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Article(id=1220689489027056331, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1220689483859677846, articleNumber=null, orderNo=null, doi=10.12102/j.issn.1009-6493.2025.19.026, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=review-article, receivedDate=1733241600000, receivedDateStr=2024-12-04, revisedDate=1757088000000, revisedDateStr=2025-09-06, acceptedDate=null, acceptedDateStr=null, onlineDate=1768964653498, onlineDateStr=2026-01-21, pubDate=1760025600000, pubDateStr=2025-10-10, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1768964653498, onlineIssueDateStr=2026-01-21, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1768964653498, creator=13701087609, updateTime=1768964653498, updator=13701087609, issue=Issue{id=1220689483859677846, tenantId=1146029695717560320, journalId=1220038315760373764, year='2025', volume='39', issue='19', pageStart='3201', pageEnd='3376', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1768964652266, creator=13701087609, updateTime=1768965013333, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1220690998338961744, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1220689483859677846, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1220690998338961745, tenantId=1146029695717560320, journalId=1220038315760373764, issueId=1220689483859677846, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3372, endPage=3376, ext={EN=ArticleExt(id=1220689489291297497, articleId=1220689489027056331, tenantId=1146029695717560320, journalId=1220038315760373764, language=EN, title=Research progress on risk factors for renal scarring after urinary tract infection, columnId=1220689485315101342, journalTitle=Chinese Nursing Research, columnName=Review Articles, runingTitle=null, highlight=null, articleAbstract=

This study reviewed the clinical factors,laboratory indicators,genetic testing,and predictive models related to renal scarring after urinary tract infection.The aim was to provide references for clinical medical staff to identify high-risk patients early,to intervene promptly,and to reduce the risk of renal scarring.

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JIANG Xuesong, E⁃mail:
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对尿路感染后肾脏瘢痕形成的相关临床因素、实验室指标、基因检测和预测模型等进行综述，旨在为临床医护人员早期识别、及时干预、降低肾脏瘢痕形成风险提供参考。

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蒋雪松，E⁃mail：
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周晓敏，护士，硕士研究生在读

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周晓敏，护士，硕士研究生在读

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尿路感染后肾脏瘢痕形成风险因素的研究进展
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周晓敏 1 , 蒋雪松 2 , 刘愔 1 , 张纾豪 1 , 高嘉淏 1
护理研究 | 科研综述 2025,39(19): 3372-3376
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护理研究 | 科研综述 2025, 39(19): 3372-3376
尿路感染后肾脏瘢痕形成风险因素的研究进展
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周晓敏1, 蒋雪松2 , 刘愔1, 张纾豪1, 高嘉淏1
作者信息
  • 1.河南中医药大学护理学院，河南 450000
  • 2.河南中医药大学第一附属医院

    • 周晓敏，护士，硕士研究生在读

通讯作者:

蒋雪松，E⁃mail：
Research progress on risk factors for renal scarring after urinary tract infection
Xiaomin ZHOU1, Xuesong JIANG2 , Yin LIU1, Shuhao ZHANG1, Jiahao GAO1
Affiliations
  • 1.School of Nursing, Henan University of Chinese Medicine, Henan 450000 China
  • 2.First Affiliated Hospital of Henan University of Chinese Medicine
出版时间: 2025-10-10 doi: 10.12102/j.issn.1009-6493.2025.19.026
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摘要
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对尿路感染后肾脏瘢痕形成的相关临床因素、实验室指标、基因检测和预测模型等进行综述，旨在为临床医护人员早期识别、及时干预、降低肾脏瘢痕形成风险提供参考。

儿童  /  尿路感染  /  肾脏瘢痕  /  影响因素  /  预测模型  /  综述

This study reviewed the clinical factors,laboratory indicators,genetic testing,and predictive models related to renal scarring after urinary tract infection.The aim was to provide references for clinical medical staff to identify high-risk patients early,to intervene promptly,and to reduce the risk of renal scarring.

