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Keywords:

  • Risperidone;
  • metabolic parameters;
  • prepuberty

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

Background

This study investigates changes in metabolic parameters in prepubertal children after 14–16 weeks of treatment with low-dose risperidone.

Method

Thirty-one children (mean age 5.46 ± 1.98 years) were treated with risperidone (0.25–1 mg/day; 0.01–0.07 mg/kg/day). Patients were excluded if they were using any medication other than risperidone or were diagnosed with any medical problem in addition to a non-psychotic disorder.

Results

Weight (Δ: 2.51 ± 1.94 kg), height (Δ: 0.03 ± 0.04 cm), BMI (Δ: 0.82 ± 1.4), BMI percentile (Δ: 9.72 ± 16.40), BMI z-score (Δ: 0.33 ± 1.03), triglyceride (Δ: 1.50 ± 23.97 mg/dl), very low density lipoprotein (Δ: 2.99 ± 4.76 mg/dl), insulin (Δ: 3.07 ± 3.38 mIU/ml), and leptin (Δ: 3.02 ± 4.69 ng/ml) were significantly increased (p < .05).

Conclusion

The metabolic side effects of risperidone must be carefully monitored in prepubertal children.

Key Practitioner Message
  • Risperidone is the most frequently prescribed second generation antipsychotic (SGA) to children and adolescents. However, the potentially serious effects of SGAs on metabolic functions has been of great concern
  • Early detection of risks for weight gain and/or metabolic changes is important to prevent metabolic syndrome
  • We found important changes in weight and metabolic parameters in prepubertal children during risperidone treatment
  • All children treated with risperidone, even with low doses and for short treatment periods, should be followed up based on BMI-percentile charts so as to determine their growth

Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

The lower rate of extrapyramidal side effects and hyperprolactinemia has led to an increase in preference for second-generation antipsychotics (SGAs) in children and adolescents (Patel, Sanchez, Johnsrud, & Crismon, 2002). Risperidone is the first SGA approved by the US Food and Drug Administration (FDA) for patients aged <18 years. As with other SGAs, risperidone is used off label to treat self-injurious behaviors, impulsivity, irritability, and aggression associated with disruptive behavior disorders (DBD), tic disorders, anxiety disorders, and mood disorders (Croonenberghs, Fegert, Findling, De Smedt, & Dongen, 2005). At the time, the present study was conducted risperidone was the only SGA approved by the Turkish Ministry of Health for children aged <18 years and was commonly prescribed to children with autism spectrum disorders (ASD) (Ulay & Cengel Kultur, 2006).

Although SGAs are reported to be well tolerated, children and adolescents are more vulnerable than adults to their hyperprolactinemia, weight gain, and cardiometabolic side effects (Cohen, Bonnot, & Laurent, 2012; Correll, 2008; Correll et al., 2009; Hellings, Zarcone, Crandall, Wallace, & Schroeder, 2001; Safer, 2004; Sikich, Hamer, Basford, Sheitman, & Lieberman, 2004). When compared with other SGAs, the potential for weight gain and an increase in glucose and lipid levels associated with risperidone is considered moderate (Baptista, Kin, Beaulieu, & de Baptista, 2002; Cohen et al., 2012; Sikich et al., 2004). The FDA issued a warning about SGA-induced hyperglycemia and diabetes mellitus (DM), suggesting that every patient given SGAs must be evaluated for metabolic syndrome (MS), however, MS is a complex disorder and its very definition remains a controversial topic especially in children (Kassi, Pervanidou, Kaltsas, & Chrousos, 2011; Zimmet et al., 2007).

Although MS is associated with overweight, and insulin resistance (IR) plays a central role in the pathophysiology of MS, a number of other conditions are involved in the pathogenesis (Kassi et al., 2011). Numerous interactions between genetic (Farooqi & O'Rahilly, 2006) and nongenetic factors cause overweight and obesity; in many patients the etiology of obesity is too complicated to be definitively determined except for iatrogenic risk factors.

