Kits and methods to distinguish false labor and true labor
Inventors
TARCA, Adi L. • Chaemsaithong, Piya • Chaiworapongsa, Tinnakorn • Hassan, Sonia S. • Romero, Roberto
Assignees
Wayne State University • US Department of Health and Human Services
Publication Number
US-11906528-B2
Publication Date
2024-02-20
Expiration Date
2036-11-07
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Abstract
Kits and methods to distinguish between false and true labor are provided. The kits and methods can utilize differences in abundance and/or differences in the rate of change in abundance of B7-H2, SORC2, TF, C1-Esterase Inhibitor, Ran, IMDH1 and/or PGAM1, as markers of true labor.
Core Innovation
The invention provides kits and methods to distinguish between false and true labor in pregnant women. This is achieved by utilizing differences in the abundance or the rate of change in abundance of specific biomarkers present in maternal blood plasma, notably including B7-H2, SORC2, TF, C1-Esterase Inhibitor, Ran, IMDH1, and PGAM1. Two principal models are described: one based on the rate of change in protein abundance across at least two time points, and another based on the absolute abundance of markers at a single time point at hospital admission.
The problem addressed is the lack of precise, objective diagnostic tests to distinguish true labor from false labor. Traditional clinical criteria and physical examinations, like the Bishop score and symptoms such as contractions, often result in overdiagnosis or misdiagnosis, especially at term or preterm, leading to unnecessary medical interventions, hospitalizations, and increased healthcare costs. The invention seeks to fill this unmet need for a robust and specific biological marker-based test.
The disclosed methods involve collecting a biological sample (plasma or serum) from a pregnant female experiencing symptoms associated with labor and analyzing the designated markers. For the first model, the rate of change in abundance of B7-H2, SORC2, TF, and C1-Esterase Inhibitor is calculated between two samples collected at different gestational ages, providing a true labor score. For the second model, the abundance levels of TF, Ran, IMDH1, and PGAM1 at the time of admission are compared to reference values. Both models can be used separately or in combination, with validation studies indicating high specificity in predicting true labor.
Claims Coverage
The patent includes three main independent inventive features related to the method of distinguishing between false and true labor by measuring specific biomarkers in pregnant females.
Method for measuring marker abundance in pregnant females presenting with labor symptoms
This feature involves obtaining a biological sample from a pregnant female experiencing symptoms associated with false labor and true labor, and measuring in the sample the abundance of either: - Tissue factor (TF), ICOS Ligand (B7-H2), VPS10 Domain Containing Receptor SorCS2 (SORC2), and Plasma Protease C1 Inhibitor (C1-Esterase Inhibitor), or - TF, Ras-related Nuclear protein (Ran), Inosine-5′-monophosphate dehydrogenase (IMDH1), and Phosphoglycerate mutase 1 (PGAM1).
Calculation of rate of change of marker abundance to identify true labor
This inventive feature entails calculating the rate of change of abundance of TF, B7-H2, SORC2, and C1-Esterase Inhibitor between two samples obtained from the same pregnant female at two different times, and using the calculated rate of change to identify whether the pregnant female is in true labor or false labor. The formula for calculating the rate of change is specified as: (AbundanceT2−AbundanceT1)/(GAT2−GAT1), where GA refers to gestational age in weeks and T1, T2 are two time points.
Calculation of change in abundance compared to reference population
This inventive feature includes calculating changes in abundance of TF, Ran, IMDH1, and PGAM1 as compared to a value derived from a reference population that has not experienced true labor, and using the calculated change in abundance to identify whether the pregnant female is in true labor or false labor. The change in abundance values can also be used in a Linear Discriminant Analysis (LDA) model to derive a true labor score.
In summary, the claims cover methods for distinguishing true from false labor in pregnant women by measuring and analyzing the abundance or rate of change of specific biomarkers, using either a direct measurement at admission or a comparative analysis over time, including mathematical models to derive a true labor score.
Stated Advantages
The kits and methods provide high specificity (as high as 94%) in distinguishing true from false labor, allowing accurate identification of patients unlikely to deliver.
Use of these methods can reduce unnecessary hospital admissions, medical interventions, and healthcare costs associated with misdiagnosis of labor.
The measurement approach reduces patient-to-patient variability by using each patient as their own control through rate of change analysis.
The described models have important clinical implications, as a negative result reliably indicates a low likelihood of imminent delivery, minimizing unnecessary interventions.
Documented Applications
Identifying true labor in pregnant females presenting with symptoms associated with both false and true labor.
Guiding clinical decisions to avoid unnecessary hospitalization and medical interventions in patients unlikely to deliver imminently.
Supporting the diagnosis of true or false labor in conjunction with clinical signs, symptoms, and other labor indicators such as cervical length.
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