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NIPT / Verifi

Prenatal Screening Test - Verifi

Verifi is a non-invasive prenatal genomic test (NIPT) to screen for trisomies 21, 18 and 13. Available from the 10th week of pregnancy, it can optionally predict the sex of the fetus and detect sex chromosome aneuploidy. This genomic test requires a blood sample, also known as venipuncture, and uses sequencing technology to provide precise information to pregnant patients, regardless of their age. Compared with traditional biochemical screening tests, it offers a higher detection rate for trisomies and a lower number of false positives, thereby avoiding unnecessary invasive procedures.
A positive result to the Verifi test indicates a high risk of having a baby with trisomy. A positive predictive value (PPV) is associated with the positive result. This value is established based on specific characteristics of the patient, including her age. This PPV is expressed as a percentage and indicates the probability that the positive result actually points to a high risk of trisomy. This means a diagnostic test is necessary to confirm the presence of trisomy. In contrast, a negative result indicates a low risk of having a baby with trisomy. However, this result does not guarantee the absence of chromosomal abnormality.

Although the Verifi test is recommended for all pregnant people who wish to know their risk of having a baby with genetic abnormalities, certain factors make prenatal screening even more important. :

  • Individual who previously carried a baby with trisomy 21, 18 or 13
  • Individual aged 40 or over at the time of childbirth
  • Maternal anxiety
  • Pregnancy with twins
Biron sets itself apart

Non-invasive prenatal genetic screening

For peace of mind when it comes to your baby’s health

  • Detects the main trisomy’s (21, 18 and 13)
  • Determines the sex of the fetus (optional)

A medical prescription is required for this test.

Laboratory, Sampling and Nursing Care


Term of the Week

Predictive medicine

Medicine that links medical knowledge with data to predict a patient’s potential health problems. Examples include artificial intelligence and genetics.