【摘要】：非酒精性脂肪肝(NAFLD)是指排除酒精和其他明確的損肝因素所致的肝細(xì)胞內(nèi)脂肪過(guò)度沉積為主要特征的臨床病理綜合征,是與胰島素抵抗和遺傳易感性密切相關(guān)的獲得性代謝應(yīng)激性肝損傷。近年來(lái),隨著生活習(xí)慣、飲食結(jié)構(gòu)的改變,NAFLD發(fā)病率和患病率不斷上升;并且由于其危害不僅僅累及肝臟組織,而且還是心血管疾病、代謝綜合征、慢性腎病等嚴(yán)重慢性病的危險(xiǎn)因素,已引起了研究者的廣泛關(guān)注。其中,對(duì)NAFLD的早篩查和早診斷尤為重要。為此,本研究依托"山東多中心健康管理縱向觀察隊(duì)列",分別利用橫斷面資料和隊(duì)列資料,采用Logistic回歸和Cox比例風(fēng)險(xiǎn)模型構(gòu)建了 NAFLD的篩查模型和3年風(fēng)險(xiǎn)評(píng)估模型,以用于人群的NAFLD篩查及3年風(fēng)險(xiǎn)評(píng)估。研究結(jié)果如下:一、NAFLD篩查模型的研究1.共有18620名符合納入標(biāo)準(zhǔn)者進(jìn)入了篩查模型的研究。其中,男性10030名,有3811名被檢出NAFLD,檢出率為38.00%;女性8590名,有1898名被檢出NAFLD,檢出率為22.10%。男性NAFLD檢出率高于女性(χ2=550.27,P0.001)。男、女性NAFLD檢出率均隨年齡增長(zhǎng)而增加,均呈現(xiàn)上升趨勢(shì)。2.在NAFLD患者和非NAFLD患者比較中,男性,除年齡外,兩組間各項(xiàng)指標(biāo)的差異均具有統(tǒng)計(jì)學(xué)意義(P0.05);而女性,兩組間所有指標(biāo)的差異都具有統(tǒng)計(jì)學(xué)意義(P0.05)。3.采用多因素Logistic回歸(后退法)進(jìn)行變量篩選及建模。最終,無(wú)論男女,進(jìn)入模型的9個(gè)指標(biāo)完全相同,分別是年齡、體重指數(shù)、舒張壓、谷丙轉(zhuǎn)氨酶、谷氨酰轉(zhuǎn)肽酶、空腹血糖、甘油三酯、高密度脂蛋白和低密度脂蛋白。其中,除高密度脂蛋白是NAFLD的保護(hù)因素外,其它指標(biāo)均為NAFLD的危險(xiǎn)因素。4.對(duì)所構(gòu)建的NAFLD篩查模型進(jìn)行評(píng)價(jià),男女性ROC曲線(xiàn)下面積AUC(95%CI)分別為0.800(0.792,0.807)和0.844(0.836,0.852)。經(jīng)十折交叉驗(yàn)證對(duì)篩查模型進(jìn)行內(nèi)部評(píng)價(jià),男女性AUC(95%CI)分別為0.798(0.790,0.807)和 0.843(0.833,0.852)。男女性外部驗(yàn)證的 AUC(95%CI)分別為0.845(0.832,0.858)和 0.868(0.854,0.882)。二、NAFLD的3年風(fēng)險(xiǎn)評(píng)估模型的研究1.NAFLD風(fēng)險(xiǎn)評(píng)估模型隊(duì)列共有3429人,男性1847名,有683名在隨訪期內(nèi)(4514人年)發(fā)生NAFLD,發(fā)病密度為15.13/100人年,女性1582名,有431名在隨訪期內(nèi)(4142人年)發(fā)生NAFLD,發(fā)病密度為10.14/100人年。2.對(duì)隨訪期內(nèi)發(fā)生NAFLD者與未發(fā)生NAFLD者進(jìn)行比較,男性?xún)山M間各項(xiàng)指標(biāo)的差異均具有統(tǒng)計(jì)學(xué)意義(P0.05);女性,兩組間除單核細(xì)胞絕對(duì)值的差異無(wú)統(tǒng)計(jì)學(xué)意義外,其它指標(biāo)的差異均具有統(tǒng)計(jì)學(xué)意義(P0.05)。3.采用多因素Cox回歸(后退法)構(gòu)建3年NAFLD風(fēng)險(xiǎn)評(píng)估模型,最終,男性有體重指數(shù)、舒張壓、谷丙轉(zhuǎn)氨酶、甘油三酯、高密度脂蛋白和低密度脂蛋白等6個(gè)指標(biāo)進(jìn)入模型。女性指標(biāo)有年齡、體重指數(shù)、舒張壓、甘油三酯、高密度脂蛋白和低密度脂蛋白等6個(gè)指標(biāo)進(jìn)入模型。4.對(duì)所構(gòu)建的3年風(fēng)險(xiǎn)評(píng)估模型進(jìn)行評(píng)價(jià),男女性ROC曲線(xiàn)下面積AUC(95%CI)分別為 0.724(0.703,0.744)和 0.773(0.751,0.793)。經(jīng)十折交叉驗(yàn)證對(duì)風(fēng)險(xiǎn)評(píng)估模型進(jìn)行內(nèi)部評(píng)價(jià),男女性AUC(95%CI)分別為0.718(0.695,0.742)和 0.766(0.740,0.791)。男女性外部驗(yàn)證的 AUC(95%CI)分別為 0.715(0.665,0.765)和 0.712(0.654,0.770)。研究結(jié)論:1.男性的NAFLD檢出率高于女性。2.本研究所構(gòu)建的男、女性NAFLD篩查模型均能較好地鑒別出NAFLD患者及非患者,且具有一定外推性。3.本研究所構(gòu)建的男、女性3年NAFLD風(fēng)險(xiǎn)評(píng)估模型,預(yù)測(cè)效果良好,具有一定的外推性。
[Abstract]:Nonalcoholic fatty liver disease (NAFLD) is a clinicopathological syndrome characterized by excessive intracellular fat deposition excluding alcohol and other specific liver damage factors. It is an acquired metabolic stress liver injury closely related to insulin resistance and genetic susceptibility. The morbidity and morbidity of NAFLD are increasing constantly, and the risk factors of serious chronic diseases, such as cardiovascular disease, metabolic syndrome, chronic kidney disease and so on, have attracted wide attention of researchers. Among them, early screening and early diagnosis of NAFLD are particularly important. Using cross-sectional data and cohort data, a three-year risk assessment model and a logistic regression model for