Diabetes after pregnancy: a study protocol for the derivation and validation of a risk prediction model for 5-year risk of diabetes following pregnancy.
Prediction model
Pregnancy
Prognosis
Risk
Study protocol
Type 2 diabetes mellitus
Journal
Diagnostic and prognostic research
ISSN: 2397-7523
Titre abrégé: Diagn Progn Res
Pays: England
ID NLM: 101718985
Informations de publication
Date de publication:
08 Mar 2021
08 Mar 2021
Historique:
received:
26
07
2020
accepted:
08
02
2021
entrez:
8
3
2021
pubmed:
9
3
2021
medline:
9
3
2021
Statut:
epublish
Résumé
Pregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman's 5-year risk of developing type 2 DM after pregnancy. Data will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke's R The derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.
Sections du résumé
BACKGROUND
BACKGROUND
Pregnancy offers a unique opportunity to identify women at higher future risk of type 2 diabetes mellitus (DM). In pregnancy, a woman has greater engagement with the healthcare system, and certain conditions are more apt to manifest, such as gestational DM (GDM) that are important markers for future DM risk. This study protocol describes the development and validation of a risk prediction model (RPM) for estimating a woman's 5-year risk of developing type 2 DM after pregnancy.
METHODS
METHODS
Data will be obtained from existing Ontario population-based administrative datasets. The derivation cohort will consist of all women who gave birth in Ontario, Canada between April 2006 and March 2014. Pre-specified predictors will include socio-demographic factors (age at delivery, ethnicity), maternal clinical factors (e.g., body mass index), pregnancy-related events (gestational DM, hypertensive disorders of pregnancy), and newborn factors (birthweight percentile). Incident type 2 DM will be identified by linkage to the Ontario Diabetes Database. Weibull accelerated failure time models will be developed to predict 5-year risk of type 2 DM. Measures of predictive accuracy (Nagelkerke's R
DISCUSSION
CONCLUSIONS
The derived RPM may help identify women at high risk of developing DM in a 5-year period after pregnancy, thus facilitate lifestyle changes for women at higher risk, as well as more frequent screening for type 2 DM after pregnancy.
Identifiants
pubmed: 33678196
doi: 10.1186/s41512-021-00095-6
pii: 10.1186/s41512-021-00095-6
pmc: PMC7938478
doi:
Types de publication
Journal Article
Langues
eng
Pagination
5Subventions
Organisme : Physicians' Services Incorporated Foundation
ID : 19-23
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