本文選題：老年髖部骨折 + 肺部感染　； 參考：《西南醫(yī)科大學》2017年碩士論文

【摘要】：目的:建立川南地區(qū)老年髖部骨折術后常見并發(fā)癥發(fā)生率和死亡率的預測模型,并檢驗其預測價值。方法:1.建立4份資料收集表,包括老年髖部骨折術后肺部感染、術后認知功能障礙(POCD)、術后下肢深靜脈血栓形成(術后LEDVT)、術后死亡;2.收集2012年1月到2016年10月于西南醫(yī)科大學附屬醫(yī)院住院手術治療的此類患者臨床數(shù)據(jù),填入相對應的資料收集表;3.然后利用Epidata3.1軟件建立相應4個數(shù)據(jù)庫并將相對應的資料收集表中的臨床數(shù)據(jù)錄入數(shù)據(jù)庫;將數(shù)據(jù)導入spss19.0軟件進行統(tǒng)計分析:計量資料采用t檢驗、計數(shù)資料采用χ2檢驗進行變量的單因素分析,獲得有統(tǒng)計學意義的變量(以?=0.05為檢驗水準,P值(27)0.05變量有統(tǒng)計學意義);4.在生理學和手術嚴重度評分系統(tǒng)(physical and operation severity score for the enumeration of mortality and morbidity,POSSUM)的基礎上,將這些變量分為生理學指標和手術嚴重性指標兩類,建立起老年髖部骨折術后肺部感染、POCD、術后LEDVT、術后死亡的評分系統(tǒng)。通過Logistic回歸分析得出此類患者術后肺部感染、POCD、術后LEDVT、術后死亡發(fā)生率預測模型;5.最后用實際值與預測值的比值、ROC曲線、Hosmer-Lemeshow檢驗來評估其預測價值。結果:1.術后肺部感染組:1)生理學指標中的年齡、白細胞、ASA分級、COPD、心功能分級、合并癥數(shù)量,以及手術嚴重性指標中的術前準備時間、手術時間、術中失血量、麻醉方式是術后肺部感染的危險因素。2)術后肺部感染風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-7.187+0.226×PS+0.161×OS。3)該模型術后肺部感染率的預測值平均8.93%,實際值9.89%,實際值/預測值1.11,兩者之間差異無統(tǒng)計學意義(χ2=0.279,P=0.6730.05)。ROC曲線結果顯示靈敏度(Se)=82.7%,特異度(Sp)=72.4%,誤診率(?)=27.6%,漏診率(β)=17.3%,ROC曲線下面積為0.814。對該預測模型進行Hosmer-Lemeshow檢驗,結果顯示,此評分系統(tǒng)預測術后肺部并發(fā)癥發(fā)生率(H2=7.707,df=8,P=0.4630.05)效果良好,數(shù)據(jù)中的信息被充分提取。2.術后LEDVT組:1)生理學指標中的年齡、FIB、血清甘油三酯、BMI、靜脈曲張、高血壓、冠心病、糖尿病、腦卒中、感染以及手術嚴重性指標中的麻醉、術前準備時間、出血量、手術時間是術后LEDVT的危險因素。2)術后LEDVT風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-11.493+0.347×PS+0.327×OS。3)該模型術后LEDVT發(fā)生率預測值為平均12.57%,實際值為13.38%,實際值/預測值為1.06,兩者之間差異無統(tǒng)計學意義(χ2=0.144,P=0.7760.05)。ROC曲線結果顯示Se=74.20%,Sp=86.20%,?=13.80%,β=25.80%,ROC曲線下面積為0.87。對該預測模型進行Hosmer-Lemeshow檢驗,結果顯示,該評分系統(tǒng)預測術后LEDVT發(fā)生率(H2=3.309,df=8,P=0.9140.05)效果良好,數(shù)據(jù)中的信息被充分提取。3.POCD組:1)生理學指標中的年齡、血壓(收縮壓)、白蛋白、氧分壓、合并癥數(shù)量,COPD、腦卒中以及手術嚴重性指標重的手術時間、失血量、麻醉方式是POCD的危險因素。2)POCD風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-6.88+0.191×PS+0.302×OS。3)該模型POCD發(fā)生率的預測值為平均12.38%,實際為14.28%,實際值/預測值為1.15,兩者之間差異無統(tǒng)計學意義(χ2=0.330,P=0.6670.05)。ROC曲線結果顯示Se=53.3%,Sp=90%,?=10%,β=46.7%,ROC曲線下面積為0.759。對該預測模型進行Hosmer-Lemeshow檢驗,結果顯示,此評分系統(tǒng)預測術后POCD發(fā)生率(H2=7.707,df=8,P=0.4630.05)效果良好,數(shù)據(jù)中的信息被充分提取。4.術后死亡組:1)生理學指標中的年齡、白細胞、白蛋白、血壓(收縮壓)、肌酐、ASA分級、心功能分級、合并癥數(shù)量、COPD、腦卒中、糖尿病以及手術嚴重性指標中的手術方式、術前準備時間、手術時間、術中失血量是術后死亡的危險因素。2)術后死亡風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-11.565+0.265×PS+0.121×OS。3)該模型術后死亡率的預測值為平均3.99%,實際為5.18%,實際值/預測值為1.3,兩者之間差異無統(tǒng)計學意義(χ2=0.820,P=0.4510.05)。ROC曲線結果顯示Se=96.2%,Sp=88.8%,?=11.2%,β=3.8%,ROC曲線下面積為0.967。對該預測模型進行Hosmer-Lemeshow檢驗,結果顯示,該評分系統(tǒng)預測術后死亡發(fā)生率(H2=10.869,df=8,P=0.2090.05)效果良好,數(shù)據(jù)中的信息被充分提取。結論:本課題初步建立起川南地區(qū)老年髖部骨折術后常見并發(fā)癥發(fā)生率和死亡率的評分系統(tǒng)及其預測模型:1)術后肺部感染風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-7.187+0.226×PS+0.161×OS。2)術后LEDVT風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-11.493+0.347×PS+0.327×OS。3)POCD風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-6.88+0.191×PS+0.302×OS。4)術后死亡風險評分系統(tǒng)預測模型:Ln[R/(1-R)]=-11.565+0.265×PS+0.121×OS。并用實際值與預測值的比值、ROC曲線、Hosmer—Lemeshow檢驗來評估其預測價值,結果顯示四個預測模型均具有良好的準確度。本課題針對術后并發(fā)癥的范圍廣泛的問題將其進行細化,對常見的不同并發(fā)癥,具體問題具體分析,得出各自的手術風險因素,排除一些與本并發(fā)癥無關的風險因素,針對性更強,效率更高。但樣本樣不足,未進行前瞻性研究,沒有將本次研究結果與PPOSSUM以及骨科POSSUM的統(tǒng)計結果相比較,故仍需要進一步的深入研究。
