1. National Center for Fetal Medicine Dept. Ob–Gyn Trondheim Norway Pregnancy dating

2. Traditionally done using the “Naegele’s rule (1812) Franz Karl Naegele 1778 - 1851

3. Naegele’s rule The rule estimates the Expected Date of Delivery (EDD) from the first day of the woman's Last Menstrual Period (LMP) by adding a year, subtracting three months and adding seven days to that date. Example, if LMP was 8 May 2007: then +1 year = 8 May 2008, -3 months = 8 February 2008, +7 days = 15 February 2008 (Pregnancy lasting 280 days would be 12 February 2008)

4. Pregnancy dating includes Prediction of expected day of delivery Assessment of Gestational age (GA)

5. Why is the gestational age important? Management of prematurity Assessment of growth Management of post term pregnancy

6. One method against the other! BPDLMP

7. Naegele’s rule Based on the woman’s physiology Survived about 200 years So - is it/was it a good rule? Why has ultrasound replaced LMP to date the pregnancy?

8. Induction for “post-term” pregnancy NICU admission Low birthweight (2500 g) 15 OR + 95% CI Benefits of routine ultrasound The Cochrane Review 1998 0.2

9. Reduce the number ofinductions for post termpregnancy with 70% Why? – Because gestational age is corrected in cases where the LMPwas inadequate as a basis forpredicting the age Benefits of routine ultrasound The Cochrane Review 1998

10. Unreliability of LMP Variation in time of ovulation Variation in time of ovulation – fertilization Irregular bleeding Bleeding in the pregnancy Pregnancy following birth control pills Human factor

11. Relationship between BPD and GA Data from eSnurra Birth weight n = 150

12. Unreliability of ultrasound Biological variation Inter – and intraobserver variation Abnorm shape of the scull Unrecognized chromosome aberrations/syndromes

13. Controversies LMP or US in general? US only when LMP is unreliable? LMP when agreement ± 14 days between LMP/US?

14. Seen from the obstetrician’s point of view The best method for predicting GA is the one whose prediction is closest to the actual day of delivery for most births (spontaneous)

15. Definitions WHONorway Preterm<259<259 Term280282 (283) Post term≥294≥296

16. Non-selected population Trondheim area, Pop. 200 000, 2 700 births One non-selected population One scanning unit One delivery dept. One pediatrician – neonatal exams One NICU One pediatric cardiology dept.

17. Spontaneous births Reliable LMP, regular cycles US LMP N days N = 9 240 0 100 200 300 400 500 -40-2002040

18. Spontaneous births Reliable LMP, regular cycles UltrasoundLMP Days% % ± 76156 ± 148884 N = 9 240

19. Spontaneous births Reliable LMP, irregular cycles US LMP days N N = 1 238 0 10 20 30 40 50 60 70 -40-2002040

20. Spontaneous births Reliable LMP, regular cycles US LMP N days N = 9 240 0 100 200 300 400 500 -40-2002040 Tunon et al UOG 1996

21. Spontaneous births Reliable LMP, regular cycles US LMP

22. Ultrasound and dating Reduction of post-term pregnancies according to US is caused by a correction of the GA where there is unrecognized discrepancy between LMP and the ovulation - delayed ovulation

23. Spontaneous births Reliable LMP, regular cycles UltrasoundLMP Days% % Preterm44 Post term29 N = 9 240

24. Ultrasound versus LMP US term later 60 US term earlier 33 Agreement7 100 % Total

25. Best predictor of birth US-term earlier later than LMP-term Days % 0 50 100 >148-14 1-7 8-14 >14 LMP better Equal US better 91 8 36 47 51 45 22 6251 4752 77 89 319 2623 3782 1311 448 N

26. Seen from the obstetrician’s point of view The best method for predicting GA is the one whose prediction is closest to the actual day of delivery for most births (spontaneous) US is a better predictor than LMP

27. Conclusion US versus LMP US–term later in 2/3 of the women Delivery around US–term regardless of LMP–term Narrower distribution around US-term Decreased number of post term pregnancies according to US-method