SGA-related weight gain has been explained via a series of hypotheses (Coccurello & Moles, 2010). Although the underlying mechanism of weight gain due to SGAs is associated with H1 and H3 receptors (Huang, Weston-Green, & Deng, 2010; Kroeze et al., 2003) and 5-HT2c receptor polymorphism (Reynolds, Templeman, & Zhang, 2005), the pharmacological basis of other metabolic changes is not fully understood. The impact of peptide hormones (leptin, adiponectin) on food intake and other metabolic parameters has gained importance as adipose tissue has become considered an endocrine organ (Jin, Meyer, Mudaliar, & Jeste, 2008; Zhang et al., 1994). Studies on the effects of SGAs on these hormones have shown that leptin increases in association with weight gain during SGA treatment, but the reported findings have been inconsistent, especially in terms of adiponectin (Calarge, Xie, Fiedorowicz, Burns, & Haynes, 2012; Jin et al., 2008).

Although there are many studies on the metabolic effects of SGAs in adult and adolescent patients, to the best of our knowledge only a few have investigated metabolic changes associated with SGA in prepubertal children (Calarge, Acion, Kuperman, Tansey, & Schlechte, 2009; Calarge et al., 2012). When children aged 3–6 years were prescribed SGA, risperidone was preferred more often than all other antipsychotics (Governale & Mehta, 2009). Therefore, it is crucial that weight gain and metabolic changes related to risperidone are investigated in prepubertal patients because, as mentioned earlier, the risk of metabolic changes is higher in children (Cohen et al., 2012; Correll, 2008; Correll et al., 2009; Hellings et al., 2001; Safer, 2004; Sikich et al., 2004) and because of the disparity between prepubertal, pubertal, and adult physiology. Additionally, as shown in adults, the risk of metabolic side effects of SGA increases as the age at which such treatment begins decreases (Bai et al., 2009). As such, this study aimed to investigate changes in weight, metabolic parameters (glucose and lipid profiles), and adipocytokines (leptin, adiponectin) after 14–16 weeks of open-label prospective risperidone treatment in patients aged ≤10 years. The study hypothesis was that risperidone treatment in prepubertal children would result in significant change in weight and other metabolic parameters similar to those reported in adults and adolescents.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

Participants

This study used a prospective open-label design to measure changes in metabolic parameters during risperidone treatment provided in a naturalistic setting. Consecutive patients that were prescribed risperidone irrespective of their primary psychiatric diagnosis or indication for risperidone were enrolled, at Hacettepe University, Department of Child and Adolescent Psychiatry. This study was approved by the Clinical Research Ethics Committee of 3rd Ankara Research. The patients were permitted to receive psychosocial intervention, in addition to risperidone. The patients that, along with their parents, provided informed consent were included, and were interviewed monthly during the study visits by 1 researcher (BEA) in addition to the psychiatrist that managed the psychosocial interventions and risperidone treatment (dosage, drug cessation, and side effect monitoring), as this was a naturalistic study.

The study excluded patients aged ≥11 years and/or those that exhibited signs of puberty according to parent-rated drawings of secondary sex characteristics, those that were using any medication other than risperidone or had a history of psychotropic medication treatment, those that were diagnosed with traumatic brain injury, other neurological disorders or any disease that could have an effect on adipocytokines and the other metabolic parameters studied (such as hypertension, DM, hypercholesterolemia, corticosteroid-dependent diseases, and significant hormonal abnormalities) based on chart review, and those that could not continue risperidone treatment for any reason.

Procedure

Blood glucose, adiponectin, leptin and insulin levels, lipid profile, weight, and height were assessed after 8 hr of fasting, before initiation of risperidone treatment. After 14–16 weeks of risperidone treatment the metabolic parameters, height, and weight were reassessed.

Assessments

Weight and height were measured with the patients in light clothing without shoes using a stadiometer and a calibrated balance beam.

To assess the nutritional status and growth of children, BMI was calculated as kg/m2, BMI percentile (BMI-p) was determined based on BMI-p curves for age and sex, and the BMI z-score was calculated according to the Centers for Disease Control and Prevention, National Center of Health Statistics, 2000 Growth Charts (Kuczmarski et al., 2002). A BMI in the 85th–94.9th percentiles was defined as overweight, and a BMI ≥95th percentile was considered obese (Diezt & Bellizzi, 1999; Rolland-Cachera et al., 1991).

