Analysis of Down syndrome failed to be diagnosed after prenatal screening: A multicenter study.

To analyze the characters of Down syndrome (DS) who failed to be diagnosed after prenatal screening and hope to be able to improve the programs of prenatal screening and reduce the missed diagnosis of DS. In this multicenter study, we collected the missed cases from 3 prenatal diagnosis centers and analyzed their characters. A total of 126 DS babies failed to be diagnosed after prenatal screening. Their mothers accepted the prenatal screening in second trimester. We collected the mothers' blood and detected the levels of alpha-fetoprotein (AFP) and the free beta subunit of human chorionic gonadotropin (fβhCG) by time-resolved fluoroimmunoassay. The values were also presented as multiples of the median (MoM) and determined the risk of carrying a fetus with DS by Wallace LifeCycle Elipse analysis software. Compared with normal control group, the level of fβhCG and hCG MoM were dramatically increased, while AFP and AFP MoM were decreased. The area under the receiver-operating-characteristic curve of trisomy 21 was 0.8387 for hCG-MoM and AFP-MoM testing. The sensitivity, specificity, positive predictive value, and negative predictive value were 84.6%, 74.8%, 75.4%, and 83.6%, respectively. Meanwhile, the prediction mode was "0.39957 + 1.90897HCG-MOM -3.32713AFP-MOM". It was worthwhile noting that the risk of 65.9% DS missed diagnosis group were higher than 1/1000, 92.9% higher than 1/3000. However, 72.5% cases in normal control group were lower than 1/3000. Only 9.2% mothers would be higher than the value of risk in 1/1000. The prediction mode of hCG MoM and AFP MoM might be able to help us reduce the missed diagnosis. It is also necessary to adjust more reasonable range of noninvasive prenatal testing with further clinical researches

Simplified Multiuser Detection for SCMA with Sum-Product Algorithm

Sparse code multiple access (SCMA) is a novel non-orthogonal multiple access technique, which fully exploits the shaping gain of multi-dimensional codewords. However, the lack of simplified multiuser detection algorithm prevents further implementation due to the inherently high computation complexity. In this paper, general SCMA detector algorithms based on Sum-product algorithm are elaborated. Then two improved algorithms are proposed, which simplify the detection structure and curtail exponent operations quantitatively in logarithm domain. Furthermore, to analyze these detection algorithms fairly, we derive theoretical expression of the average mutual information (AMI) of SCMA (SCMA-AMI), and employ a statistical method to calculate SCMA-AMI based specific detection algorithm. Simulation results show that the performance is almost as well as the based message passing algorithm in terms of both BER and AMI while the complexity is significantly decreased, compared to the traditional Max-Log approximation method