Abstract

METHOD

RESULTS

Preliminary analyses

Means and standard deviations of cognitive function outcomes can be found in Table 1. Mean FSIQ was 96 (SD = 11.44) for cases and 102.83 (SD = 10.89) for sibling controls. Mean index scores ranged from 93.83 (PRI) to 101.94 (VCI) for cases and 99.39 (PRI) to 105.17 (VCI) for sibling controls.

Table 1

Cognitive Outcomes in Cases and Sibling Controls

	Case	Sibling	Sibling comparison		Norm comparison
	Mean (SD)	Mean (SD)	t	d	t	d
FSIQ	96.00 (11.44)	102.83 (10.89)	−2.66*	−.61	−1.48	−.35
VCI	101.94 (11.79)	105.17 (11.05)	−1.11	−.28	.70	.16
PRI	93.83 (11.39)	99.39 (11.90)	−1.85+	−.48	−2.30*	−.54
WMI	93.11 (14.91)	100.56 (14.40)	−1.96+	−.52	−1.96+	−.46
PSI	95.94 (10.33)	103.17 (11.06)	−2.53*	−.73	−1.67	−.39

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Notes: FSIQ = Full Scale IQ, VCI = Verbal Comprehension Index, PRI = Perceptual Reasoning Index, WMI = Working Memory Index, PSI = Processing Speed Index

^*p<.05

⁺p<.10

FSIQ scores for CHD cases ranged from 68 to 119 (see Figure 1). Two (11%) had FSIQs in the High Average range (110–119), 12 (67%) in the Average range (90–109), 3 (17%) in the Below Average range (80–89), and 1 (5%) in the Extremely Low range (60–69). FSIQ scores for sibling controls ranged from 86 to 121. One (5%) had a FSIQ in the Superior range (120–129), 5 (28%) in the High Average range (110–119), 10 (56%) in the Average range (90–109), and 2 (11%) in the Below Average range (80–89). Because of the variance in IQ data, we compared the cases and siblings both with and without the highest and lowest cases (i.e., univariate outliers), and the pattern of results was the same with effect sizes in the same range. Because none of the cases exceeded the Mahalanobis Distance cutoff, only findings from comparisons with the complete sample are reported below.

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Figure 1

Full Scale Intelligence Quotient (FSIQ) in Cases and Sibling Controls.

Means and standard deviations of attention outcomes can be found in Table 2. According to case self-reports, 18% of cases were within the borderline clinical range on the Attention Problems and AD/H scales as compared to 16% that would be expected in a normative sample (i.e., T > 65); T scores ranged from 50 to 66 for Attention Problems and 50 to 64 for AD/H problems. According to parent reports, 21% were within the borderline clinical range on the Attention Problems scale and 14% were within the borderline clinical range for the AD/H scale; T scores ranged from 50 to 67 for Attention Problems and 50 to 65 for AD/H problems. According to sibling control self-report, 5% of siblings were within the borderline clinical range on the Attention Problems and AD/H scales; T-scores ranged from 50 to 64 for Attention Problems and 50 to 60 for AD/H problems. Cases’ self-reports and mothers’ reports were significantly and positively correlated for Attention Problems (r = .53, p = .05) and AD/H Problems (r = .57, p = .05)

Table 2

Self-reports and Parent Reports of Attention

	Case self-report	Self-report to norm comparison	Mother report of case	Mother report to norm comparison	Sibling self-report	Case to sibling comparison
	M (SD)	t	M (SD)	t	M (SD)	t
Attention Problems	54.47 (4.96)	3.71**	55.14 (5.83)	3.30**	53.18 (3.81)	1.65
AD/H	55.82 (4.16)	5.78**	53.86 (4.79)	3.01*	53.24 (3.09)	2.62*

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Notes: Scores are age- and sex-adjusted T-scores from the ABCL, CBCL, YSR, and ASR

AD/H = Attention Deficit/Hyperactivity Scale

n = 15 mother report

^**p<.01,

^*p<.05,

⁺p<.10

Exploratory analyses indicated that age was not significantly related to measures of cognitive function or reports of attention. In addition, reports of attention were not significantly related to FSIQ or index scores for either cases or siblings.