[Abstract]:Objective: to establish a predictive model for the incidence and mortality of common complications after hip fracture in the south of Sichuan, and to test its predictive value. Methods: 1., 4 data collection tables were established, including postoperative pulmonary infection, postoperative cognitive dysfunction (POCD), postoperative deep venous thrombosis (postoperative LEDVT), postoperative death, and postoperative death; 2. The clinical data of these patients who were hospitalized in the Affiliated Hospital of Southwest Medical University from January 2012 to October 2016 were collected and the corresponding data collection table was filled. 3. then the corresponding 4 databases were established by using Epidata3.1 software and the clinical data in the corresponding data collection table were recorded into the database; the data were introduced into the spss19.0 software. Statistical analysis: the measurement data were tested by T, and the count data were analyzed by the x 2 test for single factor analysis. The statistical variables were statistically significant (with =0.05 as the test level and the P value (27) 0.05 variables were statistically significant); 4. was in the physiological and surgical severity score system (physical and operation severity score for the enumeration. On the basis of of mortality and morbidity, POSSUM), these variables are divided into two categories of physiological index and surgical severity index. The scoring system for postoperative lung infection, POCD, postoperative LEDVT, and postoperative death of the aged hip fractures is established. The postoperative pulmonary infection, POCD, postoperative LEDVT, and postoperative death are obtained by Logistic regression analysis. Incidence prediction model; 5. finally, using the ratio of actual value to predicted value, ROC curve, and Hosmer-Lemeshow test to evaluate its predictive value. Results: 1. postoperative pulmonary infection group: 1) age, leukocyte, ASA classification, COPD, cardiac function classification, number of complications, and preoperative preparation time in surgical severity index, operation time, operation time, operation time, operation time, operation time, operation time, operation time, operation time, operation time, operation time, operation time, operation time The amount of blood loss during the operation, the way of anesthesia was the risk factor of pulmonary infection after operation.2) the prediction model of the lung infection risk score system after operation: Ln[R/ (1-R)]=-7.187+0.226 x PS+0.161 x OS.3) the predicted value of the pulmonary infection rate of the model was 8.93%, the actual value was 9.89%, the actual value / prediction value was 1.11, there was no statistical difference between the two (x 2=0.27). 9, P=0.6730.05).ROC curve showed sensitivity (Se) =82.7%, specificity (Sp) =72.4%, misdiagnosis rate (?) =27.6%, missed diagnosis rate (beta) =17.3%, and 0.814. under ROC curve for Hosmer-Lemeshow test of the prediction model. The results showed that the rate of lung complications after the pre test of this scoring system was good, data were good, data were good, data The information in the LEDVT group was fully extracted after.2.: 1) age, FIB, serum triglycerides, serum triglycerides, BMI, varicose veins, hypertension, coronary heart disease, diabetes, stroke, infection, and surgical severity indicators, preoperative preparation time, bleeding volume, and operation time, the risk factor of LEDVT after operation,.2), LEDVT risk score after operation. System prediction model: Ln[R/ (1-R)]=-11.493+0.347 x PS+0.327 x OS.3) the prediction value of LEDVT incidence of the model after operation is 12.57%, the actual value is 