Children with Down syndrome often require several specialty doctors and multidisciplinary teams for their associated anomalies. This may impact their quality of life and creates gaps in treatment monitoring. No studies have yet been conducted in Thailand to measure their quality of life and level of comprehensive health supervision. Therefore, we aimed to study the quality of life among children with Down syndrome and determine if they receive comprehensive health supervision for their condition. In this descriptive research, data were collected from a medical record review of children with Down syndrome during a 1-year period in our Pediatric Outpatient Clinic; 50 children and 39 caregivers participated. Mean total quality of life score of the children was 67.9/100 points. The children had the highest scores (73.6 ± 12.8) in emotional functioning and the lowest (57.2 ± 25.6) in cognitive functioning. It appears that the quality of life may be lower in Down syndrome patients than in Thai children without it. Regarding health supervision, all 50 were screened for thyroid function, and 48 received cardiac evaluations. However, only 17 (34%) received "complete basic assessment" of 5 screening combinations with developmental evaluations and growth monitoring. Furthermore, none received "comprehensive" evaluations for all recommended conditions. While these findings show a need for health supervision improvement for children with Down syndrome within our hospital, they may also be indicative for most care facilities throughout Thailand.

Craniofacial dysmorphism recognition is the first step in diagnosing most genetic syndromes. However, the number of genetic syndromes is enormous, and the specific facial features are difficult to memorize. For clinical practice, recent advances in artificial intelligence can be of use. One such tool, Face2Gene (FDNA, Inc., Boston, MA), is an innovative free group of applications, that helps clinicians recognize possible genetic syndromes from patients' facial two-dimensional photos. The initial data set used to train this technology consisted primarily of Caucasian patients. Because ethnic differences affect patients' facial features, the recognition probability in Asian patients may be limited. Our aim was to test the technology's recognition probability on Thai children with Down Syndrome (DS) as compared to Thai children without DS (non-DS). Two separate control groups of Thai non-DS children, either unaffected or having other syndromes, were included. Frontal photographs were obtained from all the participants. All 30 children with DS were recognized as DS in the top 10 syndrome-matches (100% sensitivity), and 27 were in the first ranking of suggested syndromes. Eighteen non-DS were recognized as DS (87.2% specificity) with an accuracy of 89%. We present a scientific basis for this novel tool, useful in the clinic where patients are of a different ethnicity unfamiliar to the evaluator. However, Face2Gene cannot be considered a replacement for clinicians' knowledge of phenotypes. Further studies on other genetic syndromes/ethnicities being identified by software algorithms are needed.

Background: Craniofacial dysmorphism plays a major part in the evaluation of many genetic syndromes. Facial pattern recognition has been typically used by clinicians before sending the patients' blood for specific diagnostic tests. However, the number of genetic syndromes is enormous, and the specific facial features are difficult to memorize for all syndromes. Therefore facial dysmorphology novel analysis (FDNA) technology, innovative software, was developed to help clinicians recognize probable genetic syndromes from patients' facial gestalts by ranking. Ethnic differences might have a major effect on patients' facial features. The FDNA database mainly consists of Caucasian patients; therefore, the probability recognition for Asian patients may be limited. The aim of this project is to test the software's recognition probability (sensitivity) on Thai Down Syndrome (DS) children compared to Thai non-Down syndrome (non-DS) children (specificity).