Leptin, adiponectin, and insulin were measured using a radioimmunoassay kit (DIA source for leptin and insulin, Millipore for adiponectin). Lipid and glucose were measured using a MODULAR analytic system (Roche Diagnostic/Hitachi).

A fasting glucose level <100 mg/dl was considered normal, 100–125 mg/dl was considered impaired fasting glucose, and ≥126 mg/dl was considered DM (American Diabetes Association, 2012). Hyperinsulinemia (insulin level >15 mIU/ml) and IR, which are independent risk factors for DM and MS, were assessed based on HOMA-IR. HOMA-IR was calculated as follows: serum fasting insulin level (μIU/ml) × serum fasting glucose level (mg/dl)/405 (Eyzaguirre & Mericq, 2009). The threshold value was determined as 2.22 for females and 2.67 for males, according to Kurtoglu et al. (2010). Lipid levels were evaluated according to the percentiles for age and gender.

Statistics

The Pass 11 package was used to calculate the sample size, and a total of 24 participants achieves 80% power to detect a mean of paired differences of 0.3 with an estimated standard deviation of differences of 0.5 and with a significance level (alpha) of 0.050 using a two-sided Wilcoxon test assuming that the actual distribution is non-normal for the primary outcome measurement (BMI). Data were analyzed using SPSS 16.0 for Windows. The normality assumption was evaluated using the Kolmogorov–Smirnov test. To compare baseline and posttreatment measurements, the dependent samples t-test or Wilcoxon test was used (Wilcoxon for BMI z-score and t-test for all others). Baseline BMI-p categories (<85th, 85th–94.9th, and ≥95th) were compared with respect to baseline and posttreatment differences in HOMA-IR, HDL (high-density lipoprotein), LDL (low-density lipoprotein), VLDL (very low density lipoprotein), TG (triglyceride), leptin, and adiponectin using the Kruskal–Wallis test. When the Kruskal–Wallis test results were significant Conover's multiple comparison method, which is a rank-based method to test the significance of individual pairs of differences, was used. Mann–Whitney U-test was performed to compare two age groups (0–5.9 years- and 6 and above years-old). To determine the relationship between the categorical variables, Pearson's chi-square test or Fisher's exact chi-square test was used, according to the sparseness of the contingency table. The marginal homogeneity test was used to compare the frequency of the BMI-p categories between baseline and posttreatment. The level of statistical significance was set at p < .05.

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

In total, one patient was excluded due to use of a psychotropic medication other than risperidone and five were excluded due to medication noncompliance. The remaining 31 patients aged 2.58–10.5 years (mean: 5.46 ± 1.98 years) participated in the study (4 females, 27 males). Patients' diagnoses according to DSM-IV criteria were as follows: ASD (n = 12 [38.71%]), DBD (n = 14 [45.16%]), and mental retardation (MR) (n = 5 [16.13%]). All participants were drug-naive at the beginning of the study and received risperidone monotherapy during the study. The mean duration of treatment was 120.20 ± 17.08 days. The total dose was calculated as follows: [(starting dose (mg) × time to change dose (day)) + (new dose (mg) × time to measurement (day))]/duration of treatment (day). As such, the risperidone dose range was 0.25–1 mg/day (0.01–0.07 mg/kg/day). Parent reported adverse effects other than weight gain were transient pruritus (n = 2), and sedation (n = 2).

Overall outcomes

As shown in Table 1, weight, height, BMI, BMI-p, BMI z-score, leptin, insulin, HOMA-IR, TG, and VLDL increased significantly after 14–16 weeks of treatment, whereas adiponectin and HDL decreased, but not significantly. One patient's weight decreased by <1 kg and one patient's weight was the same as at baseline. In the other 29 patients (93.55%), their weight increased by varying degrees (median: 2.2 kg; range: 0.30–9.5 kg [11.13 ± 6.70% of baseline]). Only one patient had weight gain ≥7 kg (9.5 kg). The mean increase in BMI was 4.67 ± 8.35%.

