School outcomes in children registered in the studies for pediatric liver transplant (SPLIT) consortium†
See Editorial on Page 1013
Abstract
School performance is an important aspect of functional outcomes for pediatric liver transplant (LT) recipients. This longitudinal analysis conducted through the Studies of Pediatric Liver Transplantation (SPLIT) research consortium examines several indicators of school function in these patients. A total of 39 centers participated in data collection using a semistructured questionnaire designed specifically for this study. The survey queried school attendance, performance and educational outcomes including the need for special educational services. Participants included 823 of 1133 (73%) eligible patients, mean age 11.34 ± 3.84 years, 53% female, median age at LT 4.6 (range 0.05-17.8) years, and mean interval from transplant was 5.42 ± 2.79. Overall, 34% of patients were receiving special educational services and 20% had repeated a grade, with older participants more likely to have been held back (P = 0.0007). Missing more than 10 days of school per year was reported by one-third of the group, with this level of absence being more common in older participants (P = 0.0024) and children with shorter intervals from LT (P < 0.0001). Multivariate analysis revealed the following factors were associated with the need for special educational services; type of immunosuppression at 6 months post-LT, cyclosporine A (odds ratio [OR] = 1.8, confidence interval [CI] = 1.1-3.1), or other (OR = 4.9, 95% CI = 1.4-17.6) versus tacrolimus, symptomatic cytomegalovirus infection within 6 months of liver transplantation (OR = 3.1, CI = 1.6-6.1), and pretransplant special educational services (OR = 22.5, CI = 8.6-58.4). Liver Transpl 16:1041–1048, 2010. © 2010 AASLD.
Advances in medical and surgical techniques in liver transplantation have enabled long-term survival for pediatric recipients1 and allowed a shift in research toward examining the long-term functional outcomes of these children. One of the most important areas of function in children and adolescents is school performance, because it reflects their developmental status and prepares them for independent functioning in adulthood. Impaired cognitive development, below average school performance, and inconsistent attendance have all been documented in chronic childhood illness, including solid organ transplantation.2, 3 It has also been suggested that teachers tend to have lower expectations for academic achievement of the chronically ill child.4 It is likely that several mechanisms observed in the setting of chronic disease adversely affect cognitive function. Some of these include the impact of the illness and its treatment on the growing brain, particularly when disease onset is during infancy, and the impact of multiple hospitalizations on psychosocial development and behavior. Approximately half of the pediatric liver transplant population require the procedure during infancy, which is a particularly vulnerable period of neurological development. Children with liver failure frequently experience hepatic encephalopathy and advanced malnutrition. Transplantation reverses these medical problems, but exposes the patients to potentially neurotoxic medications and is associated with the need for prolonged hospitalization. The end result of these insults can be expressed as poor school performance and, hence, the potential requirement for special educational resources later in childhood.2
Previous single-center studies evaluating the cognitive outcomes in children following liver transplantation have found variable prevalence rates for intelligence quotient (IQ) delays (defined as an IQ < 70) ranging from 5%-24%.5-8 Kennard's cohort of children and adolescents who were evaluated at various intervals after liver transplant demonstrated the diagnosis of cognitive delay in 18% and learning disability in 26% of children.5 These previous studies have included relatively small patient cohorts which have limited the investigators' ability to assess for practice variables that may influence cognitive outcomes.
The Studies of Pediatric Liver Transplant (SPLIT) research consortium has allowed investigators a unique opportunity to survey outcomes over a large cross-section of patients. The School Attendance and Academic Performance Survey (SAAPS) is an annual survey administered through SPLIT and represents the largest accumulation of parent-reported information on educational outcomes and school attendance in the pediatric post–liver transplant population. The primary objectives of this study were severalfold. Our first goal was to detail the characteristics of school attendance after liver transplantation. Second, we wanted to quantify the number of liver transplant recipients requiring special educational assistance and describe the types of services they required. Finally, we sought to develop a model to identify variables that predicted the need for special educational services in this population.
