1.Suggestions for standardized management of nomenclature and classification of neonatal diseases.
Mao-Jun LI ; Juan MA ; Xiao-Mei SHAO ; Qing WU ; Wei SHI ; Yan-Sheng HU ; Ai-Min LIU ; Chang-Hui CHEN
Chinese Journal of Contemporary Pediatrics 2016;18(11):1059-1064
Nomenclature and classification of diseases are not only related to clinical diagnosis and treatment, but also involved in the fields such as management and exchange of medical information, medical expense payments, and medical insurance payment. In order to standardize clinical physicians' diagnostic and treatment activities, medical records, and the first page of medical records, this article elaborates on the basic principles and methods for nomenclature and classification of diseases with reference to international nomenclature of diseases and international classification of diseases. Meanwhile, in view of the problems in clinical practice, this article proposes the classification of neonatal diseases, the basic procedure and writing rules in the diagnosis of neonatal diseases, and death diagnosis principles.
Humans
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Infant, Newborn
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Infant, Newborn, Diseases
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classification
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diagnosis
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International Classification of Diseases
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Terminology as Topic
2.6q24 transient neonatal diabetes mellitus: the first case report from China.
Bin YAO ; Xinhan ZHANG ; Hua LIANG ; Wen XU ; Mengyin CAI ; Jinhua YAN ; Jianping WENG
Chinese Medical Journal 2014;127(20):3680-3680
5.A case of localized persistent interstitial pulmonary emphysema.
Mee Hye OH ; Mi Young KIM ; Woo Sup SHIM ; Sam Se OH ; Bong Kyoung SHIN ; Seong Jin CHO ; Han Kyeom KIM
Journal of Korean Medical Science 2001;16(2):225-228
Interstitial pulmonary emphysema is a well-documented complication of assisted mechanical ventilation in premature infants with respiratory distress syndrome. Localized persistent interstitial pulmonary emphysema (LPIPE) confined to a single lobe was incidentally presented in a 4-day-old female infant. This patient was a normal full-term baby with no respiratory distress symptom and no experience of assisted mechanical ventilation. Chest radiograph showed radiolucent area in right lower lobe zone, which needed differential diagnosis from other congenital lesions such as congenital cystic adenomatoid malformation and congenital lobar emphysema. CT scan showed irregular-shaped air cystic spaces and pathologically, cystic walls primarily consisted of compressed lung parenchyma and loose connective tissue intermittently lined by multinucleated foreign body giant cells.
Diagnosis, Differential
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Female
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Human
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Infant, Newborn
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Infant, Newborn, Diseases/*pathology/radiography
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Pulmonary Emphysema/*pathology/radiography
6.Clinical characteristics of abdominal distention in early newborns.
An CHEN ; Jing DU ; Li-Zhong DU
Chinese Journal of Contemporary Pediatrics 2013;15(12):1074-1078
OBJECTIVEAbdominal distention is a common disorder in newborns, which can be life-threatening in severe cases. Currently, little literature is available regarding early identification of the etiology of this disorder in newborn babies, which is imperative to reducing the likelihood of serious consequences. This retrospective study was conducted to analyze the clinical characteristics of early newborns with abdominal distention, aiming at identifying the underlying etiologic factors.
METHODSMedical records of 201 (65 premature and 136 full-term) early newborns with abdominal distention between January 2011 and December 2012 were retrieved.
RESULTSCongenital malformations (including congenital megacolon, anal atresia, malrotation, intestinal atresia, intestinal duplication and posterior urethral valves) occurred in 44.6% of the premature newborns with abdominal distention and 61.8% of the full-term newborns with the disorder. Congenital megacolon was the number one cause of abdominal distention in the full-term group (33.8%) and the number two cause in the preterm group (13.8%). As far as other individual abnormalities were concerned, sepsis was the number one cause of abdominal distention in the preterm group (35.4%) and the number two cause in the full-term group (21.3%). Vomiting was a main symptom associated with abdominal distension, occurring in 64.0% of the full-term newborns and 44.6% of the preterm newborns. The most pronounced X-ray manifestation was bowel distention with an air-fluid level in the preterm group (47.7%) but was bowel distention without a fluid level in the full-term group (57.3%). Eliological and symptomatic treatment was effective in 86.2% of the premature cases and 88.2% in the full-term cases (P>0.05).
