本文選題：小于胎齡兒 + 危險因素　； 參考：《北京協(xié)和醫(yī)學(xué)院》2015年博士論文

【摘要】：研究目的：小于胎齡兒(small for gestational age, SGA)是對出生體重小于一定標(biāo)準(zhǔn)的一類新生兒的總稱,這部分新生兒不但在圍產(chǎn)期有著極高的風(fēng)險,其在學(xué)齡期以及成年期也會存在著一系列問題。具體而言,SGA患兒在圍產(chǎn)期的死亡率較體重正常的新生兒高出很多,而且其罹患新生兒低血糖、新生兒低體溫、新生兒呼吸窘迫綜合征(neonatal respiratory distress Syndrome, NRDS)、Ⅲ級以上的早產(chǎn)兒視網(wǎng)膜病(retinopathy of prematurity, ROP)以及壞死性小腸結(jié)腸炎(necrotizing enterocolitis, NEC)等疾病的風(fēng)險也相應(yīng)增加；同時,當(dāng)這部分孩子成長至學(xué)齡期,亦容易出現(xiàn)認(rèn)知障礙、學(xué)習(xí)能力下降的情況；而在成年之后,他們之中將有很多的人的成年終身高低于人群的-2標(biāo)準(zhǔn)差(standard deviation, SD);此外,近年來,有回顧性研究發(fā)現(xiàn),出生時為SGA的人其成年后出現(xiàn)超重或肥胖、糖代謝和脂代謝異常甚至是高血壓的可能性亦明顯升高。正是因為SGA患兒在人生中的各個時期都存在著一系列的健康問題,故一直以來,研究者們一直在尋找造成SGA的危險因素方面努力探尋,并期待能夠通過建立SGA風(fēng)險預(yù)測模型來實現(xiàn)對SGA的早期診斷,從而為早期干預(yù)SGA打下基礎(chǔ)。截至目前為止,很多研究都發(fā)現(xiàn),遺傳因素,母親的基本情況以及孕前和孕期生活情況、心理狀態(tài)和健康情況等因素均可影響新生兒體重。但這些研究所著眼的項目多僅集中在飲食、藥物和疾病等有限的方面,樣本量較小,而且多為回顧性或觀察性的研究,其研究結(jié)論可靠性及實用性亦有待商榷。同時,近年來研究者們所建立出的預(yù)測模型多需要進(jìn)行很多正常產(chǎn)檢之外的檢查項目,而且有些項目還與醫(yī)師經(jīng)驗水平密切相關(guān),這使得上述模型在臨床實際操作過程中存在著很大的局限性。因而,我們擬就SGA發(fā)生的危險因素的問題進(jìn)行一項覆蓋面、樣本量大的研究,并在此基礎(chǔ)上依據(jù)支持向量機(support vector machine, SVM)理論建立SGA的預(yù)測模型,以期為日后對SGA采取早期干預(yù)措施打下基礎(chǔ)。研究方法：我們采用2010年至2012年“國家免費孕前優(yōu)生健康檢查項目”中的相關(guān)數(shù)據(jù),經(jīng)過變量篩選、數(shù)據(jù)預(yù)處理等工作,采用卡方檢驗、Mann-WhitneyU檢驗等方法對數(shù)據(jù)進(jìn)行單因素分析,找到與新生兒發(fā)生SGA相關(guān)的變量,并進(jìn)一步采用二分類Logistics回歸分析的方法對與新生兒發(fā)生SGA有相關(guān)關(guān)系的變量進(jìn)行多因素分析。最后依據(jù)SVM理論建立SGA風(fēng)險預(yù)測模型。結(jié)果：1.在研究人群中,如以出生體重低于同胎齡同性別的新生兒的出生體重的第3百分位數(shù)為診斷標(biāo)準(zhǔn)時,SGA發(fā)生率為6.0%,其中男嬰的發(fā)生率為6.3%,而女嬰的為5.6%；若以出生體重低于同胎齡同性別的新生兒的出生體重的第10百分位數(shù)為診斷標(biāo)準(zhǔn)時,SGA的發(fā)生率為11.2%,男嬰的發(fā)生率為12.0%,女嬰的為10.4%。從地域分布來看,在以第3和第10百分位數(shù)為診斷標(biāo)準(zhǔn)時,北方人口的SGA發(fā)生率分別為5.1%和9.4%,而這一數(shù)字在南方人口中達(dá)到了6.4%和12.0%。2.父母親人口學(xué)特征、社會心理狀態(tài)、生活習(xí)慣、既往生殖系統(tǒng)健康情況、環(huán)境有害因素暴露情況、母親孕期狀態(tài)以及其他理化檢查結(jié)果等變量與孩子會對孩子是否發(fā)生SGA產(chǎn)生一定的影響。3.通過SVM理論可建立的新生兒SGA風(fēng)險預(yù)測模型,在以第3和第10百分位數(shù)為診斷標(biāo)準(zhǔn)時,其預(yù)測準(zhǔn)確度分別為：99.227%和83.239%。結(jié)論：父母親人口學(xué)特征、社會心理狀態(tài)、生活習(xí)慣、既往生殖系統(tǒng)健康情況、環(huán)境有害因素暴露情況、母親孕期狀態(tài)以及其他理化檢查結(jié)果等變量與孩子會對孩子是否發(fā)生SGA產(chǎn)生一定的影響。此外,通過SVM理論可建立新生兒SGA風(fēng)險預(yù)測模型,且預(yù)測效能較高。
[Abstract]:Research objectives: small for gestational age (SGA) is the general term for a class of newborns with a certain birth weight less than a certain standard. This part of the newborn not only has a high risk of perinatal period, but also has a series of problems at the school age and in adulthood. Specifically, the mortality of children in the perinatal period is more than that of SGA. Normal newborn babies are much higher, and they suffer from neonatal hypoglycemia, hypothermia of the newborn, neonatal respiratory distress syndrome (neonatal respiratory distress Syndrome, NRDS), retinopathy of retinopathy of prematurity (ROP) above grade III and necrotizing enterocolitis (necrotizing enterocolitis, NEC), etc. The risk of disease increases correspondingly; at the same time, when this part of the child grows to the school age, it is also prone to cognitive impairment and a decline in learning ability; and in adulthood, many of them have a year-end height below the -2 standard (standard deviation, SD). In addition, in recent years, a retrospective study found that People who were born SGA were overweight or obese in adulthood, and the possibility of glucose metabolism and lipid metabolism, even hypertension, was also significantly