Abbreviations:
CMV, cytomegalovirus; FSIQ, Full-Scale Score IQ; IEP, individualized educational plan; IQ, intelligence quotient; SAAPS, School Attendance and Academic Performance Survey; SPLIT, Studies of Pediatric Liver Transplantation; Tx, transplantation.
PATIENTS AND METHODS
The SPLIT data registry is a multicenter data registry for pediatric liver transplant candidates and recipients and includes 45 centers in Canada and the United States. All SPLIT centers have individual Institutional Review Board approval and individual informed consent that is obtained from the parents or guardians. Coded information is submitted to the SPLIT data coordinating center via a standardized Web-based data entry system beginning at the time of listing for transplantation. Data collection includes detailed information regarding clinical status, laboratory values, medical and operative therapies, and patient complications and outcomes.
The SAAPS is a semistructured questionnaire that was specifically designed for all school-age children, 6-18 years old, who participate in the SPLIT project (see Supporting Appendix 1). The survey is completed by the child's primary caregiver during all annual posttransplant assessments. The survey contains three domains: (1) school attendance; (2) school performance and educational outcomes; and (3) parental concerns regarding development and behavior. In the section regarding school performance and educational outcomes, parents are asked to indicate the specific types of special educational support the child receives, including individualized educational plans (IEPs) and 504 Plans.9
Potential risk factors for the need for special educational services were assessed and included both pretransplant and posttransplant variables. Pretransplant variables included recipient's age at transplant, interval since transplant, sex, race, highest parental education, primary diagnosis, and requirement of special education before transplant. Transplant variables included graft type, era of transplant (≤2001 versus ≥2002), patient's status at transplant, Pediatric End-Stage Liver Disease (PELD) score10 at transplant, log international normalized ratio, total bilirubin and albumin at transplant, height and weight z-score at transplant, growth failure at transplant (≤ −2 standard deviations for height or weight), nutritional intake at listing, and wait time for transplant. Because growth failure at transplant had a lower significance value (P = 0.048) in univariate analysis than either height (P = 0.051) or weight (P = 0.17) z-score at transplant, the combined variable was selected for the model. Posttransplant variables included: retransplantation within the first month; steroid use at transplant; use of polyclonal or monoclonal antibodies at transplant; type of immunosuppressant at 6 months posttransplant; rejection within the first 6 months; biliary tract complication within the first 6 months; vascular complication within the first 6 months; hospital days following transplantation; interval from transplant; glucose intolerance within the first 6 months; symptomatic Epstein-Barr virus, cytomegalovirus (CMV), or posttransplant lymphoproliferative disease within the first 6 months; patient's current age group (6-11, 12-14, or 15-18 years of age), and change in weight z-score at 6 months posttransplant. Change in height z-score at 6 months was not included because a prior analysis of posttransplant growth revealed limited variability in this parameter at 6 months.11 Likewise, growth failure at 6 months was not included because it was highly correlated with growth failure at transplant. Data from later time points following transplant could not be included because some patients (n = 40) had only completed 9-17 months of follow-up.
Patients
Eligible patients were school age (between 6 and 18 years) and had survived liver transplantation by at least 9 months. The SAAPS was completed between June 1, 2005, and March 31, 2008, and all patients considered eligible for this analysis were maintaining routine follow-up at their transplant center as evidenced by a completed SPLIT long-term follow-up form recorded during the study period. If parents had completed the SAAPS twice during the study period, only data from the last form filed was included. Although SPLIT includes 45 centers, only 39 chose to participate in SAAPS data collection.
Statistics
Descriptive data was summarized, comparing survey participants and nonparticipants, with means, medians, standard deviations, and standard errors for continuous factors and proportions for categorical factors. Educational outcomes of the survey participants were analyzed for the total sample and by subsets based on the age of the child at survey (6-11 years, 12-14 years, and 14-18 years) and time interval from transplant (9-17 months, 18-35 months, and ≥ 36 months). Univariate analyses of variables associated with the requirement for special education were performed using the Kruskal-Wallis test for continuous factors and chi-squared test for categorical factors. Variables significant at the 0.10 level in the univariate logistic regression analysis were included in the multivariate model. Final multivariate models were derived using a stepwise backward elimination process. Model simplification continued until the reduced model yielded significance (P < 0.05). All statistical analyses were performed using SAS for Windows, version 9.2 (SAS Institute, Inc., Cary, NC).
