title: Detecting evidence of luteal activity by least-squares quantitative basal temperature analysis against urinary progesterone metabolites and the effect of wake-time variability.
abstract: OBJECTIVE
  To assess computerised least-squares analysis of quantitative basal temperature (LS-BT) against urinary pregnanediol glucuronide (PdG) as an indirect measure of ovulation, and to evaluate the stability of LS-QBT to wake-time variation.
  
  
  METHODS
  Cross-sectional study of 40 healthy, normal-weight, regularly menstruating women aged 19-34. Participants recorded basal temperature and collected first void urine daily for one complete menstrual cycle. Evidence of luteal activity (ELA), an indirect ovulation indicator, was assessed using Kassam's PdG algorithm, which identifies a sustained 3-day PdG rise, and the LS-QBT algorithm, by determining whether the temperature curve is significantly biphasic. Cycles were classified as ELA(+) or ELA(-). We explored the need to pre-screen for wake-time variations by repeating the analysis using: (A) all recorded temperatures, (B) wake-time adjusted temperatures, (C) temperatures within 2h of average wake-time, and (D) expert reviewed temperatures.
  
  
  RESULTS
  Relative to PdG, classification of cycles as ELA(+) was 35 of 36 for LS-QBT methods A and B, 33 of 34 (method C) and 30 of 31 (method D). Classification of cycles as ELA(-) was 1 of 4 (methods A and B) and 0 of 3 (methods C and D). Positive predictive value was 92% for methods A-C and 91% for method D. Negative predictive value was 50% for methods A and B and 0% for methods C and D. Overall accuracy was 90% for methods A and B, 89% for method C and 88% for method D. The day of a significant temperature increase by LS-QBT and the first day of a sustained PdG rise were correlated (r=0.803, 0.741, 0.651, 0.747 for methods A-D, respectively, all p<0.001).
  
  
  CONCLUSIONS
  LS-QBT showed excellent detection of ELA(+) cycles (sensitivity, positive predictive value) but poor detection of ELA(-) cycles (specificity, negative predictive value) relative to urinary PdG. Correlations between the methods and overall accuracy were good and similar for all analyses. Findings suggest that LS-QBT is robust to wake-time variability and that expert interpretation is unnecessary. This method shows promise for use as an epidemiological tool to document cyclic progesterone increase. Further validation relative to daily transvaginal ultrasound is required.
authors: Human Nutrition, The University of British Columbia, Vancouver, British Columbia, V6T 1Z4, Canada.
authors: Jennifer L
authors: JL
authors: Bedford
authors: Jerilynn C
authors: JC
authors: Prior
authors: Christine L
authors: CL
authors: Hitchcock
authors: Susan I
authors: SI
authors: Barr
mesh_terms: D000328:Adult; D001831:Body Temperature; D005260:Female; D006801:Humans; D016018:Least-Squares Analysis; D008597:Menstrual Cycle / Q000652:urine*; D010061:Ovulation Detection / Q000379:methods*; D011237:Predictive Value of Tests; D011276:Pregnanediol / Q000031:analogs & derivatives / Q000652:urine; D011374:Progesterone / Q000652:urine*; D012680:Sensitivity and Specificity; D013997:Time Factors; D014851:Wakefulness
chemical_list: C022270:pregnanediol-3 alpha-glucuronide; D011374:Progesterone; D011276:Pregnanediol