children  /  urinary tract infection  /  renal scarring  /  influencing factors  /  predictive model  /  review
周晓敏, 蒋雪松, 刘愔, 张纾豪, 高嘉淏. 尿路感染后肾脏瘢痕形成风险因素的研究进展. 护理研究, 2025 , 39 (19) : 3372 -3376 . DOI: 10.12102/j.issn.1009-6493.2025.19.026
Xiaomin ZHOU, Xuesong JIANG, Yin LIU, Shuhao ZHANG, Jiahao GAO. Research progress on risk factors for renal scarring after urinary tract infection[J]. Chinese Nursing Research, 2025 , 39 (19) : 3372 -3376 . DOI: 10.12102/j.issn.1009-6493.2025.19.026
正文
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尿路感染（urinary tract infection，UTI）是泌尿系统常见疾病，若未得到有效控制，反复感染可能会使肾脏形成瘢痕。大量瘢痕形成不仅会增加高血压、先兆子痫和慢性肾脏病等远期并发症的发生风险，还可能导致终末期肾脏病[1]。因此，准确预测尿路感染后肾脏瘢痕（renal scarring，RS）形成的风险具有重要意义。临床预测模型可帮助医护人员识别高危个人，以开展密切的随访或实施更积极的管理。因此，本研究对尿路感染后肾脏瘢痕形成的临床因素、实验室指标、基因检测以及相关预测模型进行综述，以帮助临床医护人员早期识别高危儿童，制定个性化的治疗和监测方案，降低肾脏瘢痕形成风险以改善个人的预后。
1 肾脏瘢痕的定义
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肾脏瘢痕是指肾脏组织受到损伤后，在修复过程所形成的纤维性病变。正常情况下，肾脏具有一定的自我修复能力，但当受到反复或严重的尿路感染等有害因素侵袭时，细菌产生的毒素、炎症反应中的免疫细胞及释放的炎症介质等会对肾脏组织造成损害。肾脏在自我修复时，纤维组织过度增生填补受损区域，从而形成瘢痕。这种瘢痕组织和正常肾脏组织不同，它缺乏正常肾脏组织的滤过、重吸收等功能，会在一定程度上影响肾脏的整体功能，并且可能成为后续肾脏病发生发展的病理基础。
2 肾脏瘢痕风险因素
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2.1　一般资料及临床因素
2.1.1　年龄
儿童时期是尿路感染后肾脏瘢痕形成的关键阶段。新生儿和婴幼儿由于泌尿系统发育尚未完善，在发生肾盂肾炎后更易形成肾脏瘢痕。Bamshmous等[2]研究表明，1岁以内的婴儿在首次急性肾盂肾炎发作后，肾脏瘢痕形成率可达20%~40%，而5岁以上儿童相对较低。
2.1.2　性别
性别对肾脏瘢痕形成风险的影响存在一定争议。Pokrajac等[3]研究发现，女性患儿在尿路感染后出现肾脏瘢痕的比例相对较高，可能与女性尿道短且直，更易发生上行感染有关。然而，Bamshmous等[2]研究指出，性别并非独立的强预测因素，在综合考虑其他因素时，性别差异对风险的预测价值相对有限。
2.1.3　膀胱输尿管反流
Mathias等[4]研究表明，膀胱输尿管反流是儿童发生肾脏感染最重要的危险因素之一，膀胱输尿管反流严重程度通常分为5级，其与肾脏瘢痕形成的发生率相关。Shaikh等[5]研究表明，Ⅳ级或Ⅴ级膀胱输尿管反流患儿出现肾脏瘢痕形成的概率是无膀胱输尿管反流患儿的22倍，相比之下，Ⅰ级或Ⅱ级膀胱输尿管反流患儿出现肾脏瘢痕形成的概率仅略高于无膀胱输尿管反流患儿。
2.1.4　尿路感染病史
尿路感染的次数与肾脏瘢痕形成密切相关。反复发生的尿路感染使肾脏反复遭受炎症侵袭，增加了肾脏组织损伤和瘢痕形成的可能性。Su等[6⁃7]研究显示，经历3次以上尿路感染的人群，其肾脏瘢痕形成风险是单次感染人群的13.7倍。诊治延误也是肾脏瘢痕形成的重要因素。尿路感染后若未能被及时诊断和恰当治疗，炎症持续时间延长，肾脏长期处于炎性环境中，会促进瘢痕组织的形成。Karavanaki等[8]研究发现，尿路感染发热持续72 h以上才开始进行抗菌治疗的病人，肾脏瘢痕发生率明显升高。但Doganis等[9⁃10]研究发现，一旦出现急性肾盂肾炎，肾实质损伤和随后的瘢痕形成与治疗延迟无关。