13.38%, the actual value / prediction value is 1.06, there is no statistical difference between the two (P=0.7760.05).ROC curve fruit display Se=74.20%, Sp=86.20%, beta, beta area under the curve area Hosmer-Lemeshow test was performed on the 0.87. model for the prediction model. The results showed that the scoring system predicted the LEDVT incidence (H2=3.309, df=8, P=0.9140.05) after operation. The information in the data was fully extracted from the.3.POCD group: 1) age, blood pressure (systolic pressure), albumin, oxygen pressure, number of complications, COPD, stroke and hands in the physiological indexes. The operation time, the amount of blood loss and the way of anesthesia were the risk factor of POCD.2) POCD risk scoring system prediction model: Ln[R/ (1-R)]=-6.88+0.191 x PS+0.302 x OS.3) the predicted value of the POCD incidence of the model was 12.38%, the actual value was 14.28%, the actual value / prediction value was 1.15, there was no statistical difference between the two (x 2=0.330,) P=0.6670.05) the results of the.ROC curve show Se=53.3%, Sp=90%, =10%, beta =46.7%, and 0.759. under ROC curve for the Hosmer-Lemeshow test of this prediction model. The results show that this scoring system predicts the incidence of POCD after operation (H2=7.707, df=8,) is good, and the information in the data is fully extracted after the operation: 1) physiological index The age, white blood cell, albumin, blood pressure (systolic pressure), creatinine, ASA classification, cardiac function classification, complication number, COPD, stroke, diabetes and surgical severity index, preoperative preparation time, operation time, intraoperative blood loss are the risk factors for postoperative death.2) the prediction model of postoperative death risk score system: Ln[ R/ (1-R)]=-11.565+0.265 x PS+0.121 x OS.3) the predictive value of postoperative mortality of the model was 3.99%, the actual value was 5.18%, the actual value / prediction value was 1.3. There was no statistical difference between the two models (P=0.4510.05).ROC curve results showed Se=96.2%, Sp=88.8%, =11.2%, beta =3.8%. Smer-Lemeshow test, the results showed that the scoring system predicted the incidence of postoperative mortality (H2=10.869, df=8, P=0.2090.05), and the information in the data was fully extracted. Conclusion: this project initially established a scoring system for the incidence and mortality of common complications after hip fracture in the south of Sichuan Province and its prediction model: 1) lung after operation. Ln[R/ (1-R)]=-7.187+0.226 x PS+0.161 x OS.2) prediction model of LEDVT risk scoring system after operation: Ln[R/ (1-R)]=-11.493+0.347 x PS+0.327 x OS.3) POCD risk scoring system prediction model: the prediction model of postoperative mortality risk score system 565+0.265 x PS+0.121 x OS. and the ratio of the actual value to the predicted value, the ROC curve and the Hosmer Lemeshow test to evaluate their predictive value. The results show that the four prediction models have good accuracy. Analyze the risk factors of the operation and eliminate some risk factors that are not related to the complications, which are more pertinent and more efficient. However, there is no prospective study on the sample sample and no comparison between the results of this study and the statistical results of the PPOSSUM and Department of orthopedics in the Department of orthopedics, so further in-depth study is needed.

