Publications by authors named "Niyati Malkani"

Background: Occurrences of weight stigma have been documented in prenatal clinical settings from the perspective of pregnant patients, however little is known from the viewpoint of healthcare providers themselves. Reported experiences of weight stigma caused by maternal healthcare providers may be due to negative attitudes towards obesity in pregnancy and a lack of obesity specific education. The objective of this study was to assess weight-related attitudes and assumptions towards obesity in pregnancy among maternal healthcare providers in order to inform future interventions to mitigate weight stigma in prenatal clinical settings.

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Objective: To evaluate the diagnostic and screening utility of Kleihauer-Betke (KB) testing as a triage tool in predicting adverse fetal outcomes associated with fetomaternal hemorrhage (FMH).

Study Design: Single center retrospective cohort study evaluated a primary composite outcome of fetal complications associated with FMH between KB-negative and KB-positive test groups. Screening tests for sensitivity, specificity, positive predictive value and negative predictive value were determined.

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Insulin-like growth factor binding protein-1 (IGFBP-1), secreted by fetal liver, is a key regulator of IGF-I bioavailability and fetal growth. IGFBP-1 phosphorylation decreases IGF-I bioavailability and diminishes its growth-promoting effects. Growth-restricted fetuses have decreased levels of circulating essential amino acids.

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Insulin-like growth factor-1 (IGF-I) is the key regulator of fetal growth. IGF-I bioavailability is markedly diminished by IGF binding protein-1 (IGFBP-1) phosphorylation. Leucine deprivation strongly induces IGFBP-1 hyperphosphorylation, and plays an important role in fetal growth restriction (FGR).

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Background: Next-generation sequencing (NGS) is nearing routine clinical application, especially for diagnosis of rare monogenic cardiovascular diseases. But NGS uncovers so much variation in an individual genome that filtering steps are required to streamline data management. The first step is to determine whether a potential disease-causing variant has been observed previously in affected patients.

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