Abstract
INTRODUCTION: It is still difficult to predict the outcome of preeclampsia and determine the individual procedure with regards to the time of birth. Cut-offs of the sFlt-1/PlGF ratio with a high risk for imminent delivery have been previously published and analyzed by our study group, but could not be confirmed. The aim of the current study is to re-evaluate the described cut-off values again in a new period of time.
MATERIALS AND METHODS: We performed a retrospective analysis (IRB 1279/2020) including all preeclampsia patients delivering in our department over a 3-year period. Patients were divided into 2 groups - gestational week 24+0-33+6 with an s-Flt1/PlGF > 655.2 and 34+0-37+0 weeks with an sFlt-1/PlGF > 201 and were compared with preeclampsia patients of the same weeks with sFlt-1/PlGF values below the described cut-offs. Correlation between sFlt-1/PlGF ratio and time to delivery was assessed.
RESULTS: The association between sFlt-1/PlGF above the threshold and delivery within 48 h is significant for the high ratio early group (p < 0.01) but not for the high ratio late group (p = 0.62). In the early group, 60% of patients with sFlt-1/PlGF > 655.2 but only 8% in the low ratio group delivered within 48 h. In both the early and the late preeclampsia group, a high number of patients remained pregnant even though they showed elevated ratios.
CONCLUSION: High sFlt-1/PlGF ratios seem to correlate with a shorter pregnancy duration to some extent. Nevertheless, not all patients need to be delivered within 48 h, so the decision should never be based on the laboratory test alone.
| Translated title of the contribution | Risiko für eine drohende Entbindung bei Präeklampsie basierend auf dem sFlt-1/PlGF-Quotienten: Brauchen wir neue Grenzwerte? |
|---|---|
| Original language | English |
| Pages (from-to) | 190-199 |
| Number of pages | 10 |
| Journal | Geburtshilfe und Frauenheilkunde |
| Volume | 85 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - Feb 2025 |
Fields of science
- 302022 Gynaecology
- 101018 Statistics
- 502051 Economic statistics
- 105108 Geostatistics
- 302 Clinical Medicine
- 302017 Obstetrics
- 101029 Mathematical statistics
- 102009 Computer simulation
- 101026 Time series analysis
- 303 Health Sciences
- 304 Medical Biotechnology
- 101024 Probability theory
- 102037 Visualisation
- 303007 Epidemiology
- 303040 Health services research
- 502025 Econometrics
- 504006 Demography
- 305907 Medical statistics
- 504004 Population statistics
- 509013 Social statistics
- 509 Other Social Sciences
- 102035 Data science
- 301 Medical-Theoretical Sciences, Pharmacy
- 302014 Endocrinology
- 106007 Biostatistics
- 305 Other Human Medicine, Health Sciences
- 504007 Empirical social research
- 101007 Financial mathematics
- 302081 Thoracic surgery
- 302018 Vascular surgery
- 302026 Heart surgery
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- Sustainable Development: Responsible Technologies and Management
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