2023
DOI: 10.1161/circgen.122.004050
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Implementation of Rapid Genome Sequencing for Critically Ill Infants With Complex Congenital Heart Disease

Thomas Hays,
Rebecca Hernan,
Michele Disco
et al.

Abstract: BACKGROUND: Rapid genome sequencing (rGS) has been shown to improve care of critically ill infants. Congenital heart disease (CHD) is a leading cause of infant mortality and is often caused by genetic disorders, yet the utility of rGS has not been prospectively studied in this population. METHODS: We conducted a prospective evaluation of rGS to improve the care of infants with complex CHD in our cardiac neonatal intensive care unit. … Show more

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Cited by 6 publications
(5 citation statements)
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“…These data may help clinicians provide more informed guidance to families and lead to better clinical decision-making in rare presentations. 29 These data indicate the need for a greater index of suspicion for multiple critical illnesses, such as sepsis in the setting of trisomy 21 and NEC in the setting of cystic fibrosis. Given the trend towards greater adjusted odds of multiple morbid outcomes, clinicians should also consider genetic evaluation when caring for preterm infants with critical illnesses.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…These data may help clinicians provide more informed guidance to families and lead to better clinical decision-making in rare presentations. 29 These data indicate the need for a greater index of suspicion for multiple critical illnesses, such as sepsis in the setting of trisomy 21 and NEC in the setting of cystic fibrosis. Given the trend towards greater adjusted odds of multiple morbid outcomes, clinicians should also consider genetic evaluation when caring for preterm infants with critical illnesses.…”
Section: Discussionmentioning
confidence: 99%
“…outcome.full$`Genetic Disorder`[8] <-"Klinefelter syndrome" outcome.full$`Genetic Disorder`[9] <-"Turner syndrome" outcome.full$`Genetic Disorder`[10] <-"Unspecified Aneuploidy" outcome.full$`Genetic Disorder`[12] <-"13q deletion syndrome" outcome.full$`Genetic Disorder`[13] <-"Cri-du-chat syndrome" outcome.full$`Genetic Disorder`[14] <-"DiGeorge syndrome" outcome.full$`Genetic Disorder`[15] <-"Unspecified CNV" outcome.full$`Genetic Disorder`[18] <-"Thalassemia" outcome.full$`Genetic Disorder`[19] <-"Hemoglobin bart's" #should i name this as Alpha Thalassemia? outcome.full$`Genetic Disorder`[20] <-"Sickle cell disease" outcome.full$`Genetic Disorder`[21] <-"G6PD deficiency" outcome.full$`Genetic Disorder`[22] <-"Hemophilia A" outcome.full$`Genetic Disorder`[23] <-"Hemophilia B" outcome.full$`Genetic Disorder`[25] <-"Cystic fibrosis" outcome.full$`Genetic Disorder`[26] <-"Fragile X syndrome" outcome.full$`Genetic Disorder`[27] <-"Hypophosphatasia" outcome.full$`Genetic Disorder`[28] <-"Fanconi Anemia" outcome.full$`Genetic Disorder`[29] <-"Multiple Disorders" # outcome.full$`Genetic Disorder`[29] <-"Absent" colnames(outcome.full)[3] <-"ICH" colnames(outcome.full)[4] <-"NEC" colnames(outcome.full)[5] <-"BPD" colnames(outcome.full)[9] <-"Mortality" colnames(outcome.full)[10] <-"Mortality or Any Severe Morbidity" corrected.outcomes <-outcome.full[, c(1, 10, 9, 2, 3, 4, 5, 6, 7, 8)] library(dplyr) library(tidyverse) library(pixiedust) library(kableExtra) library(knitr) outcome.counts <-dust(corrected.outcomes, rownames = F) %>% sprinkle(col = 1:9, round = 0) %>% #bold = T, part = "head") sprinkle(col = 10, halign = "center") %>% kable(align=c(rep('lcc'))) %>% kable_styling(font_size = 20) %>% kable_classic(full_width = F, html_font = "Cambria") tmp.1 <-add_indent(outcome.counts, c(1:2, 4:10, 12:15, 17, 24), level_of_indent = 1, all_cols = FALSE) tmp.2<-add_indent(tmp.1, c(18:23, 25:28), level_of_indent = 2, all_cols = FALSE) outcome.finals <-tmp.2 %>% row_spec(0,bold = T) %>% row_spec(1:2, italic = T) %>% column_spec(1, width = "20em") outcome.n.…”
mentioning
confidence: 99%
“…Several studies support the use of CMA and exome sequencing for CHD [10][11][12]14,16,[53][54][55][56][57][58]. However, additional research is needed to determine performance and cost-effectiveness of genome sequencing for CHD, and some groups have begun exploring this [59][60][61]. GS has the ability to ascertain a fuller spectrum of CHD genetic etiologies singularly and efficiently-aneuploidies, copy-number variants, monogenic disorders, multiple co-occurring genetic disorders, and non-coding variation previously elusive to gene panels and exome sequencing.…”
Section: Discussionmentioning
confidence: 99%
“…However, diagnostic rates still differ across the studies and tested phenotypes [17][18][19]. In addition, rapid WGS demonstrated the yield in 27% of individuals with CHD, leading to changes in clinical management in 62% of patients with diagnostic results [20].…”
Section: Discussionmentioning
confidence: 99%