investigate the relationship between neuropsychological outcomes and age at stroke onset, age at PSQ assessment, time since stroke, and total PSOM scores. We conducted exploratory analysis of index scores of intellectual outcomes that correlated significantly with more than one predictor using stepwise multiple linear regression. We used the Akaike's information criterion corrected for small-sample bias to select the most important predictors of the outcomes. All relevant assumptions for the regression analyses were examined. P-values <0.05 were considered to be statistically significant. Statistical analyses were conducted using SAS University Edition (SAS Institute, Inc, Cary, NC). 3. Results A total of 260 children were screened, 102 of whom were eligible to participate and were assessed for the presence of OSAS. Of the 158 excluded children: 50 children were <2 years of age at the time of assessment and 108 did not have AIS diagnosis. The median age of children at the time of inclusion was 9 (IQR: 6e14) years with almost equal proportions of males and females (Table 1). The median age at stroke onset was 2 years with a neonatal stroke incidence of 22%. Eleven children (11%) were overweight and 19 (18.6%) were obese. One-third of participants were prescribed a concomitant medication that had effects on sleep architecture. Concomitant medications included antiepileptics (17.4%), antihypertensives (8.7%), and central nervous system stimulants (4.4%). 3.1. Prevalence of OSAS: clinical and demographic determinants The prevalence of OSAS in our study cohort was 25.5% (N ¼ 26), which was significantly higher than the normative prevalence rate (5%) reported by Archbold et al. (p < 0.001).4 Differences in demographic and clinical characteristics between children with OSAS and those without OSAS are presented in Table 1. At the time of stroke onset, patients with OSAS were more likely to have anterior and posterior circulation territory infarcts compared to children without OSAS (37.5% vs 9.5%, p ¼ 0.021). No differences were found in age at stroke onset, gender, artery size, infarct location, presence
3
of fever, respiratory difficulties, and seizure at the time of stroke onset. At the time of sleep study assessment, no differences in age, time since stroke, or obesity/overweight prevalence were found between children with and without OSAS. On the other hand, children with OSAS had significantly higher median PSOM scores (2 [IQR: 0e2] vs 1 [IQR: 1e3.5], p ¼ 0.01) and were more likely to be prescribed concomitant medications that affect sleep architecture (50% vs 22.4%, p ¼ 0.007) (Table 1). Specifically, children with AIS and OSAS were more likely to have received medications that could potentially disrupt sleep architecture (42.3% vs 17.1%, p ¼ 0.01) (Table 1). 3.2. Effects of OSAS on neuropsychological outcomes Forty-three children were assessed for their intellectual ability. AIS patients with OSAS had lower scores on all indices but differences were statistically significant for FSIQ and WMI at 73.5 ± 18.2 vs 88.4 ± 19.5 (p ¼ 0.026) and 78.2 ± 16.7 vs 94.7 ± 20.2 (p ¼ 0.015), respectively. A trend toward statistical significance was seen with verbal comprehension index (79.1 ± 16.3 in OSAS-positive vs 90.8 ± 19.6 in OSAS-negative, p ¼ 0.06) (Fig. 1). ABAS-2 parent and teacher forms were evaluated in 26 and 18 children, respectively; children with OSAS performed lower on all composite scales with differences reaching statistical significance for the conceptual and practical composite scores of the parent form (71 ± 13.3 vs 94.3 ± 19.5, p ¼ 0.005 and 71.3 ± 15 vs 84.8 ± 19.3, p ¼ 0.04, respectively) and for the general adaptive composite scores for both the parent and teacher forms (Table 2). BRIEF parent and teacher forms were administered in 32 and 22 children with AIS, respectively; children with OSAS had more pronounced deficits on all executive summary scores of both the parent and teacher forms. With respect to CVLT-C assessment which was conducted in 23 children, those with OSAS scored significantly lower on the T1-5 t score only (37.9 ± 13 vs 47.1 ± 7.4, p ¼ 0.04). 3.3. Effects of other demographic and clinical characteristics on neuropsychological outcomes Comparisons of neuropsychological outcomes based on gender, obesity, arterial size and territory, and history of seizure are summarized in Supplementary Table 1. No differences were found in any of the neuropsychological outcomes between males and females, whereas children classified as overweight/obese had significantly lower scores on the WMI index of the intellectual ability and on the different measures of the CVLT-C compared to those with normal BMI scores. We did not find any differences in neuropsychological outcomes based on the size of the affected artery or history of seizure. However, children with AIS in which both the anterior and posterior circulation were affected had significantly lower scores on the different indices of intellectual ability. As shown in Supplementary Table 2, there were no significant correlations between the age at stroke onset and the different neuropsychological outcomes. Significant negative correlations were demonstrated between age at PSQ assessment and WMI (Pearson's r ¼ 0.36, p ¼ 0.021) and time since stroke onset and PRI (Pearson's r ¼ 0.36, p ¼ 0.03). We also found significant negative correlations between the total PSOM scores at the time of sleep assessment with most of the neuropsychological outcomes. 3.4. Predictors of impaired intellectual function We fitted three stepwise multiple linear regression models to assess the impact of OSAS, obesity/overweight, severity of neurologic impairment (using PSOM) and arterial territory on FSIQ, VCI and WMI index scores (Table 3).
