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Laboratory methods for evaluating early pregnancy loss in an industry-based population
B L Lasley1, P Lohstroh, A Kuo
1Institute of Toxicology and Environmental Health, School of Medicine, University of California, Davis 95616-8615, USA.
American Journal of Industrial Medicine
|December 1, 1995
Summary
This study effectively used screening assays for human chorionic gonadotropin (hCG) to identify early pregnancy loss. Combining screening with definitive tests and hormone analysis improved detection accuracy in daily urine samples.
Area of Science:
- Reproductive Endocrinology
- Biomarker Analysis
- Occupational Health
Background:
- Analyzing large volumes of daily urine samples presents logistical challenges.
- Accurate detection of early pregnancy and fetal loss is crucial for reproductive health studies.
Purpose of the Study:
- To develop and validate efficient laboratory methods for analyzing daily urine samples.
- To assess the effectiveness of screening assays for human chorionic gonadotropin (hCG) in identifying conception and early fetal loss.
- To evaluate the utility of multiple urinary biomarkers in detecting nonconceptive hCG-positive cycles.
Main Methods:
- Adapted and developed laboratory assays for approximately 70,000 daily urine samples across 2,500+ menstrual cycles.
- Employed an immunoenzymometric assay (IEMA) for initial screening of human chorionic gonadotropin (hCG).
- Confirmed hCG presence using a definitive immunoradiometric assay (IRMA) and analyzed ovarian and pituitary hormones.
Main Results:
- The IEMA screening assay eliminated 78% of cycles, optimizing resource allocation.
- 38 out of 448 cycles were confirmed hCG-positive by IRMA.
- 17 of the 38 hCG-positive cycles were identified as nonconceptive after further evaluation.
Conclusions:
- Screening assays for hCG are effective in optimizing laboratory workflows for large-scale sample analysis.
- Utilizing multiple urinary biomarkers alongside definitive hCG testing is essential for accurately detecting early fetal loss.
- This approach enhances the understanding of reproductive events in women working in the semiconductor industry.