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Diagnostic and service impact of genomic testing technologies in a neonatal intensive care unit
Author(s) -
Tan Natalie B,
Tan Tiong Yang,
Martyn Melissa M,
Savarirayan Ravi,
Amor David J,
Moody Amanda,
White Susan M,
Stark Zornitza
Publication year - 2019
Publication title -
journal of paediatrics and child health
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.631
H-Index - 76
eISSN - 1440-1754
pISSN - 1034-4810
DOI - 10.1111/jpc.14398
Subject(s) - medicine , concordance , neonatal intensive care unit , geneticist , exome sequencing , medical genetics , referral , genetic testing , pediatrics , intensive care , retrospective cohort study , emergency medicine , intensive care medicine , family medicine , mutation , genetics , biology , gene
Aim To investigate the diagnostic and service impact of chromosomal microarray and whole exome sequencing (WES) in a neonatal intensive care unit (NICU). Methods This was a retrospective medical record review of NICU patients referred for genetics consultation at three time points over a 9‐year period at a single centre to determine referral indications, genetic consultation outcomes and time to diagnosis. Results The number of NICU patients referred for genetics consultation increased from 44 in 2007 to 95 in 2015. The proportion of NICU patients suspected of having a genetic condition following clinical geneticist assessment remained stable, averaging 5.3% of all admissions. The proportion of patients receiving a confirmed diagnosis rose from 21% in 2007 to 53% in 2015, with a shift from primarily chromosomal abnormalities to a broad range of monogenic disorders, increasingly diagnosed by WES as a first‐tier test. The average age at diagnosis in 2015 was 19 days (range 12–38 days) for chromosomal abnormalities and 138 days (range 10–309 days) for monogenic conditions. Conclusions The adoption of new genetic technologies at our centre has increased the proportion of patients receiving a confirmed genetic diagnosis. This study provides important benchmark data to measure further improvements as turn‐around times for genomic testing decrease.