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
4
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Table 1 Demographic and clinical characteristics in the overall sample and among children with and without OSAS. p<0.05: statistically significant (appearing in bold).
Demographic, clinical and radiographic characteristics at stroke onset Age at stroke, years Male, n (%) Age group at stroke, n (%) Childhood Neonatal Fever, n (%) Respiratory difficulties, n (%) Seizure, n (%) Artery size, n (%) Small Large None Arterial territory, n (%) Anterior circulation Posterior circulation Both None Infarct location, n (%) Infratentorial Supratentorial Both None Demographic and clinical characteristics at the time of PSQ assessment Age at PSQ assessment, years Time lag between stroke onset and PSQ assessment, years Total PSOM score Normal/mild neurologic outcome, n (%) Moderate/severe neurologic outcome, n (%) BMI, n (%) Overweight Obese Use of concomitant medications affecting sleep architecture, n (%) Sleep aida Sleep disrupta
Total sample N ¼ 102
OSAS-negative N ¼ 76
OSAS-positive N ¼ 26
P-value
2 (1e6) 56/101 (55.5)
2 (1e6) 45 (60)
2 (0.02e6) 11 (42.3)
0.986 0.118 0.828
80 (78.4) 22 (21.6) 3/98 (3.1) 7/98 (7.1) 34/102 (33.3)
60 (79) 16 (21) 1 (1.4) 4 (5.4) 24 (31.6)
20 (76.9) 6 (23.1) 2 (8.3) 3 (12.5) 10 (38.5)
15/98 (15.3) 43/98 (43.9) 40/98 (40.8)
12 (16.2) 30 (40.5) 32 (43.2)
3 (12.5) 13 (54.2) 8 (33.3)
34/98 (34.7) 9/98 (9.2) 16/98 (16.3) 39/98 (39.8)
28 (37.8) 8 (10.8) 7 (9.5) 31 (41.9)
6 1 9 8
3/98 (3.1) 50/98 (51) 5/98 (5.1) 40/98 (40.8)
2 (2.7) 39 (52.7) 2 (2.7) 31 (41.9)
1 (4.2) 11 (45.8) 3 (12.5) 9 (37.5)
9 (6e14) 5 (3e8) 1 (0e2.5) 76 (74.5) 26 (25.5)
9 (6e14.5) 4 (3e9) 1 (0e2) 60 (79) 16 (21)
9 (6e14) 5 (3e8) 2 (1e3.5) 16 (61.5) 10 (38.5)
0.611 0.847 0.010 0.078
11/102 (10.8) 19/102 (18.6) 30/102 (29.4) 8/102 (7.8) 24/102 (23.5)
7 (9.2) 14 (18.4) 17 (22.4) 5 (6.6) 13 (17.1)
4 (15.4) 5 (19.2) 13 (50) 3 (11.5) 11 (42.3)
0.465 1 0.007 0.417 0.01
0.147 0.357 0.631 0.505
0.021 (25) (4.2) (37.5) (33.3) 0.261
Continuous variables are expressed as median (25e75 Interquartile range). AIS: arterial ischemic stroke; BMI: body mass index; PSOM: pediatric stroke outcome measure; PSQ: pediatric stroke questionnaire; OSAS: obstructive sleep apnea syndrome. a Two children had concomitant prescription of sleep aid and sleep disrupt medications.