2.1.5　突破性尿路感染
突破性尿路感染是新发肾脏瘢痕形成的独立危险因素。这种感染是指在接受预防性抗生素治疗过程中发生的尿路感染，其发生可能是因为抗生素未覆盖致病病原体或细菌耐药，也可能是有新细菌进入泌尿系统。这种复杂的感染情况使得炎症难以控制，增加了肾脏瘢痕的形成风险。Mir等[11]的回顾性研究发现，有突破性尿路感染患儿的肾脏瘢痕发生率比无突破性尿路感染的患儿约高2倍。
2.1.6　肥胖
肥胖可致机体代谢紊乱，同时易伴有高血压、高血脂等，损害肾血管和减少灌注，这些因素都会导致肾组织损伤，增加肾脏瘢痕形成的风险。Byun等[12]研究发现，肥胖是肾脏瘢痕形成的易感因素，特别是对年龄<5岁的膀胱输尿管反流患儿影响较大。
2.2　实验室指标
2.2.1　肾脏瘢痕形成相关的尿液生物标志物
尿液生物标志物通常由肾脏直接产生，或通过肾脏从血液中滤过。尿液生物标志物对肾功能和损伤的早期变化更敏感，并且通过非侵入性手段采集尿液样本，简便易行，更利于个人遵循监测方案[13]。多项研究探讨了多种尿液生物标志物在预测儿童肾脏瘢痕风险的作用[14⁃25]。半胱氨酸蛋白酶抑制剂C（Cys⁃C）能够精准地估算肾小球滤过率且不易受其他因素影响，可作为发热性尿路感染儿童感染严重程度的指标，但其在预测肾脏瘢痕发生风险方面结论不一。Gunasekara等[14⁃15]研究发现，半胱氨酸蛋白酶抑制剂C水平的升高与肾脏瘢痕的形成有关，并且与瘢痕的严重程度呈正相关。肾损伤分子⁃1和中性粒细胞明胶酶相关脂运载蛋白能够增强肾脏疾病早期阶段预测的敏感度和特异度。Gunasekara等[14,16]研究发现，发生肾脏瘢痕的病人肾损伤分子⁃1和中性粒细胞明胶酶相关脂运载蛋白指标升高，但Naik等[17⁃18]研究则未发现肾损伤分子⁃1和中性粒细胞明胶酶相关脂运载蛋白与肾脏瘢痕的相关性。Sheu等[19⁃20]研究表明，尿液白介素⁃6（IL⁃6）与肾脏瘢痕形成有关，但Nickavar等[21]研究则显示尿液白介素⁃6与肾脏瘢痕形成无明显相关性。Pentraxin⁃3（PTX3）作为一种炎症介质，其与自身免疫、心血管疾病和肾脏疾病的严重程度和进展之间存在关联。Becerir等[22]研究在瘢痕组检测到了高水平的uPTX3水平，且发现肾脏瘢痕组尿液PTX3和尿液PTX3/肌酐比值的受试者工作特征曲线下面积约为0.67，表明PTX3可以预测肾脏瘢痕的形成。尿液基质金属蛋白酶⁃9（uMMP⁃9）和金属蛋白酶组织抑制剂⁃1（uTIMP⁃1）是肾脏瘢痕形成的非特异性危险因素，Yilmaz等[23]研究发现，肾脏瘢痕组uTIMP1水平高于无肾脏瘢痕组，预测特异度为90%，敏感度为75%，是预测肾脏瘢痕形成的有效标志物。尿内皮素⁃1水平也是肾脏瘢痕形成的预测指标，Yilmaz等[24]研究发现，尿内皮素⁃1预测肾脏瘢痕的最佳临界值为1.064 fmol/mL，具有较高的特异度和敏感度，可辅助避免不必要的二巯基丁二酸（DMSA）检查。Rafiei等[25]研究发现，肝型脂肪酸结合蛋白水平与肾脏瘢痕形成有关，但特异度和敏感度有待提高。总之，这些尿液生物标志物在评估儿童肾脏瘢痕形成方面有潜在作用，但目前研究结果尚不统一，仍需进一步深入探究以确定其确切价值。
2.2.2　肾脏瘢痕形成相关的血液生物标志物
2.2.2.1　外周血白细胞计数
外周血白细胞计数在肾脏瘢痕筛查中具有重要地位，Yazilitas等[26]的回顾性研究发现，在预测肾脏瘢痕的几个指标中，外周血白细胞计数的受试者工作特征曲线下面积最大，为0.892，其敏感度和特异度分别为83.3%和82.8%，是肾脏瘢痕筛查的首选诊断指标。
2.2.2.2　C⁃反应蛋白
C⁃反应蛋白水平的高低与肾脏瘢痕形成风险呈正相关，提示炎症反应越剧烈，肾脏组织受损及后续瘢痕形成的可能性就越大。研究发现，血清C反应蛋白预测肾脏瘢痕形成的最佳临界点为115 mg/L，其受试者工作特征曲线下面积为0.75，可以作为尿路感染后肾脏瘢痕形成的预测因子[27]。
2.2.2.3　降钙素原
降钙素原对尿路感染晚期瘢痕形成具有较强的预测能力，Leroy等[28]研究结果显示，降钙素原>0.5 ng/mL与晚期肾脏瘢痕形成存在关联，其预测能力优于C反应蛋白和血白细胞计数，但鉴于其常作为重症监护室环境中全身炎症和败血症的标志物[29]，对住院病人使用时要谨慎。
2.2.2.4　其他
