Immortal Time Bias in the Study of Stillbirth Risk Factors
Bibliographic record
Abstract
BACKGROUND: Current understanding of the increased risk for stillbirth in gestational diabetes mellitus is often based on large cohort studies in which the risk of stillbirth in women with this disease is compared with the risk in women without. However, such studies could be susceptible to immortal time bias because, although many cohorts begin at 20 weeks' gestation, pregnancies must "survive" until 24-28 weeks in order to be screened and diagnosed with gestational diabetes. METHODS: We describe the theoretical potential for immortal time bias in studies of stillbirth and gestational diabetes and then quantify the magnitude of the bias using 2006 United States vital statistics data. RESULTS: Although gestational diabetes was protective against stillbirth when including all births (relative risk = 0.88 [95% confidence interval = 0.79-0.99]), restricting analyses to births at >28 weeks' gestation reversed the effect and diabetes became associated with an increased risk of stillbirth (1.25 [1.11-1.41]). CONCLUSION: Immortal time before diagnosis of gestational diabetes may bias our understanding of the stillbirth risk associated with this condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".