DR. KURTZMAN is Associate Professor, Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of California, Irvine Medical Center, Irvine, CA.

James Kurtzman, MD

Using traditional risk factors to screen for PTD is clearly inadequate. In fact, such screening fails to identify up to 

 of patients who delivered at less than 37 weeks' gestation.

  Similarly, screening for demographic, social, and medical risk factors for PTD has had limited effectiveness.

  Complicating matters even further, in approximately 80% of cases in which signs and symptoms of preterm labor are present, PTD does not occur.

On a more positive note, newer biologic markers for PTD, including fetal fibronectin (fFN) in cervicovaginal secretions and shortened cervical length (CL), as determined by ultrasound, have been more closely linked to PTD.

  With that in mind, our goal here is to introduce the concept of a multifactorial delivery probability profile (DPP) that has the potential to predict PTD using these newer markers. 

Setting the groundwork for the Delivery Probability Profile 

 Several studies have confirmed that the presence of fFN in cervicovaginal secretions between 22 and 34 weeks' gestation is associated with PTD in symptomatic

  women. In the Preterm Prediction Study, patients with a positive fFN at 24 weeks' were 59.2 times more likely to deliver within 4 weeks, and fFN identified nearly two thirds of patients destined to deliver in this time period.

  The relative risk for spontaneous PTD when fFN was present was greater than with any other risk factor at each point in time during pregnancy (Table 1).

  Additionally, though a history of prior PTD was an independent risk factor for recurrent PTD, the presence of fFN was three times more likely to predict recurring PTD than history alone.

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Can a "Delivery Probability Profile" help ob/gyns determine who's most likely to deliver prematurely? One expert in the field examines the evidence.

James Kurtzman, MD

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The Delivery Probability Profile: A new tool to predict PTD?