Regression analysis revealed that PSQ score, obesity and arterial territory were the strongest predictors of FSIQ accounting for 38% of its total variance, F (5, 36) ¼ 5.43, p ¼ 0.001 and of the WMI accounting for 44.9% of its total variance, F (5, 37) ¼ 7.04, p < 0.001. At the level of VCI scores, moderate/severe neurologic disability and PSQ scores were the only significant predictors of poor verbal and comprehension explaining a total of 28.9% of its variance, F (2, 38) ¼ 8.7, p < 0.001. Of interest, the contribution of the total PSQ to the variance in FSIQ and WMI scores remained statistically significant when accounting for other predictors. 4. Discussion To our knowledge, this is the first study to investigate the prevalence of OSAS in children with AIS and its association with neuropsychological outcomes. In our current study, we found significantly elevated prevalence rates of OSAS in children with AIS compared with published rates in healthy children. The presence of OSAS correlated significantly with poor neurocognitive and adaptive function. OSAS represents a continuum of breathing abnormalities during sleep that affect both adults and children.23 In children with AIS, the prevalence of OSAS (25.5%) was significantly higher than the prevalence rates described in the scientific literature for the general pediatric population. However, it is comparable to prevalence rates
of OSAS documented in other disease conditions such as hypertension and non-infectious respiratory conditions.4,24 A reciprocal relationship is thought to exist between OSAS and general health in childhood.25 While OSAS is known for its detrimental health outcomes, the risk of OSAS occurrence in childhood increases remarkably in the presence of certain acute or chronic disease conditions.6 Hence, OSAS can be the consequence of underlying disease-related mechanisms or medication-related adverse reaction or the cause of disease conditions.6,26e28 Specifically, multiple studies demonstrated the presence of a bidirectional relationship between OSAS as a risk factor for stroke and as a potential consequence of stroke.9,28e30 In a meta-analysis of adult stroke survivors, Johnson and Johnson30 demonstrated that sleep apnea is significantly elevated reaching 72% in patients with ischemic or hemorrhagic stroke and TIA. The development of respiratory disturbances following stroke is highly dependent on the affected brain region.31e35 Supra or infratentorial stroke lesions favor the development of obstructive sleep apnea by inducing disturbed coordination of upper airways, intercostal and diaphragmatic muscles.28 Damage to the brainstem respiratory control following medullary brain lesions leads to decreased ventilatory sensitivity to carbon dioxide and increased predisposition to sleep apnea.36 In addition, it has been postulated that stroke may disrupt breathing through the disturbance of central rhythm generation, interruption of descending respiratory pathways or by causing bulbar weakness/aspiration.37 Other
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
5
Fig. 1. Differences in intellectual ability between children with and without OSAS. *p < 0.05. FSIQ: full scale IQ; OSAS: obstructive sleep apnea syndrome; PRI: Perceptual Reasoning Index; PSI: processing speed index; WMI: working memory index; VCI: verbal comprehension index.
predisposing factors include the incidence of respiratory infections, decreased voluntary chest movements on the paralyzed side, prolonged supine position, and increased sleep fragmentation due to stroke complications.28 In our current study, although statistical significance was not reached, children with stroke who were OSASpositive were more likely to have infarcts in both supra and infratentorial regions. These findings were comparable to those reported in adults by Kaneko et al.38 Furthermore, children with stroke and OSAS-positive were more likely to have their stroke affecting both anterior and posterior circulations. A recently published nationwide cohort study in children and adolescents showed that the risk of major adverse cardiovascular events is doubled in the presence of obstructive sleep apnea.27 Similarly, a significant association between OSAS and cerebrovascular events including stroke is found in the adult population. In their cross-sectional study, Shahar et al. reported significantly elevated relative odds for disordered apnea-hypopnea index (1.58;
95% CI: 1.02e2.46) in stroke patients.39 Causal association between obstructive sleep apnea and stroke in adults was confirmed in the large cohort study conducted by Yaggi et al. in which a two-fold increase in the risk of stroke in patients with obstructive sleep apnea was found.9 Several mechanisms have been postulated to be responsible for the increased risk of stroke in patients with OSAS. Acute apneic episodes are associated with hemodynamic changes that cause significant decline in cerebral blood flow due to reduction in cardiac output predisposing subjects to cerebrovascular accidents.40 OSAS has also been shown to be associated with systemic hypertension and endothelial dysfunction following sympathetic nervous system activation in addition to increased platelet aggregability, and paradoxical embolization.41 In children with stroke, there is mounting evidence which points toward the potential involvement of hypertension, arteriosclerosis and endothelial dysfunction, in the underlying pathogenesis of stroke.42e44 However, the potential contribution of OSAS to these underlying
Table 2 Differences in neuropsychological function between children with and without OSAS. p<0.05: statistically significant (appearing in bold).
