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1.
Chinese Journal of Contemporary Pediatrics ; (12): 197-203, 2022.
Article in English | WPRIM | ID: wpr-928587

ABSTRACT

Neonatal seizures are the most common clinical manifestations of critically ill neonates and often suggest serious diseases and complicated etiologies. The precise diagnosis of this disease can optimize the use of anti-seizure medication, reduce hospital costs, and improve the long-term neurodevelopmental outcomes. Currently, a few artificial intelligence-assisted diagnosis and treatment systems have been developed for neonatal seizures, but there is still a lack of high-level evidence for the diagnosis and treatment value in the real world. Based on an artificial intelligence-assisted diagnosis and treatment systems that has been developed for neonatal seizures, this study plans to recruit 370 neonates at a high risk of seizures from 6 neonatal intensive care units (NICUs) in China, in order to evaluate the effect of the system on the diagnosis, treatment, and prognosis of neonatal seizures in neonates with different gestational ages in the NICU. In this study, a diagnostic study protocol is used to evaluate the diagnostic value of the system, and a randomized parallel-controlled trial is designed to evaluate the effect of the system on the treatment and prognosis of neonates at a high risk of seizures. This multicenter prospective study will provide high-level evidence for the clinical application of artificial intelligence-assisted diagnosis and treatment systems for neonatal seizures in the real world.


Subject(s)
Humans , Infant, Newborn , Artificial Intelligence , Electroencephalography/methods , Epilepsy/diagnosis , Infant, Newborn, Diseases/diagnosis , Intensive Care Units, Neonatal , Multicenter Studies as Topic , Prospective Studies , Randomized Controlled Trials as Topic , Seizures/drug therapy
2.
Chinese Journal of Contemporary Pediatrics ; (12): 308-313, 2018.
Article in Chinese | WPRIM | ID: wpr-689635

ABSTRACT

<p><b>OBJECTIVE</b>To study the association between the prevalence of overweight/obesity and copy number variations (CNVs) among Han, Uyghur, and Kazak children in Xinjiang, China.</p><p><b>METHODS</b>The kindergartens in Ili, Altay, and Karamay in Xinjiang were selected as research sites, and stratified cluster sampling was used to select the children aged 3-7 years. Body height and body weight were measured, and exfoliated buccal mucosa cells were collected. CNVplex® was used to measure the CNVs of FTO_1, IRX3_1, IRX3_2, MC4R_1, and MC4R_2.</p><p><b>RESULTS</b>A total of 603 children were surveyed (307 boys and 296 girls). There were 261 Han children, 194 Uyghur children, and 148 Kazak children. The overweight/obesity rates in Han, Uyghur, and Kazak children were 28.3%, 10.3%, and 31.1%, respectively (P<0.001). In Kazak children, the CNVs of IRX3_1 and MC4R_2 were associated with overweight/obesity (P<0.05). The multivariate logistic regression analysis showed that the risk of overweight/obesity in Han and Kazak children was 3.443 times (95%CI: 2.016-5.880) and 3.924 times (95%CI: 2.199-7.001), respectively, that in Uyghur children. The CNV of IRX3_1 was a risk factor for overweight/obesity (P=0.028, OR=2.251, 95%CI: 1.418-5.651).</p><p><b>CONCLUSIONS</b>The CNV of IRX3_1 is associated with overweight/obesity in Han, Uyghur, and Kazak children, and the association between the CNV of IRX3_1 and overweight/obesity in Kazak children should be taken seriously.</p>


Subject(s)
Child , Child, Preschool , Female , Humans , Male , China , Ethnology , DNA Copy Number Variations , Homeodomain Proteins , Genetics , Logistic Models , Obesity , Genetics , Overweight , Genetics , Risk Factors , Transcription Factors , Genetics
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