连续性肾脏替代治疗患者导管相关感染预测模型的构建与验证

王天琦; 戴伟英; 夏柳勤; 余梦莎

doi:10.16766/j.cnki.issn.1674-4152.004445

连续性肾脏替代治疗患者导管相关感染预测模型的构建与验证

doi: 10.16766/j.cnki.issn.1674-4152.004445

王天琦^{1, 2},
戴伟英^2, ,,
夏柳勤²,
余梦莎²

1.
浙江中医药大学研究生院，浙江杭州 310000
2.
杭州市第一人民医院重症医学科，浙江杭州 310006

基金项目:

浙江省医药卫生科技计划项目 2024KY188

详细信息

通讯作者:
戴伟英，E-mail：52372577@qq.com

中图分类号: R459.5
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出版历程
- 收稿日期: 2024-12-03

Construction and validation of a catheter-related infection prediction model for patients undergoing continuous renal replacement therapy

WANG Tianqi^{1, 2},
Dai Weiying^{2
, ,},
Xia Liuqin²,
Yu Mengsha²

1.
Graduate School, Zhejiang Chinese Medical University, Hangzhou, Zhejiang 310000, China

摘要

摘要: 目的探究行连续性肾脏替代治疗(CRRT)患者导管相关感染(CRI)的风险因素并构建预测模型，评估该模型的临床应用价值。方法回顾性收集2023年1—12月于杭州市第一人民医院ICU行CRRT治疗的208例患者临床资料。利用单因素和多因素logistic逐步回归分析筛选CRRT发生CRI的风险因素并构建预测模型。利用ROC曲线、校准曲线、决策曲线和临床影响曲线分别评估模型的区分度、校准度和临床实用性。结果本研究中CRRT患者CRI发生率为16.8%(35例)。多因素logistic逐步回归分析结果显示，年龄、急性生理和慢性健康评分Ⅱ(APECHE Ⅱ)、合并糖尿病、置管部位、CD4⁺/CD8⁺、白蛋白(ALB)、操作人员手卫生是CRRT发生CRI的风险因素(OR分别为3.494、3.270、4.004、2.328、0.385、0.916和0.390，均P < 0.05)。基于以上7个风险因素构建预测模型。模型ROC曲线下面积为0.854(95% CI：0.784~0.923)。校准曲线结果显示模型预测的校正曲线与理想曲线吻合度良好。决策曲线结果显示当阈概率大于15%时使用该模型作出临床决策，患者净获益均高于不干预或全部干预的极端曲线。临床影响曲线结果显示当阈概率大于30%时，模型判定为CRI高风险人群与实际发生CRI人群匹配度良好。结论本研究构建的CRRT患者CRI发生风险模型具有较高的预测效能及临床应用价值，有助于临床医护人员早期识别CRRT发生CRI的高危人群，进行及时干预，从而改善患者预后。
- 连续性肾脏替代治疗 /
- 导管相关感染 /
- 风险因素 /
- 预测模型
Abstract: Objective To investigate the risk factors for catheter-related infection (CRI) in patients undergoing continuous renal replacement therapy (CRRT), to construct a prediction model, and to evaluate its clinical application value. Methods The clinical data of 208 patients who underwent CRRT in Hangzhou First People ' s Hospital from January to December 2023 were collected. Univariate and multiple logistic regression analyses were used to screen the risk factors for CRI in CRRT patients, and a prediction model was constructed. Receiver operating characteristic (ROC) curve, calibration curve (CC), decision curve analysis (DCA), and clinical impact curve (CIC) were used to evaluate the discrimination, calibration, and clinical utility of the model. Results The incidence of CRI in CRRT patients was 16.8%. Multiple logistic regression analysis showed that age, acute physiology and chronic health evaluation Ⅱ, diabetes mellitus, catheterization site, CD4⁺/CD8⁺, albumin level, and operator hand hygiene (OR=3.494, 3.270, 4.004, 2.328, 0.385, 0.916, and 0.390, respectively; all P < 0.05) were associated with CRI in CRRT patients. A prediction model was constructed based on these seven risk factors. The area under the ROC curve (AUC) was 0.854 (95% CI: 0.784-0.923). The results of the CC showed that the predicted calibration curve of the model closely matched the ideal curve, indicating good agreement. The results of the DCA showed that using this model to guide clinical decisions provided higher net benefits for patients than the extreme strategies of no intervention or full intervention when the threshold probability was greater than 15%. The results of the CIC showed that the population identified as high risk for CRI by the model matched well with the actual population when the threshold probability was greater than 30%. Conclusion The risk prediction model constructed in this study demonstrates high predictive efficacy and clinical utility, which could help identify patients at high risk of CRI during CRRT at an early stage and enable timely intervention, thereby improving prognosis.
- Continuous renal replacement therapy /
- Catheter-related infection /
- Risk factors /
- Prediction model
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图 1 CRRT患者CRI发生风险模型的列线图