higher. It is because children in SGA have a series of health problems at all times of life, so researchers have been searching for the risk factors for SGA. It is expected that the early diagnosis of SGA can be realized through the establishment of the SGA risk prediction model, thus laying the foundation for early intervention in SGA. So far, many studies have found that genetic factors, the basic situation of mothers, life conditions in pregnancy and pregnancy, mental state and health condition can affect the weight of the newborn. Most of the projects focused on limited areas such as diet, medicine and disease, small sample size, and many retrospective or observational studies, the reliability and practicability of its findings are still open to discussion. And some projects are also closely related to the level of the physician's experience, which makes the above model very limited in clinical practice. Therefore, we have a coverage of the risk factors for SGA, a large sample of samples, and based on the support vector machine (support vector machine, SVM). The theory set up the prediction model of SGA in order to lay the foundation for the early intervention measures for SGA. Research methods: we adopt the relevant data in the "national free prenatal health examination project" from 2010 to 2012, through the selection of variables, data preprocessing, and the use of chi square test, Mann-WhitneyU test and other methods. According to the single factor analysis, we found the variables related to the occurrence of SGA in the newborn, and further used the two classification Logistics regression analysis to analyze the variables related to the newborn SGA. Finally, the SGA risk prediction model was established based on the SVM theory. Results: 1. in the study population, such as the birth weight is lower than the birth weight. The incidence of SGA was 6% in the third percentile of birth weight at the same age of the same gestational age. The incidence of male babies was 6.3%, while the female baby was 5.6%. The incidence of SGA was 11.2% when the birth weight was lower than the same birth weight of the same baby. The incidence of the baby was 11.2%. The incidence of 10.4%. was 12%. From the geographical distribution, the incidence of SGA in the northern population was 5.1% and 9.4%, respectively, with the third and tenth percentiles as the diagnostic criteria, and this number reached 6.4% and 12.0%.2. in the southern population. The exposure of environmental harmful factors, maternal pregnancy state and other physical and chemical tests and other variables and children will have a certain influence on the child's occurrence of SGA, and the.3. model of neonatal SGA risk can be established through the SVM theory. The prediction accuracy is 99.227% and 83., respectively, with the third and tenth percentiles as the diagnostic criteria. 239%. conclusion: the oral and family characteristics, social psychological state, life habits, the health of the reproductive system, the exposure of the environmental harmful factors, the mother's pregnancy state and other physical and chemical examination results have a certain effect on the child's occurrence of SGA. In addition, the risk of neonatal SGA can be established through the SVM theory. Prediction model and high prediction efficiency.
【學(xué)位授予單位】：北京協(xié)和醫(yī)學(xué)院
【學(xué)位級別】：博士
【學(xué)位授予年份】：2015
【分類號】：R722.1
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本文編號：2082562