切换至 "中华医学电子期刊资源库"
高级检索
中华实验和临床感染病杂志(电子版)

中华实验和临床感染病杂志(电子版) ›› 2023, Vol. 17 ›› Issue (05) : 299 -306. doi: 10.3877/cma.j.issn.1674-1358.2023.05.003

论著

术前预测感染性肾结石列线图模型的构建及验证
郑鹏, 吴赛萍, 谢秀璋, 史庆丰†()   
  1. 213000　常州市，江苏大学附属武进医院（徐州医科大学武进临床学院）感染管理科
    200032　上海，复旦大学附属中山医院感染管理科
  • 收稿日期:2023-05-05 出版日期:2023-10-15
  • 通信作者: 史庆丰
  • 基金资助:
    2019年度上海市卫生健康委员会卫生行业临床研究专项项目(No. 201940413)

Construction and validation of a nomogram model for predicting infectious kidney stones before surgery

Peng Zheng, Saiping Wu, Xiuzhang Xie, Qingfeng Shi†()   

  1. Department of Infection Management, Wujin Hospital Affiliated to Jiangsu University (Wujin Clinical College of Xuzhou Medical University), Changzhou 213000, China
    Department of Infection Management, Zhongshan Hospital, Fudan University, Shanghai 200032, China
  • Received:2023-05-05 Published:2023-10-15
  • Corresponding author: Qingfeng Shi
全文 ( ) 下载PDF ( ) 导出引用
引用本文：

郑鹏, 吴赛萍, 谢秀璋, 史庆丰. 术前预测感染性肾结石列线图模型的构建及验证[J]. 中华实验和临床感染病杂志(电子版), 2023, 17(05): 299-306.

Peng Zheng, Saiping Wu, Xiuzhang Xie, Qingfeng Shi. Construction and validation of a nomogram model for predicting infectious kidney stones before surgery[J]. Chinese Journal of Experimental and Clinical Infectious Diseases(Electronic Edition), 2023, 17(05): 299-306.

目的

建立一款用于术前预测感染性肾结石的列线图模型并进行验证。

方法

回顾性总结2020年2月至2023年2月江苏大学附属武进医院（徐州医科大学武进临床学院）诊断肾结石患者共350例，按7︰3随机分为建模集（245例）和验证集（105例）。建模集中感染性肾结石91例和无感染性肾结石154例，验证集中感染性肾结石患者39例和无感染性肾结石患者66例。比较建模集中感染性肾结石组与无感染性肾结石组患者的临床资料，采用最小绝对值收敛和选择算子回归（Lasso）模型和多因素Logistic回归模型筛选感染性肾结石的危险因素，R软件建立列线图模型，采用1 000次自我重复采样进行验证。

结果

单因素分析发现，建模集患者中感染性肾结石组女性、复发性肾结石和鹿角形结石、结石面积较无感染性肾结石组显著增加，而结石Hounsfield单位（HU）显著降低；术前膀胱尿液培养阳性（PBUC）、尿白细胞计数（WBC）和细菌量、尿蛋白阳性、尿亚硝酸盐阳性、尿白细胞酯酶阳性（ULE）、尿pH值升高、尿液浊度阳性例数占比较无感染性肾结石组显著增多，而尿比重显著下降；血尿酸水平较无感染性肾结石组降低，但血磷和血镁升高，差异均有统计学意义（P均< 0.05）。Lasso回归分析筛选出8个最具差异性的指标，即女性、复发性肾结石、结石面积≥ 601 mm2、HU值< 1 000、阳性PBUC、阳性ULE、尿pH和尿液浊度阳性。Logistic回归分析显示，女性（OR = 1.568、95%CI：1.231~1.902、P < 0.001）、复发性肾结石（OR = 3.023、95%CI：2.568~3.467、P < 0.001）、结石面积≥ 601 mm2（OR = 2.123、95%CI：1.756~2.569、P < 0.001）、HU值< 1 000（OR = 3.856、95%CI：3.456~4.325、P < 0.001）、阳性PBUC（OR = 1.895、95%CI：1.623~2.325、P < 0.001）、阳性ULE（OR = 1.754、95%CI：1.326~2.124、P < 0.001）、尿pH > 6.5（OR = 1.323、95%CI：1.102~1.889、P < 0.001）和尿液浊度阳性（OR = 1.602、95%CI：1.314~1.956、P < 0.001）均为感染性肾结石的危险因素。通过R软件建立列线图模型，总分220分。受试者工作曲线（ROC）显示，列线图模型预测验证集感染性肾结石敏感度和特异度分别为79.8%和83.2%，ROC曲线下面积（AUC）为0.856（95%CI：0.810~0.912、P < 0.001），提示模型的诊断区分效能较好。校正曲线和决策曲线也显示模型有较好的吻合度和临床净获益比。