ABAS-2 parent form composite scores Conceptual composite (n ¼ 26) Social composite (n ¼ 25) Practical composite (n ¼ 25) General adaptive composite (n ¼ 25) ABAS-2 teacher form composite scores Conceptual composite (n ¼ 18) Social composite (n ¼ 18) Practical composite (n ¼ 17) General adaptive composite (n ¼ 17) BRIEF (T scores) e parent form BRI (n ¼ 32) MCI (n ¼ 31) GEC (n ¼ 33) BRIEF (T scores) e teacher form BRI (n ¼ 22) MCI (n ¼ 22) GEC (n ¼ 22) CVLT-C T1-5 t score (n ¼ 23) Long Del. Free Recall Z (n ¼ 23) List B Z (n ¼ 23) a
Total sample
OSAS-negative
OSAS-positive
N ¼ 26 87.1 ± 20.7 90.6 ± 19.6 80.5 ± 18.9 83.3 ± 20.4 N ¼ 18 88.3 ± 28.3 88.5 ± 26.7 88.6 ± 21.4 90.5 ± 20.6 N ¼ 34 59.7 ± 11.7 59.8 ± 11 59.5 ± 11.9 N ¼ 22 58.3 ± 14.9 61.7 ± 12.5 61.1 ± 13.1 N ¼ 23 43.9 ± 10.4 0.66 ± 1.3 0.59 ± 0.9
N ¼ 18 94.3 ± 19.5 93.5 ± 21.2 84.8 ± 19.3 89.3 ± 20.6 N ¼ 13 92.4 ± 29.6 90.7 ± 30.2 94.7 ± 16.8 96.9 ± 17.1 N ¼ 21 55.6 ± 11.4 55.7 ± 9.9 55 ± 10.5 N ¼ 13 51.3 ± 7.7 57.1 ± 13.7 55 ± 11 N ¼ 15 47.1 ± 7.4 0.3 ± 1.1 0.6 ± 0.8
N¼8 71 ± 13.3 84.4 ± 15 71.3 ± 15 70.5 ± 13.5 N¼5 77.8 ± 24.3 82.8 ± 15.7 74 ± 26 75.2 ± 21.8 N ¼ 13 65.5 ± 10 66.2 ± 9.8 67.3 ± 10.3 N¼9 68.5 ± 17.2 68.4 ± 6.8 69.9 ± 10.9 N¼8 37.9 ± 13 1.3 ± 1.5 0.6 ± 1.3
P-value 0.005 0.285 0.035a 0.028 0.183a 0.590 0.068 0.044 0.008 0.008 0.003 0.001 0.033 0.005 0.039 0.106 0.891
ManneWhitney U test.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
6
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Table 3 Stepwise multiple linear regression modelsa for predictors of intellectual ability index scores. Slope (B) FSIQ Constant Total PSQ score Overweight/obesity Arterial territory Ref ¼ “None” Anterior Posterior Both VCI Constant Total PSQ score Moderate/Severe neurologic impairmentb Ref ¼ “Normal/Mild” WMI Constant Total PSQ score Overweight/obesity Arterial territory Ref ¼ “None” Anterior Posterior Both
95% CI
Adjusted R2
t
P-value
0.38 92.3 45.9 16.6
81.1, 103.5 83.9, 8.1 29.9, 3.3
16.8 2.48 2.55
<0.001 0.019 0.016
14.5 19.9 10.7
2.1, 26.8 5.1, 44.9 26.5, 5.2
2.4 1.6 1.4
0.023 0.115 0.178
101.2 32.7 17.5
91.3, 111.1 70.8, 5.3 28.8, 6.3
20.8 1.75 3.2
<0.001 0.089 0.0031
97.1 43.2 21.2
86.6, 107.6 79.5, 6.8 34.1, 8.2
18.9 2.42 3.33
<0.001 0.022 0.002
19.8 20.6 8
7.9, 31.8 3.73, 44.9 23.4, 7.4
3.4 1.72 1.1
0.002 0.094 0.298
0.289
0.44
CI: confidence interval; FSIQ: full scale IQ; PSQ: pediatric stroke questionnaire; WMI: working memory index; VCI: verbal comprehension index. a For each of the models, total PSQ scores, overweight/obesity status, arterial territory, and severity of neurologic important were incorporated as predictor variables. b Neurologic impairment severity was classified based on the Pediatric Stroke Outcome Measure subscale scores.
