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Comparing the results from a Swedish pregnancy cohort using data from three automated placental growth factor immunoassay platforms intended for first-trimester preeclampsia prediction.

Ylva CarlssonAnna SandströmLina BergmanPeter ConnerStefan HanssonMarius KublickaUzay GörmüşPeter LindgrenGöran OlerödAnna-Karin WikströmAnders Larsson
Published in: Acta obstetricia et gynecologica Scandinavica (2023)
The three PlGF methods have different calibrations. This is most likely due to the lack of an internationally accepted reference material for PlGF. Despite different calibrations, the Deming regression analysis indicated good agreement between the three methods, which suggests that results from one method may be converted to the others and hence used in first-trimester prediction models for preeclampsia.
Keyphrases
  • growth factor
  • pregnancy outcomes
  • early onset
  • machine learning
  • electronic health record
  • high throughput
  • big data
  • pregnant women
  • preterm birth
  • sensitive detection
  • artificial intelligence