The Indian Journal of Pediatrics

, Volume 81, Supplement 2, pp 125–128 | Cite as

CDC Kerala 11: Diagnosis of Autism Among Children Between 2 and 6 y - Comparison of CARS against DSM-IV-TR

  • Babu George
  • M. S. Razeena Padmam
  • M. K. C. Nair
  • M. L. Leena
  • G. L. Prasanna
  • Paul Swamidhas Sudhakar Russell
Original Article
First Online:
Received:
Accepted:

Abstract

Objectives

To compare diagnosis of childhood autism using CARS cut off scores of ≥30 and the new Indian cut off scores of ≥33 against the gold standard DSM-IV-TR criteria available during the study period 2009–10.

Methods

The study was conducted at the autism clinic of Child Development centre (CDC), Kerala. Two hundred consecutive children between 2 and 6 y with symptoms suggestive of autism were administered both CARS by a trained developmental therapist and DSM-IV-TR by a developmental pediatrician on the same day, both blind to the test results of each other. Diagnosis of autism using CARS cut off scores 30 and above, as suggested in original tool administration manual and 33 and above, as suggested for diagnostic use in Indian population was compared with DSM-IV-TR diagnosis. Data was analyzed using SPSS (version 19.0) software.

Results

Against DSM-IV-TR diagnosis as gold standard, the new CARS cut off scores ≥33 had a higher Specificity (74.3 %), Positive predictive value (PPV) (81.9 %), Positive likelihood ratio (LR) (2.66) and Negative LR (0.43), but had a lower Sensitivity (68.3 %), Negative predictive value (NPV) (57.9 %) and accuracy (70.5 %), as compared to the cut off scores of ≥30.

Conclusions

The CARS prevalence of autism for cut off points ≥30 and ≥33 was 71.5 and 52.5 % respectively against 63 % prevalence by DSM-IV-TR.

Keywords

Autism CARS DSM-IV-TR Cut off points 
This is a preview of subscription content, log in to check access.

Notes

Acknowledgments

The authors gratefully acknowledge the cooperation and support received from staff of Child Development Centre, Kerala, specially Dr. G. Suresh Kumar, Registrar; Ms. Prasanna G.L, Developmental Therapist; Ms. Deepa NR, PS to Director; Mr. Asokan N, PA to Director; Ms. Suja S, Junior Programmer; CDC, Medical College, Thiruvananthapuram, in conduction of this study.

Conflict of Interest

None.

Source of Funding

This study is supported by Child Development Centre, Thiruvananthapuram.

References

  1. 1.
    Lai DC, Tseng YC, Hou YM, Guo HR. Gender and geographic differences in the prevalence of autism spectrum disorders in children: analysis of data from the national disability registry of Taiwan. Res Dev Disabil. 2012;33:909–15.PubMedCrossRefGoogle Scholar
  2. 2.
    Amr M, Bu Ali W, Hablas H, Raddad D, El-Mehesh F, El-Gilany AH, et al. Sociodemographic factors in arab children with autism spectrum disorders. Pan Afr Med J. 2012;13:65.PubMedCentralPubMedGoogle Scholar
  3. 3.
    Mandell DS, Novak MM, Zubritsky CD. Factors associated with age of diagnosis among children with autism spectrum disorders. Pediatrics. 2005;116:1480–6.PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    American Psychiatric Association. Pervasive developmental disorders. In: Diagnostic and Statistical Manual of Mental Disorders, 2000. 4th ed---text revision (DSM-IV-TR). Washington, DC: American Psychiatric Association; p. 69–70.Google Scholar
  5. 5.
    DSM­5 Autism Spectrum Disorder. URL: http://depts.washington.edu/dbpeds/Screening%20Tools/DSM-5 (ASD.Guidelines) Feb2013.pdf Accessed on 24/02/2014.
  6. 6.
    Schopler E, Reichler R, Rochen-Renner B. The childhood autism rating scale (CARS). Los Angeles (CA): Western Psychological Services; 1988.Google Scholar
  7. 7.
    Russell PS, Daniel A, Russell S, Mammen P, Abel JS, Raj LE, et al. Diagnostic accuracy, reliability and validity of childhood autism rating scale in India. World J Pediatr. 2010;6:141–7.PubMedCrossRefGoogle Scholar
  8. 8.
    Jensen CM, Steinhausen HC, Lauritsen MB. Time trends over 16 years in incidence-rates of autism spectrum disorders across the lifespan based on nationwide Danish register data. J Autism Dev Disord. 2014 Feb 20. [Epub ahead of print]Google Scholar
  9. 9.
    Stenberg N, Bresnahan M, Gunnes N, Hirtz D, Hornig M, Lie KK, et al. Identifying children with autism spectrum disorder at 18 months in a general population sample. Paediatr Perinat Epidemiol. 2014. doi: 10.1111/ppe.12114.PubMedGoogle Scholar
  10. 10.
    Maenner MJ, Schieve LA, Rice CE, Cunniff C, Giarelli E, Kirby RS, et al. Frequency and pattern of documented diagnostic features and the age of autism identification. J Am Acad Child Adolesc Psychiatry. 2013;52:401–13. e8.PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Kulage KM, Smaldone AM, Cohn EG. How will DSM-5 affect autism diagnosis? A systematic literature review and meta-analysis. J Autism Dev Disord. 2014 Feb 16. [Epub ahead of print].Google Scholar
  12. 12.
    García-López C, Narbona J. Clinical usefulness of IDEA and CARS: concordance with DSM-IV-TR in children and adolescents with suspicion of PDD. An Pediatr (Barc). 2014;80:71–6.CrossRefGoogle Scholar
  13. 13.
    Tachimori H, Osada H, Kurita H. Childhood autism rating scale–Tokyo version for screening pervasive developmental disorders. Psychiatry Clin Neurosci. 2003;57:113–8.PubMedCrossRefGoogle Scholar

Copyright information

© Dr. K C Chaudhuri Foundation 2014

Authors and Affiliations

  • Babu George
    • 1
  • M. S. Razeena Padmam
    • 2
  • M. K. C. Nair
    • 1
  • M. L. Leena
    • 1
  • G. L. Prasanna
    • 1
  • Paul Swamidhas Sudhakar Russell
    • 3
  1. 1.Child Development CentreThiruvananthapuram Medical CollegeThiruvananthapuramIndia
  2. 2.School of Behavioural SciencesMahatma Gandhi UniversityKottayamIndia
  3. 3.Child and Adolescent Psychiatry Unit, Department of PsychiatryChristian Medical CollegeVelloreIndia

Personalised recommendations