RESULTS
During the study period, 1133 patients were eligible for participation, of which 823 participated (72.6%) and 310 were nonparticipants (27.4%). Table 1 compares selected demographic and medical variables between participants and nonparticipants. Of note, participants had a lower mean calculated PELD score at the time of transplant (11.5 ± 14.5 versus 13.8 ± 13.8, P = 0.0087). Participating patients had a mean age at survey of 11.34 ± 3.84 years, a median age at LT of 4.6 (range 0.05-17.8) years, and a mean interval from transplant of 5.42 ± 2.79 years. Overall, 95.6% of children had attended school during the 12 months prior to completion of the SAAPS. Outcomes for the entire group and subset analysis are demonstrated in Tables 2 through 4. Table 2 details the number of days of school that were missed due to illness or doctor' visits. Note that 32.8% of children missed more than 10 days of school per year. Older participants (P = 0.0024) and children with shorter intervals from transplant (P < 0.0001) were more likely to miss more than 10 days of school in the preceding year (Tables 3 and 4).
Characteristic | Survey Participants | P Value | |||
---|---|---|---|---|---|
Yes (n = 823) | No (n = 310) | ||||
N | % | N | % | ||
Sex | P = 0.4080 | ||||
Male | 389 | 47.3 | 138 | 44.5 | |
Female | 434 | 52.7 | 172 | 55.5 | |
Race | |||||
White | 514 | 62.5 | 175 | 56.5 | P = 0.0777 |
Black | 128 | 15.6 | 54 | 17.4 | |
Hispanic | 103 | 12.5 | 38 | 12.3 | |
Asian/Pacific | 34 | 4.1 | 21 | 6.8 | |
Aboriginal | 9 | 1.1 | 9 | 2.9 | |
Other | 31 | 3.7 | 10 | 3.2 | |
Primary Diagnosis | |||||
Biliary atresia | 307 | 37.3 | 115 | 37.1 | P = 0.8880 |
Other cholestatic/metabolic | 268 | 32.6 | 102 | 32.9 | |
Fulminant liver failure | 115 | 14.0 | 49 | 15.8 | |
Cirrhosis | 57 | 6.9 | 18 | 5.8 | |
Other | 76 | 9.2 | 26 | 8.4 | |
Age at Transplant | |||||
0-6 months | 49 | 6.0 | 20 | 6.5 | P = 0.2272 |
6-12 months | 123 | 14.9 | 62 | 20.0 | |
1-5 years | 258 | 31.3 | 91 | 29.4 | |
5-13 years | 294 | 35.7 | 96 | 31.0 | |
13-17 years | 99 | 12.0 | 41 | 13.2 | |
Primary Payor | |||||
Medicaid | 278 | 33.8 | 114 | 36.8 | P = 0.4566 |
Provincial government | 74 | 9.0 | 30 | 9.7 | |
HMO/managed care | 162 | 19.7 | 67 | 21.6 | |
Private insurance | 220 | 26.7 | 65 | 21.0 | |
Military | 12 | 1.5 | 3 | 1.0 | |
PELD | |||||
Mean | 11.5 ± 14.5 | 13.8 ± 13.8 | P = 0.0087 | ||
Wait time for transplant (months) | |||||
Mean | 6.2 ± 11.7 | 5.6 ± 11.2 | P = 0.0847 |
School Attendance | N | Percent | |
---|---|---|---|
Attended school in last 12 months* | No | 36 | 4.4 |
Yes | 774 | 95.6 | |
Missed > 10 days of school | |||
No | 512 | 67.2 | |
Yes | 250 | 32.8 | |
School days missed | Total | 762 | 100.0 |
0-4 | 277 | 36.4 | |
5-10 | 235 | 30.8 | |
11-20 | 116 | 15.2 | |
21-30 | 47 | 6.2 | |
31+ | 87 | 11.4 |
- * A total of 13 patients with missing data.