processes requires further investigation. Children with AIS and OSAS had greater neurologic deficits at the time of sleep assessment as indicated by the significantly higher PSOM scores. This is in keeping with the adult literature in which OSAS in patients with stroke was shown to be associated with poorer functional outcomes.31,45 This could also explain the higher frequency of prescription drugs used among these children that are potentially linked to the disruption of sleep architecture. However, the specific effects of the concomitant medications on the sleep cycle in our study cannot be elucidated using the PSQ. Improved understanding of this requires larger prospective studies with objective polysomnographic evaluation. Neuropsychological impairments secondary to pediatric stroke have been documented in several short and long-term studies that reported reductions in various domains including intellectual function, attention, verbal learning and memory, visual-spatial processing, processing speed, and executive function.46 Demographic and clinical determinants including age at stroke, time since stroke, laterality, and lesion characteristics are wellestablished risk factors for impaired neuropsychological function in children with stroke.47 In addition to these factors, our current study attempted to assess the potential role for OSAS as a contributing factor to neuropsychological impairments following pediatric AIS. Pediatric OSAS can negatively influence children's development, resulting in significant cognitive and behavioral deficits.48,49 In our study, the presence of OSAS was associated with significantly worse performance across the different neuropsychological domains assessed. Full scale IQ and working memory were the most affected, though non-significant trends were observed for the other scales from the intellectual battery. OSAS in children is independently linked with adverse neurocognition and increased severity of OSAS was associated with worse neurocognitive performance.50 Adenoidectomy and/or tonsillectomy are typically the first line of therapy for children with sleep apnea who have adenoidal or tonsillar hypertrophy. These surgical interventions are associated with improvements in neurobehavioral and cognitive performance especially where there is complete resolution of sleep apnea.51 In children with persistent OSA post-
adenotonsillectomy, continuous positive airway pressure (CPAP) is typically prescribed. In one study evaluating the effects of CPAP in 52 children with sleep apnea, significant improvements in neurobehavioral parameters were found after 3 months of treatment despite the fact that the average use of CPAP was approximately 3 h per night.52 However, it must be considered that the effects of OSAS on neuropsychological function in children with stroke may not be independent of stroke-related factors. Interestingly, in the randomized clinical trial conducted by Ryan et al.53 in adult stroke survivors with obstructive sleep apnea, CPAP therapy led to improved functional and motor outcomes but not neurocognitive outcomes. Since these studies may not necessarily be extrapolated to children with OSAS in the absence of stroke, future studies should focus on evaluating neurocognition, behavior and functional outcomes in children with stroke pre and post therapeutic interventions for OSAS. Such information will facilitate knowledge for advanced therapeutics to improve outcomes following stroke in children. Our findings of abnormal behavioral and adaptive functioning in children with stroke and OSAS as demonstrated using ABAS-2 composite scores are comparable to results reported in previous studies in which significantly increased risk of hyperactivity, lower social competency, diminished adaptive skills, and aggressive and inattentive behavior in children with OSAS were found.54,55 A plausible negative association between OSAS and executive function was also evident in our study, which is consistent with findings from a previous study showing significant association between sleep-disordered breathing and executive function in children.56 The exact mechanism through which OSAS induces cognitive and adaptive impairments remains unclear. It has been hypothesized that sleep fragmentation, arousals and intermittent hypoxemia interfere with restorative sleep processes and cellular homeostasis of the prefrontal cortex, inducing systemic inflammatory and vascular changes in the brain, as observed in children with OSAS.57e59 The use of a subjective sleep measure represents a limitation in our study. Nevertheless, the PSQ has displayed adequate validity
