Predicting dysglycaemia in individuals with gestational diabetes immediately postpartum using continuous glucose monitoring (PREDISPOSE) in a multicentre prospective cohort study in Canada: a study protocol
Bibliographic record
Abstract
INTRODUCTION: Gestational diabetes is a common metabolic disorder in pregnancy which identifies a substantial increased risk of future diabetes. Despite this risk, many individuals are not screened for dysglycaemia in the postpartum period. Continuous glucose monitoring (CGM) is an evolving technology that provides details of an individual's glucose levels throughout the day; however, it has not yet been evaluated as a screening tool for postpartum dysglycaemia. To address this gap, this prospective cohort study will examine the use of CGM in the early postpartum period to predict the risk of maternal dysglycaemia after delivery. METHODS AND ANALYSIS: The Predicting Dysglycaemia in Individuals with Gestational Diabetes Immediately Postpartum using CGM (PREDISPOSE) study is a prospective cohort study designed to assess the ability of a CGM device (Freestyle Libre 2) worn in the postpartum period to detect persistent dysglycaemia in individuals with gestational diabetes. The study will recruit 240 individuals with gestational diabetes. Each participant will wear the CGM immediately postpartum and before attending routine postpartum diabetes screening, consisting of a 75-gram oral glucose tolerance test (OGTT) and related blood work (haemoglobin A1c (HbA1c), complete blood count and lipid profile). The primary outcome is the accuracy of the area under the curve for all glucose measurements from the first CGM wear to detect postpartum dysglycaemia. We will perform sensitivity and specificity analyses to determine optimal CGM cut-offs to diagnose diabetes or prediabetes. Secondary outcomes include the incidence of postpartum dysglycaemia (based on 75-gram OGTT and/or HbA1c), incidence of postpartum dyslipidaemia, patient acceptability of CGM testing, data variability from CGM and cardiometabolic health outcomes diagnosed in years one, two and five after delivery. ETHICS AND DISSEMINATION: All participating sites have received ethics approval of the current protocol and have started recruitment of participants to the study. The ethics boards that approved this study are the Biomedical Research Ethics Board at the University of Manitoba, the Conjoint Health Research Ethics Board at the University of Calgary, the Mount Sinai Hospital Research Ethics Board at Mount Sinai Hospital and the Comité d'éthique de la Recherche at Université Laval. Study results will be disseminated through conference presentations and publication in a peer-reviewed journal, regardless of study findings. TRIAL REGISTRATION NUMBER: NCT04972955. Registration date: 28 June 2021.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".