28. Conclusion US versus LMP Difference between methods ≤ ±7 days –No difference in births closest to the predicted day –Higher number of post term pregnancies for the LMP-method Ultrasound is the method of choice

29. Possible effect on the prediction of day of delivery Sex of the fetus Parity Maternal age Smoking Different operators Time of the scan

30. Conclusion Accuracy of prediction of day of delivery by ultrasound is influenced by the gender, parity, maternal age, and the experience of the operator, but these differences are small and of no clinical importance

31. How long does the human prenancy last? According to Naegele’s rule 280 - 283 According to WHO 280 According to population based data 283 (median)

32. Useful parameters to predict GA and EDD BPDFL

33. Snurra Born in Ålesund 1984 Fits in every pocket Tables –CRL –BPD –MAD –SF Introduced standarization of the ultrasound measurements in Norway 20 years ago

34. Pregnant women with highly reliable LMP-data Ultrasound measurements in a specified range (10 - 25 weeks) Regression between US-measurements and LMP data Results presented in a table for clinical purpose Estimation of day of delivery (EDD) Indirect method

35. EDD + 282 days LMP Regression 12 - 22 weeks

36. Estimation of day of delivery (EDD) Indirect method LMP We may estimate an “LMP” with prediction limits EDD + 282 days By adding 282 days to the “LMP” we estimate the day of delivery - but cannot estimate prediction limits of EDD

37. Estimation of day of delivery (EDD) Indirect method The negative aspects –Sensitive to selection criteria of the pregnant women with respect to LMP history and normality of pregnancy –A possible unreliability of the LMP is built into the method –For over 25 years we have claimed that the use of the LMP is not adequate, but then we build our prediction model on the LMP

38. eSnurra

39. Estimation of day of delivery (EDD) Direct method - eSnurra Birth Estimation 12 - 22 weeks US measurements Remaining time of pregnancy

40. Estimation of day of delivery (EDD) Direct method - eSnurra Birth Estimation Independent of LMP Independent of true length of pregnancy Direct prediction of wanted information Can estimate time of birth with Prediction Interval Needs high number of data points (50,000 - 100,000) No need for prospective testing

41. Estimation of day of delivery (EDD) Direct method - eSnurra We are predicting remaining time of pregnancy For a given BPD-value there is a given number of days left until birth N = 39,509 BPD Remaining time - Days

42. Estimation of day of delivery (EDD) Direct method - eSnurra Birth Regression One of many benefits: May produce a Prediction Interval for a given value of BPD Cannot be done with the indirect method T Gjessing HK, Grøttum P, Eik-Nes SH. A direct method for ultrasound prediction of day of delivery: a new, population-based approach. Ultrasound Obstet Gynecol 2007; 30: 19-27

43. % N = 52,999 Prediction of Birth Interval BPD 45 Result: There is an 87% chance birth will be at T +/- 14 days

44. Why do we want to predict a Birth Interval? –only 6% deliver on their “term” –it helps organize the social life - maternity leave etc. –will stimulate more research re. time of birth etc. Prediction of Birth Interval

45. N = 21,112 Estimation of day of delivery (EDD) Direct method - eSnurra Optimal prediction in the full range from BPD 25 - 60 mm Validation

46. Stable estimation over the full inclusion range of BPD (30 -60) High rate of delivery within ± 2 weeks (86 - 87%) Estimation of day of delivery (EDD) Direct method - eSnurra

47. eSnurra Population based model to predict Term Population based model to predict GA (283) Population based model to assess Growth Deviation (in percent or percentiles)

48. eSnurra ”Classic” A compact wheel containing the necessary information Estimated day of delivery Gestational age Growth - all parameters Fetal weight

49. eSnurra ”Classic” A compact wheel containing the necessary information Estimated day of delivery Gestational age Growth - all parameters Fetal weight

50. Thank you! Åbødalen - my favorite mountains