Outcome | Age Groups | Total (N = 823) | P Value | ||||||
---|---|---|---|---|---|---|---|---|---|
6-11 Years (N = 509) | 12-14 Years (N = 125) | 15-18 Years (N = 189) | |||||||
N* | % | N* | % | N* | % | N** | % | ||
Currently receiving special education | 163 | 34.1 | 38 | 32.2 | 60 | 34.7 | 769 | 33.9 | P = 0.962 |
Testing for IEP | 175 | 35.4 | 42 | 34.4 | 73 | 39.9 | 800 | 36.3 | P = 0.328 |
History of 504 Plan | 44 | 8.9 | 14 | 11.5 | 29 | 16.2 | 796 | 10.9 | P = 0.008 |
Repeated grade | 80 | 16.2 | 29 | 24.0 | 50 | 27.3 | 797 | 19.9 | P = 0.001 |
Attended school in last 12 months | 480 | 95.6 | 119 | 96.7 | 175 | 94.6 | 810 | 95.6 | P = 0.689 |
Missed school > 10 days | 140 | 29.6 | 36 | 30.8 | 74 | 43.0 | 762 | 32.8 | P = 0.002 |
- N*, Number of patients with outcome among total evaluable; %, Percent of patients with outcome among total evaluable; N**, Number evaluable for each outcome.
Outcome | Time Interval from Transplant | Total (N = 823) | P Value | ||||||
---|---|---|---|---|---|---|---|---|---|
9-17 Months (N = 71) | 18-35 Months (N = 128) | ≥ 36 Months (N = 624) | |||||||
N* | % | N* | % | N* | % | N** | % | ||
Currently receiving special education | 22 | 35.5 | 37 | 32.2 | 202 | 34.1 | 769 | 33.9 | P = 0.988 |
Testing for IEP | 26 | 38.8 | 40 | 32.5 | 224 | 36.7 | 800 | 36.3 | P = 0.891 |
History of 504 plan | 14 | 20.9 | 12 | 9.8 | 61 | 10.1 | 796 | 10.9 | P = 0.030 |
Repeated grade | 16 | 23.2 | 25 | 20.7 | 118 | 19.4 | 797 | 19.9 | P = 0.451 |
Attended school in last 12 months | 62 | 89.9 | 116 | 94.3 | 596 | 96.4 | 810 | 95.6 | P = 0.034 |
Missed school >10 days | 41 | 67.2 | 45 | 38.8 | 164 | 28.0 | 762 | 32.8 | P < 0.0001 |
- N*, Number of patients with outcome among total evaluable; %, Percent of patients with outcome among total evaluable; N**, Number evaluable for each outcome.
Table 3 demonstrates the educational outcomes for the entire cohort. Overall, 33.9% of participants were receiving special educational services at the time of survey. This percentage ranged from 32.2%-35.5% depending on age and interval from transplant (Tables 3 and 4). A history of having had testing for an IEP was reported for 36.3%, and a history of receiving classroom accommodations via a 504 Plan was reported for 10.9% of participants. A 504 Plan was reported more often for older participants (P = 0.0075) and those with the shortest interval from transplant (P = 0.0297). The number of participants who repeated a grade level was 19.9% with the older participants more likely to have repeated a grade level (P = 0.0007). Parents reported that their child had previously been given a diagnosis of learning disability or mental retardation in 17.4% and 5.2%, respectively.
