To evaluate the algorithms of risk assessment for Down syndrome (DS).Methods
Cohort study conducted in women at risk undergoing midtrimester genetic sonogram. Univariate and logistic regression analysis were used to relate findings to the occurrence of DS. The resulting model was validated in an independent population of patients.Results
In a multivariable model adjusted for gestational age and maternal age, nuchal fold thickness (NFT) ≥5 mm (OR = 4.6, 95% CI 0.9-23.9), presence of renal pelvic dilation (OR = 18.0, 95% CI 2.9-110.5), absent mid-phalanx of the 5th finger (OR = 29.9, 95% CI 6.1-145.8), presence of noncardiac malformations (OR = 20.1, 95% CI 2.6-154.7) or isolated heart defects (OR = 60.2, 95% CI 9.5-382.8), the interactions of gestational age with NFT ≥5 mm (P = 0.04) and malformations with heart defects (P = 0.03) were significantly associated with DS. Utilizing this model and a risk cutoff point of 1/270, the sensitivity was 83.3% (5/6) with a false positive rate (FPR) of 28.5% (159/558).Conclusion
Genetic sonogram has adequate accuracy to be incorporated into management algorithms for risk assessment of DS in women at risk.