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Inborn Errors of Metabolism Collaborative (IBEMC): Large scale data collection about long-term follow-up for newborn-screened conditions
PURPOSE: The Inborn Errors of Metabolism Information System (IBEM-IS) collects data on clinical history of inborn errors of metabolism (IBEM). The IBEM-IS is accessible to metabolic clinics nationwide and seeks: 1) to impact clinical management for affected individuals and 2) to provide information...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5116297/ https://www.ncbi.nlm.nih.gov/pubmed/27195819 http://dx.doi.org/10.1038/gim.2016.57 |
Sumario: | PURPOSE: The Inborn Errors of Metabolism Information System (IBEM-IS) collects data on clinical history of inborn errors of metabolism (IBEM). The IBEM-IS is accessible to metabolic clinics nationwide and seeks: 1) to impact clinical management for affected individuals and 2) to provide information to support public health decision-making. METHODS: Thirty centers in 21 states are enrolling persons with newborn-screened conditions, collecting information on diagnosis and treatment at the time of enrollment and all subsequent visits. Prospective data are collected using electronic capture forms allowing aggregation of information regarding outcomes for individuals affected with IBEM. RESULTS: 1893 subjects have been enrolled in the IBEM-IS and >540,000 individual data points have been collected. Data collection has been initiated for subjects with 41 of 46 conditions on the RUSP; 4 conditions have >100 subjects enrolled. Median follow-up time for subjects with >1 visit (n=898) is 1.5 years (interquartile range = 2.2 years). Subjects with critical conditions are more likely to have emergency letters and sick-day plans. Mortality was exclusive to children with critical conditions. CONCLUSION: Large-scale prospective data collection can be accomplished for individuals with rare conditions, permitting enhanced decision-making for clinical management and supporting decision-making in public health newborn screening programs. |
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