Browsing by Author "Fuller, Stephanie"

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    Design and Harmonization Approach for the Multi-Institutional Neurocognitive Discovery Study (MINDS) of Adult Congenital Heart Disease (ACHD) Neuroimaging Ancillary Study: A Technical Note
    (MDPI, 2023-09-06) Panigrahy, Ashok; Schmithorst, Vanessa; Ceschin, Rafael; Lee, Vince; Beluk, Nancy; Wallace, Julia; Wheaton, Olivia; Chenevert, Thomas; Qiu, Deqiang; Lee, James N.; Nencka, Andrew; Gagoski, Borjan; Berman, Jeffrey I.; Yuan, Weihong; Macgowan, Christopher; Coatsworth, James; Fleysher, Lazar; Cannistraci, Christopher; Sleeper, Lynn A.; Hoskoppal, Arvind; Silversides, Candice; Radhakrishnan, Rupa; Markham, Larry; Rhodes, John F.; Dugan, Lauryn M.; Brown, Nicole; Ermis, Peter; Fuller, Stephanie; Cotts, Timothy Brett; Rodriguez, Fred Henry; Lindsay, Ian; Beers, Sue; Aizenstein, Howard; Bellinger, David C.; Newburger, Jane W.; Glass Umfleet, Laura; Cohen, Scott; Zaidi, Ali; Gurvitz, Michelle; Pediatric Heart Network MINDS Neuroimaging Ancillary Study Investigators; Radiology and Imaging Sciences, School of Medicine
    Dramatic advances in the management of congenital heart disease (CHD) have improved survival to adulthood from less than 10% in the 1960s to over 90% in the current era, such that adult CHD (ACHD) patients now outnumber their pediatric counterparts. ACHD patients demonstrate domain-specific neurocognitive deficits associated with reduced quality of life that include deficits in educational attainment and social interaction. Our hypothesis is that ACHD patients exhibit vascular brain injury and structural/physiological brain alterations that are predictive of specific neurocognitive deficits modified by behavioral and environmental enrichment proxies of cognitive reserve (e.g., level of education and lifestyle/social habits). This technical note describes an ancillary study to the National Heart, Lung, and Blood Institute (NHLBI)-funded Pediatric Heart Network (PHN) “Multi-Institutional Neurocognitive Discovery Study (MINDS) in Adult Congenital Heart Disease (ACHD)”. Leveraging clinical, neuropsychological, and biospecimen data from the parent study, our study will provide structural–physiological correlates of neurocognitive outcomes, representing the first multi-center neuroimaging initiative to be performed in ACHD patients. Limitations of the study include recruitment challenges inherent to an ancillary study, implantable cardiac devices, and harmonization of neuroimaging biomarkers. Results from this research will help shape the care of ACHD patients and further our understanding of the interplay between brain injury and cognitive reserve.
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    Development and Validation of a Seizure Prediction Model in Neonates Following Cardiac Surgery
    (Elsevier, 2020) Naim, Maryam Y.; Putt, Mary; Abend, Nicholas S.; Mastropietro, Christopher W.; Frank, Deborah U.; Chen, Jonathan M.; Fuller, Stephanie; Gangemi, James J.; Gaynor, J. William; Heinan, Kristin; Licht, Daniel J.; Mascio, Christopher E.; Massey, Shavonne; Roeser, Mark E.; Smith, Clyde J.; Kimmel, Stephen E.; Pediatrics, School of Medicine
    BACKGROUND Electroencephalographic seizures (ES) following neonatal cardiac surgery are often subclinical and have been associated with poor outcomes. An accurate ES prediction model could allow targeted continuous electroencephalographic monitoring (CEEG) for high-risk neonates. METHODS Development and validation of ES prediction models in a multi-center prospective cohort where all postoperative neonates with cardiopulmonary bypass (CPB) underwent CEEG. RESULTS ES occurred in 7.4% of neonates (78 of 1053). Model predictors included gestational age, head circumference, single ventricle defect, DHCA duration, cardiac arrest, nitric oxide, ECMO, and delayed sternal closure. The model performed well in the derivation cohort (c-statistic 0.77, Hosmer-Lemeshow p=0.56), with a net benefit (NB) over monitoring all and none over a threshold probability of 2% in decision curve analysis (DCA). The model had good calibration in the validation cohort (Hosmer-Lemeshow, p=0.60); however, discrimination was poor (c-statistic 0.61) and in DCA there was no NB of the prediction model between the threshold probabilities of 8% and 18%. Using a cut-point that emphasized negative predictive value (NPV) in the derivation cohort, 32% (236 of 737) of neonates would not undergo CEEG, including 3.5% (2 of 58) with ES (NPV 99%, sensitivity 97%). CONCLUSIONS In this large prospective cohort, a prediction model of ES in neonates following CPB had good performance in the derivation cohort with a NB in DCA. However, performance in the validation cohort was weak with poor discrimination, calibration, and no NB in DCA. These findings support CEEG monitoring of all neonates following CPB.