Universal cervical‐length screening to prevent preterm birth in twin pregnancy: cost‐utility analysis
Bibliographic record
Abstract
OBJECTIVE: The purpose of this cost-utility analysis was to model the clinical and economic impact of three cervical-length screening strategies among low-risk twin pregnancies: two-step universal screening (at 18-20 and 20-22 weeks), one-step universal screening (at 18-20 weeks) and no screening. METHODS: This study used a decision-analytic model (decision tree and cohort state transition model) with a 100-year time horizon in a Canadian context. The population included dichorionic diamniotic twin pregnancies without a history of preterm birth or prophylactic progesterone or cerclage. The model assumed that vaginal progesterone was initiated for cervical length ≤ 25 mm and that cervical cerclage was performed plus vaginal progesterone treatment for cervical length ≤ 15mm. The primary outcomes were total lifetime health-related costs (in 2023 Canadian dollars ($)), quality-adjusted life years (QALYs) and incremental cost-effectiveness ratios. Clinical outcomes included the probability of preterm birth (≤ 28 and ≤ 34 weeks), probability of stillbirth and life expectancy. Probabilistic and deterministic sensitivity analyses were carried out. RESULTS: Base-case and probabilistic sensitivity analysis showed that, when compared with no screening, the two-step screening strategy increased the QALYs modestly (0.62 (95% credible interval (CrI), -0.16 to 1.41)) and decreased lifetime costs (-$2460 (95% CrI, -$4850 to $251)) by reducing the rate of preterm birth. The one-step screening strategy, although inferior to the two-step screening strategy, also increased the QALYs and reduced costs. Findings consistent with these were obtained on testing of the model assumptions with deterministic sensitivity analysis. CONCLUSIONS: This cost-utility analysis supports a universal two-step screening strategy for twin pregnancies in a Canadian context. Although the conclusions of this analysis are robust in terms of the sensitivity analysis, more reliable predictions of long-term costs and quality of life require more twin-specific lifetime data. Additionally, cost-utility analyses in other healthcare contexts are needed. © 2025 The Author(s). Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
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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 | 0.000 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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) | 0.000 | 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 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".