Figure 1. Nomogram of the risk prediction model for catheter-related infections in CRRT patients

下载: 全尺寸图片幻灯片

图 2 CRRT患者CRI发生风险模型评价

注：A为ROC曲线；B为校准曲线；C为决策曲线；D为临床影响曲线。

Figure 2. Evaluation of the risk prediction model for catheter-related infections in CRRT patients

下载: 全尺寸图片幻灯片

表 1 CRRT患者CRI发生的单因素分析

Table 1. Univariate analysis of CRI in CRRT patients

项目	感染组(n=35)	未感染组(n=173)	统计量	P值
年龄[例(%)]			9.189^a	0.002
＜60岁	8(22.85)	88(50.87)
≥60岁	27(77.15)	85(49.13)
性别[例(%)]			0.243^a	0.621
男性	19(54.29)	86(49.71)
女性	16(45.71)	87(50.29)
BMI(x±s)	24.01±2.20	23.39±1.92	1.704^b	0.089
APECHE Ⅱ评分[例(%)]			11.121^a	0.001
＜20分	13(37.14)	114(65.90)
≥20分	22(62.86)	59(34.10)
糖尿病[例(%)]			13.74^a	< 0.001
否	12(34.29)	117(67.63)
是	23(65.71)	56(32.37)
高血压[例(%)]			1.241^a	0.265
否	15(42.86)	92(53.20)
是	20(57.14)	81(46.82)
贫血[例(%)]			3.483^a	0.062
否	17(48.57)	113(65.32)
是	18(51.43)	60(34.68)
置管部位[例(%)]			5.214^a	0.022
颈内静脉	15(42.86)	110(63.58)
股静脉	20(57.14)	63(36.42)
穿刺次数[例(%)]			3.883^a	0.048
1次	28(80.00)	160(92.49)
≥2次	7(20.00)	13(7.51)
住院时间[例(%)]			2.578^a	0.108
＜14 d	13(37.14)	90(52.02)
≥14 d	22(62.86)	83(47.98)
置管时间[例(%)]			4.742^a	0.029
＜7 d	19(54.29)	126(72.83)
≥7 d	16(45.71)	47(27.17)
导管移动[例(%)]			4.314^a	0.037
否	21(60.00)	133(76.88)
是	14(40.00)	40(23.12)
使用免疫抑制剂[例(%)]			1.463^a	0.226
否	29(82.86)	158(91.33)
是	6(17.14)	15(8.67)
使用抗生素[例(%)]			4.166^a	0.041
否	16(45.71)	111(64.16)
是	19(54.29)	62(35.84)
抗凝治疗[例(%)]			2.737^a	0.098
否	22(62.86)	132(76.30)
是	13(37.14)	41(23.70)
CD4⁺/CD8⁺[例(%)]			6.110^a	0.013
＜1	24(68.57)	79(45.66)
≥1	11(31.43)	94(54.34)
IgG(x±s, g/L)	9.12±0.95	8.93±1.14	0.896^b	0.371
ALB(x±s, g/L)	28.75±6.54	31.25±5.05	2.530^b	0.012
操作人员相关工作年限[例(%)]			5.452^a	0.019
＜5年	16(45.71)	45(26.01)
≥5年	19(54.29)	128(73.99)
操作人员手卫生[例(%)]			6.155^a	0.013
差	23(65.71)	74(42.77)
较好	12(34.29)	99(57.23)
注：^a为χ²值，^b为t值。

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表 2 影响CRRT患者CRI发生的多因素分析

Table 2. Multivariate analysis of factors associated with CRI in CRRT patients

变量	B	SE	Waldχ²	P值	OR(95% CI)
年龄	1.251	0.430	8.453	0.004	3.494(1.503~8.121)
APECHEⅡ评分	1.185	0.385	9.478	0.002	3.270(1.538~6.952)
糖尿病	1.387	0.391	12.563	< 0.001	4.004(1.859~8.624)
置管部位	0.845	0.376	5.042	0.025	2.328(1.113~4.868)
CD4⁺/CD8⁺	-0.954	0.395	5.839	0.016	0.385(0.178~0.835)
ALB	-0.088	0.036	6.049	0.014	0.916(0.854~0.982)
操作人员手卫生	-0.942	0.388	5.895	0.015	0.390(0.182~0.834)

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