Evidence map›Paper›PMID 33678196›Full record

ArticleDiagnostic and prognostic research2021

Diabetes after pregnancy: a study protocol for the derivation and validation of a risk prediction model for 5-year risk of diabetes following pregnancy.

Stephanie H Read, Laura C Rosella, Howard Berger, Denice S Feig, Karen Fleming, Padma Kaul, Joel G Ray, Baiju R Shah, Lorraine L Lipscombe

Open access · goldAbstract read
In one paragraph

Article in Diagnostic and prognostic research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.9field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Pregnancy as an opportunity to prevent type 2 diabetes mellitus: FIGO Best Practice Advice.International journal of gynaecology and obstetrics: the official organ of the International Federation of Gynaecology and Obstetrics · 2023
    Review
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Stephanie H ReadWomen's College Research Institute, Women's College Hospital, 76 Grenville Street, Toronto, Ontario, M5S 1B2, Canada. Steph.Read@hotmail.com.ORCID http://orcid.org/0000-0002-2087-7358
Laura C RosellaInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Howard BergerDivision of Maternal-Fetal Medicine, St. Michael's Hospital, Toronto, Ontario, Canada.
Denice S FeigInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Karen FlemingDepartment of Family and Community Medicine, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
Padma KaulFaculty of Medicine and Dentistry, University of Alberta, Edmonton, Alberta, Canada.
Joel G RayInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Baiju R ShahInstitute for Clinical Evaluative Sciences, Toronto, Ontario, Canada.
Lorraine L LipscombeWomen's College Research Institute, Women's College Hospital, 76 Grenville Street, Toronto, Ontario, M5S 1B2, Canada.
St. Michael's Hospital · CAUniversity of Toronto · CACeres · USSunnybrook Health Science Centre · CAUniversity of Alberta · CA

Funding

Physicians' Services Incorporated Foundation 19-23
6 · The paper itself

Abstract

backgroundPregnancy 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.

methodsData 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: 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.

Indexed as

Prediction modelPregnancyPrognosisRiskStudy protocolType 2 diabetes mellitus

Identifiers

PMID33678196
PMCPMC7938478
OpenAlexW3135659546

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.