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MON-249 Algorithm-Driven Electronic Health Record Notification Enhances the Detection of Turner Syndrome
BACKGROUND: Turner syndrome (TS) results from a complete or partial loss of the second X chromosome and affects 25-50 per 100,000 females. TS is common in females with unexplained short stature, but the diagnosis is often not made until late childhood (8-9 years) if classic features are not present...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Endocrine Society
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6551104/ http://dx.doi.org/10.1210/js.2019-MON-249 |
Sumario: | BACKGROUND: Turner syndrome (TS) results from a complete or partial loss of the second X chromosome and affects 25-50 per 100,000 females. TS is common in females with unexplained short stature, but the diagnosis is often not made until late childhood (8-9 years) if classic features are not present or recognized in infancy. This results in delayed medical intervention and screening for comorbid conditions. The aim of our study was to determine if an electronic health record (EHR) notification model improves the timing and rate of detection of TS. METHODS/RESULTS: A search of the EHR was performed to identify a cohort of females with idiopathic short stature (ISS) who were seen in the endocrine clinic from 2012-2017. Selection criteria included a height ≤ -2 SD, BMI > 5%-ile, absence of chronic illness, and presence of mid-parental height (MPH) data, which yielded 216 patients. Given that a height deflection from MPH %-ile is one of the better predictors of TS(1), we focused on those ≥ 1 SD below MPH %-ile. Of these 189 patients, 72 (38%) hadn’t received prior genetic testing. This group formed our study population and microarray analysis was performed on available samples to assess for undiagnosed TS or other chromosomal abnormalities. A total of 39 patient samples were prospectively recruited or obtained from an IRB approved biobank (including 5 TS controls). Microarray data was generated for 37 samples, as 2 had an insufficient quantity of DNA, and data was manually analyzed by a cytogeneticist. We identified two cases of undiagnosed TS (6%) and one with a different chromosomal abnormality (3%). One of these patients returned to endocrine clinic prior to microarray analysis and had a karyotype of 45,X/46,XY. The two other chromosomal abnormalities were picked up by microarray. One had mosaic monosomy X (45,X/46,XX). The other had a 2.7 Mb deletion from chromosome 1 (1q25.3->1q31.1) and a 2.1 Mb duplication from 22q11.21, which has been associated with short stature. CONCLUSIONS: The EHR algorithm was effective at identifying patients at risk for TS that merit genetic testing. Of the ISS females ≥ 1 SD below their MPH %-ile, 38% never had a karyotype done and on further investigation two new cases of TS (6%) and one other chromosomal abnormality (3%) were found. Although not all patients had DNA available for microarray analysis, if we assume that all other cases were negative, the rate of undiagnosed TS would still approach 3%. Extrapolating this data to a larger scale suggests that the diagnosis of TS may be delayed for many females with ISS, even after evaluation in endocrine clinics. We recommend the implementation of additional tools in the clinic workflow, such as EHR alerts based on specific growth parameters, to increase clinical suspicion and testing for TS. REFERENCES: 1. Grote, FK, et al (2008). Developing evidence-based guidelines for referral for short stature. Archives of Disease in Childhood,93(3), 212-217. |
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