结论

女性、复发性肾结石、结石面积≥ 601 mm2、HU值< 1 000、阳性PBUC、阳性ULE、尿pH和尿液浊度阳性可辅助评估感染性肾结石的发生风险，本研究建立的列线图模型可指导临床实践，有较好的应用潜力。

关键词: 感染性肾结石, 列线图模型, 术前膀胱尿液培养, 尿白细胞酯酶
Objective

To establish a nomogram model for preoperative prediction of infectious kidney stones.

Methods

Total of 350 patients with kidney stones diagnosed in Wujin Hospital Affiliated to Jiangsu University (Wujin Clinical College of Xuzhou Medical University) from February 2020 to February 2023 were summarized, retrospectively, and were randomly divided into a modeling set (245 cases) and a validation set (105 cases) according to 7︰3. The modeling focused on 91 cases with infectious kidney stones and 154 cases with non-infectious kidney stones, and verified 39 cases of concentrated infectious kidney stones and 66 cases of non-infectious kidney stones. The clinical data of patients in infective kidney stone group and non-infective kidney stone group were compared in the modeling set. The minimum absolute convergence and selection operator regression (Lasso) model and multi-factor Logistic regression model were used to screen the risk factors of infective kidney stone. The nomographic model was established and verified by 1 000 self-repeated samples through R software.

Results

Univariate comparison showed that female, recurrent kidney stones and staghorn stones in the infectious kidney stones group were more, the stone area was larger, while the Hounsfield unit (HU) of stones was significantly fewer; positive preoperative bladder urine culture (PBUC), urine white blood cell count (WBC) and bacterial count, urine protein positive, urine nitrite positive, positive urine leukocyte esterase (ULE), urine pH value, and urine turbidity positive were significantly higher, while urine specific gravity was significantly lower; blood uric acid was lower, while blood phosphorus and magnesium were higher (all P < 0.05). Lasso screened 8 most differential indicators, namely female, recurrent kidney stones, stone area ≥ 601 mm2, HU value < 1 000, positive PBUC, positive ULE, urine pH and urine turbidity positive. Logistic regression showed that female (OR = 1.568, 95%CI: 1.231-1.902, P < 0.001), recurrent kidney stones (OR = 3.023, 95%CI: 2.568-3.467, P < 0.001), stone area ≥ 601 mm2 (OR = 2.123, 95%CI: 1.756-2.569, P < 0.001), HU value < 1 000 (OR = 3.856, 95%CI: 3.456-4.325, P < 0.001), positive PBUC (OR = 1.895, 95%CI: 1.623-2.325, P < 0.001), positive ULE (OR = 1.754, 95%CI: 1.326-2.124, P < 0.001), urinary pH > 6.5 (OR = 1.323, 95%CI: 1.102-1.889, P < 0.001) and positive urine turbidity (OR = 1.602, 95%CI: 1.314-1.956, P < 0.001) were the risk factors to infectious kidney stones. R software was used to establishe a nomogram model, with a total score of 220 points. The receiver operating curve (ROC) showed that the area under the curve (AUC) of the nematic model was 0.856 (95%CI: 0.810-0.912, P < 0.001), the sensitivity and specificity were 79.8% and 83.2%, respectively, indicating that the diagnostic areas of the model were better. The calibration curve and decision curve also showed that the model had a good fit and clinical net benefit ratio.

Conclusions

Female, recurrent kidney stones, stone area ≥ 601 mm2, HU value < 1 000, positive PBUC, positive ULE, urine pH and positive urine turbidity could assist in assessing the risk of infectious kidney stones. A nomogram model that has good application potential to guide clinical practice was established.