此外，研究发现，血管紧张素Ⅱ以及平均血小板体积也可以作为预测尿路感染后肾脏瘢痕形成的标志物[30⁃31]。各指标都展示出在尿路感染患儿肾脏瘢痕形成预测中的价值，但也有其局限性，临床应用时需综合考量并谨慎抉择，以准确评估肾脏瘢痕形成风险。
2.3　基因多态性
随着基因研究的深入，发现某些基因多态性与尿路感染后肾脏瘢痕形成相关。研究发现，当个体携带特定的影响线粒体功能的多态性时，会增加肾脏瘢痕形成的可能性，这种基因变化可以作为提前判断肾脏瘢痕是否会形成的依据[32]。对于血管紧张素转换酶I/D（angiotensin converting enzyme I/D，ACE I/D）多态性与肾脏瘢痕风险之间的关联存在争议。Zhou等[33]研究表明，血管紧张素转换酶I/D多态性与总体人群的肾脏瘢痕形成风险并无关联。而Ai等[34]研究表明，血管紧张素转换酶DD基因型增加了总体研究人群肾脏瘢痕形成的风险。按种族分层的亚组分析结果表明，DD基因型和D等位基因增加了土耳其人发生肾脏瘢痕的风险。各研究结果不一致可能归因于单项调查的样本量偏小以及研究人群之间存在种族差异等。除此之外，Hussein等[35]研究针对转化生长因子⁃β1和血管内皮生长因子基因的功能多态性进行分析，发现其功能变异在尿路感染后肾实质瘢痕形成的儿童中出现频率增加，提示该基因可能是尿路感染后肾脏瘢痕形成的潜在危险因素。
以上研究通过对特定基因的检测和分析，有望在分子水平上更精准地预测肾脏瘢痕形成的风险，为肾脏瘢痕的预防和治疗提供依据。
2.4　输尿管直径比
输尿管直径比的计算方法是将最大输尿管直径除以腰椎（L）1~3椎体之间的距离。研究表明，输尿管直径比的测量可有效预测膀胱输尿管反流的结局[36]。对172例膀胱输尿管反流病人的人口学资料和临床相关资料进行回归分析发现，在影响膀胱输尿管反流病人瘢痕形成的众多因素中，尿管直径比的比值比最高，这可为临床医生预测原发性膀胱输尿管反流病人的肾脏瘢痕形成提供帮助[37]。但是可能存在个体差异，还需对其他相关因素进行综合性考量。此外，单次的测量结果可能具有一定偏倚，需要进行多次测量，或将其与其他影像学检查及实验室指标相结合，以提高肾脏瘢痕形成预测的准确性和可靠性。
3 肾脏瘢痕形成的风险预测模型
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风险预测模型是指利用多因素模型估算患某疾病发生的概率或者未来某结局发生的概率[38]。目前，关于肾脏瘢痕形成的风险预测模型相对较少，主要以临床因素、实验室指标和影像学检查结果为预测因子构建的综合模型为主。
Shaikh等[5]对来自9项研究的1 280例首次患尿路感染的儿童进行了荟萃分析，并运用Logistic回归构建了3个预测模型。其中，模型1以超声检查结果异常、大肠杆菌以外的病原体和发热≥39 °C为预测变量。除了模型1中的3个变量外，模型2还包括超过40 mg/L的C反应蛋白水平和超过60%的多形核细胞计数。模型3则是在模型2的基础上，添加了输尿管膀胱造影结果。模型1、2、3的受试者工作特征曲线下面积分别为0.69，0.72，0.74。与模型1相比，血清生物标志物水平和膀胱输尿管造影仅将预测能力分别提高了3、5个百分点。模型1评分达到2分或2分以上时，其敏感度和特异度分别为44.9%和82.4%，可以检测到68.2%Ⅳ级或Ⅴ级膀胱输尿管反流的个体。相较于其他2个模型，模型1表现较为稳健，可为临床提供可行的筛选策略。
Ganapathy等[39]研究以肾损伤分子⁃1（KIM⁃1）、中性粒细胞明胶酶相关脂运载蛋白（NGAL）、尿肌酐以及肾脏瘢痕状态为预测因子，建立了逻辑回归、判别分析、贝叶斯逻辑回归、朴素贝叶斯和决策树5种模型，以预测肾脏瘢痕形成的风险。单个生物标志中性粒细胞明胶酶相关脂运载蛋白、肾损伤分子⁃1、中性粒细胞明胶酶相关脂运载蛋白/尿肌酐以及肾损伤分子⁃1/尿肌酐的受试者工作特征曲线下面积分别为0.77，0.52，0.61，0.66。Logistic回归模型的受试者工作特征曲线下面积为0.83，敏感度和特异度分别为77.8%和75.5%，错误分类率为23.4%；二元判别分析的受试者工作特征曲线下面积为0.83,敏感度和特异度分别为75.5%和81.6%，错误分类率为21.3%；贝叶斯模型的结果与逻辑回归模型相似。朴素贝叶斯模型的受试者工作特征曲线下面积为0.81,敏感度和特异度分别为77.8%和81.6%，诊断肾脏瘢痕形成的错误分类率估计为20.2%；决策树模型的受试者工作特征曲线下面积为0.83,敏感度和特异度分别为91.1%和67.3%，检测肾脏瘢痕形成的错误分类率为21.3%。综上所述，NGAL是肾脏瘢痕形成个人分类中最主要的肾脏生物标志物，每个模型的表现都优于单个生物标志物，在这些模型中决策树和朴素贝叶斯模型表现较好。将这些生物标志物进行结合构建预测模型，往往会得出更为准确的结果。
