The challenge of estimating the prevalence and predictors of gestational diabetes mellitus in St. Vincent and the Grenadines
Bibliographic record
Abstract
Background: Gestational diabetes mellitus (GDM) is a disease which results in numerous consequences for both pregnant women and their infants.Objective: The study aimed to estimate the prevalence of gestational diabetes and determine the predictors associated with the development of gestational diabetes in a population of pregnant women in the Caribbean island of St. Vincent and the Grenadines (SVG).Methods: A retrospective study was performed from August to October 2011 at 29 antenatal clinics throughout SVG using perinatal and antenatal records for 454 pregnant women who had singleton pregnancies.Statistical analyses of continuous and categorical variables were performed using t test and chi square test respectively to compare differences between pregnant women with impaired glucose tolerance (IGT) and GDM and women without IGT and GDM.Fisher's exact test was used for analyses involving small numbers.Results: Of the 454 pregnant women, only 11 had a documented oral glucose tolerance test (OGTT).Of these 11, 5 women had IGT and 2 had GDM.Significant predictors for the development of GDM were higher first documented weight (p < 0.001), higher last documented weight (p < 0.001), having a previous stillborn (p = 0.030) and a past medical history of a reproductive tract surgery (p = 0.005).Predictors that showed a tendency were higher prepregnancy weight (p = 0.056) and a previous caesarean section (p = 0.055).The significant pregnancy outcomes were a higher neonate birth weight (p = 0.002) and macrosomia (p = 0.002).Large quantities of missing data were present particularly for maternal height and pre-pregnancy weight limiting conclusions.Heights were missing for 71% of women with IGT/GDM and 66% of women without the conditions.There was 71% missing data for pre-pregnancy weight for those with IGT/GDM and 55% for women without IGT/GDM.Conclusion: Predictors associated with GDM were a higher first and last documented weight, having a previous stillborn and reproductive tract surgery and the associated pregnancy outcomes were increasing neonatal birth weight particularly a neonate birth weight greater than 4000 grams.The prevalence of gestational diabetes in St. Vincent and the Grenadines remains unknown as there is no routine screening. Keywords: gestational diabetes mellitus, St. Vincent and the Grenadines, prevalence, predictors Professor Katherine Gray-Donald, I particularly want to thank you for your guidance, support and supervision during my two years at McGill University; I couldn't have asked for a better supervisor.You have always risen above and beyond your call of duty as a supervisor.To my committee members Drs.Timothy Johns
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".