Key words: Infectious kidney stones, Nomogram model, Preoperative bladder urine culture, Urinary leukocyte esterase
表1 245例建模集无感染性肾结石组和感染性肾结石组患者的临床资料
临床资料 无感染性肾结石组（154例） 感染性肾结石组（91例） 统计量 P值
人口学信息        
男/女（例） 98/56 36/55 χ2 = 13.380 < 0.001
年龄（ ± s，岁） 55.6 ± 6.7 56.8 ± 7.2 t = 0.564 0.423
BMI（ ± s，kg/m2） 23.2 ± 1.4 23.4 ± 1.5 t = 0.236 0.687
高血压[例（%）] 62（40.3） 32（35.2） χ2 = 0.628 0.428
糖尿病[例（%）] 31（20.1） 11（12.1） χ2 = 2.604 0.107
结石特征        
复发性肾结石[例（%）] 32（20.8） 36（39.6） χ2 = 10.062 0.002
鹿角形结石[例（%）] 33（21.4） 31（34.1） χ2 = 4.734 0.030
双侧结石[例（%）] 19（12.3） 12（13.2） χ2 = 0.037 0.847
结石面积（ ± s，mm2） 658.9 ± 123.4 1 023.5 ± 325.6 t = 32.526 < 0.001
HU值（ ± s） 989.7 ± 253.2 754.5 ± 102.2 t = 19.658 < 0.001
治疗方式[例（%）]     χ2 = 1.131 0.568
mPCNL 62（40.3） 35（38.5）    
RIRS 53（34.4） 37（40.7）    
ESWL 39（25.3） 19（20.8）    
留置输尿管支架[例（%）] 17（11.0） 13（14.3） χ2 = 0.561 0.454
经皮肾造口术[例（%）] 15（9.7） 10（11.0） χ2 = 0.097 0.755
尿液分析        
阳性PBUC [例（%）] 38（24.7） 49（53.8） χ2 = 21.254 < 0.001
WBC（ ± s，× 109/L） 326.5 ± 112.4 512.6 ± 102.4 t = 10.235 < 0.001
RBC（ ± s，× 109/L） 135.6 ± 45.7 123.5 ± 42.3 t = 0.869 0.232
细菌量（ ± s，个/ml） 75.6 ± 12.3 125.4 ± 23.6 t = 9.635 < 0.001
蛋白阳性[例（%）] 36（23.4） 40（44.0） χ2 = 11.321 0.001
亚硝酸盐阳性[例（%）] 31（20.1） 35（38.5） χ2 = 9.766 0.002
ULE阳性[例（%）] 75（48.7） 74（81.3） χ2 = 25.537 < 0.001
pH（ ± s） 6.1 ± 0.3 6.5 ± 0.4 t = 5.003 < 0.001
浊度阳性[例（%）] 32（20.8） 33（36.3） χ2 = 7.036 0.008
比重（ ± s） 1.010 ± 0.003 1.008 ± 0.003 t = 3.968 0.003
血生化（ ± s）        
肌酐（μmol/L） 116.9 ± 22.4 120.2 ± 23.6 t = 0.654 0.369
BUN（mmol/L） 6.2 ± 1.3 6.3 ± 1.2 t = 0.352 0.845
尿酸（μmol/L） 388.9 ± 52.3 356.5 ± 45.9 t = 4.124 0.001
PTH（pg/ml） 52.6 ± 13.4 50.2 ± 12.3 t = 0.458 0.723
钙（mmol/L） 2.28 ± 0.13 2.26 ± 0.12 t = 0.069 0.912
磷（mmol/L） 1.14 ± 0.03 1.18 ± 0.03 t = 3.996 0.002
镁（mmol/L） 0.83 ± 0.02 0.85 ± 0.03 t = 3.325 0.005
图1 感染性肾结石的危险因素Lasso回归分析注：A：采用最小准则进行五倍交叉验证，绘制部分似然偏差（二项偏差）与对数（lambda）的关系曲线。采用最小准则和1-SE准则在最佳点绘制垂直虚线得到最佳参数（lambda）；B：根据对数（lambda）序列绘制系数剖面图，由五倍交叉验证所得最佳参数（lambda）处绘制垂直线，得出最佳参数应对应8个具有非零系数的特征
表2 感染性肾结石的危险因素Logistic回归分析
影响因素 β值 Wald χ2值 OR值 95%CI P值
女性 0.602 6.897 1.568 1.231~1.902 < 0.001
复发性肾结石 1.235 32.321 3.023 2.568~3.467 < 0.001
结石面积≥ 601 mm2 0.963 15.587 2.123 1.756~2.569 < 0.001
HU值< 1 000 1.528 52.634 3.856 3.456~4.325 < 0.001
阳性PBUC 0.898 13.325 1.895 1.623~2.325 < 0.001
阳性ULE 0.756 9.032 1.754 1.326~2.124 < 0.001
尿pH > 6.5 0.456 5.265 1.323 1.102~1.889 < 0.001
尿液浊度阳性 0.668 8.124 1.602 1.314~1.956 < 0.001
图2 预测感染性肾结石的列线图模型
图3 列线图预测感染性肾结石的ROC曲线
