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Gynecol Obstet Invest. 2013;75(1):41-5. doi: 10.1159/000343231. Epub 2012 Oct 27.

The K-P algorithm: a new first-trimester growth model - comparison with other formulae and correlations with recorded embryonic lengths.

Author information

1
Acute Gynaecology, Early Pregnancy and Advanced Endosurgery Unit, Sydney Medical School Nepean, University of Sydney, Nepean Hospital, Penrith, N.S.W., Australia. max_mongelli @ yahoo.com

Abstract

OBJECTIVE:

To generate and validate individually fitted first-trimester growth curves using a new growth model. Secondary aims were to compare this new model with actual recorded embryonic measurements and validate its predictive accuracy.

METHODS:

A prospective study of women presenting to the Early Pregnancy Unit in the first trimester. Women with viable singleton pregnancies at the end of the first trimester who had had at least two crown-rump length (CRL) measurements were selected. An individual power function of CRL was derived from serial CRL measurements. Individual curves were fitted using computer software to estimate a dating adjustment factor ('k'), and a growth coefficient ('P') for each case. The predictive accuracy of the growth curves was then tested in a validation subset of the population that had a third CRL measurement. The population average curve from the developed model was also extrapolated to day 27 menstrual age (Carnegie stage 6), day 30 menstrual age (Carnegie stage 7) and day 84 menstrual age, and values were compared to previously reported measurements.

RESULTS:

326 viable pregnancies were selected for CRL growth curve development. The mean time interval between CRL measurements was 20.5 days (range 2-44). The mean value for 'P' was 2.058, and for 'k' 24.6. Testing the model on a subset of 81 cases showed that the average error in predicting a third CRL measurement was 1% (SD 9.1%).

CONCLUSIONS:

These new, individually fitted growth curves for the first trimester correlate more closely with the recorded embryonic lengths than other standards.

PMID:
23108459
DOI:
10.1159/000343231
[Indexed for MEDLINE]

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