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      The Co-Morbidity Burden of Children and Young Adults with Autism Spectrum Disorders

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          Abstract

          Objectives

          Use electronic health records Autism Spectrum Disorder (ASD) to assess the comorbidity burden of ASD in children and young adults.

          Study Design

          A retrospective prevalence study was performed using a distributed query system across three general hospitals and one pediatric hospital. Over 14,000 individuals under age 35 with ASD were characterized by their co-morbidities and conversely, the prevalence of ASD within these comorbidities was measured. The comorbidity prevalence of the younger (Age<18 years) and older (Age 18–34 years) individuals with ASD was compared.

          Results

          19.44% of ASD patients had epilepsy as compared to 2.19% in the overall hospital population (95% confidence interval for difference in percentages 13.58–14.69%), 2.43% of ASD with schizophrenia vs. 0.24% in the hospital population (95% CI 1.89–2.39%), inflammatory bowel disease (IBD) 0.83% vs. 0.54% (95% CI 0.13–0.43%), bowel disorders (without IBD) 11.74% vs. 4.5% (95% CI 5.72–6.68%), CNS/cranial anomalies 12.45% vs. 1.19% (95% CI 9.41–10.38%), diabetes mellitus type I (DM1) 0.79% vs. 0.34% (95% CI 0.3–0.6%), muscular dystrophy 0.47% vs 0.05% (95% CI 0.26–0.49%), sleep disorders 1.12% vs. 0.14% (95% CI 0.79–1.14%). Autoimmune disorders (excluding DM1 and IBD) were not significantly different at 0.67% vs. 0.68% (95% CI −0.14-0.13%). Three of the studied comorbidities increased significantly when comparing ages 0–17 vs 18–34 with p<0.001: Schizophrenia (1.43% vs. 8.76%), diabetes mellitus type I (0.67% vs. 2.08%), IBD (0.68% vs. 1.99%) whereas sleeping disorders, bowel disorders (without IBD) and epilepsy did not change significantly.

          Conclusions

          The comorbidities of ASD encompass disease states that are significantly overrepresented in ASD with respect to even the patient populations of tertiary health centers. This burden of comorbidities goes well beyond those routinely managed in developmental medicine centers and requires broad multidisciplinary management that payors and providers will have to plan for.

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          Most cited references71

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          Advances in autism genetics: on the threshold of a new neurobiology.

          Autism is a heterogeneous syndrome defined by impairments in three core domains: social interaction, language and range of interests. Recent work has led to the identification of several autism susceptibility genes and an increased appreciation of the contribution of de novo and inherited copy number variation. Promising strategies are also being applied to identify common genetic risk variants. Systems biology approaches, including array-based expression profiling, are poised to provide additional insights into this group of disorders, in which heterogeneity, both genetic and phenotypic, is emerging as a dominant theme.
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            Systematic review of type 1 and type 2 diabetes mellitus and risk of fracture.

            The authors conducted a systematic review of published data on the association between diabetes mellitus and fracture. The authors searched MEDLINE through June 2006 and examined the reference lists of pertinent articles (limited to studies in humans). Summary relative risks and 95% confidence intervals were calculated with a random-effects model. The 16 eligible studies (two case-control studies and 14 cohort studies) included 836,941 participants and 139,531 incident cases of fracture. Type 2 diabetes was associated with an increased risk of hip fracture in both men (summary relative risk (RR) = 2.8, 95% confidence interval (CI): 1.2, 6.6) and women (summary RR = 2.1, 95% CI: 1.6, 2.7). Results were consistent between studies of men and women and between studies conducted in the United States and Europe. The association between type of diabetes and hip fracture incidence was stronger for type 1 diabetes (summary RR = 6.3, 95% CI: 2.6, 15.1) than for type 2 diabetes (summary RR = 1.7, 95% CI: 1.3, 2.2). Type 2 diabetes was weakly associated with fractures at other sites, and most effect estimates were not statistically significant. These findings strongly support an association between both type 1 and type 2 diabetes and increased risk of hip fracture in men and women.
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              Serving the enterprise and beyond with informatics for integrating biology and the bedside (i2b2).

              Informatics for Integrating Biology and the Bedside (i2b2) is one of seven projects sponsored by the NIH Roadmap National Centers for Biomedical Computing (http://www.ncbcs.org). Its mission is to provide clinical investigators with the tools necessary to integrate medical record and clinical research data in the genomics age, a software suite to construct and integrate the modern clinical research chart. i2b2 software may be used by an enterprise's research community to find sets of interesting patients from electronic patient medical record data, while preserving patient privacy through a query tool interface. Project-specific mini-databases ("data marts") can be created from these sets to make highly detailed data available on these specific patients to the investigators on the i2b2 platform, as reviewed and restricted by the Institutional Review Board. The current version of this software has been released into the public domain and is available at the URL: http://www.i2b2.org/software.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2012
                12 April 2012
                : 7
                : 4
                : e33224
                Affiliations
                [1 ]Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
                [2 ]Children's Hospital Informatics Program, Children's Hospital, Boston, Massachusetts, United States of America
                [3 ]i2b2 National Center for Biomedical Computing, Brigham and Women's Hospital, Boston, Massachusetts, United States of America
                [4 ]Beth Israel Deaconess Medical Center, Harvard Medical School Information Technology, Boston, Massachusetts, United States of America
                [5 ]Center for Developmental Medicine, Children's Hospital, Boston, Massachusetts, United States of America
                [6 ]Program in Genomics, Children's Hospital, Boston, Massachusetts, United States of America
                [7 ]Information Systems Department, Children's Hospital, Boston, Massachusetts, United States of America
                [8 ]Partners Healthcare System Information Technology, Boston, Massachusetts, United States of America
                [9 ]Department of Neurology, Children's Hospital, Boston, Massachusetts, United States of America
                [10 ]Massachusetts General Hospital, Boston, Massachusetts, United States of America
                University of Illinois-Chicago, United States of America
                Author notes

                Conceived and designed the experiments: ISK SS LK LR. Performed the experiments: ISK. Analyzed the data: ISK. Contributed reagents/materials/analysis tools: AM SNM NW JB DM SC GW. Wrote the paper: ISK.

                Article
                PONE-D-12-00026
                10.1371/journal.pone.0033224
                3325235
                22511918
                e1271e24-a8f5-4e28-a522-3e7d7a169d63
                Kohane et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 28 December 2011
                : 8 February 2012
                Page count
                Pages: 7
                Categories
                Research Article
                Biology
                Neuroscience
                Behavioral Neuroscience
                Developmental Neuroscience
                Population Biology
                Epidemiology
                Disease Informatics
                Computer Science
                Computer Applications
                Medicine
                Clinical Immunology
                Autoimmune Diseases
                Diabetes Mellitus Type 1
                Gastroenterology and Hepatology
                Inflammatory Bowel Disease
                Mental Health
                Psychiatry
                Schizophrenia
                Neurology
                Developmental and Pediatric Neurology
                Pediatrics
                Developmental and Pediatric Neurology

                Uncategorized
                Uncategorized

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