表3 列线图预测建模集与验证集感染性肾结石的效能验证
组别 敏感度（%） 特异度（%） 阳性预测值（%） 阴性预测值（%） AUC 95%CI P值
建模集 85.2 90.3 84.3 95.2 0.899 0.831~0.945 < 0.001
验证集 79.8 83.2 79.8 86.5 0.856 0.810~0.912 < 0.001
图4 列线图预测感染性肾结石的校准曲线注：实际状态表示临床上感染性肾结石的实际发生率，偏差校正为列线图预测感染性肾结石的发生概率，理想状态表示两者完全吻合
图5 列线图预测感染性肾结石的决策曲线注：预测模型代表列线图预测感染性肾结石的高风险阈值和净获益比，提示在0.36~0.79阈值范围可获得满意的净获益比；全部表示所有患者均存在感染性肾结石，无代表所有患者均未发生感染性肾结石
[1]
何祥彪, 刘杨洋, 杜丹, 等. 部分无管化与标准经皮肾镜取石术治疗上尿路结石的有效性及安全性研究[J]. 现代泌尿外科杂志,2023,4(4):1-4.
[2]
Geavlete B, Mareș C, Mulțescu R, et al. Hybrid flexible ureteroscopy strategy in the management of renal stones-a narrative review[J]. J Med Life,2022,15(8):919-926.
[3]
Espinosa-Ortiz EJ, Eisner BH, Lange D, et al. Current insights into the mechanisms and management of infection stones[J]. Nat Rev Urol,2019,16(1):35-53.
[4]
Song F, Liu C, Zhang J,et al. Antibacterial effect of fosfomycin tromethamine on the bacteria inside urinary infection stones[J]. Int Urol Nephrol,2020,52(4):645-654.
[5]
Gao X, Lu C, Xie F, et al. Risk factors for sepsis in patients with struvite stones following percutaneous nephrolithotomy[J]. World J Urol,2020,38(1):219-229.
[6]
Yang Z, Lin D, Hong Y, et al. The effect of preoperative urine culture and bacterial species on infection after percutaneous nephrolithotomy for patients with upper urinary tract stones[J]. Sci Rep,2022,12(1): 4833-4835.
[7]
Chen D, Jiang C, Liang X, et al. Early and rapid prediction of postoperative infections following percutaneous nephrolithotomy in patients with complex kidney stones[J]. BJU international, 2019,123(6):1041-1047.
[8]
Chugh S, Pietropaolo A, Montanari E, et al. Predictors of Urinary infections and urosepsis after ureteroscopy for stone disease: a systematic review from EAU Section of Urolithiasis (EULIS)[J]. Curr Urol Rep,2020,21(4):16-18.
[9]
Zhang D, Li S, Zhang Z, et al. Urinary stone composition analysis and clinical characterization of 1520 patients in central China[J]. Sci Rep,2021,11(1):6467.
[10]
苏晓伟, 王大明, 丁德茂, 等. 感染性结石的相关临床易感因素研究[J]. 临床泌尿外科杂志,2021,36(4):284-287.
[11]
Yuan F, Huang Z, Yang T, et al. Pathogenesis of proteus mirabilis in catheter-associated urinary tract infections[J]. Urol Int,2021,105(5-6):354-361.
[12]
刘笑宇, 刁呈文, 付青松, 等. 输尿管镜钬激光碎石术在口服抗血栓药物合并上尿路结石患者中的应用[J]. 临床泌尿外科杂志,2022,37(6):431-435.
[13]
Haas CR, Li G, Hyams ES, et al. Delayed decompression of obstructing stones with urinary tract infection is associated with increased odds of death[J]. J Urol,2020,204(6):1256-1262.
[14]