Predictors of Utilization of Special Educational Services
Variables with a significance level of ≤ 0.10 in univariate analysis are detailed in Table 5. Logistic regression analysis with stepwise backward selection procedure was performed on 562 patients with complete data for these variables (Table 6). The use of cyclosporine, (odds ratio [OR] = 1.83; 95% confidence interval [CI] = 1.08, 3.10; P = 0.0239) and noncalcineurin inhibitor–based immunosuppressant regimes (OR = 4.88; 95% CI = 1.35, 17.61; P = 0.0154) compared to tacrolimus at 6 months posttransplant were associated with increased utilization of special educational services. Of note, all but 14 patients received either cyclosporine or tacrolimus at this early time point. Symptomatic CMV infection within the first 6 months posttransplantation (OR = 3.10; 95% CI = 1.57, 6.09; P = 0.0011) and a history of special educational services in the pretransplant period (OR = 22.46; 95% CI = 8.64, 58.42; P < 0.0001) were also both associated with posttransplant special educational support.
Factor | Comparison Group | Reference Group | Odds Ratio | P Value |
---|---|---|---|---|
Primary diagnosis | Other cholestatic or Metabolic | Biliary atresia | 1.54 | P = 0.0448 |
Fulminant liver failure | 1.01 | |||
Cirrhosis | 0.63 | |||
Other | 1.27 | |||
Growth deficit at Tx | Yes | No | 1.39 | P = 0.0477 |
Immunosuppression at Tx | Cyclosporine | Tacrolimus | 1.72 | P = 0.0057 |
Other | 0.63 | |||
Immunosuppression at 6 months post-Tx | Cyclosporine | Tacrolimus | 1.59 | P = 0.0019 |
Other | 5.49 | |||
Nutrition intake at listing | Tube | Mouth | 1.75 | P = 0.0289 |
Intravenous | 1.38 | |||
Early use of monoclonal or polyclonal antibodies | Yes | No | 1.41 | P = 0.0846 |
Symptomatic CMV within 6 months of Tx | Yes | No | 2.15 | P = 0.0051 |
Pre-Tx special education needs | Yes | No | 13.97 | P < 0.0001 |
Parent highest education | College or Above | Less than College | 0.70 | P = 0.0234 |
Year of Tx | ≥2002 | ≤2001 | 0.72 | P = 0.0354 |
Initial Hospital Stay | Continuous Predictor | 1.01 | P = 0.0008 | |
Log international normalized ratio | Continuous Predictor | 0.75 | P = 0.0985 | |
Change in weight z-score at 6 months post-Tx | Continuous Predictor | 0.87 | P = 0.0600 |
Factor | Comparison Group | Reference Group | Odds Ratio | 95% CI | P Value |
---|---|---|---|---|---|
Immunosuppression at 6 months posttransplant (overall P = 0.0061) | Cyclosporine | Tacrolimus | 1.83 | (1.08, 3.10) | P = 0.0239 |
Other | 4.88 | (1.35, 17.61) | P = 0.0154 | ||
Symptomatic CMV within 6 months of transplant | Yes | No | 3.10 | (1.57, 6.09) | P = 0.0011 |
Pretransplant special education needs (overall P < 0.0001) | Yes | No | 22.46 | (8.64, 58.42) | P < 0.0001 |
No education | 1.70 | (1.08, 2.66) | P = 0.0211 |
- Sample size was limited to 562 patients who had complete data for all the variables included in the model.
DISCUSSION
As the population of children who achieve long-term survival following liver transplantation increases, it is becoming more important to understand and optimize their functional outcomes.12 Previous literature has been hampered by single-center design and small sample sizes5, 7, 8, 13 and has focused on IQ measurements or registration in school.5, 7, 8, 13, 14 This study greatly expands upon the previous literature by examining functional outcomes, such as school attendance and utilization of special educational services, in a large cohort representing a broader spectrum of children post–liver transplant in a multicenter design.
The SPLIT cohort of 823 participants represents the most comprehensive analysis to date of school outcomes following pediatric liver transplantation. Three-quarters of eligible SPLIT patients participated in the survey. Participants were representative of the SPLIT database in terms of demographics, but participants may have been slightly healthier at transplant as evidenced by their lower PELD score. However, the clinical relevance of this small difference is questionable.15 Therefore, we believe the data collected on this patient cohort is representative of the larger group.