4 小结及展望
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尿路感染后肾脏瘢痕形成受多种危险因素影响，临床因素中严重的膀胱输尿管反流(Ⅳ级和Ⅴ级)是肾脏瘢痕形成的一个重要的独立危险因素，其次尿路感染反复发作、接受抗生素预防治疗时发生突破性尿路感染以及肥胖等都是肾脏瘢痕形成的危险因素。所有这些因素均需要在临床治疗和护理中引起注意，对于存在膀胱输尿管反流、反复尿路感染的高危病人以及持续接受抗生素预防治疗的患儿，护理人员应加强监测频率，定期辅助完成超声等检查，一旦发生病情变化，应及时告知医生调整治疗方案，以降低肾脏进一步受损的风险，同时加强对患儿及其家属的健康教育，强调遵医嘱按时按量服药以及做好个人卫生防护的重要性。而对于肥胖病人，护理人员应帮助制定科学、合理的饮食和运动计划，通过控制体重减轻肾脏的代谢负担，改善肾脏血液循环，从而在一定程度上降低肾脏瘢痕形成的可能性。此外，还应综合考虑实验室指标，如关注尿液生物标志物中某些指标的异常变化，可作为肾脏早期损伤的预警信号；血液生物标志物，如白细胞计数、C⁃反应蛋白等的波动也能反映炎症程度与肾脏瘢痕风险的关联。基因多态性方面的研究成果虽存在争议，但也为未来实现更精准的个体化预测和防治提供了潜在的方向。在临床实践中，将各种危险因素有机结合进行综合评估与管理，才能更有效地预防和减少肾脏瘢痕的形成，提高个人的生活质量并降低远期并发症的发生风险。
同时，现有的肾脏瘢痕形成风险预测模型通过综合多因素能更精确地评估风险，但也存在一定的局限性。其主要的制约因素是所采用健康数据集的质量，因为很多数据集是通过回顾性收集的，存在变量缺失或使用了自我报告的测量值等情况，这可能会降低预测模型的准确性。大部分研究的数据均仅来自1所医院，这可能会限制模型在其他环境中的普适性和有用性。此外，由于纳入的样本量较小，尚未使用独立的数据集对所构建的模型进行验证，这可能会降低模型的外推性。建议在未来的研究中进一步探索并验证肾脏瘢痕形成的潜在预测因素，在多中心、大样本的基础上，采用不同方法构建简约且易于临床使用的模型，并开展严格的内外部验证，提高模型的可靠性和外推性，使其切实应用到临床实践中，帮助医护人员及早发现存在肾脏瘢痕风险的儿童，及时制定特定的治疗方案和个性化的护理计划，以降低肾脏瘢痕形成风险，减少远期并发症发生，提高个人生活质量并改善预后。
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2025年第39卷第19期
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doi: 10.12102/j.issn.1009-6493.2025.19.026
  • 接收时间：2024-12-04
  • 首发时间：2026-01-21
  • 出版时间：2025-10-10
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  • 收稿日期：2024-12-04
  • 修回日期：2025-09-06
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    1.河南中医药大学护理学院，河南 450000
    2.河南中医药大学第一附属医院

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2种不同金属材料的力学参数
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Number of
genus		 种数
Number of
species		 占总种数比例
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total species (%)		 属
Genus		 种数
Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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