NAFLD screening and a three-year risk assessment model for NAFLD screening were constructed using Cox proportional hazard model. Among them, 1 030 males and 3 811 females were detected with NAFLD, the detection rate was 38.00%; 8 590 females and 1 898 females were detected with NAFLD, the detection rate was 22.10%. The detection rate of NAFLD in males was higher than that in females (2 = 550.27, P 0.001). The detection rate of NAFLD in males and females increased with age, showing an upward trend. In NAFLD patients and non-NAFLD patients, except age, the differences of all the indicators between the two groups were statistically significant (P 0.05); while in women, the differences of all the indicators between the two groups were statistically significant (P 0.05). 3. Multivariate logistic regression (regression) was used to screen variables and model. Finally, both men and women entered the model. Nine indexes were identical, including age, body mass index, diastolic blood pressure, glutamic-alanine aminotransferase, glutamyl transpeptidase, fasting blood glucose, triglyceride, high density lipoprotein and low density lipoprotein. The ROC curve area under AUC (95% CI) was 0.800 (0.792,0.807) and 0.844 (0.836,0.852) for men and women, respectively. The internal evaluation of the screening model was carried out by 10-fold cross-validation. AUC (95% CI) for men and women were 0.798 (0.790,0.807) and 0.843 (0.833,0.852). AUC (95% CI) for men and women were 0.845 (0.832,0.858) and 0.854 (0.854, respectively). NAFLD risk assessment model cohort of 3 429 people, 1 847 men, 683 in the follow-up period (4 514 person-years) NAFLD incidence density of 15.13/100 person-years, 1582 women, 431 in the follow-up period (4 142 person-years) NAFLD incidence density of 10.14/100 person-years. Comparing the patients with NAFLD with those without NAFLD, the difference of each index between male and female groups was statistically significant (P 0.05); the difference of other indexes between the two groups except the absolute value of monocytes was statistically significant (P 0.05). 3. Finally, men entered the model with six indicators, including body mass index, diastolic blood pressure, alanine aminotransferase, triglyceride, high-density lipoprotein and low-density lipoprotein. Women's indicators included age, body mass index, diastolic blood pressure, triglyceride, high-density lipoprotein and low-density lipoprotein. AUC (95% CI) was 0.724 (0.703, 0.744) and 0.773 (0.751, 0.793) for men and women, respectively. The risk assessment model was evaluated internally by 10-fold cross-validation. AUC (95% CI) for men and women were 0.718 (0.695, 0.742) and 0.766 (0.740, 0.791), respectively. 765) and 0.712 (0.654, 0.770). Conclusion: 1. The detection rate of NAFLD in males is higher than that in females. 2. The NAFLD screening models of males and females can distinguish NAFLD patients and non-patients well, and have extrapolation. 3. The three-year NAFLD risk assessment model of males and females constructed in this study has good predictive effect and has certain extrapolation. Push sex.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：R575.5

