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Published on: August 7, 2018
Validation Study of a Photo-Based Menstrual Blood Loss Metric
Jacqueline Fahey1, Ram K Parvataneni1, L Elaine Waetjen1
1Department of Obstetrics and Gynecology, David Geffen School of Medicine at UCLA, Los Angeles, California; Department of Obstetrics and Gynecology, UC Davis School of Medicine, Sacramento, California; and Department of Obstetrics, Gynecology, and Reproductive Sciences, UC San Francisco School of Medicine, San Francisco, California.
A new photo-based method accurately quantifies menstrual blood loss, offering a practical alternative to the standard alkaline hematin test for diagnosing heavy menstrual bleeding.
Area of Science:
- Gynecology and Reproductive Health
- Medical Imaging and Diagnostics
- Biomedical Engineering
Background:
- Heavy menstrual bleeding (HMB) affects millions of women globally.
- Current diagnostic methods, like the alkaline hematin method, are invasive and cumbersome.
- There is a need for accessible, objective tools to quantify menstrual blood loss.
Purpose of the Study:
- To validate an objective, photo-based electronic method for quantifying menstrual blood loss.
- To compare the accuracy of this novel method against the gold standard alkaline hematin method.
- To assess the utility of the photo-based method in diagnosing HMB.
Main Methods:
- A multicenter, prospective cohort study involving 79 premenopausal women with self-reported HMB.
- Participants used smartphone-captured images of menstrual pads for analysis.
- A photo-based smartphone application quantified blood loss volume, compared to the alkaline hematin method.
Main Results:
- The photo-based method showed strong correlation with the alkaline hematin standard (R²=0.75 per pad, R²=0.83 per cycle).
- High agreement with minimal bias was observed.
- The method demonstrated 100% sensitivity and 93.5% specificity for diagnosing HMB (≥80 mL/cycle).
Conclusions:
- The photo-based method is a valid, practical, and accessible alternative for quantifying menstrual blood loss.
- It enables accurate diagnosis and monitoring of HMB in clinical and research settings.
- This technology can improve HMB management and patient outcomes.
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