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  1. Tan DSK
    Med J Malaysia, 1985 Mar;40(1):11-4.
    PMID: 3831727
    Of the five diseases generally recognised as causing congenital defects, viz., toxoplasmosis, rubella, cy tomegaloviral infection, herpes simplex and syphilis (TORCHES) studied in Malaysia, rubella was found to be the most important. A total of 574 children with features of congenital rubella syndrome (CRS) were examined for rubella-specific IgM (in infants four months and below), and for rubella HAl antibodies (in children six months to four-years-old), and compared with 374 normal children of the same age groups. Whereas the prevalence rate of rubella in normal children was only 1.3%, in children with CRS (multiple defects) it was 87.3%; with congenital heart disease 71.0%; with congenital cataract 64.0%; with deafness 60.1%; with rash 30.8%; with hepatomegaly 17.1%; with mental retardation 4.1 %. Congenital rubella was not important as a cause of neonatal jaundice (0.9%)
    and CNS defects (0%).
    Matched MeSH terms: Abnormalities, Multiple/epidemiology*
  2. Dowsett L, Porras AR, Kruszka P, Davis B, Hu T, Honey E, et al.
    Am J Med Genet A, 2019 02;179(2):150-158.
    PMID: 30614194 DOI: 10.1002/ajmg.a.61033
    Cornelia de Lange syndrome (CdLS) is a dominant multisystemic malformation syndrome due to mutations in five genes-NIPBL, SMC1A, HDAC8, SMC3, and RAD21. The characteristic facial dysmorphisms include microcephaly, arched eyebrows, synophrys, short nose with depressed bridge and anteverted nares, long philtrum, thin lips, micrognathia, and hypertrichosis. Most affected individuals have intellectual disability, growth deficiency, and upper limb anomalies. This study looked at individuals from diverse populations with both clinical and molecularly confirmed diagnoses of CdLS by facial analysis technology. Clinical data and images from 246 individuals with CdLS were obtained from 15 countries. This cohort included 49% female patients and ages ranged from infancy to 37 years. Individuals were grouped into ancestry categories of African descent, Asian, Latin American, Middle Eastern, and Caucasian. Across these populations, 14 features showed a statistically significant difference. The most common facial features found in all ancestry groups included synophrys, short nose with anteverted nares, and a long philtrum with thin vermillion of the upper lip. Using facial analysis technology we compared 246 individuals with CdLS to 246 gender/age matched controls and found that sensitivity was equal or greater than 95% for all groups. Specificity was equal or greater than 91%. In conclusion, we present consistent clinical findings from global populations with CdLS while demonstrating how facial analysis technology can be a tool to support accurate diagnoses in the clinical setting. This work, along with prior studies in this arena, will assist in earlier detection, recognition, and treatment of CdLS worldwide.
    Matched MeSH terms: Abnormalities, Multiple/epidemiology
  3. Kruszka P, Addissie YA, Tekendo-Ngongang C, Jones KL, Savage SK, Gupta N, et al.
    Am J Med Genet A, 2020 Feb;182(2):303-313.
    PMID: 31854143 DOI: 10.1002/ajmg.a.61461
    Turner syndrome (TS) is a common multiple congenital anomaly syndrome resulting from complete or partial absence of the second X chromosome. In this study, we explore the phenotype of TS in diverse populations using clinical examination and facial analysis technology. Clinical data from 78 individuals and images from 108 individuals with TS from 19 different countries were analyzed. Individuals were grouped into categories of African descent (African), Asian, Latin American, Caucasian (European descent), and Middle Eastern. The most common phenotype features across all population groups were short stature (86%), cubitus valgus (76%), and low posterior hairline 70%. Two facial analysis technology experiments were conducted: TS versus general population and TS versus Noonan syndrome. Across all ethnicities, facial analysis was accurate in diagnosing TS from frontal facial images as measured by the area under the curve (AUC). An AUC of 0.903 (p < .001) was found for TS versus general population controls and 0.925 (p < .001) for TS versus individuals with Noonan syndrome. In summary, we present consistent clinical findings from global populations with TS and additionally demonstrate that facial analysis technology can accurately distinguish TS from the general population and Noonan syndrome.
    Matched MeSH terms: Abnormalities, Multiple/epidemiology*
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