【相似文獻(xiàn)】

相關(guān)期刊論文 前4條

1 梁偉璋;黃啟濤;鐘梅;陳敦金;余艷紅;汪麗萍;鐘柳英;行李琳;羅漫靈;李佳;陳茜;;兩種風(fēng)險(xiǎn)評(píng)估模型在孕產(chǎn)婦下肢深靜脈血栓形成中預(yù)測(cè)價(jià)值的比較[J];現(xiàn)代婦產(chǎn)科進(jìn)展;2014年08期

2 馬貴平,史喜菊;化妝品傳播瘋牛病風(fēng)險(xiǎn)評(píng)估模型的建立[J];檢驗(yàn)檢疫科學(xué);2005年06期

3 孫樨陵;談立峰;郝東平;嚴(yán)旭東;蔡軍;;區(qū)域性大型活動(dòng)餐飲安全風(fēng)險(xiǎn)評(píng)估指標(biāo)及模型的建立[J];中國(guó)食品衛(wèi)生雜志;2012年03期

4 厲小燕;陳坤;張美辨;鄒華;周莉芳;;國(guó)際采礦與金屬委員會(huì)職業(yè)健康風(fēng)險(xiǎn)評(píng)估模型在火力發(fā)電廠的應(yīng)用研究[J];浙江預(yù)防醫(yī)學(xué);2013年11期

相關(guān)會(huì)議論文 前8條

1 海然;謝小權(quán);;基于多要素融合的風(fēng)險(xiǎn)評(píng)估模型的設(shè)計(jì)[A];全國(guó)計(jì)算機(jī)安全學(xué)術(shù)交流會(huì)論文集（第二十二卷）[C];2007年

2 薛曄;黃崇福;;自然災(zāi)害風(fēng)險(xiǎn)評(píng)估模型的研究進(jìn)展[A];中國(guó)災(zāi)害防御協(xié)會(huì)風(fēng)險(xiǎn)分析專(zhuān)業(yè)委員會(huì)第二屆年會(huì)論文集（二）[C];2006年

3 高峰;黨亞茹;高潔;;三峽庫(kù)區(qū)船舶散裝化學(xué)品風(fēng)險(xiǎn)評(píng)估模型及其應(yīng)用[A];中國(guó)航海學(xué)會(huì)2007年度學(xué)術(shù)交流會(huì)優(yōu)秀論文集[C];2007年

4 高峰;黨亞茹;高潔;;三峽庫(kù)區(qū)船舶散裝化學(xué)品風(fēng)險(xiǎn)評(píng)估模型及其應(yīng)用[A];2007年船舶防污染學(xué)術(shù)年會(huì)論文集[C];2007年

5 丁移粟;王宇;;基于證據(jù)理論的涉密人員風(fēng)險(xiǎn)評(píng)估模型研究[A];2012年全國(guó)網(wǎng)絡(luò)與數(shù)字內(nèi)容安全學(xué)術(shù)年會(huì)論文集[C];2012年

6 陳佑平;張真路;李夢(mèng)雅;;心腦血管病自動(dòng)化風(fēng)險(xiǎn)評(píng)估系統(tǒng)的建立及其初步應(yīng)用效果分析[A];第十二屆全國(guó)脂質(zhì)與脂蛋白學(xué)術(shù)會(huì)議論文匯編[C];2014年

