PREPARE: protocol for a stepped wedge trial to evaluate whether a risk stratification model can reduce preterm deliveries among women with suspected or confirmed preterm pre-eclampsia
Bibliographic record
Abstract
BACKGROUND: Preeclampsia (PE) is a major cause of short and long-term morbidity for affected infants, including consequences of fetal growth restriction and iatrogenic prematurity. In Brazil, this is a special problem as PE accounts for 18% of preterm births (PTB). In the PREPARE (Prematurity REduction by Pre-eclampsia cARE) study, we will test a novel system of integrated care based on risk stratification and knowledge transfer, to safely reduce PTB. METHODS: This is a stepped wedge cluster randomised trial that will include women with suspected or confirmed PE between 20 + 0 and 36 + 6 gestational weeks. All pregnant women presenting with these findings at seven tertiary centres in geographically dispersed sites, throughout Brazil, will be considered eligible and evaluated in terms of risk stratification at admission. At randomly allocated time points, sites will transition to risk stratification performed according to sFlt-1/PlGF (Roche Diagnostics) measurement and fullPIERS score with both results will be revealed to care providers. The healthcare providers of women stratified as low risk for adverse outcomes (sFlt-1/PlGF ≤38 AND fullPIERS< 10% risk) will receive the recommendation to defer delivery. sFlt-1/PlGF will be repeated once and fullPIERS score twice a week. Rates of prematurity due to preeclampsia before and after the intervention will be compared. Additionally, providers will receive an active program of knowledge transfer about WHO recommendations for preeclampsia, including recommendations regarding antenatal corticosteroids for foetal benefits, antihypertensive therapy and magnesium sulphate for seizure prophylaxis. This study will have 90% power to detect a reduction in PTB associated with PE from a population estimate of 1.5 to 1.0%, representing a 33% risk reduction, and 80% power to detect a reduction from 2.0 to 1.5% (25% risk reduction). The necessary number of patients recruited to achieve these results is 750. Adverse events, serious adverse events, both anticipated and unanticipated will be recorded. DISCUSSION: The PREPARE intervention expects to reduce PTB and improve care of women with PE without significant adverse side effects. If successful, this novel pathway of care is designed for rapid translation to healthcare throughout Brazil and may be transferrable to other low and middle income countries. TRIAL REGISTRATION: ClinicalTrials.gov : NCT03073317.
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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 | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.005 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.119 | 0.016 |
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".