兒科多烯磷脂酰膽堿輸液滲漏Logistic回歸預(yù)測模型的建立及其應(yīng)用
發(fā)布時間：2018-10-26 09:12
【摘要】：目的篩選兒科多烯磷脂酰膽堿輸液滲漏有統(tǒng)計學意義的危險因素,初步建立logistic回歸模型,評價該模型的預(yù)測價值。方法選擇兒科脈輸注多烯磷脂酰膽堿患兒153例,其中103例作為模型訓練組用于模型的創(chuàng)建,另外50例作為模型驗證組用于模型的評判。采用單因素和多因素非條件Logistic回歸分析模型訓練組中患兒發(fā)生輸液滲漏的危險因素。通過優(yōu)化組合方式建立Logistic回歸模型,對其穩(wěn)定性進行驗證,并將得到的預(yù)測模型代入驗證數(shù)據(jù)集進行評價。結(jié)果年齡、同一血管進針次數(shù)、護士工作年限及用藥時間4個危險因素在經(jīng)過Logistic回歸分析之后進入模型;利用該回歸模型對模型驗證組中50例多烯磷脂酰膽堿輸注病人進行預(yù)報,其曲線下面積、靈敏性、特異性分別為0.983,92.3%,91.6%。結(jié)論 Logistic回歸分析能夠篩選出對兒科多烯磷脂酰膽堿輸液滲漏有意義的危險因素;該Logistic回歸模型對兒科多烯磷脂酰膽堿輸液滲漏風險有初步預(yù)判的作用。
[Abstract]:Objective to screen the risk factors of polyene phosphatidylcholine infusion leakage in pediatrics and to establish a logistic regression model and evaluate the predictive value of the model. Methods 153 children with Paediatric vein infusion of polyenylphosphatidylcholine were selected, of which 103 were used as model training group and 50 as model validation group. Univariate and multivariate non-conditional Logistic regression analysis was used to analyze the risk factors of transfusion leakage in the training group. The Logistic regression model is established by optimizing the combination method, and its stability is verified, and the prediction model is added to the validation data set to evaluate the stability of the model. Results four risk factors, age, times of injection of the same blood vessel, working life of nurses and duration of medication, entered the model after Logistic regression analysis. The regression model was used to predict 50 patients with polyene phosphatidylcholine infusion in the model verification group. The area, sensitivity and specificity under the curve were 0.983C 92.3% and 91.6%, respectively. Conclusion Logistic regression analysis can screen out the risk factors of percolation of pediatric polyenylphosphatidylcholine infusion, and the Logistic regression model has a preliminary predictive effect on the risk of percolation of pediatric polyene phosphatidylcholine infusion.
【作者單位】： 四川大學華西第二醫(yī)院兒科;出生缺陷與相關(guān)婦兒疾病教育部重點實驗室;
【基金】：國家自然科學基金(81501301) 國家臨床重點�？平ㄗh項目(1311200003303)資助
【分類號】：R473.72
，
本文編號：2295250
[Abstract]:Objective to screen the risk factors of polyene phosphatidylcholine infusion leakage in pediatrics and to establish a logistic regression model and evaluate the predictive value of the model. Methods 153 children with Paediatric vein infusion of polyenylphosphatidylcholine were selected, of which 103 were used as model training group and 50 as model validation group. Univariate and multivariate non-conditional Logistic regression analysis was used to analyze the risk factors of transfusion leakage in the training group. The Logistic regression model is established by optimizing the combination method, and its stability is verified, and the prediction model is added to the validation data set to evaluate the stability of the model. Results four risk factors, age, times of injection of the same blood vessel, working life of nurses and duration of medication, entered the model after Logistic regression analysis. The regression model was used to predict 50 patients with polyene phosphatidylcholine infusion in the model verification group. The area, sensitivity and specificity under the curve were 0.983C 92.3% and 91.6%, respectively. Conclusion Logistic regression analysis can screen out the risk factors of percolation of pediatric polyenylphosphatidylcholine infusion, and the Logistic regression model has a preliminary predictive effect on the risk of percolation of pediatric polyene phosphatidylcholine infusion.
【作者單位】： 四川大學華西第二醫(yī)院兒科;出生缺陷與相關(guān)婦兒疾病教育部重點實驗室;
【基金】：國家自然科學基金(81501301) 國家臨床重點�？平ㄗh項目(1311200003303)資助
【分類號】：R473.72
，
本文編號：2295250
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