DISCUSSION

Results indicated that adolescents and young adults with operated TOF and d-TGA CHD demonstrate relative weaknesses across a range of domains of neurocognitive function. Effect sizes ranged from small to large across indices, with medium to large effects for processing speed, perceptual reasoning, and working memory indices from WISC-IV and WAIS-IV, and reports of attention problems. These findings are especially important given that the study focused on adolescents and young adults with moderate, not severe single ventricle CHD. This group has been given less research attention, but represents a large and growing number of patients moving into adolescence and young adulthood (Sable et al., 2011; Warnes et al., 2008).

This study focused on the period of adolescence and young adulthood, and although this was a single time point study, our results suggest that differences in neurocognitive function observed in childhood may continue to be salient for many older CHD survivors. Indeed, the effect sizes in the current study were larger than in the Karsdorp et al., (2007) meta-analysis, which primarily focused on children in early and middle childhood. This could be an artifact of the relatively small sample size in the current study, or may suggest progressive worsening over time. However, the findings in the current study suggest that future research should more closely examine cognitive trajectories as children with CHD age. Adolescence and young adulthood represents a developmental period when continued medical monitoring is required (Sable et al., 2011), functioning may worsen, and additional surgical interventions may be required with associated risk for cerebrovascular events. These factors combined with our results suggest that patients’ cognitive functioning should also continue to be monitored.

The results from the current study are similar to the findings from previous research that focused on school-aged children with CHD, particularly those involving the PRI, which reflects visual-spatial skills (Bellinger & Newburger, 2003), and the WMI, which represents auditory working memory (Calderon et al., 2010). Although processing speed is understudied in this population, it appears that vulnerabilties in this domain could underlie poor performance in some tasks of executive function as suggested in a previous study (Calderon et al., 2014). Findings regarding attention problems expand upon previous studies by utilizing both patient- and parent-reported symptoms as well as using clinically relevant measures (Calderon et al., 2010; McCusker, Armstrong, Mullen, Doherty, & Casey, 2013). Verbal IQ appears to be unaffected in this sample, which is also consistent with previous studies of children with CHD (Karsdorp et al., 2007), although some studies have found deficits in higher-order language skills, such as use of complex language in social communication (Bellinger et al., 2003). Taken together, these findings suggest a cognitive profile with relative weaknesses in the areas of visual-spatial processing and cognitive proficiency and relative strength in verbal comprehension. A preserved VCI remains a provocative but unexplained phenomenon. It has clinical implications, as verbal comprehension as an area of relative strength can be leveraged for educational planning. Preserved verbal comprehension also suggests that differences in cognitive function may not be primarily due to poor educational environments during periods of hospitalization, but that other causal processes may underlie neurocognitive functioning in this population.

These findings are qualified by differences depending on the comparison group. When compared to established norms, patients demonstrated significantly lower performance on tasks of perceptual reasoning, and reduction in working memory that approached significance. Effect sizes ranged from small to medium. The findings are different when examining sibling controls. Notably, when compared to their healthy siblings, patients demonstrated significantly lower scores on full scale IQ and processing speed, and trending differences on perceptual reasoning and working memory, with medium to large effect sizes. Indeed, Figure 1 suggests a shift in the cases’ distribution of FSIQ scores to the left of the siblings’ distribution reflecting lower scores. This indicates that comparisons to national norms, which are the traditional benchmark, may underestimate differences in performance. Sibling controls are more closely matched demographically and take into account the expected cognitive potential given the family environment. The correlation between siblings on measures of cognitive function is typically in the moderate range (Deary, 2012; Nesbitt et al., 2012), and siblings provide an interesting comparison beyond a healthy control recruited from the community. For example, the current sample represented a higher level of parental education than regional demographics and siblings performed higher than established norms on several indices. However, it is also important to note that cases with CHD did not uniformly perform lower than their siblings. This suggests that the population as a whole may not demonstrate overall cognitive impairments or weaknesses. Instead, it appears that the majority of adolescents and young adults with CHD (72% of our sample) demonstrate relative weaknesses compared to siblings. This variability may have clinical implications for screening, intervention, and future research.