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
and reliability as a screen for polysomnographically defined OSAS.12 In addition, PSQ has been shown to be of important utility in epidemiological studies as a screening tool for OSAS and it has been shown to correctly classify 86.4% of subjects with sleep related breathing disorders.60 Assuming misclassification rates of 14%, prevalence rates of OSAS in pediatric stroke remain significantly elevated at 22%. The absence of clinical assessment for other known risk factors of OSAS, such as adenotonsillar hypertrophy is a limitation in our current study. Conducting the correlation analyses between OSAS and neuropsychological function in subsets of the total sample could have increased the potential of selection bias. Finally, the lag time between sleep and neuropsychological testing is another drawback in the design of our study; however, despite the tendency for OSAS to improve with time in some children, significant negative correlations between OSAS and neuropsychological outcomes were obtained. Our study highlights the relatively increased prevalence of OSAS in children with AIS and its association with poor neurocognitive and adaptive function. Poor neurological outcomes, infarcts affecting both the anterior and posterior circulation, and increased use of medications affecting sleep architecture correlated significantly with OSAS in children with AIS. Our current study highlights the importance of regular screening for OSAS among children with stroke. We suggest consideration of referral for polysomnography and respiratory consultation for assessment and confirmation of diagnosis if a validated screening threshold is reached, i.e. total PSQ scores0.33. Implementation of this approach is likely to lead to the identification of children with an added modifiable risk of poor neuropsychological outcome. The beneficial effects of therapeutic interventions targeting OSAS on the neurological and neuropsychological outcomes warrant further investigation. Declaration of Competing Interest The authors have indicated they have no potential conflicts of interest to disclose. Appendix A. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.ejpn.2019.11.006. Funding source All phases of this study were supported by The Auxilium Foundation. ABAS-2: Adaptive Behavior Assessment System, 2nd edition; BRI: Behavioral Regulation Index; BRIEF: Behavior Rating Inventory Executive Function; CVLT-C: California Verbal Learning Test for Children; FSIQ: full scale IQ; GEC: Global Executive Composite; Long Del. Free Recall: Long Delay Free Recall; MCI: Metacognition Index; PRI: Perceptual Reasoning Index; OSAS: obstructive sleep apnea syndrome; PSI: processing speed index; WMI: working memory index; VCI: verbal comprehension index. References 1 V.K. Chattu, S.M. Sakhamuri, R. Kumar, et al., Insufficient Sleep Syndrome: is it time to classify it as a major noncommunicable disease? Sleep Sci 11 (2018) 56e64. 2 V. Kapur, K.P. Strohl, S. Redline, et al., Underdiagnosis of sleep apnea syndrome in U.S. communities, Sleep Breath 6 (2002) 49e54. 3 M. Anstead, B. Phillips, The spectrum of sleep-disordered breathing, Respir Care Clin N Am 5 (1999) 363e377 [viii]. 4 K.H. Archbold, K.J. Pituch, P. Panahi, R.D. Chervin, Symptoms of sleep disturbances among children at two general pediatric clinics, J Pediatr 140 (2002) 97e102.
7
5 K.A. Bonuck, R.D. Chervin, T.J. Cole, et al., Prevalence and persistence of sleep disordered breathing symptoms in young children: a 6-year population-based cohort study, Sleep 34 (2011) 875e884. 6 A.S. Lewandowski, T.M. Ward, T.M. Palermo, Sleep problems in children and adolescents with common medical conditions, Pediatr Clin N Am 58 (2011) 699e713. 7 R.D. Chervin, K.H. Archbold, J.E. Dillon, et al., Inattention, hyperactivity, and symptoms of sleep-disordered breathing, Pediatrics 109 (2002) 449e456. 8 N. Glozier, T.J. Moullaali, B. Sivertsen, et al., The course and impact of poststroke insomnia in stroke survivors aged 18 to 65 Years: results from the psychosocial outcomes in StrokE (POISE) study, Cerebrovasc Dis Extra 7 (2017) 9e20. 9 H.K. Yaggi, J. Concato, W.N. Kernan, et al., Obstructive sleep apnea as a risk factor for stroke and death, N Engl J Med 353 (2005) 2034e2041. 