脓毒症相关急性肾损伤早期预测的研究进展
Research Progress in Early Prediction of Sep-tic Associated Acute Kidney Injury
DOI: 10.12677/ACM.2022.1281162, PDF, HTML, XML, 下载: 290  浏览: 403 
作者: 李文敬:青海大学研究生院,青海 西宁;侯 明*:青海大学附属医院急诊,青海 西宁
关键词: 脓毒症急性肾损伤早期预测肾阻力指数新型生物标志物Sepsis Acute Kidney Injury Early Prediction Renal Resistance Index Novel Biomarkers
摘要: 脓毒症作为ICU常见疾病,病死率一直居高不下,特别是脓毒症引发的AKI,是造成患者病死率显著升高的重要原因,脓毒症引发的AKI的发生率在40%左右。那么,及时准确的预测脓毒症患者AKI的发生,避免进一步的肾脏损害,早期及时的治疗,对患者的预后及生活质量有很大的影响,这篇综述的目的是探讨RI (肾动脉阻力指数)及早期标志物在预测脓毒症患者发生急性肾损伤的早期诊断的研究进展。
Abstract: Sepsis, as a common disease in ICU, has a high fatality rate, especially sepsis induced AKI, which is an important reason for the significant increase in the fatality rate of patients. The incidence rate of SEPSIS induced AKI is about 40%. Then, in time accurately predicting the occurrence of AKI in pa-tients with sepsis, avoiding further renal damage, and providing early and timely treatment have a great impact on the prognosis and quality of life of patients. The purpose of this review is to inves-tigate the RI (renal artery resistance index) and early marker in predicting sepsis patients in the early diagnosis of acute kidney injury.
文章引用:李文敬, 侯明. 脓毒症相关急性肾损伤早期预测的研究进展[J]. 临床医学进展, 2022, 12(8): 8071-8076. https://doi.org/10.12677/ACM.2022.1281162

1. 引言

脓毒症(sepsis)是由感染引起的全身炎症反应综合征(systemic inflammatory response syndrome, SIRS),其病理机制复杂,患病率和病死率极高,易发展为脓毒性休克及多器官功能障碍综合征(multiple organ dysfunction syndrome, MODS),危及生命 [1] [2]。以肾功能进行性减退为主要病理特点的急性肾损伤(acute kidney injury, AKI)为脓毒症常见并发症 [3]。由于败血症标准和AKI标准之间以及在这些领域工作的研究人员之间缺乏协调的流行病学,人们对SA-AKI的流行病学知之甚少,即使只是脓毒症的全球发病率在很大程度上也是未知的。Adhikari等人推断估计全世界每年有多达1900万例病例,但实际发病率可能要高得多 [4]。因为大约三分之一的脓毒症患者会发生AKI,SA-AKI的年全球发病率可能约为600万例或每1000人中接近1例。对于ICU的患者,ICU中约40%至50%的AKI患者发现脓毒症 [5]。一项前瞻性队列研究包括24个欧洲国家198个ICU的1177名脓毒症患者,报告AKI发生率为51%,ICU死亡率为41% [6] [7] [8] [9]。一项包含146,148名患者的中国回顾性研究在47.1%的脓毒症病例中发现了AKI [10]。一项对包括1243名患者的感染性休克的多中心随机对照试验(RCT)的辅助分析显示,急诊科入组时有50.4%的患者出现AKI,另外18.7%的患者在7天内发生了随后的AKI [11]。脓毒症不仅严重威胁人类健康,也给医疗卫生带来了巨大的经济负担。因此早期预测AKI发生的能力对于制定预防策略至关重要。