Table 1. Anthropometric and Metabolic Parameters at Baseline and PostTreatment
 Baseline measurementPosttreatment measurementDifferenceStatistics
Mean ± SDMean ± SDΔ ± SD p
  1. a

    p < .05.

Weight (kg)22.126.2124.647.502.511.94<.001
Height (m)1.130.131.160.120.030.04<.001
BMI (kg/m2)17.172.0017.992.630.821.40.003a
BMI-p70.7026.8380.1226.979.7216.40.003a
BMI z-score0.891.181.231.600.331.03.001a
Leptin (ng/ml)2.573.005.595.973.024.69.001a
Adiponectin (μg/mg)31.3710.5526.4910.304.8714.05.063
Glucose (mg/dl)91.657.3791.948.840.2910.70.881
Insulin (mIU/ml)7.662.5610.734.283.073.38<.001
HOMA-IR1.750.652.471.090.720.98<.001
Total cholesterol (mg/dl)158.5823.19152.9024.875.6819.34.113
LDL (mg/dl)93.7722.2588.4824.145.2916.69.088
HDL (mg/dl)55.6815.2253.5213.702.1618.83.275
TG (mg/dl)62.7727.4177.7432.621.5023.97.002a
VLDL (mg/dl)12.555.4815.556.512.994.76.001a

Changes in the percentage of all metabolic parameters and weight were not associated with the diagnostic group (ASD, DBD, MR). According to age groups, only the change in percentage of adiponectin was associated with age (p: .022) which decreased by 23% in ≥6 years-old and increased by 2% in <6 years-old.

Analysis of glucose and lipid metabolism

In all, five patients (16.1%) had hyperinsulinemia, whereas six patients (19.4%) had an impaired fasting glucose level (p = .062 and .508, respectively) after 14–16 weeks of treatment. Six patients (19.4%) had a significantly higher HOMA-IR than at baseline (p = .031). The correlations between risperidone dose, and change in BMI, leptin, TG, and HOMA-IR were not strong (r = 0.255 and p = .167, r = −0.078 and p = .676, r = 0.088 and p = .637, and r = −0.028 and p = .881, respectively). Only the change in leptin was strongly correlated with a change in weight, BMI, insulin, and HOMA-IR (r = 0.527 and p = .002, r = 0.414 and p = .021, and r = 0.519 and p = .003, respectively), whereas the other parameters were not correlated with each other.

Analysis according to BMI

The posttreatment changes in BMI-p categories were not significant (p = .695) (Table 2). Mean weight increase was 2.20 ± 1.44 kg in patients in the ≥95th BMI-p, 4.43 ± 3.62 kg in those in the 85th–94.9th BMI-p, and 2.24 ± 1.54 kg in those in the ≤84.9th BMI-p. Changes in weight were not correlated with BMI-p categories (p = .129).

Table 2. Posttreatment Changes in BMI-p Categories
Baseline BMI-p categories n (%)Posttreatment BMI-p categories n (%)Total n (%)Statistics p
≥ 95th85th–94.9th<85th
≥ 95th7 (22.58)1 (3.23)0 (0)8 (25.81).695
85th–94.9th4 (12.90)0 (0)0 (0)4 (12.90)
<85th1 (3.23)5 (16.13)13 (41.94)19 (61.30)
Total12 (38.71)6 (19.35)13 (41.94)31 (100)

The only significant relationship between the baseline BMI-p categories and metabolic parameters was the increase in HOMA-IR which was significantly higher in overweight patients (p: .042) according to the Kruskal–Wallis multiple comparison test (Table 3).

Table 3. Posttreatment Change in Metabolic Parameters, According to baseline BMI-p
Change (mean ± SD)Baseline BMI-pStatistics
<85th (n = 19)85th–94.9th (n = 4)≥95th (n = 8) p
  1. a

    p < .05.

