Improving antenatal detection of small‐for‐gestational‐age fetus: economic evaluation of Growth Assessment Protocol
Bibliographic record
Abstract
OBJECTIVE: To determine whether the Growth Assessment Protocol (GAP), as implemented in the DESiGN trial, is cost-effective in terms of antenatal detection of small-for-gestational-age (SGA) neonate, when compared with standard care. METHODS: This was an incremental cost-effectiveness analysis undertaken from the perspective of a UK National Health Service hospital provider. Thirteen maternity units from England, UK, were recruited to the DESiGN (DEtection of Small for GestatioNal age fetus) trial, a cluster randomized controlled trial. Singleton, non-anomalous pregnancies which delivered after 24 + 0 gestational weeks between November 2015 and February 2019 were analyzed. Probabilistic decision modeling using clinical trial data was undertaken. The main outcomes of the study were the expected incremental cost, the additional number of SGA neonates identified antenatally and the incremental cost-effectiveness ratio (ICER) (cost per additional SGA neonate identified) of implementing GAP. Secondary analysis focused on the ICER per infant quality-adjusted life year (QALY) gained. RESULTS: The expected incremental cost (including hospital care and implementation costs) of GAP over standard care was £34 559 per 1000 births, with a 68% probability that implementation of GAP would be associated with increased costs to sustain program delivery. GAP identified an additional 1.77 SGA neonates per 1000 births (55% probability of it being more clinically effective). The ICER for GAP was £19 525 per additional SGA neonate identified, with a 44% probability that GAP would both increase cost and identify more SGA neonates compared with standard care. The probability of GAP being the dominant clinical strategy was low (11%). The expected incremental cost per infant QALY gained ranged from £68 242 to £545 940, depending on assumptions regarding the QALY value of detection of SGA. CONCLUSION: The economic case for replacing standard care with GAP is weak based on the analysis reported in our study. However, this conclusion should be viewed taking into account that cost-effectiveness analyses are always limited by the assumptions made. © 2022 The Authors. 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 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 | 0.090 | 0.175 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.006 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.016 | 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".