2. 血清肌酐和尿量用于定义和诊断S-AKI的局限性

AKI的诊断目前仍然基于血清肌酐浓度升高和/或尿量减少。虽然有用,但这些措施具有局限性。肌酐的释放会随着年龄、性别、基础代谢率、饮食情况、肌肉质量、药物、肝功能障碍和体位状况的情况而变化。来自多个回顾性队列研究的证据还表明,通过血清肌酐和尿量诊断的同一阶段AKI可能会带来不同的风险。基于单独尿量的AKI会增加发病率和死亡率(与无AKI相比),但这些风险低于基于血清肌酐的AKI所带来的风险 [12] [13] [14]。另外,血清肌酐水平变得异常,肾小球滤过率(GFR)降低超过50% [14] [15] [16] [17] [18]。受伤和随后血清肌酐升高之间存在延迟,这表明可能需要长达48小时才能检测到足够的升高 [14] [15] [16] [17] [18]。Doi等人显示脓毒症减少了肌酐的产生,从而抑制了脓毒症后血清肌酐的增加,可能会限制使用该标志物检测AKI [19]。此外,AKI患者的AKI诊断和预后预测在常规ICU实践中很重要 [14] [15] [16] [17] [18]。如果尽早诊断出AKI,则可以采取预防措施,例如避免使用肾毒性药物和放射造影剂暴露。早期诊断有助于预防急性肾功能不全的发展和进展,因此,需要更新的方法来检测AKI和SA-AKI,近些年,多普勒彩超和不同生物学指标用于早期发现AK和SA-AKI的研究。

3. 肾动脉阻力指数(RRI)

脓毒症是危重患者AKI的最常见原因,尽管如此,SA-AKI的具体病理生理机制尚不清楚,与免疫炎症反应、微循环障碍、能量代谢异常等有关。其中肾血管剧烈收缩,引起肾脏血流灌注不足,肾性低血压和相关缺血被认为是SA-AKI的主要病变 [20]。肾脏多普勒超声是一种简单、快速、无创和可重复的技术,是评估重症监护病房(ICU) AKI风险的一种有希望的工具 [21] [22]。肾脏多普勒超声可以很好地确定每位患者的最佳平均动脉压(MAP) [23]。此外,肾脏多普勒超声不仅可以检测肾脏形态异常,还可以提供肾内或肾外脉管系统的定性或定量血流动力学信息。肾动脉阻力指数(RRI)可以提高AKI的早期诊断,是预测肾功能的有效指标,也与肾脏疾病的进展相关,多普勒超声评估的肾阻力指数(RRI)被认为是AKI的潜在预测因子 [21] [22]。在AKI的进展过程中,RRI的敏感性高于恢复和发展区域中血清肌酐(Cr)值的变化 [24]。肾动脉阻力指数(RRI)可以提高AKI的早期诊断,是预测肾功能的有效指标,也与肾脏疾病的进展相关,多普勒超声评估的肾阻力指数(RRI)被认为是AKI的潜在预测因子 [21] [22]。多普勒超声用于评估肾脏疾病的潜在用途的研究需要细致的技术,应使用提供可测量波形的最高频率探头,并根据血管定位的需要辅以彩色或功率多普勒超声检查,对弓形动脉(在皮质髓质交界处)或叶间动脉(邻近髓质锥体)进行超声检查。检测在双肾的上级、中部、下级三个部位进行测量,测量其舒张期最低流速(EDV)、收缩期最高流速(PSV)、阻力指数(RI),主要在于检测肾血管收缩期最高血流速度和舒张末期最低血流速度,对叶间动脉阻力指数进行计算。从每个肾脏获得三到五个可重复的波形,并对这些波形的RI进行平均以得出每个肾脏的平均RI值。RRI = [(收缩期峰值流速(peak systolic velocity, PSV) − 舒张末期流速(end diastolic velocity, EDV)]/PSV。几项研究表明,正常的平均肾脏RI约为0.60,一般来说,大多数超声医师现在认为0.70是正常成人RI的上限 [25]。多普勒超声测量的肾阻力指数(RRI)可以准确预测AKI的发生 [26]。RRI可用作急性和慢性肾脏疾病和肾功能衰竭的独立预测因子 [27]。

4. 新型生物标志物在SA-AKI中的作用

血清胱抑素C是一种新的生物标志物,近年来被用于尽早诊断AKI。Cystatin C是一种非糖基化的13-kDa蛋白,是半胱氨酸蛋白酶抑制剂的cystatin超家族成员。它由所有有核细胞定期产生,在肾小球自由过滤,大部分通过巨蛋白介导的内吞作用在近端小管重吸收,最后分解代谢 [28]。胱抑素C是危重患者AKI发展的良好预测因子,与血清肌酐相比,血清胱抑素C的水平不受年龄、性别、种族或肌肉质量的显着影响 [4]。此外,几项研究和随后的荟萃分析表明,血浆胱抑素C在检测GFR轻微降低和急性变化方面优于血清肌酐 [29]。然而,血清胱抑素C对AKI诊断和预后的优越性并不一致 [30] [31]。在危重患者中进行的几项研究表明,血清胱抑素C在检测AKI方面表现更好 [32]。然而,比较脓毒症诱导的AKI中的生物标志物性能的报告相对稀少。迪纳尔多等人研究发现,与没有AKI的患者相比,患有AKI的严重脓毒症儿童的血清胱抑素C中位数显着增加,这表明胱抑素C可能是严重脓毒症儿童AKI的更特异性生物标志物 [33]。Leem AY等人研究表明ICU入院时血清胱抑素C水平的升高与AKI显着相关 [34]。