熊波波, 张劲松, 李宁, 等. 硕通镜和输尿管镜钬激光在输尿管上段感染性结石疗效对比[J]. 临床泌尿外科杂志,2020,35(7):566-570.
[15]
Peng C, Chen Z, Xu J. Risk factors for urinary infection after retrograde upper urinary lithotripsy: Implication for nursing[J]. Medicine (Baltimore),2021,100(31):e26172.
[16]
Bauza JL, Pieras EC, Grases F, et al. Urinary tract infection’s etiopathogenic role in nephrolithiasis formation[J]. Med Hypotheses, 2018,118(9):34-35.
[17]
李海桃, 郭晶平, 薛鹏, 等. 膀胱肿瘤切除术后尿路感染病原学和危险因素[J]. 中华医院感染学杂志,2020,30(7):1091-1095.
[18]
Gadalla AAH, Friberg IM, Kift-Morgan A, et al. Identification of clinical and urine biomarkers for uncomplicated urinary tract infection using machine learning algorithms[J]. Sci Rep,2019,9(1):19694.
[19]
王碧霄, 姬超岳, 宋海峰, 等. 鸟粪石的临床特点和内镜术后肾功能转归的影响因素分析[J]. 微创泌尿外科杂志,2022,11(3):171-177.
[20]
Shen C, Zhu Q, Dong F, et al. Identifying two novel clusters in calcium oxalate stones with urinary tract infection using 16S rDNA sequencing[J]. Front Cell Infect Microbiol,2021,11(11):723781.
[21]
肖楠, 周佳, 段宁, 等. 尿干化学和尿流式检测结果快速预测肾结石患者尿路细菌感染模型的建立与评价[J]. 检验医学,2021,36(1):75-79.
[22]
乔鹏飞, 易虎, 田振涛, 等. 感染性肾结石患者尿代谢及细菌培养结果分析[J]. 中国临床新医学,2022,15(10):981-985.
[23]
Espinosa-Ortiz EJ, Eisner BH, Lange D, et al. Current insights into the mechanisms and management of infection stones[J]. Nat Rev Urol,2019,16(1):35-53.
[24]
熊庄, 程帆. 微通道经皮肾镜取石术用于不同类型肾结石的临床应用进展[J]. 中国医药导报,2022,42(4):57-61.
[25]
Zawaideh JP, Simonato A, Barbero S, et al. Gas-containing renal stones: a red flag for renal infection[J]. Acta Radiol,2022,63(11): 1563-1569.
[26]
康永明, 奉友刚, 何俊, 等. 经皮肾镜碎石取石术后发热原因及治疗分析[J/CD]. 中华实验和临床感染病杂志(电子版),2014,8(2):50-52.
[1] 郑庆发, 白建祥, 黄成文. 基于血小板和淋巴细胞计数比值的列线图模型预测腹膜透析相关腹膜炎患者治疗预后的价值[J]. 中华实验和临床感染病杂志(电子版), 2023, 17(02): 117-124.
[2] 陈华文, 仇成华, 李晓青, 谢鹏. 冠状动脉旁路移植术后手术部位感染风险预测模型及管理策略[J]. 中华实验和临床感染病杂志(电子版), 2022, 16(01): 39-46.
[3] 程丹丹, 许月娥. 预测乳腺癌术后切口愈合不良的列线图模型建立[J]. 中华普通外科学文献(电子版), 2022, 16(03): 215-219.
[4] 甄子铂, 刘金虎. 基于列线图模型探究静脉全身麻醉腹腔镜胆囊切除术患者术后肠道功能紊乱的影响因素[J]. 中华普外科手术学杂志(电子版), 2024, 18(01): 61-65.
[5] 蒋美玲, 张凯. 老年患者腹壁切口疝修补术后复发的危险因素探讨及风险列线图模型的建立[J]. 中华疝和腹壁外科杂志(电子版), 2022, 16(02): 191-195.
[6] 江涛. 腹腔镜下经腹腹膜前疝修补术后慢性疼痛的风险模型构建[J]. 中华疝和腹壁外科杂志(电子版), 2021, 15(05): 512-516.
[7] 屠松霞, 郑红艳, 朱姝, 徐夏君. 食管癌术后患者肠内营养耐受不良的影响因素及列线图风险模型[J]. 中华消化病与影像杂志(电子版), 2023, 13(02): 73-77.
[8] 姜巧, 张溱乐, 张艳玲, 余展鹏. 基于MIMIC-Ⅲ数据库的急性胰腺炎并发脓毒症风险预测模型构建与评价[J]. 中华临床实验室管理电子杂志, 2023, 11(03): 151-157.
[9] 杨婷, 邱晓珏, 陈青雅, 张宝晶, 王伟伟. 经内镜逆行胰胆管造影术后胰腺炎预测模型的建立与评价[J]. 中华胃肠内镜电子杂志, 2023, 10(03): 200-204.
阅读次数
全文


摘要

版权所有 中华医学会 中华医学电子音像出版社有限责任公司  京ICP备14006079号-1  网络出版服务许可证：(署)网出证(京)字第075号