【學位授予單位】：西南醫(yī)科大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：R687.3

【參考文獻】

相關期刊論文 前10條

1 魏濱;張華;王軍;張利萍;郭向陽;李民;周方;;2種不同麻醉方法對髖部骨折老年患者術后肺部并發(fā)癥發(fā)生的多因素分析[J];中國微創(chuàng)外科雜志;2015年04期

2 夏樂強;王瑛;陳文亞;王琰;;老年患者術后認知功能障礙與2型糖尿病及糖化血紅蛋白水平的關系[J];華西醫(yī)學;2014年02期

3 武成興;吳軍;張蜀平;包遠祥;王小強;孫錦波;;老年髖關節(jié)置換術后深靜脈血栓形成的危險因素研究[J];現(xiàn)代預防醫(yī)學;2012年21期

4 郝建國;王梯健;;POSSUM及P-POSSUM骨科評分系統(tǒng)在髖部骨折的應用[J];浙江中西醫(yī)結合雜志;2010年05期

5 蘭秀夫;于騰波;孫紅振;殷翔;王愛民;;建立一種新評分系統(tǒng)用于術前評估老年髖部骨折手術風險[J];中華創(chuàng)傷雜志;2010年03期

6 王鑫;黃朝梁;鄧忠良;陳世榮;柯珍勇;陳富;;老年髖部骨折術后認知障礙[J];中國老年學雜志;2005年12期

7 方秀統(tǒng),張新,王博,豐景斌,高鵬;老年人髖部骨折術后死亡分析[J];骨與關節(jié)損傷雜志;2004年07期

8 饒忠,黃謙,周紅菊;改良POSSUM評分系統(tǒng)預測老年燒傷患者術后并發(fā)癥的價值[J];廣西醫(yī)科大學學報;2004年01期

9 羅紅;術后ICU患者精神障礙相關因素的分析[J];中國現(xiàn)代醫(yī)學雜志;2003年15期

10 張挺杰,皋源,江燕,于昕,王祥瑞,杭燕南;老年病人術后精神障礙的發(fā)生率和病因分析[J];臨床麻醉學雜志;2003年02期

相關碩士學位論文 前3條

1 張志強;改良POSSUM和P-POSSUM評分系統(tǒng)預測中老年股骨粗隆間骨折內固定術后死亡率和并發(fā)癥率的價值[D];廣州中醫(yī)藥大學;2009年

2 李元城;改良POSSUM與P-POSSUM系統(tǒng)對老年人工髖關節(jié)置換患者術前評估價值初探[D];四川大學;2007年

3 張博皓;改良生理學和手術嚴重度評分系統(tǒng)（POSSUM）預測髖部骨折手術并發(fā)癥發(fā)生率及死亡率的價值[D];吉林大學;2004年

，

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