In general, school attendance was excellent with almost 96% of school age children attending school over the past 12 months. Of note, 2% reported being home schooled and only 1% reported being unable to attend school for medical reasons. Although almost all were attending school, one-third of these patients missed more than 2 weeks of school (10 school days) in the proceeding school year and more than 11% missed greater than 6 weeks. This is compared to national statistics on chronic school absence which reveals that approximately 10% of children in primary grades miss 12-18 days per year and only 5% miss 18 days or more.16 As expected, it was more likely for children to miss school within the first 18 months after transplantation. Also, older adolescent patients (15-18 years) were more likely to have missed school regardless of interval from transplant. Reasons for missed days require further investigation, because attendance likely influences school performance and academic achievement. Likewise, the relationship between missed school days and cognitive function were not explored in this study, but will be addressed in a longitudinal analysis of cognitive function that is currently in progress.
A diagnosis of learning disability was reported in 17.4% of participants. The expected normative population rate of learning disability is 8%17; therefore, the postpediatric liver transplant rate is more than twice what is expected. Furthermore, one-third (33.9%) of participants were receiving special education services at the time of survey. This suggests that patients were experiencing a broader range of academic difficulties requiring special education supports than those fitting narrowly in the category of learning disabilities and/or that parents were underreporting (and perhaps lacking awareness of) their children's learning disabilities. The pediatric liver transplant population is not dissimilar to other pediatric groups with chronic diseases because many of these have also been associated with neurocognitive impairment and school achievement issues. These findings have been attributed to multiple factors including a disruption of development, chronic effects of the specific condition on central nervous system growth, or treatment-specific effects.3, 18 Some well-documented groups include childhood cancer survivors, individuals with chronic renal disease, and those with juvenile diabetes. Among childhood cancer survivors, special education use is reported in 23% compared to 8% in their siblings.19 Children with chronic end-stage renal disease are at increased risk for neurocognitive impairment,18 and poor metabolic control in patients with insulin-dependent diabetes is related to weaker academic performance compared to siblings or matched controls.20
A high prevalence of special education requirements in the liver transplant population is supported by previous single-center studies examining neurocognitive outcomes and documenting mean Full-Scale Score IQ (FSIQ) ranging from 84-94.5, 6, 8, 21 Because FSIQ more than 1 standard deviation below the mean (FSIQ < 86) usually requires a modified learning environment,5 the finding of a high proportion of the SPLIT cohort using special education services is consistent with prior IQ results. Although other chronic pediatric diseases have diminished school achievement, the prevalence of special education utilization in pediatric liver transplant patients is higher and indicates a need for further studies to assess the potential influencing factors.
Other potential indicators of school problems included development of a 504 Plan for classroom accommodations/modifications and grade retention. More than one-third (36.3%) of participants required an IEP. An IEP identifies a student's specific learning expectations and outlines how a school will address these expectations through appropriate accommodations, program modifications, and/or alternative programs as well as specific instructional and assessment strategies. Among participants, only 10.9% overall had a 504 Plan, although the rate was higher for participants closer to the time of their transplant.
Parents reported that their child had been retained at least 1 grade in 20% of the sample, and this was more likely in the older participants. This prevalence is lower than that of the requirement for special education but that may be due to different factors such as the policy for grade retention varying between jurisdictions. Interestingly, grade retention is more common in the older age group possibly because the requirements for senior matriculation are more rigorous than in earlier grades.
Identifying and describing at-risk populations is key to allowing clinicians to better counsel and assist families as well as to determine modifiable practice variables that influence school outcomes. The multivariate analysis examined the relationship between utilization of special education and multiple variables. The most striking predictor was the pretransplant requirement for special education (OR = 22.46, P < 0.0001). This finding suggests that most neurocognitive deficits resulting in special education utilization originate prior to transplant. Although many pediatric liver transplant patients are very young and are not yet in school prior to transplant, these children also incurred a higher risk of using special education supports after transplantation (OR = 1.70). Thus, factors related to disease and treatment prior to transplant appear to have the largest impact. In this analysis, age at liver transplantation and measures of nutritional status prior to liver transplantation were not associated with increased utilization of services. These factors have previously been associated with lower neurocognitive function in studies that have included individual patient testing.8, 22 Reasons for this difference are not immediately apparent because this cohort did include an adequate number of children younger than 12 months of age at transplant (n = 166) and a large number with pretransplant growth failure (n = 239). Further studies that include individual patient testing to identify risk factors for lower cognitive outcomes coupled with more detailed anthropometric analysis to quantify malnutrition are ongoing within several pediatric liver disease research consortia.
