PEDIATRICSGenetic & Genomic MedicinePeer-reviewed journal article
Multidimensional and Longitudinal Impact of a Genetic Diagnosis for Critically Ill Infants
Monica Hsiung WojcikiD, Maya C. del RosarioiD, Henry A. FeldmaniD, Hadley Stevens SmithiD, Ingrid A. HolmiD
Abstract
Background and ObjectivesMany genetic conditions present in the neonatal intensive care unit (NICU), where a diagnostic evaluation is pursued. However, understanding of the impact of a genetic diagnosis on clinical outcomes and health-related quality of life for these infants remains incomplete. We therefore evaluated parent-reported outcomes complemented by clinical outcomes measures over one year for a cohort of infants in the NICU undergoing genetic evaluation. MethodsProspective cohort study evaluating outcomes after genetics consultation in a level IV NICU via parent-report and electronic medical records (EMR) review. Eligible infants were genetically undiagnosed at enrollment. Parent surveys were administered at baseline and three, six-, and 12-months following enrollment and assessed genetic testing utility as well as parent-reported infant health-related quality of life using the Infant Toddler Quality of Life Questionnaire. Results110 infant-parent pairs were enrolled. Infants had a median age at enrollment of 15 days (interquartile range 8-37.75). At baseline, 74% (81/110) of parents endorsed high importance of finding a genetic diagnosis, but perceived importance significantly decreased over time. Over the study period, 38 infants received a molecular diagnosis per parent report, though this was discordant with EMR review. Identification of a diagnosis did not significantly impact health-related quality of life across most domains, which was lower overall than population norms. ConclusionsA genetic diagnosis is highly desired by parents in the NICU, though waning interest over time for undiagnosed families may reflect parental emotional adaptation and acceptance. Additional supports are needed to improve perceived quality of life.
- organism: human
- assay: electronic health records
- research focus: benchmarking
- approach: statistical model
- Citations
- 4
- FWCI
- 1.07
- Field percentile
- top 24%
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