CONCLUSIONSCongenital malformations may be the major cause of abdominal distension in early newborns. Sepsis and congenital megacolon are the single disease most frequently associated with abdominal distention in preterm and full-term newborns respectively. Vomiting is a main accompanying symptom in early newborns with abdominal distention. X-ray manifestations seem to be more severe in preterm newborns than in full term newborns. A satisfactory outcome can be achieved after treatment in both preterm and full-term newborns with this disorder.
Abdomen ; pathology ; Dilatation, Pathologic ; Female ; Humans ; Infant, Newborn ; Infant, Newborn, Diseases ; diagnosis ; Male ; Radiography, Abdominal
8.Recent research on machine learning in the diagnosis and treatment of necrotizing enterocolitis in neonates.
Cheng CUI ; Fei-Long CHEN ; Lu-Quan LI
Chinese Journal of Contemporary Pediatrics 2023;25(7):767-773
Necrotizing enterocolitis (NEC), with the main manifestations of bloody stool, abdominal distension, and vomiting, is one of the leading causes of death in neonates, and early identification and diagnosis are crucial for the prognosis of NEC. The emergence and development of machine learning has provided the potential for early, rapid, and accurate identification of this disease. This article summarizes the algorithms of machine learning recently used in NEC, analyzes the high-risk predictive factors revealed by these algorithms, evaluates the ability and characteristics of machine learning in the etiology, definition, and diagnosis of NEC, and discusses the challenges and prospects for the future application of machine learning in NEC.
Infant, Newborn
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Humans
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Enterocolitis, Necrotizing/therapy*
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Infant, Newborn, Diseases
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Prognosis
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Gastrointestinal Hemorrhage/diagnosis*
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Machine Learning
10.Neonatal Diabetes in a Singapore Children's Hospital: Molecular Diagnoses of Four Cases.
Rashida F VASANWALA ; Song Hai LIM ; Sian ELLARD ; Fabian YAP
Annals of the Academy of Medicine, Singapore 2014;43(6):314-319
INTRODUCTIONNeonatal diabetes (ND) presents below 6 months of age, and is caused by a genetic defect in glucose homeostasis. Molecular genetic diagnosis can identify the exact molecular aetiology and guide clinical management. The objective of this study was to identify ND among children with diabetes in a major children's hospital in Singapore and to characterise their molecular and clinical features.
MATERIALS AND METHODSThe study identified all infants below 6 months of age who presented with diabetes to our centre from January 2008 to December 2010. It also reviewed diabetes database comprising 662 patients, to identify those who were diagnosed with diabetes below 6 months of age between January 1997 and December 2010. Four patients (3 females and 1 male) were identified and their molecular aetiology was investigated.
RESULTSA molecular aetiology was found in each of the 4 patients identified. Two patients (Patient 1 and 2) had permanent ND (PND). Patient 1 who has KCNJ11/R201H mutation was successfully switched from insulin to oral glibenclamide and Patient 2 who has a novel mutation INS/C109Y continues to be treated with insulin. Two patients (Patient 3 and 4) had transient ND (TND) and no longer require insulin or any other intervention to maintain normoglycaemia. Patient 3 has a novel mutation ABCC8/F1182S and Patient 4 has a paternal duplication on chromosome 6q24.
CONCLUSIONThis study identified 4 cases of ND in our cohort of diabetes children and confirmed their molecular diagnosis. Molecular genetic testing for these children led to accurate diagnosis and appropriate management.
Diabetes Mellitus ; diagnosis ; Female ; Hospitals, Pediatric ; Humans ; Infant ; Infant, Newborn ; Infant, Newborn, Diseases ; diagnosis ; Male ; Molecular Diagnostic Techniques ; Singapore