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Your search keyword '"Yamamoto, Jennifer M"' showing total 12 results
Start Over Author "Yamamoto, Jennifer M" Publisher american diabetes association
12 results on '"Yamamoto, Jennifer M"'

3. A Primer on Systematic Review and Meta-analysis in Diabetes Research.

Author

Tobias, Deirdre K., Papatheodorou, Stefania, Yamamoto, Jennifer M., and Hu, Frank B.

Abstract

A systematic review is a rigorous process that involves identifying, selecting, and synthesizing available evidence pertaining to an a priori–defined research question. The resulting evidence base may be summarized qualitatively or through a quantitative analytic approach known as meta-analysis. Systematic review and meta-analysis (SRMAs) have risen in popularity across the scientific realm including diabetes research. Although well-conducted SRMAs are an indispensable tool in informing evidence-based medicine, the proliferation of SRMAs has led to many reviews of questionable quality and misleading conclusions. The objective of this article is to provide up-to-date knowledge and a comprehensive understanding of strengths and limitations of SRMAs. We first provide an overview of the SRMA process and offer ways to identify common pitfalls at key steps. We then describe best practices as well as evolving approaches to mitigate biases, improve transparency, and enhance rigor. We discuss several recent developments in SRMAs including individual-level meta-analyses, network meta-analyses, umbrella reviews, and prospective meta-analyses. Additionally, we outline several strategies that can be used to enhance quality of SRMAs and present key questions that authors, editors, and readers should consider in preparing or critically reviewing SRMAs. [ABSTRACT FROM AUTHOR]

Published
2023
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4. Novel Biochemical Markers of Glycemia to Predict Pregnancy Outcomes in Women With Type 1 Diabetes

Author

Meek, Claire L, Tundidor, Diana, Feig, Denice S, Yamamoto, Jennifer M, Scott, Eleanor M, Ma, Diane D, Halperin, Jose A, Murphy, Helen R, Corcoy, Rosa, CONCEPTT Collaborative Group, Meek, Claire L [0000-0002-4176-8329], Scott, Eleanor M [0000-0001-5395-8261], Murphy, Helen R [0000-0001-6876-8727], Corcoy, Rosa [0000-0001-5055-6814], and Apollo - University of Cambridge Repository

Subjects
Blood Glucose, Glycated Hemoglobin, Diabetes Mellitus, Type 1, endocrine system diseases, Pregnancy, Blood Glucose Self-Monitoring, Infant, Newborn, Pregnancy Outcome, Humans, nutritional and metabolic diseases, Female, Biomarkers
Abstract

Objective: The optimal method of monitoring glycemia in pregnant women with type 1 diabetes remains controversial. This study aimed to assess the predictive performance of HbA1c, continuous glucose monitoring (CGM) metrics, and alternative biochemical markers of glycemia to predict obstetric and neonatal outcomes. Methods: 157 women from the CGM in pregnant women with type 1 diabetes trial (CONCEPTT) were included in this pre-specified secondary analysis. HbA1c, CGM data, and alternative biochemical markers (glycated CD59, 1,5 anhydroglucitol, fructosamine and glycated albumin) were compared at approximately 12, 24 and 34 weeks gestation using logistic regression and ROC curves to predict pregnancy complications (pre-eclampsia, preterm delivery, large-for-gestational-age, neonatal hypoglycemia, admission to neonatal intensive care unit). Results: HbA1c, CGM metrics, and alternative laboratory markers were all significantly associated with obstetric and neonatal outcomes at 24 weeks gestation. More outcomes were associated with CGM metrics during the 1st trimester and with laboratory markers (area under ROC generally 140 mg/dl; >7.8 mmol/l) were the most consistently predictive CGM metrics. HbA1c was also a consistent predictor of suboptimal pregnancy outcomes. Some alternative laboratory markers showed promise, but overall, they had lower predictive ability than HbA1c. Conclusions: HbA1c is still an important biomarker for obstetric and neonatal outcomes in type 1 diabetes pregnancy. Alternative biochemical markers of glycemia and other CGM metrics did not substantially increase the prediction of pregnancy outcomes compared to widely available HbA1c and increasingly available CGM metrics (TIR and TAR).

Published
2021

11. Gestational Diabetes Mellitus and Diet: A Systematic Review and Meta-analysis of Randomized Controlled Trials Examining the Impact of Modified Dietary Interventions on Maternal Glucose Control and Neonatal Birth Weight

Author

Yamamoto, Jennifer M., primary, Kellett, Joanne E., additional, Balsells, Montserrat, additional, García-Patterson, Apolonia, additional, Hadar, Eran, additional, Solà, Ivan, additional, Gich, Ignasi, additional, van der Beek, Eline M., additional, Castañeda-Gutiérrez, Eurídice, additional, Heinonen, Seppo, additional, Hod, Moshe, additional, Laitinen, Kirsi, additional, Olsen, Sjurdur F., additional, Poston, Lucilla, additional, Rueda, Ricardo, additional, Rust, Petra, additional, van Lieshout, Lilou, additional, Schelkle, Bettina, additional, Murphy, Helen R., additional, and Corcoy, Rosa, additional

Published
2018
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