Litcius/Paper detail

Agreement Between the 2- and 3-Step Methods for Identifying Subtle Menstrual Disturbances

Dionne A. Noordhof, Madison Taylor, Virginia de Martin Topranin, Tina P. Engseth, Øyvind Sandbakk, John O. Osborne

2024International Journal of Sports Physiology and Performance19 citationsDOI

Abstract

Recent methodological recommendations suggest the use of the "3-step method," consisting of calendar-based counting, urinary ovulation testing, and serum blood sampling, for the identification of subtle menstrual disturbances (SMDs). However, the use of the 3-step method is not always feasible, so a less demanding combination of calendar-based counting and urinary ovulation testing, that is, the 2-step method, may be a viable alternative. PURPOSE: To investigate the agreement between the 2- and 3-step methods for the detection of SMDs. METHODS: Menstrual cycles (MCs, 98) of 59 athletes were assessed using the 2- and 3-step methods. Regular-length MCs (ie, ≥21 and ≤35 d) were classified as either having no SMD (luteal phase length ≥10 d, midluteal progesterone concentration ≥16 nmol·L-1, and being ovulatory) or having an SMD (eg, short luteal phase [<10 d], inadequate luteal phase [midluteal progesterone concentration <16 nmol·L-1], or being anovulatory). Method agreement was assessed using the McNemar test and Cohen kappa (κ). RESULTS: Substantial agreement was observed between methods (κ = .72; 95% CI, .53-.91), but the 2-step method did not detect all MCs with an SMD, resulting in evidence of systematic bias (χ2 = 5.14; P = .023). The 2-step method detected 61.1% of MCs that had an SMD ([51.4, 70.8]), as verified using the 3-step method, and correctly identified 100% of MCs without an SMD. CONCLUSIONS: MCs classified as being disturbed using the 2-step method could be considered valid evidence of SMDs. However, MCs classified without SMDs do not definitively confirm their absence, due to the proven underdetection via the 2-step method.

Topics & Concepts

Luteal phaseMcNemar's testOvulationMedicineKappaInternal medicineGynecologyMathematicsFollicular phaseStatisticsHormoneGeometryMenstrual Health and DisordersBone health and osteoporosis researchOvarian function and disorders