中性粒细胞明胶酶相关脂质运载蛋白(NGAL)已在各种AKI表型中进行了广泛研究。NGAL由活化的中性粒细胞和包括肾TECs在内的各种上皮细胞释放。在早期研究中,NGAL对AKI的预测表现出良好的敏感性,也是RRT需求和住院死亡率的有用预后工具。SA-AKI患者的血浆和尿NGAL水平通常高于其他原因引起的AKI患者 [35] [36]。血浆NGAL似乎可用于预测SA-AKI患者出院时的肾脏恢复情况 [37]。脓毒症患者对NGAL还应考虑潜在的非肾脏来源。在没有AKI证据的情况下,血浆NGAL可能会增加全身感染和炎症 [38]。Lubell等研究指出,尿NGAL可作为脓毒症AKI发生的预测指标,可作为AKI发生的早期评价指标 [39]。

尿肾损伤分子-1 (KIM-1)是另一种肾损伤生物标志物,在缺血性和肾毒性损伤后在肾近端TECs中上调。一项荟萃分析表明,尿KIM-1是AKI的良好预测指标(曲线下面积为0.86,敏感性为74%,特异性为86%) [40]。专门用于SA-AKI的KIM-1的数据很少。一项前瞻性研究表明,使用24小时尿KIM-1预测脓毒症患者早期AKI的曲线下面积为0.91,非幸存者在24小时和48小时尿KIM-1水平显着升高 [41]。

FABP1是一种14 kDa的蛋白质,主要在肝脏中产生,肝脏的产生似乎决定了血液中FABP1的水平。FABP1可以通过肾小球过滤,因为它的分子大小很小,并且像其他小蛋白如视黄酸结合蛋白和α1-微球蛋白一样在近端小管上皮细胞中重吸收 [42]。最近,在感染性休克患者中检查了尿FABP1,感染性休克患者的尿FABP1水平显着高于健康受试者。另一个队列中的40名感染性休克患者接受了多粘菌素B固定纤维(PMX-F)血液灌流治疗。自1994年以来,日本已对30,000多名患者进行PMX-F治疗以治疗严重脓毒症,一项荟萃分析证明了其对脓毒性休克治疗的疗效 [43]。在40名脓毒症患者中,28人幸存,12人死亡。在幸存的患者中,尿FABP1水平通过治疗降低。然而,与幸存者相比,未存活患者的尿FABP1水平较高,治疗后下降幅度较小。这些结果表明,尿FABP1水平可能能够反映脓毒症的严重程度,也可以监测治疗的有效性 [44]。

5. 结语

脓毒症仍然是重症患者的严重问题,脓毒症患者并发AKI时死亡率急剧增加。因此在脓毒症的情况下早期识别AKI对于提供最佳治疗和避免进一步的肾损伤是至关重要的。在临床实践中,AKI通常通过测量血清肌酐水平来诊断。然而,肌酐已被证明是AKI相对不敏感和晚期的指标。因此,在脓毒症患者中提供更好的肾损伤测量的新兴技术和生物标志物的需求是至关重要的。