Symptomatic CMV disease in the first 6 months following liver transplantation was associated with an OR of 3.1 for special education utilization. The finding of this association is novel and has not been previously described in this patient population. Congenital CMV is a well-recognized cause of permanent neurological injury. Even asymptomatic congenital CMV is associated with increased rates of school failure and trends toward below-average intelligence and language development scores.23 Although the adverse neurological effects have most commonly been associated with congenital infection, immunosuppressed patients are a population also noted to be at risk for neurological sequela.24 This suggestion that CMV infection may have detrimental effects on long-term intellectual outcomes in pediatric liver transplant recipients warrants further study.
The multivariate model suggesting the use of cyclosporine in the early posttransplant period was associated with increased risk (OR = 1.83), which was not influenced by the era of transplant. The association was even greater when comparing other immunosuppressive regimes to tacrolimus (OR = 4.88), but this very small group of patients may have possessed some other confounding variable not assessed in this analysis, such as a posttransplant seizure disorder or pretransplant neurological injury. Both cyclosporine and tacrolimus have been associated with transient neurotoxicity,25, 26 and it is generally accepted that both drugs pose a similar risk of neurological side effects.27 Thus, this observation should likewise be confirmed in more detailed assessments of long-term neurocognitive function.
Although the study represents the largest cohort of post–liver transplant children with prospectively collected clinical variables, the results must be interpreted within the confines of their limitations. This is a parent-reported questionnaire and is not validated through school records or concurrent neuropsychological assessment. Whether or not a parent reported participation in special education depends on their perception of what constitutes special education. The incidence of special education requirements in this population appears to exceed that seen in other chronic disorders, but whether a child receives this type of support may be a function not only of their academic ability and performance, but also a reflection of social support and parental influence. Special educational services are regulated by a complex range of federal, state, and local laws with requirements varying somewhat by state in the United States and by province in Canada. These criteria have been established to regulate the expenditure of these costly services, with services being granted to only those who have clearly demonstrated the need based on individual patient testing and classroom reports. In the United States, it may be somewhat easier to qualify for these services on the basis of a 504 Plan, which by federal mandate provides children who have chronic diseases and disabling conditions with appropriate modifications within their educational program to accommodate their special needs. However, these accommodations may be implemented in a regular classroom and do not require children be placed in a special educational program, and only 10.9% of the patients in this report used a 504 Plan. Therefore, although criteria may have varied within the different geographic areas studied, it would appear that these services were granted by objective criteria and not solely on the basis of the history of having received a liver transplant. Thus, we believe the prevalence of special educational services in this report is not an overestimation of actual need. In fact, smaller single-center studies that have included direct patient testing have suggested that special education needs are actually under-recognized by both families and the education system.5, 21
In summary, this study provides important information because it is the largest study examining the educational outcomes of postpediatric liver transplant patients. Through this large cohort, some novel variables such as immunosuppression, CMV, and pretransplant special education have been identified. However, it is clear that further investigation is required to research educational attainment of children after liver transplantation. If at least one-third of children who have undergone liver transplantation are using special education services, then close monitoring and judicious neuropsychological and educational assessment are likely to be key to obtaining effective interventions. Evidence suggests that the most successful time for intervention is not when deficits are detected in the classroom but prior to and in anticipation of academic performance deficits.2 Understanding risk factors that identify the patient at high risk for lower school performance would assist clinicians and educators in designing proactive programs to minimize academic performance deficits and maximize classroom success.