Cargando…

Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach

BACKGROUND: Characterizing maternal glucose sampling over the course of the entire pregnancy is an important step toward improvement in prediction of adverse birth outcome, such as preterm birth, for women with type 1 diabetes mellitus (T1DM). OBJECTIVES: To characterize the relationship between the...

Descripción completa

Detalles Bibliográficos
Autores principales: Gupta, Resmi, Khoury, Jane C., Altaye, Mekibib, Jandarov, Roman, Szczesniak, Rhonda D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333058/
https://www.ncbi.nlm.nih.gov/pubmed/32685553
http://dx.doi.org/10.1155/2020/3074532
_version_ 1783553668733206528
author Gupta, Resmi
Khoury, Jane C.
Altaye, Mekibib
Jandarov, Roman
Szczesniak, Rhonda D.
author_facet Gupta, Resmi
Khoury, Jane C.
Altaye, Mekibib
Jandarov, Roman
Szczesniak, Rhonda D.
author_sort Gupta, Resmi
collection PubMed
description BACKGROUND: Characterizing maternal glucose sampling over the course of the entire pregnancy is an important step toward improvement in prediction of adverse birth outcome, such as preterm birth, for women with type 1 diabetes mellitus (T1DM). OBJECTIVES: To characterize the relationship between the gestational glycemic profile and risk of preterm birth using a joint modeling approach. METHODS: A joint model was developed to simultaneously characterize the relationship between a longitudinal outcome (daily blood glucose sampling) and an event process (preterm birth). A linear mixed effects model using natural cubic splines was fitted to predict the longitudinal submodel. Covariates included mother's age at last menstrual period, age at diabetes onset, body mass index, hypertension, retinopathy, and nephropathy. Various association structures (value, value plus slope, and area under the curve) were examined before selecting the final joint model. We compared the joint modeling approach to the time-dependent Cox model (TDCM). RESULTS: A total of 16,480 glucose readings over gestation (range: 50-260 days) with 32 women (28%) having preterm birth was included in the study. Mother's age at last menstrual period and age at diabetes onset were statistically significant (beta = 1.29, 95% CI 1.10, 1.72; beta = 0.84, 95% CI 0.62, 0.98) for the longitudinal submodel, reflecting that older women tended to have higher mean blood glucose and those with later diabetes onset tended to have a lower mean blood glucose level. The presence of nephropathy was statistically significant in the event submodel (beta = 2.29, 95% CI 1.05, 4.48). Cumulative association parameterization provided the best joint model fit. The joint model provided better fit compared to the time-dependent Cox model (DIC (JM) = 19,895; DIC (TDCM) = 19,932). CONCLUSION: The joint model approach was able to simultaneously characterize the glycemic profile and assess the risk of preterm birth and provided additional insights and a better model fit compared to the time-dependent Cox model.
format Online
Article
Text
id pubmed-7333058
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher Hindawi
record_format MEDLINE/PubMed
spelling pubmed-73330582020-07-16 Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach Gupta, Resmi Khoury, Jane C. Altaye, Mekibib Jandarov, Roman Szczesniak, Rhonda D. J Diabetes Res Research Article BACKGROUND: Characterizing maternal glucose sampling over the course of the entire pregnancy is an important step toward improvement in prediction of adverse birth outcome, such as preterm birth, for women with type 1 diabetes mellitus (T1DM). OBJECTIVES: To characterize the relationship between the gestational glycemic profile and risk of preterm birth using a joint modeling approach. METHODS: A joint model was developed to simultaneously characterize the relationship between a longitudinal outcome (daily blood glucose sampling) and an event process (preterm birth). A linear mixed effects model using natural cubic splines was fitted to predict the longitudinal submodel. Covariates included mother's age at last menstrual period, age at diabetes onset, body mass index, hypertension, retinopathy, and nephropathy. Various association structures (value, value plus slope, and area under the curve) were examined before selecting the final joint model. We compared the joint modeling approach to the time-dependent Cox model (TDCM). RESULTS: A total of 16,480 glucose readings over gestation (range: 50-260 days) with 32 women (28%) having preterm birth was included in the study. Mother's age at last menstrual period and age at diabetes onset were statistically significant (beta = 1.29, 95% CI 1.10, 1.72; beta = 0.84, 95% CI 0.62, 0.98) for the longitudinal submodel, reflecting that older women tended to have higher mean blood glucose and those with later diabetes onset tended to have a lower mean blood glucose level. The presence of nephropathy was statistically significant in the event submodel (beta = 2.29, 95% CI 1.05, 4.48). Cumulative association parameterization provided the best joint model fit. The joint model provided better fit compared to the time-dependent Cox model (DIC (JM) = 19,895; DIC (TDCM) = 19,932). CONCLUSION: The joint model approach was able to simultaneously characterize the glycemic profile and assess the risk of preterm birth and provided additional insights and a better model fit compared to the time-dependent Cox model. Hindawi 2020-06-24 /pmc/articles/PMC7333058/ /pubmed/32685553 http://dx.doi.org/10.1155/2020/3074532 Text en Copyright © 2020 Resmi Gupta et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gupta, Resmi
Khoury, Jane C.
Altaye, Mekibib
Jandarov, Roman
Szczesniak, Rhonda D.
Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title_full Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title_fullStr Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title_full_unstemmed Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title_short Assessing the Relationship between Gestational Glycemic Control and Risk of Preterm Birth in Women with Type 1 Diabetes: A Joint Modeling Approach
title_sort assessing the relationship between gestational glycemic control and risk of preterm birth in women with type 1 diabetes: a joint modeling approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7333058/
https://www.ncbi.nlm.nih.gov/pubmed/32685553
http://dx.doi.org/10.1155/2020/3074532
work_keys_str_mv AT guptaresmi assessingtherelationshipbetweengestationalglycemiccontrolandriskofpretermbirthinwomenwithtype1diabetesajointmodelingapproach
AT khouryjanec assessingtherelationshipbetweengestationalglycemiccontrolandriskofpretermbirthinwomenwithtype1diabetesajointmodelingapproach
AT altayemekibib assessingtherelationshipbetweengestationalglycemiccontrolandriskofpretermbirthinwomenwithtype1diabetesajointmodelingapproach
AT jandarovroman assessingtherelationshipbetweengestationalglycemiccontrolandriskofpretermbirthinwomenwithtype1diabetesajointmodelingapproach
AT szczesniakrhondad assessingtherelationshipbetweengestationalglycemiccontrolandriskofpretermbirthinwomenwithtype1diabetesajointmodelingapproach