作者贡献

李文敬负责查阅文献、撰写论文与修订论文;侯明负责文章审查和质量控制。

利益冲突

本文无利益冲突。

NOTES

*通讯作者。

参考文献

[1] 戴甜, 曹书华, 杨晓龙. 连续性肾脏替代治疗与间歇性血液透析对脓毒症急性肾损伤的临床疗效比较[J]. 中华危重病急救医学, 2016, 28(3): 277-280.
[2] 张继翱, 李家瑞, 乔佑杰, 尚跃丰, 宋石林. 血必净注射液治疗脓毒症急性肾损伤的临床疗效及对炎症因子的影响[J]. 天津中医药, 2016, 33(1): 13-17.
[3] 王敏, 刘虹, 程威. 脓毒症急性肾损伤早期生物标志物的新进展[J]. 中国临床研究, 2016, 29(3): 424-426.
[4] Uchino, S., Kellum, J.A., Bellomo, R., Doig, G.S., Morimatsu, H., Morgera, S., et al. (2005) Acute Renal Failure in Critically Ill Patients: A Mul-tinational, Multicenter Study. JAMA, 294, 813-818.
https://doi.org/10.1001/jama.294.7.813
[5] Bagshaw, S.M., Uchino, S., Bellomo, R., et al. (2007) Septic Acute Kidney Injury in Critically Ill Patients: Clinical Characteristics and Outcomes. Clinical Journal of the American Society of Nephrology, 2, 431-439.
https://doi.org/10.2215/CJN.03681106
[6] Bouchard, J., Acharya, A., Cerda, J., et al. (2015) A Prospective In-ternational Multicenter Study of AKI in the Intensive Care Unit. Clinical Journal of the American Society of Nephrology, 10, 1324-1331.
https://doi.org/10.2215/CJN.04360514
[7] Hoste, E.A., Bagshaw, S.M., Bellomo, R., et al. (2015) Epidemiology of Acute Kidney Injury in Critically Ill Patients: The Multinational AKI-EPI Study. Intensive Care Medicine, 41, 1411-1423.
https://doi.org/10.1007/s00134-015-3934-7
[8] Adhikari, N.K., Fowler, R.A., Bhagwanjee, S., et al. (2010) Crit-ical Care and the Global Burden of Critical Illness in Adults. Lancet, 376, 1339-1346.
https://doi.org/10.1016/S0140-6736(10)60446-1
[9] Murugan, R., Karajala-Subramanyam, V., Lee, M., et al. (2010) Acute Kidney Injury in Non-Severe Pneumonia Is Associated with an Increased Immune Response and Lower Survival. Kidney Internatio, 77, 527-535.
https://doi.org/10.1038/ki.2009.502
[10] Vincent, J.L., Sakr, Y., Sprung, C.L., et al. (2006) Sepsis in European Intensive Care Units: Results of the SOAP Study. Critical Care Medicine, 34, 344-353.
https://doi.org/10.1097/01.CCM.0000194725.48928.3A
[11] Xu, X., Nie, S., Liu, Z., et al. (2015) Epidemiology and Clinical Correlates of AKI in Chinese Hospitalized Adults. Clinical Journal of the American Society of Nephrology, 10, 1510-1518.
https://doi.org/10.2215/CJN.02140215
[12] Jin, K., Murugan, R., Sileanu, F.E., et al. (2017) In-tensive Monitoring of Urine Output Is Associated with Increased Detection of Acute Kidney Injury and Improved Out-comes. Chest, 152, 972-979.
https://doi.org/10.1016/j.chest.2017.05.011
[13] Kellum, J.A., Sileanu, F.E., Murugan, R., Lucko, N., Shaw, A.D. and Clermont, G. (2015) Classifying AKI by Urine Output versus Serum Creatinine Level. Journal of the American So-ciety of Nephrology, 26, 2231-2238.
https://doi.org/10.1681/ASN.2014070724
[14] Quan, S., Pannu, N., Wilson, T., et al. (2016) Prognostic Implica-tions of Adding Urine Output to Serum Creatinine Measurements for Staging of Acute Kidney Injury after Major Sur-gery: A Cohort Study. Nephrology Dialysis Transplantation, 31, 2049-2056.
https://doi.org/10.1093/ndt/gfw374
[15] Nejat, M., Pickering, J.W., Walker, R.J. and Endre, Z.H. (2010) Rapid Detection of Acute Kidney Injury by Plasma Cystatin C in the Intensive Care Unit. Nephrology Dialysis Transplantation, 25, 3283-3289.
https://doi.org/10.1093/ndt/gfq176
[16] Herget-Rosenthal, S., Marggraf, G., Hüsing, J., Göring, F., Pietruck, F., Janssen, O., et al. (2004) Early Detection of Acute Renal Failure by Serum Cystatin C. Kidney International, 66, 1115-1122.
https://doi.org/10.1111/j.1523-1755.2004.00861.x
[17] Bagshaw, S.M. and Gibney, R.T. (2008) Conventional Markers of Kidney Function. Critical Care Medicine, 36, S152-S158.
