Prospective Study Evaluating the Association Between sFlt-1/PlGF Ratio and Adverse Outcomes in Preterm Preeclampsia
Bibliographic record
Abstract
OBJECTIVES: To estimate the association between maternal soluble Fms tyrosine kinase 1 to placental growth factor (sFlt-1/PlGF) ratio and adverse outcomes related to preterm preeclampsia. METHODS: weeks of gestation. The sFlt-1/PlGF ratio was measured in maternal serum at admission and was reported according to pregnancy outcomes (delivery in <7 days after admission, severe preeclampsia before term, and serious complications, including stillbirth; eclampsia; hemolysis, elevated liver enzymes, and low platelet syndrome; and acute renal failure). Receiver-operator characteristics curve analyses using the Youden index were used to determine optimal sFlt-1/PlGF ratio thresholds. RESULTS: weeks; IQR 31-36), 373 (80%) delivered in <7 days after admission; 387 (83%) developed severe preeclampsia before term, including 18 (4%) with serious complications. Three sFlt-1/PlGF threshold values were identified: 68, 250, and 500. SFlt-1/PlGF ratios less than 68, between 68 and 249, between 250 and 299, and ≥500 were associated with delivery in <7 days after admission (in 54%, 73%, 88%, and 91%, respectively, P < 0.001), with severe preeclampsia before term (in 51%, 77%, 86%, and 88%, respectively, P < 0.001) and with serious complications (in 0%, 0%, 3%, and 8%, respectively, P < 0.001). The higher the ratio, the lower the interval between admission and birth (4 days [IQR 0-21], 1 [IQR 0-8], 0.5 [IQR 0-2], and 0 [IQR 0-2], respectively, P < 0.01). CONCLUSIONS: Among women with preterm preeclampsia, an sFlt-1/PlGF ratio >250 is associated with short admission to delivery interval, severe preeclampsia, and serious complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".