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急诊住院患者急性肾损伤的预测模型构建 |
苏一奇,沈道琪,王一梅,徐夏莲,滕杰,丁小强
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1.复旦大学附属中山医院厦门医院肾内科, 厦门 361006;2.复旦大学附属中山医院肾内科, 上海肾脏疾病临床医学中心, 上海市肾病与透析研究所, 上海市肾脏疾病与血液净化重点实验室, 上海 200032
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摘要: |
目的: 建立急诊住院患者急性肾损伤(acute kidney injury, AKI)发病的预测模型,并进行验证。方法: 连续收集2014年10月至2015年9月复旦大学附属中山医院310例急诊科住院患者入院时的临床资料。采用单因素logistic回归计算各指标预测发生AKI的OR值及P值;多因素logistic回归采用逐步后退法,筛选出独立危险因素并纳入预测模型。将310例患者随机分为2组,206例为训练组,用其指标构建模型,104例为验证组。计算模型在2组的区分度(ROC曲线)、校准度(校准曲线)和临床适用性(DCA曲线)。采用多因素logistic回归分析筛选出的独立危险因素绘制列线图,预测急诊住院患者AKI的发生风险。结果: AKI的发病率为36.1%(112/310)。血红蛋白、尿素、肌酐、血清镁等11项指标在AKI组与非AKI组间差异有统计学意义(P<0.05)。多因素logistic回归显示,白蛋白、肌酐、血清镁、血糖是AKI发生的独立危险因素(P<0.05)。AKI预测模型为logitic(PAKI)=-0.113白蛋白+0.021肌酐+3.837血清镁+0.108血糖-2.878,高于0.398认为存在AKI。此模型在训练组和验证组的AUC分别是0.790(95%CI 0.722~0.859,P<0.001)、0.752(95%CI 0.646~0.858,P<0.001)。校准曲线U检验显示,训练组与验证组的校准度均较好(P>0.05)。DCA曲线显示,该模型具有较好的临床适用性。结论: 该含血清镁的模型对急诊住院患者AKI发生有较好的预测价值,对临床具有较好的指导作用。 |
关键词: 急诊 急性肾损伤 预测模型 血清镁 危险因素 临床适用性 |
DOI:10.12025/j.issn.1008-6358.2021.20201944 |
分类号:R692 |
基金项目:国家自然科学基金(81770734),上海市肾脏疾病临床医学中心建设项目(2017ZZ01015),上海市肾脏疾病与血液净化重点实验室项目(14DZ2260200). |
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Establishment of a predictive model for acute kidney injury in emergency inpatients |
SU Yi-qi1, SHEN Dao-qi2,3,4,5, WANG Yi-mei2,3,4,5, XU Xia-lian2,3,4,5, TENG Jie1,2,3,4,5, DING Xiao-qiang2,3,4,5
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1.Department of Nephrology, Xiamen Branch, Zhongshan Hospital, Fudan University, Xiamen 361006, Fujian, China;2.Department of Nephrology, Zhongshan Hospital, Fudan University;3.Shanghai Medical Center of Kidney Disease;4.Shanghai Institute of Kidney Disease and Dialysis;5.Shanghai Laboratory of Kidney Disease and Dialysis, Shanghai 200032, China
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Abstract: |
Objective: To establish and verify the prediction model of acute kidney injury (AKI) in emergency inpatients. Methods: The clinical data of 310 inpatients admitted to the Emergency Department of Zhongshan Hospital, Fudan University from October 2014 to September 2015 were collected. Univariate logistic regression was used to calculate the OR value and P value of each index for AKI occurrence. Independent risk factors were selected by stepwise multiple factor logistic regression method and included in the AKI prediction model. 206 patients were included in the training group, and 104 patients were included in the validation group. The discrimination (ROC curve), calibration degree (calibration curve), and clinical applicability (DCA curve) of the model in the two groups were calculated. Multivariate logistic regression was used to draw a nomogram to predict the risk of AKI in emergency inpatients. Results: The incidence rate of AKI was 36.1% (112/310). There were significant differences in albumin, urea, creatinine, serum magnesium, and other 7 indexes between the AKI and non-AKI groups (P<0.05). Multivariate logistic regression showed that albumin, creatinine, serum magnesium, and blood glucose were independent risk factors for AKI. The prediction model of AKI was logitic (PAKI)=-0.113albumin+0.021creatinine+3.837serum magnesium + 0.108 blood glucose -2.878, and AKI is considered if the result is higher than 0.398. The AUC of the model in the training group and validation group were 0.790(95%CI 0.722-0.859,P<0.001) and 0.752(95%CI 0.646-0.858,P<0.001), respectively. Calibration curve U-test showed that the calibration degree of the training group and validation group were good (P>0.05). DCA curve showed that the model had good clinical applicability. Conclusions: The model including serum magnesium has a good predictive value in the incidence of AKI in emergency inpatients and has a good guiding role in clinical practice. |
Key words: emergency acute kidney injury prediction model serum magnesium risk factor clinical applicability |