https://doi.org/10.1097/CCM.0b013e318168c613
[18] Aydoğdu, M., Gürsel, G., Sancak, B., Yeni, S., Sarı, G., Taşyürek, S., et al. (2013) The Use of Plasma and Urine nEutrophil Gelatinase Associated Lipocalin (NGAL) and Cysta-tin C in Early Diagnosis of Septic Acute Kidney Injury in Critically Ill Patients. Disease Markers, 34, Article ID: 740351.
https://doi.org/10.1155/2013/740351
[19] Doi, K., Yuen, P.S., Eisner, C., Hu, X., Leelahavanichkul, A., Schnermann, J., et al. (2009) Reduced Production of Creatinine Limits Its Use as Marker of Kidney Injury in Sepsis. Journal of the American Society of Nephrology, 20, 1217-1221.
https://doi.org/10.1681/ASN.2008060617
[20] Poston, J.T. and Koyner, J.L. (2019) Sepsis Associated Acute Kidney Injury. BMJ, 364, Article No. k4891.
https://doi.org/10.1136/bmj.k4891
[21] Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney In-jury Work Group (2012) KDIGO Clinical Practice Guideline for Acute Kidney Injury. Kidney International Supplements, 2, 1-138.
[22] Leedahl, D.D., Frazee, E.N., Schramm, G.E., et al. (2014) Derivation of Urine Output Thresholds That Identify a Very High Risk of AKI in Patients with Septic Shock. Clinical Journal of the American Society of Nephrology, 9, 1168-1174.
https://doi.org/10.2215/CJN.09360913
[23] Pravisani, R., Baccarani, U., Langiano, N., et al. (2020) Predictive Value of Intraoperative Doppler Flowmetry for Delayed Graft Function in Kidney Transplantation: A Pilot Study. Trans-plantation Proceedings, 52, 1556-1558.
https://doi.org/10.1016/j.transproceed.2020.02.049
[24] Wang, Z., Xiao, J., Zhang, Z., Qiu, X. and Chen, Y. (2018) Chronic Kidney Disease Can Increase the Risk of Preoperative Deep Vein Thrombosis in Middle-Aged and Elderly Pa-tients with Hipfractures. Clinical Interventions in Aging, 13, 1669-1674.
https://doi.org/10.2147/CIA.S174691
[25] Platt, J. (1992) Doppler Evaluation of Native Kidney Dysfunction: Ob-structive and Nonobstructive Disease. American Journal of Roentgenolog, 158, 1035-1042.
https://doi.org/10.2214/ajr.158.5.1566663
[26] Wang, H., Feng, Q., Li, C., Zhang, H. and Peng, Y. (2022) Ultra-sonographic Study of Hemodynamics and Contrast-Enhanced Ultrasound in the Rhesus Monkey Kidney. Experimental Animals, 71, 116-122.
https://doi.org/10.1538/expanim.20-0194
[27] Kolonko, A., Chudek, J. and Więcek, A. (2018) Relationship be-tween Individual Components of the Extended-Criteria Donor Definition and the First Post-Transplant Kidney Graft Re-sistance Index, Measuredby Doppler Sonography. Transplantation Proceedings, 50, 1680-1685.
https://doi.org/10.1016/j.transproceed.2017.12.061
[28] Bagshaw, S.M. and Bellomo, R. (2010) Cystatin C in Acute Kidney Injury. Current Opinion in Critical Care, 16, 533-539.
https://doi.org/10.1097/MCC.0b013e32833e8412
[29] Segarra, A., de la Torre, J., Ramos, N., Quiroz, A., Garjau, M., Torres, I., et al. (2011) Assessing Glomerular Filtration Rate in Hospitalized Patients: A Comparison between CKD-EPI and Four Cystatin C-Based Equations. Clinical Journal of the American Society of Nephrology, 6, 2411-2420.
https://doi.org/10.2215/CJN.01150211
[30] Dharnidharka, V.R., Kwon, C. and Stevens, G. (2002) Serum Cysta-tin C Is Superior to Serum Creatinine as a Marker of Kidney Function: A Meta-Analysis. American Journal of Kidney Diseases, 40, 221-226.
https://doi.org/10.1053/ajkd.2002.34487
[31] Cruz, D.N., de Geus, H.R. and Bagshaw, S.M. (2011) Biomarker Strategies to Predict Need for Renal Replacement Therapy in Acute Kidney Injury. Seminars in Dialysis, 24, 124-131.
