How PAG Testing Helps Predict Dairy Cow Pregnancy Loss
Pregnancy loss continues to be one of the most discouraging reproductive challenges in dairy herds. Although it is not a new issue, modern diagnostic tools have revealed far more about its true frequency.
Historically, pregnancy checks were typically done by palpation around 35 to 45 days after breeding. By that time, most early embryonic losses had already occurred, so cows diagnosed open were generally thought never to have conceived.
With today’s advanced options—such as ultrasound and blood-based detection tests—producers can confirm pregnancies much earlier. This provides meaningful advantages, including identifying non-pregnant cows sooner and reinseminating them to reduce days open, ultimately boosting herd profitability.
However, these tools have also exposed a troubling reality: many cows do conceive, only to lose pregnancy during the earliest stages of development. Research shows that roughly 30% of confirmed pregnancies fail before calving, with most losses occurring before day 28 of gestation. These early losses often stem from embryo development problems.
Pregnancy failures can still occur later in gestation as well. Studies have documented losses ranging from 3.2% to more than 40% after the first month, typically tied to complications in placental development or function. Many diagnostic tests used today—including BioPRYN, DG29, and IDEXX—work by detecting placental glycoproteins circulating in the cow bloodstream.
A recent study of more than 400 lactating Holstein cows in Brazil demonstrated the value of tracking these glycoproteins. Pregnancy was confirmed at day 31 using ultrasound. By day 59, 12% of those cows had lost their pregnancies, and another 7% experienced loss later, for a total rate of 19%. Cows that carried pregnancies successfully had higher levels of pregnancy-associated glycoproteins (PAG) at day 31.
Researchers found that using a PAG cutoff value allowed them to predict future pregnancy loss with up to 95% accuracy. This could significantly influence herd management by identifying cows at greater risk, enabling closer monitoring and timely interventions to support reproductive performance and overall productivity.
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