10 M. Studer, E. Boltshauser, A. Capone Mori, et al., Factors affecting cognitive outcome in early pediatric stroke, Neurology 82 (2014) 784e792. 11 R. Westmacott, R. Askalan, D. MacGregor, P. Anderson, G. Deveber, Cognitive outcome following unilateral arterial ischaemic stroke in childhood: effects of age at stroke and lesion location, Dev Med Child Neurol 52 (2010) 386e393. 12 R.D. Chervin, K. Hedger, J.E. Dillon, K.J. Pituch, Pediatric sleep questionnaire (PSQ): validity and reliability of scales for sleep-disordered breathing, snoring, sleepiness, and behavioral problems, Sleep Med 1 (2000) 21e32. 13 G.A. deVeber, A. Kirton, F.A. Booth, et al., Epidemiology and outcomes of arterial ischemic stroke in children: the Canadian pediatric ischemic stroke registry, Pediatr Neurol 69 (2017) 58e70. 14 M. Slim, N. Dlamini, C. Fox, et al., Outcome severity assessment with the pediatric stroke outcome measure (PSOM): validation of a novel classification system. 47th Annual Meeting of the Child Neurology Society, Ann Neurol. 84 (2018) S281eS428. 15 WHO Multicentre Growth Reference Study Group, WHO Child Growth Standards: length/height-for-age, weight-for-age, weight-for-length, weight-forheight and body mass index-for-age: methods and development, World Health Organization, Geneva, 2006. 16 D. Wechsler, Wechsler intelligence scale for children, 5th ed., Pearson Education, Inc., & Psychological Corporation., San Antonio, TX, 2014. 17 D. Wechsler, Wechsler intelligence scale for children - fourth edition technical and interpretive manual, The Psychological Corporation, San Antonio, TX, 2003. 18 D. Wechsler, Wechsler adult intelligence scale, 4th ed., Pearson, San Antonio, TX, 2008. 19 D. Wechsler, Wechsler Preschool and primary scale of intelligence, 4th ed., NCS Pearson, San Antonio, TX, 2012. 20 P.L. Harrison, T. Oakland, ABAS II : adaptive behavior assessment system, Western Psychological Services, Los Angeles, Calif., 2008. 21 G.A. Gioia, P.K. Isquith, S.C. Guy, L. Kenworthy, TEST REVIEW behavior rating inventory of executive function, Child Neuropsychol 6 (2000) 235e238. 22 D.C. Delis, CVLT-C : California verbal learning test, Psychological Corporation, Harcourt Brace Corporation, San Antonio, TX, 1994. 23 R. Downey 3rd, R.M. Perkin, J. MacQuarrie, Upper airway resistance syndrome: sick, symptomatic but underrecognized, Sleep 16 (1993) 620e623. 24 M.B. Lande, S.R. Hooper, D.L. Batisky, et al., Sleep disordered breathing as measured by SRBD-PSQ and neurocognition in children with hypertension, Am J Hypertens 28 (2015) 552e558. 25 M.R. Irwin, Why sleep is important for health: a psychoneuroimmunology perspective, Annu Rev Psychol 66 (2015) 143e172. 26 R. Arens, C.L. Marcus, Pathophysiology of upper airway obstruction: a developmental perspective, Sleep 27 (2004) 997e1019. 27 N.S. Tzeng, C.H. Chung, H.A. Chang, et al., Obstructive sleep apnea in children and adolescents and the risk of major adverse cardiovascular events: a nationwide cohort study in Taiwan, J Clin Sleep Med 15 (2019) 275e283. 28 F. Alexiev, A.K. Brill, S.R. Ott, et al., Sleep-disordered breathing and stroke: chicken or egg? J Thorac Dis 10 (2018) S4244eS4252. 29 S. Jehan, M. Farag, F. Zizi, et al., Obstructive sleep apnea and stroke, Sleep Med Disord 2 (2018) 120e125. 30 K.G. Johnson, D.C. Johnson, Frequency of sleep apnea in stroke and TIA patients: a meta-analysis, J Clin Sleep Med 6 (2010) 131e137. 31 D.C. Good, J.Q. Henkle, D. Gelber, J. Welsh, S. Verhulst, Sleep-disordered breathing and poor functional outcome after stroke, Stroke 27 (1996) 252e259. 32 M. Bonnin-Vilaplana, A. Arboix, O. Parra, et al., Sleep-related breathing disorders in acute lacunar stroke, J Neurol 256 (2009) 2036e2042. 33 D.L. Brown, M. McDermott, A. Mowla, et al., Brainstem infarction and sleepdisordered breathing in the BASIC sleep apnea study, Sleep Med 15 (2014) 887e891. 34 S.M. Stahl, H.K. Yaggi, S. Taylor, et al., Infarct location and sleep apnea: evaluating the potential association in acute ischemic stroke, Sleep Med 16 (2015) 1198e1203. 35 A.L. Fisse, A. Kemmling, A. Teuber, et al., The association of lesion location and sleep related breathing disorder in patients with acute ischemic stroke, PLoS One 12 (2017), e0171243. 36 M.J. Morrell, P. Heywood, S.H. Moosavi, A. Guz, J. Stevens, Unilateral focal lesions in the rostrolateral medulla influence chemosensitivity and breathing measured during wakefulness, sleep, and exercise, J Neurol Neurosurg Psychiatry 67 (1999) 637e645. 37 R.S. Howard, A.G. Rudd, C.D. Wolfe, A.J. Williams, Pathophysiological and clinical aspects of breathing after stroke, Postgrad Med J 77 (2001) 700e702. 38 Y. Kaneko, V.E. Hajek, V. Zivanovic, J. Raboud, T.D. Bradley, Relationship of sleep apnea to functional capacity and length of hospitalization following stroke,