7 李金安;馮愛(ài)芬;;重大動(dòng)物疫情潛在風(fēng)險(xiǎn)的評(píng)估模型[A];中國(guó)畜牧獸醫(yī)學(xué)會(huì)2009學(xué)術(shù)年會(huì)論文集（下冊(cè)）[C];2009年

8 宮會(huì)麗;丁香乾;楊寧;;煙葉有害成分風(fēng)險(xiǎn)評(píng)估模型研究與應(yīng)用[A];中國(guó)災(zāi)害防御協(xié)會(huì)風(fēng)險(xiǎn)分析專(zhuān)業(yè)委員會(huì)第二屆年會(huì)論文集（一）[C];2006年

相關(guān)重要報(bào)紙文章 前3條

1 趙曉濤;從災(zāi)難中尋找安全[N];網(wǎng)絡(luò)世界;2007年

2 安菁菁;濱海新區(qū)金融機(jī)構(gòu)應(yīng)重視信用風(fēng)險(xiǎn)管理[N];中國(guó)會(huì)計(jì)報(bào);2010年

3 招商證券衍生投資部負(fù)責(zé)人 劉成彥;場(chǎng)外金融衍生品風(fēng)險(xiǎn)的類(lèi)別及對(duì)策建議[N];證券時(shí)報(bào);2013年

相關(guān)博士學(xué)位論文 前4條

1 戴明;長(zhǎng)三角地區(qū)船聯(lián)網(wǎng)信息感知與交互關(guān)鍵技術(shù)研究[D];長(zhǎng)安大學(xué);2016年

2 張萬(wàn)軍;基于大數(shù)據(jù)的個(gè)人信用風(fēng)險(xiǎn)評(píng)估模型研究[D];對(duì)外經(jīng)濟(jì)貿(mào)易大學(xué);2016年

3 徐磊;農(nóng)業(yè)巨災(zāi)風(fēng)險(xiǎn)評(píng)估模型研究[D];中國(guó)農(nóng)業(yè)科學(xué)院;2012年

4 廖年冬;信息安全動(dòng)態(tài)風(fēng)險(xiǎn)評(píng)估模型的研究[D];北京交通大學(xué);2010年

相關(guān)碩士學(xué)位論文 前10條

1 陳蓬來(lái);面向農(nóng)村的兩階段多腫瘤風(fēng)險(xiǎn)評(píng)估模型前期研究[D];安徽醫(yī)科大學(xué);2015年

2 申振華;中小企業(yè)信用風(fēng)險(xiǎn)評(píng)估模型研究[D];蘇州大學(xué);2015年

3 崔釜萍;住院患者靜脈血栓栓塞危險(xiǎn)因素的相關(guān)分析[D];華北理工大學(xué);2015年

4 劉思帆;一種基于主機(jī)日志分析的實(shí)時(shí)風(fēng)險(xiǎn)評(píng)估模型的研究與實(shí)現(xiàn)[D];復(fù)旦大學(xué);2014年

5 李美蓮;基于信息服務(wù)保障行駛安全的主動(dòng)控制策略研究[D];西安電子科技大學(xué);2014年

6 徐笑蕊;面向數(shù)字版權(quán)管理系統(tǒng)的風(fēng)險(xiǎn)評(píng)估模型研究與應(yīng)用[D];東華大學(xué);2016年

7 劉爍;物流業(yè)專(zhuān)職駕駛員健康風(fēng)險(xiǎn)評(píng)估體系研究[D];山東財(cái)經(jīng)大學(xué);2016年

8 雷霞飛;基于行業(yè)風(fēng)險(xiǎn)系數(shù)的科技型中小企業(yè)風(fēng)險(xiǎn)評(píng)估模型的研究與實(shí)現(xiàn)[D];吉林大學(xué);2016年

9 楊夢(mèng);我國(guó)上市公司信用風(fēng)險(xiǎn)評(píng)估模型比較及實(shí)證研究[D];西南交通大學(xué);2015年

10 史健;我國(guó)臺(tái)風(fēng)風(fēng)險(xiǎn)評(píng)估及臺(tái)風(fēng)保險(xiǎn)產(chǎn)品設(shè)計(jì)研究[D];廣東財(cái)經(jīng)大學(xué);2015年

，

本文編號(hào)：2177907