Evidence map›Paper›PMID 40260795›Full record

ArticlePhysiological reports2025

Comparison of two ovulation tests to predict timing of the late follicular phase for menstrual cycle research in premenopausal females.

Lindsay A Lew, Kyra E Pyke

Abstract readComparative Study
In one paragraph

Article in Physiological reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Lindsay A LewSchool of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada.ORCID 0000-0002-2294-1587
Kyra E PykeSchool of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada.ORCID 0000-0002-1818-3867

Funding

Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada (NSERC) 2019-04894
6 · The paper itself

Abstract

Menstrual cycle peak estradiol occurs in the late follicular (LF) phase just prior to the luteinizing hormone (LH) surge and ovulation. Therefore, to examine the impact of menstrual cycle estradiol fluctuations, it is desirable to perform assessments closely prior to ovulation. Standard ovulation tests (SOT) identify the LH surge and confirm that ovulation occurred after LF testing. Advanced ovulation tests (AOT) detect a rise in estrogen before the LH surge. We hypothesized that using the AOT to schedule LF testing between the rise in estradiol and LH surge would decrease the LF visit:ovulation interval vs. the SOT. Twenty-one naturally menstruating females (22 ± 4 years) participated in an early follicular (EF) and LF visit. The LF visit scheduling employed an AOT (n = 10) or SOT (n = 11). There was no difference in the LF visit:ovulation interval between tests (AOT = 2.7 ± 2.2 days, SOT = 2.5 ± 1.7 days; p = 0.859). Estradiol increased from the EF to LF phase, regardless of the ovulation test used (phase p < 0.001, test p = 0.528, interaction p = 0.099), and Δestradiol was negatively correlated with LF visit:ovulation interval (r = -0.454, p = 0.050). In this preliminary study, the AOT estrogen signal did not support scheduling the LF visit closer to ovulation or during higher estradiol vs. the SOT. Future studies should explore different methods to identify the menstrual cycle estradiol peak.

Indexed as

Follicular PhaseOvulationOvulation DetectionPremenopauseAdultEstradiolFemaleHumansLuteinizing HormoneMenstrual CycleYoung AdultEstradiolLuteinizing Hormoneestrogenlate follicular phasemenstrual cycleovulation test

Identifiers

PMID40260795
PMCPMC12012743

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.