HOMA-IR0.66 ± 0.871.92 ± 1.110.27 ± 0.75.042a
HDL−2.63 ± 12.74−3.75 ± 8.54−0.25 ± 6.94.756
LDL−4.74 ± 18.55−4.25 ± 14.57−7.13 ± 14.59.943
TG19.84 ± 24.215.25 ± 24.43.25 ± 21.92.270
Leptin2.18 ± 3.904.24 ± 3.034.42 ± 6.81.204
Adiponectin−6.65 ± 14.73−4.25 ± 15.67−0.96 ± 12.51.689

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

In this study, risperidone was used for a mean 120.20 ± 17.08 days at doses of 0.25–1 mg/day (0.01–0.07 mg/kg/day) in prepubertal children. Twenty-nine of the 31 patients (93.55%) gained varying degrees of weight (mean: 2.51 ± 1.94 kg) and weight, height, BMI, BMI-p, BMI z-score, triglyceride, VLDL, insulin, and leptin levels were significantly higher after treatment. There was no relationship between baseline BMI-p and weight gain; although overweight prepubertal children may have a high risk of developing IR soon after commencing risperidone treatment. The present study illustrates the emergence of metabolic abnormalities even in prepubertal children treated with low doses of risperidone in the absence of the confounding effect of puberty, an important developmental stage due to changes in body fat, blood pressure, lipids, and insulin sensitivity. Also to the best of our knowledge the present study is the first to investigate leptin and adiponectin levels in prepubertal patients treated with risperidone. Although metabolic parameters – especially weight gain – are thought to be mediated by many factors, such as age, gender, initial BMI, and parents' BMI (Baptista et al., 2002; Bobes et al., 2003; Hellings et al., 2001; Ratzoni et al., 2002), as described below the changes observed in this study are mostly congruent with the literature on postpubertal youth.

In the Treatment of Early-Onset Schizophrenia Spectrum Disorders Study, the efficacy and safety of SGAs and molindone were compared, and it was found that weight gain was significant in the SGAs group—the mean change in BMI-p in the patients treated with risperidone was in the 6.8 percentile (Sikich et al., 2008). In a recently published meta-analysis, mean weight gain in 25 short-term (3–12 weeks) studies that included 1040 patients treated with risperidone was 2.02 ± 0.32 kg (Cohen et al., 2012). Nicolson, Awad and Sloman (1998) reported a weight gain of 3.5 kg after 12 weeks of risperidone treatment, whereas Aman, De Smedt, Derivan, Lyons and Findling (2002) observed a weight gain of 2.2 kg after 6 weeks and Turgay, Binder, Snyder and Fisman (2002) noted 8.5 kg of weight gain after 1 year. Weight gain during risperidone treatment was reported as 7.2 ± 5.3 kg during 45 weeks of treatment (Fleischhaker et al., 2008). In this study, there was no correlation between risperidone dosage and a change in BMI; however, it is important to note that many metabolic changes were seen even at this low dose.

In the present study significant increases were observed in the BMI z-scores and BMI-p. A prospective (8 week) double-blind study compared risperidone, olanzapine, and haloperidol in 8- to 19-year-olds with psychosis (Sikich et al., 2004), and reported that a BMI change exceeding the developmentally expected change in each patient and the increase in BMI during SGA treatment was significant. Although BMI-p and weight gain were not correlated, overweight children had the highest degree of weight gain in this study, which is in accordance with findings in adults (Baptista et al., 2002), whereas the results should be interpreted with caution due to the small number of patients in each BMI-p category.

Metabolic changes (especially HOMA-IR) observed in the present study tended to be higher in overweight children, which is similar to the findings reported by Calarge, Acion et al. (2009). They reported that increases in weight and BMI were significant during a mean 2.9 years of risperidone treatment, and that hypertriglyceridemia, hyperinsulinemia, and a high HOMA-IR were observed, and were especially higher in overweight patients. We think that the risk of weight gain and IR during risperidone treatment might be mediated by a baseline BMI, because the weight gain and metabolic effects associated with SGAs are mediated by environmental and individual factors (Baptista et al., 2002).

