诊断学理论与实践 ›› 2019, Vol. 18 ›› Issue (03): 353-359.doi: 10.16150/j.1671-2870.2019.03.021

• 论著 • 上一篇    下一篇

血清降钙素原在慢性肾脏病合并细菌感染患者中的临床价值

王媛媛, 范秋灵()   

  1. 中国医科大学附属第一医院肾内科,辽宁 沈阳 110000
  • 收稿日期:2018-11-01 出版日期:2019-06-25 发布日期:2019-06-25
  • 通讯作者: 范秋灵 E-mail:cmufql@163.com
  • 基金资助:
    国家重点研发计划精准医学专项(2017YFC0907601);国家重点研发计划精准医学专项(2017YFC0907602);国家重点研发计划精准医学专项(2017YFC0907603);国家自然科学基金(81770724);沈阳市中青年科技创新人才支持计划(RC170172)

Clinical value of serum procalcitonin in patients of chronic kidney disease with bacterial infection

WANG Yuanyuan, FAN Qiuling()   

  1. Department of Nephrology, First Affiliated Hospital of China Medical University, Liaoning Shenyang 110000, China
  • Received:2018-11-01 Online:2019-06-25 Published:2019-06-25
  • Contact: FAN Qiuling E-mail:cmufql@163.com

摘要:

目的: 观察不同分期慢性肾脏病(chronic kidney disease,CKD)患者的血清降钙素原(procalcitonin,PCT)中位值,分析PCT在不同分期CKD合并细菌感染患者中的诊断最佳临界值。方法: 纳入我院肾内科住院治疗并完善PCT检测的354例CKD患者,包括合并细菌感染并予抗生素治疗的CKD患者153例,无感染症状的CKD患者201例。根据估算的肾小球滤过率(estimated glomerular filtration rate, eGFR)将所有患者分为G1期、G2期、G3期、G4期、G5期(非肾脏替代治疗)及中心静脉置管血液透析(haemodialysis, HD)组。采用Spearman相关分析评估PCT水平与血清肌酐、eGFR间的相关性。采用ROC曲线分析血清PCT诊断CKD不同分期合并细菌感染的最佳临界值,并用多因素逐步Logistic回归分析评估感染的影响因素。结果: CKD各分期感染组的血清PCT水平显著高于非感染组。PCT动态变化与临床感染恢复相平行。PCT水平与血清肌酐呈正相关(P<0.001),与eGFR呈负相关(P<0.001)。采用ROC曲线得到总CKD组及G3期、G4期、G5期(非肾脏替代治疗)、中心静脉置管HD组中,鉴别感染与非感染的血清PCT最佳临界值分别为0.40 ng/mL、0.12 ng/mL、0.23 ng/mL、0.28 ng/mL、0.60 ng/mL。多因素逐步Logistic回归分析显示,PCT、C反应蛋白、白细胞、血清白蛋白是感染的独立影响因素。结论: PCT可作为诊断CKD合并细菌感染的一个有用的临床指标,且根据肾功能分期不同,其诊断感染的阈值不同;检测PCT的动态变化对CKD患者感染的诊断和治疗监测有重要的诊断价值。

关键词: 降钙素原, 慢性肾脏病, 细菌感染, C反应蛋白, 诊断

Abstract:

Objective: Clinical data of chronic kidney disease(CKD) patients (n=354) of different disease stages were collected to analyze the median serum procalcitonin (PCT) level and diagnostic value of serum PCT in CKD patients with bacterial Infection. Methods: A total of 354 CKD patients admitted to the First Affiliated Hospital of China Medical University, including 153 patients with bacterial infection and antibiotics treatment and 201 patients without infection, were enrolled in this study. According to eGFR, patients were divided into stage 1, stage2, stage3, stage4, stage5 with nondialysis andstage5 with hemodialysis (HD) groups. Spearman correlation was used to analyze the relationship between PCT and serum creatinine and eGFR. ROC curve was used to analyze the diagnostic efficacy of serum PCT in different stage CKD patients with bacterial infection. Multivariate logistic regression analysis was used to assess the impact factors of infection. Results: The serum PCT level of CKD patients with infection was significantly higher than that of non-infected. The dynamic change of PCT was in parallel with recovery of clinical infection.PCT was positively correlated with serum creatinine, and negatively correlated with eGFR. Serum PCT cutoff values for differentiating infection and non-infection in overall CKD, stage 3, stage 4, stage 5 with nodialysis and with hemodialysis (HD) groups were 0.40 ng/mL,0.12 ng/mL, 0.23 ng/mL, 0.28 ng/mL and 0.60 ng/mL, respectively. Logistic regression analysis showed, WBC, PCT, CRP and serum albumin were independent risk factors for infection. Conclusions: PCT can be used as a useful clinical indicator of infection in different stages of CKD; the dynamic change of PCT has important diagnostic value in the diagnosis and treatment of CKD patients.

Key words: Procalcitonin, Chronic kidney disease, Bacterial Infection, C-reactive protein, Diagnosis

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