https://doi.org/10.1111/j.1525-139X.2011.00830.x
[32] Ahlström, A., Tallgren, M., Peltonen, S, and Pettilä, V. (2004) Evolution and Predictive Power of Serum Cystatin C in Acute Renal Failure. Clinical Nephrology, 62, 344-350.
https://doi.org/10.5414/CNP62344
[33] Di Nardo, M., Ficarella, A., Ricci, Z., Luciano, R., Stoppa, F., Picardo, S., et al. (2013) Impact of Severe Sepsis on Serum and Urinary Biomarkers of Acute Kidney Injury in Critically Ill Children: An Observational Study. Blood Purification, 35, 172-176.
https://doi.org/10.1159/000346629
[34] Leem, A.Y., Park, M.S., Park, B.H., Jung, W.J., Chung, K.S., Kim, S.Y., Kim, E.Y., Jung, J.Y., Kang, Y.A., Kim, Y.S., Kim, S.K., Chang, J. and Song, J.H. (2017) Value of Serum Cystatin C Measurement in the Diagnosis of Sepsis-Induced Kidney Injury and Prediction of Renal Function Recovery. Yonsei Medical Journal, 58, 604-612.
[35] Haase, M., Bellomo, R., Devarajan, P., et al. (2009) Accuracy of Neutrophil Gelatinase-Associated Lipocalin (NGAL) in Diagnosis and Progno-sis in Acute Kidney Injury: A Systematic Review and Meta-Analysis. American Journal of Kidney Diseases, 54, 1012-1024.
https://doi.org/10.1053/j.ajkd.2009.07.020
[36] Haase, M., Devarajan, P., Haase-Fielitz, A., et al. (2011) The Outcome of Neutrophil Gelatinase-Associated Lipocalin-Positive Subclinical Acute Kidney Injury: A Multi-center Pooled Analysis of Prospective Studies. Journal of the American College of Cardiology, 57, 1752-1761.
https://doi.org/10.1016/j.jacc.2010.11.051
[37] Bagshaw, S.M., Bennett, M., Haase, M., et al. (2010) Plasma and Urine Neutrophil Gelatinase-Associated Lipocalin in Septic versus Non-Septic Acute Kidney Injury in Critical Illness. Intensive Care Medicine, 36, 452-461.
https://doi.org/10.1007/s00134-009-1724-9
[38] Srisawat, N., Murugan, R., Lee, M., et al. (2011) Plasma Neu-trophil Gelatinase-Associated Lipocalin Predicts Recovery from Acute Kidney Injury Following Community-Acquired Pneumonia. Kidney International, 80, 545-552.
https://doi.org/10.1038/ki.2011.160
[39] Lubell, T.R., Barasch, J.M., Xu, K., et al. (2017) Urinary Neutrophil Gelatinase-Associated Lipocalin for the Diagnosis of Urinary Tract Infections. Pediatrics, 140, Article ID: e20171090.
https://doi.org/10.1542/peds.2017-1090
[40] Shao, X., Tian, L., Xu, W., et al. (2014) Diagnostic Value of Urinary Kidney Injury Molecule 1 for Acute Kidney Injury: A Meta-Analysis. PLOS ONE, 9, Article No. e84131.
https://doi.org/10.1371/journal.pone.0084131
[41] Tu, Y., Wang, H., Sun, R., et al. (2014) Urinary Netrin-1 and KIM-1 as Early Biomarkers for Septic Acute Kidney Injury. Renal Failure, 36, 1559-1563.
https://doi.org/10.3109/0886022X.2014.949764
[42] Noiri, E., Doi, K., Negishi, K., Tanaka, T., Hamasaki, Y., Fujita, T., et al. (2009) Urinary Fatty Acid-Binding Protein 1: An Early Predictive Biomarker of Kidney Injury. American Journal of Physiology. Renal Physiology, 296, F669-F679.
https://doi.org/10.1152/ajprenal.90513.2008
[43] Cruz, D.N., Perazella, M.A., Bellomo, R., de Cal, M., Polanco, N., Corradi, V., Lentini, P., Nalesso, F., Ueno, T., Ranieri, V.M. and Ronco, C. (2007) Effectiveness of Polymyxin B-Immobilized Fiber Column in Sepsis: A Systematic Review. Critical Care, 11, Article No. R47.
https://doi.org/10.1186/cc5780
[44] Nakamura, T., Sugaya, T. and Koide, H. (2008) Urinary Liver-Type Fatty Acid-Binding Protein in Septic Shock: Effect of Polymyxin B-Immobilized Fiber Hemoperfusion. Shock, 31, 454-459.
https://doi.org/10.1097/SHK.0b013e3181891131