In the present study, there was a significant increase in insulin and HOMA-IR. Another study reported that insulin increased by 35% and HOMA-IR increased by 27% in patients treated with risperidone within 2.9 years (Calarge, Ellingrod et al., 2009). It was reported that an elevated insulin level might be the result of compensation to avoid an increase in glucose (Eyzaguirre & Mericq, 2009). The underlying mechanism of the development of IR during SGA treatment remains unknown (Anil & Meltzer, 2001; Yurtsever, Esen-Danaci, & Deveci, 2007). In this study an increase in insulin was weakly associated with an increase in leptin and was not associated with weight gain, although it has been reported that insulin increases with weight gain; however, the relevant published findings are inconsistent (He, Votruba, Venti, & Krakoff, 2011; Potretzke, Warren, Schmitz, Gottsacker, & Jensen, 2011). One study reported a significant weight change of 4.16 kg after 8 weeks of risperidone treatment, in the absence of significant changes in leptin, glucose, and fasting insulin levels (Maayan & Vakhrusheva, 2010). Other effects (significant increases in TG and VLDL) of risperidone were also noted in this study. Correll et al. (2009) reported a mean weight gain of 5.3 kg and an increase in TG in 135 children and adolescents treated with risperidone for 12 weeks.

The relationship between adipocytokines and SGAs has also been reported in the literature (Bai et al., 2009; Brömel et al., 1998; Maayan & Vakhrusheva, 2010). Leptin was reported to be associated with weight gain during risperidone treatment (Calarge, Acion et al., 2009, 2012; Yurtsever et al., 2007). It is difficult to improve our understanding of the relationship between adipocytokines and weight gain during risperidone treatment because of the many confounding factors associated with appetite and weight change observed in healthy individuals. Despite the potential association between a leptin increase and weight gain, a weak correlation between leptin, weight gain and an increase in BMI was observed in this study. As such, the observed weight gain might not be the only cause of the observed increase in leptin. Similarly, Martin et al. (2004) reported that leptin and weight gain did not predict each other. In addition, it should be noted that we did not measure subcutaneous adipose tissue, which has a stronger association with leptin than visceral adipose tissue. Adiponectin is also associated with obesity, and its level is negatively correlated with weight and insulin level (Weyer et al., 2001). In this study, a nonsignificant decrease in adiponectin was noted. A recent study that compared the effects of risperidone and olanzapine on adiponectin for 3 months reported that there was a direct antipsychotic effect on adipose tissue (Wampers et al., 2012); however, Jin et al.'s (2008) meta-analysis reported that adiponectin did not differ between patients and normal controls, and did not change post-SGA treatment, in most studies on the effects of SGAs on leptin and adiponectin.

The present study has some limitations that should be mentioned. Firstly, the small sample limits the generalization of the findings and the statistical power to test the possible relationships between parameters. Also we could not assess the impact of gender. The short duration of follow-up is another limitation; although many changes in weight and metabolic parameters were observed, we could not forecast the progression. Additional limitations were an open-label study design, the lack of a comparison group, and lack of measurements of diet and other lifestyle factors. In order to obtain more generalizable results we believe it is necessary to conduct studies with larger samples, control groups, and longer follow-up periods.

Clinical and research implications

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

When prescribing risperidone, clinicians should know each patient's metabolic parameters and monitor these at regular intervals. Our results suggest that all children treated with risperidone, even those treated with low doses and for short treatment periods, should be followed up based on BMI-p charts so as to determine their growth. Families need to be informed about food intake and physical activity when risperidone is initiated, even in the prepupertal period.

Research is necessary to identify the pharmacodynamic effects of SGAs and their relationship with energy balance in the early detection of children at risk for weight gain and/or metabolic changes secondary to antipsychotic use.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References

This study received a grant from the Hacettepe University Scientific Research Unit (project number: 010 101 004 D02); no additional third party funding was received.

The authors have no conflicts of interest, financial or otherwise, related to the materials presented herein.

The authors thank Gulser Senses Dinc, Ayfer Alikasifoglu, Can Ates, and the psychiatrists working at Hacettepe University, Department of Child and Adolescent Psychiatry.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Clinical and research implications
  8. Acknowledgments
  9. References
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