Comparisons to established norms provide useful information about how a patient is performing relative to typically developing, same-aged peers across the country and are compelling for educational purposes, disability classification, and determining eligibility for special education services. However, local controls such as siblings are compelling for individual patients and their families; functioning at a cognitive level below their own expectations or those of family members is relevant for individual concerns and impressions of patients and parents. Some previous CHD research has also characterized children as falling below expectation, although still within the average range (Bellinger & Newburger, 2010); this is similar to findings in other pediatric populations at risk for neurocognitive problems, such as children who have had strokes (Everts et al., 2008; O’Keefe et al., 2014). Expanding comparisons to sibling controls may help elucidate subtle cognitive weaknesses associated with CHD. Future studies should therefore consider utilizing comparisons with both normative samples and local controls.

A limitation of the current study was a small sample size, which impacted our ability to detect significant effects. Given this reduction in power, effect sizes (Cohen’s d) may better elucidate areas of significant impairment. Results above should also be interpreted with caution, given that correction for multiple tests reduced significant effects. As noted in the Methods, there was some inconsistency in the recruitment of sibling controls, as testing the nearest aged sibling was not always possible. And although the sample represented a range of income and parental education levels, it was relatively racially and ethnically homogenous which may limit generalizability of findings. In addition, future studies should continue to examine different domains of functioning in this population, such as social competence, and performance-based measures of attention. Future studies should also examine performance-based measures beyond the Wechsler intelligence tests and their indices. Although the current study examined working memory and processing speed, future research and clinical work with this population should include more extensive neuropsychological assessment.

The current study also had several strengths. First, it focused on an emerging but under-studied age group of adolescents and young adults with CHD. Another strength was the study population, as TOF and d-TGA comprise a large proportion of children born with CHD and therefore present a clinically important group (Hoffman & Kaplan, 2002). In addition, this study examined cognitive domains beyond full scale, verbal, and performance IQ to include other indices from the WISC-IV and WAIS-IV, such as working memory and processing speed, as well as reports of attention. Researchers need to continue to expand the domains of function assessed in order to better understand cognitive strengths and weaknesses in this population, which will help for clinical screening and educational planning as well as elucidation of potential causal mechanisms.

There is a growing body of evidence for neurocognitive vulnerabilities in CHD especially for children with severe defects such as single ventricles (e.g., HLHS; Karsdorp et al., 2007). Findings from the current sample, as well as from similar studies (Bellinger et al., 2003; Bellinger et al., 2011), suggest that there are also cognitive vulnerabilities for patients with moderate biventricular CHD (such as TOF and d-TGA). Previous studies have also found that these populations are at risk for poor outcomes beyond cognition, including school performance, restricted quality of life, and poor psychosocial functioning (see Marino et al., 2012). However, attempts to ameliorate cognitive problems via changes in surgical care (deep hypothermia with total circulatory arrest versus continuous low-flow bypass; Bellinger et al., 2011) and medical care (e.g. tight glycemic control after cardiac surgery; Agus et al., 2012) have been only moderately to minimally successful. Children with moderate and severe CHD will continue to require surgery early in life, and the cognitive risks of cyanosis, surgery, and anesthesia will always be significant. While a portion of this patient population may fall below expectation, many of those children and adolescents are not eligible for school services. Should future studies elucidate neuropsychological deficits on a range of measures of attention, working memory, and processing speed, intervention with cognitive remediation may hold promise for a subgroup of patients who display the greatest deficits. A recent review of interventions for children with a broad range of neurological disorders, acquired brain injuries, and neurodevelopmental disorders found positive treatment effects across studies, including large effects for attention, working memory, and memory tasks, and small effects for academic achievement and behavior rating scales (Robinson, Kaizar, Catroppa, Godfrey, & Yeates, 2014). Future research should examine the potential efficacy of cognitive remediation programs for children with CHD, as these children continue to demonstrate differences in cognitive and attentional functioning as they age into adolescence and young adulthood.

Acknowledgments

Footnotes

References