Cost-effectiveness of the sFlt-1/PlGF ratio test in pregnant patients with suspected Pre-eclampsia: A Systematic Review
Bibliographic record
Abstract
Background: Pre-eclampsia (PE) affects approximately 2-4% of pregnancies. Diagnosis involves repeated assessment of pregnant patients with risk factors. The sFlt-1/PlGF ratio test is shown to have clinical utility in ruling in and out PE among at-risk patients. By excluding the probability of PE, the addition of the sFlt-1/PlGF ratio test to antenatal care, may prevent unnecessary hospital admissions, intensive management, and premature delivery, thus reducing costs. Objectives: A systematic review to determine the cost-effectiveness of the sFlt-1/PlGF ratio test globally for pregnant patients at-risk of developing PE. Search Strategy: PubMed, Medline (OVID), National Health Service Economic Evaluation Database, Web of Science, Econlit, and Cost Effectiveness Analysis Registry searched between 2013-April 2023. Selection Criteria: Empirical studies quantifying costs of the sFlt-1/PlGF ratio test compared to other treatment options for patients with suspected PE. Data collection and Analysis: Eleven studies were included; all were cost analyses and modelled economic evaluations, and most used a health system perspective. Cost data were extracted and indexed to 2022 United States Dollars (USD). Main results: All studies reported “cost-savings” of the test in antenatal care. Studies varied with costs and assumptions included, therefore a large range of incremental cost savings per patient was reported ($15-$1,881, 2022USD). No Incremental Cost-Effectiveness Ratios or health outcomes including Quality Adjusted Life Years were reported. Conclusions: The included studies demonstrated “cost-savings” of the sFlt-1/PlGF ratio test in antenatal care for at-risk pregnant patients. However, this does not account for health outcome differences and long-term health care utilisation and expenditure. Funding: Nil
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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 | 0.006 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.011 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".