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006
8
M. Slim et al. / European Journal of Paediatric Neurology xxx (xxxx) xxx
Sleep 26 (2003) 293e297. 39 E. Shahar, C.W. Whitney, S. Redline, et al., Sleep-disordered breathing and cardiovascular disease: cross-sectional results of the sleep heart health study, Am J Respir Crit Care Med 163 (2001) 19e25. 40 N. Netzer, P. Werner, I. Jochums, M. Lehmann, K.P. Strohl, Blood flow of the middle cerebral artery with sleep-disordered breathing: correlation with obstructive hypopneas, Stroke 29 (1998) 87e93. 41 R.S. Leung, T.D. Bradley, Sleep apnea and cardiovascular disease, Am J Respir Crit Care Med 164 (2001) 2147e2165. 42 J.C. Kupferman, D.I. Zafeiriou, M.B. Lande, F.J. Kirkham, S.G. Pavlakis, Stroke and hypertension in children and adolescents, J Child Neurol 32 (2017) 408e417. 43 S. Sultan, M. Dowling, A. Kirton, et al., Dyslipidemia in children with arterial ischemic stroke: prevalence and risk factors, Pediatr Neurol 78 (2018) 46e54. 44 D. Eleftheriou, V. Ganesan, Y. Hong, N.J. Klein, P.A. Brogan, Endothelial repair in childhood arterial ischaemic stroke with cerebral arteriopathy, Cerebrovasc Dis Extra 5 (2015) 68e74. 45 S. Yan-fang, W. Yu-ping, Sleep-disordered breathing: impact on functional outcome of ischemic stroke patients, Sleep Med 10 (2009) 717e719. 46 M. Greenham, V. Anderson, A. Cooper, et al., Early predictors of psychosocial functioning 5 years after paediatric stroke, Dev Med Child Neurol 59 (2017) 1034e1041. 47 A. Fuentes, A. Deotto, M. Desrocher, G. deVeber, R. Westmacott, Determinants of cognitive outcomes of perinatal and childhood stroke: a review, Child Neuropsychol 22 (2016) 1e38. 48 D.W. Beebe, Cognitive, behavioral, and functional consequences of inadequate sleep in children and adolescents, Pediatr Clin N Am 58 (2011) 649e665. 49 B. Galland, K. Spruyt, P. Dawes, et al., Sleep disordered breathing and academic performance: a meta-analysis, Pediatrics 136 (2015) e934e946. 50 S.J. Hunter, D. Gozal, D.L. Smith, et al., Effect of sleep-disordered breathing severity on cognitive performance measures in a large community cohort of
young school-aged children, Am J Respir Crit Care Med 194 (2016) 739e747. 51 C.L. Marcus, R.H. Moore, C.L. Rosen, et al., A randomized trial of adenotonsillectomy for childhood sleep apnea, N Engl J Med 368 (2013) 2366e2376. 52 C.L. Marcus, J. Radcliffe, S. Konstantinopoulou, et al., Effects of positive airway pressure therapy on neurobehavioral outcomes in children with obstructive sleep apnea, Am J Respir Crit Care Med 185 (2012) 998e1003. 53 C.M. Ryan, M. Bayley, R. Green, B.J. Murray, T.D. Bradley, Influence of continuous positive airway pressure on outcomes of rehabilitation in stroke patients with obstructive sleep apnea, Stroke 42 (2011) 1062e1067. 54 D.J. Gottlieb, R.M. Vezina, C. Chase, et al., Symptoms of sleep-disordered breathing in 5-year-old children are associated with sleepiness and problem behaviors, Pediatrics 112 (2003) 870e877. 55 M.M. Perfect, K. Archbold, J.L. Goodwin, D. Levine-Donnerstein, S.F. Quan, Risk of behavioral and adaptive functioning difficulties in youth with previous and current sleep disordered breathing, Sleep 36 (2013) 517e525B. 56 J.J. Mietchen, D.P. Bennett, T. Huff, D.W. Hedges, S.D. Gale, Executive function in pediatric sleep-disordered breathing: a meta-analysis, J Int Neuropsychol Soc 22 (2016) 839e850. 57 I. Trosman, S.J. Trosman, Cognitive and behavioral consequences of sleep disordered breathing in children, Med Sci 5 (2017). 58 C.S. Tam, M. Wong, R. McBain, S. Bailey, K.A. Waters, Inflammatory measures in children with obstructive sleep apnoea, J Paediatr Child Health 42 (2006) 277e282. 59 D. Gozal, L.D. Serpero, O. Sans Capdevila, L. Kheirandish-Gozal, Systemic inflammation in non-obese children with obstructive sleep apnea, Sleep Med 9 (2008) 254e259. 60 K. Spruyt, D. Gozal, Pediatric sleep questionnaires as diagnostic or epidemiological tools: a review of currently available instruments, Sleep Med Rev 15 (2011) 19e32.
Please cite this article as: M. Slim et al., Obstructive sleep apnea syndrome and neuropsychological function in pediatric stroke, European Journal of Paediatric Neurology, https://doi.org/10.1016/j.ejpn.2019.11.006