Compliance with daily, home-based collection of urinary biospecimens in a prospective, preconception cohort
Cox et al.
The finding, in our words
In a prospective preconception cohort, participants correctly collected 82% of expected female urine samples and 59% of male samples on investigator-identified days, with high agreement between participants and expert reviewers on fertile window timing. This demonstrates that intensively scheduled, biologically triggered, at-home urine collection can be successfully targeted to the periconceptional window and completed in longitudinal research.
A paraphrase to the Library’s standard, never the abstract. The source is one link away and is always the authority.
In a large real-world cohort of pregnancy planners using home urine tests, sensitivity was lower than expected before the expected period, with false negatives of 12.7% at 2 days, 21.4% at 3 days and 46.4% at 4 days before menses; sensitivity rose sharply thereafter to over 99% by 4 days after the expected period, and for any given test day, longer menstrual cycles were associated with higher sensitivity, especially among early testers.
The Mira fertility monitor's LH surge and urine E1-3G levels correlated strongly with the ClearBlue Fertility Monitor's LH surge and low-to-high shift in both postpartum and perimenopause transitions, supporting at-home urine hormone monitoring for fertility tracking.
All five at-home urine ovulation predictor kits demonstrated high accuracy (92–97%) when compared with blood LH levels, though sensitivity varied widely from 38% to 77% with Clinical Guard the lowest. Patient experience was comparable across kits, though Clinical Guard was slightly less favoured for future use.
This retrospective case series found that a protocol combining home-based urinary hormone testing with a smartphone application supported fertility management and family planning without unintended pregnancies. The findings suggest that integrating self-collected urinary data with digital tools offers a viable decentralised approach for ovulation prediction.
In subfertile women, urinary microbiota profiles correlated strongly with vaginal profiles but contained fewer species, indicating that vaginal sampling is preferable for predicting fertility treatment outcomes.