Purpose: This study aimed to develop a coarctation probability model incorporating prenatal cardiac sonographic markers to estimate the probability of an antenatal diagnosis of coarctation of the aorta (CoA).Methods: We reviewed 89 fetuses as a"investigation" cohort with prenatal suspicion for CoA and allotted to three ssubgroups:(1) severe CoA: symptoms onset of CoA and surgery within the rst three months (15);(2) mild CoA: surgery within four months-one year (29); (3) false-positive CoA: this outcome does not require surgery (45). Using logistic regression to creat the multi-parametric model, and validated using a "validation" cohort of 86 fetuses with suspected CoA subsequently.Results: The prediction model had optimal criterion >0.25 with sensitivity 97.7% and speci city 59.1%, the area under the receiver operator curve is 0.8 which makes sense in diagnosis of CoA and risk strati cation. The risk assessment demonstrated that fetuses with model probability>60% should make an inpatient observation for high risk of CoA whereas <15% should not undergo clinical follow-up imaging.Conclusion: Based on these results, we recommend measuring the model in all fetuses with suspected CoA may improve the accuracy of risk assessment. The objectivity of its parameters may allow its implementation working in multicenter studies of fetal cardiology.
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