Elizabeth A Jasper
Biographic Data
| ID | 9019635 |
|---|---|
| NAME | Elizabeth A Jasper |
| GIVEN NAMES | Elizabeth A |
| FAMILY NAME | Jasper |
| SIGNATURE | JASPER E A |
| AFFILIATIONS | University of Iowa |
| ORCID | 0000-0003-2444-0951 |
| VERIFIED | Yes |
| TOTAL WORKS | 4 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 4 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
Latent class analysis to characterize neonatal risk for neurodevelopmental differences
BACKGROUND: Neonatal risk factors, such as preterm birth and low birth weight, have been robustly linked to neurodevelopmental deficits, yet it is still unclear why some infants born preterm and/or low birth weight experience neurodevelopmental difficulties while others do not. The current study investigated this heterogeneity in neurodevelopmental abilities by examining additional neonatal morbidities as risk factors, utilizing latent class anal…
Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation
Background: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last decade, metabolic gestational dating approaches emerged in response to a global health need; because in most of the developing world, accurate antenatal gestational age estimates are not feasible. These methods initially developed in North America have now been externally validated in two studies in developing countries, however, require shipment o…
Using Amanhi-ACT cohorts for external validation of Iowa new-born metabolic profiles based models for postnatal gestational age estimation
BACKGROUND: Globally, 15 million infants are born preterm and another 23.2 million infants are born small for gestational age (SGA). Determining burden of preterm and SGA births, is essential for effective planning, modification of health policies and targeting interventions for reducing these outcomes for which accurate estimation of gestational age (GA) is crucial. Early pregnancy ultrasound measurements, last menstrual period and post-natal ne…
Gestational age dating using newborn metabolic screening
Background Limited ultrasound capacity in low-resource settings makes correct gestational age (GA) dating difficult. Previous work demonstrated that newborn metabolic profiles can accurately determine gestational age, but this relationship has not been evaluated in low-income countries. The objective of this study was to validate and adapt a metabolic GA dating model developed using newborn blood spots for use in a low-resource setting in rural U…
No prominent works on this page.
Using Amanhi-ACT cohorts for external validation of Iowa new-born metabolic profiles based models for postnatal gestational age estimation
BACKGROUND: Globally, 15 million infants are born preterm and another 23.2 million infants are born small for gestational age (SGA). Determining burden of preterm and SGA births, is essential for effective planning, modification of health policies and targeting interventions for reducing these outcomes for which accurate estimation of gestational age (GA) is crucial. Early pregnancy ultrasound measurements, last menstrual period and post-natal ne…
Gestational age dating using newborn metabolic screening
Background Limited ultrasound capacity in low-resource settings makes correct gestational age (GA) dating difficult. Previous work demonstrated that newborn metabolic profiles can accurately determine gestational age, but this relationship has not been evaluated in low-income countries. The objective of this study was to validate and adapt a metabolic GA dating model developed using newborn blood spots for use in a low-resource setting in rural U…
Machine learning prediction of gestational age from metabolic screening markers resistant to ambient temperature transportation
Background: Knowledge of gestational age is critical for guiding preterm neonatal care. In the last decade, metabolic gestational dating approaches emerged in response to a global health need; because in most of the developing world, accurate antenatal gestational age estimates are not feasible. These methods initially developed in North America have now been externally validated in two studies in developing countries, however, require shipment o…
Latent class analysis to characterize neonatal risk for neurodevelopmental differences
BACKGROUND: Neonatal risk factors, such as preterm birth and low birth weight, have been robustly linked to neurodevelopmental deficits, yet it is still unclear why some infants born preterm and/or low birth weight experience neurodevelopmental difficulties while others do not. The current study investigated this heterogeneity in neurodevelopmental abilities by examining additional neonatal morbidities as risk factors, utilizing latent class anal…
Gestational age (4 works) · Medicine (4 works) · Pregnancy (4 works) · Biology (3 works) · Neonatal and fetal brain pathology (3 works) · Confidence interval (2 works) · Internal Medicine (2 works) · Obstetrics (2 works) · Pediatrics (2 works) · Pregnancy and preeclampsia studies (2 works)