红细胞容积分布宽度与肾移植术后ARDS患者病死率的相关性分析

阳敏; 刘洪; 佘兴国; 牛英; 万齐全; 庄权; 彭博; 朱毅; 李偲; 明英姿

doi:10.3969/j.issn.1674-7445.2017.04.005

红细胞容积分布宽度与肾移植术后ARDS患者病死率的相关性分析

doi: 10.3969/j.issn.1674-7445.2017.04.005

410013 长沙, 中南大学湘雅三医院移植中心

基金项目:

吴阶平医学基金会临床科研专项资助基金 320.6750.15070

湖南省自然科学基金平衡项目 2016JJ4105

详细信息

通讯作者:
明英姿, Email: myz_china@aliyun.com

中图分类号: R617, R441.8
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- 被引次数: 0
出版历程
- 收稿日期: 2017-04-21
- 网络出版日期: 2021-01-19
- 刊出日期: 2017-07-15

Correlation analysis between red cell volume distribution width and the mortality rate in ARDS patients after renal transplantation

Transplantation Center of the Third Xiangya Hospital, Central South University, Changsha 410013, China

More Information

Corresponding author: Ming Yingzi, Email: myz_china@aliyun.com

摘要

摘要: 目的探讨红细胞容积分布宽度（RDW）与肾移植术后急性呼吸窘迫综合征（ARDS）患者病死率的相关性。方法回顾性分析106例肾移植术后ARDS患者的临床资料, 根据RDW的高低分为RDW正常组（≤15.0%, 68例）和RDW升高组（ > 15.0%, 38例）。比较两组患者的基本情况和不良事件发生情况, 绘制Kaplan-Meier曲线比较两组的50 d病死率, 采用Cox比例风险回归分析ARDS患者死亡的风险因素。结果 106例患者中, 50 d内死亡总例数为46例（43.4%）。两组在序贯器官衰竭评估（SOFA）评分、血清肌酐、血红蛋白及血小板计数的差异有统计学意义（均为P < 0.05）。RDW升高组患者的50 d病死率及感染性休克发生率明显高于RDW正常组, 差异均有统计学意义（均为P < 0.05）, Kaplan-Meier生存曲线分析表明, RDW升高组与正常组患者的50 d病死率差异有统计学意义（P < 0.01）。Cox比例风险回归法单因素分析发现, 血红蛋白 < 100 g/L、血清肌酐 > 133 μmol/L、血小板计数 < 100×10⁹/L、重度ARDS、RDW > 15.0%均为ARDS患者50 d内死亡的潜在危险因素（均为P < 0.05）。多因素分析发现, 重度ARDS[比值比（OR）=12.77, 95%可信区间（CI）11.63~15.39, P < 0.001]和RDW > 15.0%（OR=2.01, 95%CI 1.02~3.94, P < 0.043）为ARDS患者50 d内死亡的独立危险因素。结论 RDW升高与肾移植术后ARDS患者疾病严重程度和50 d病死率相关, 可以作为一项较有意义的预测肾移植术后ARDS患者预后的临床指标。
- 红细胞容积分布宽度（RDW） /
- 急性呼吸窘迫综合征（ARDS） /
- 肾移植 /
- 肺部感染 /
- 预后 /
- 预测因素 /
- 公民逝世后器官捐献 /
- 脓毒血症
Abstract: Objective To investigate the correlation between red cell volume distribution width (RDW) and the mortality rate of acute respiratory distress syndrome (ARDS) patients after renal transplantation. Methods Clinical data of 106 ARDS patients undergoing renal transplantation were retrospectively analyzed. According to RDW, all patients were assigned into the normal (≤15.0%, n=68) and increasing RDW groups ( > 15.0%, n=38). Baseline data and the incidence of adverse events were statistically compared between two groups. Kaplan-Meier survival curve was adopted to compare the 50 d-mortality rate between two groups. Cox's proportional hazards regression model was utilized to identify the risk factors of the mortality of ARDS patients. Results Among 106 patients, the 50 d-mortality rate was calculated as 43.4% (46/106). The sequential organ failure assessment (SOFA) score, serum creatinine, hemoglobin and platelet count significantly differed between two groups (all P < 0.05). In the increasing RDW group, the 50 d-mortality rate and the incidence of infectious shock were significantly higher than those in the normal RDW group (both P < 0.05). Kaplan-Meier survival curve demonstrated that the 50 d-mortality rate significantly differed between two groups (P < 0.01). Cox's proportional hazards regression model univariate analysis revealed that hemoglobin level < 100 g/L, serum creatinine > 133 μmol/L, platelet count < 100×10⁹/L, severe ARDS and RDW > 15.0% were the potential risk factors of the 50 d-mortality rate in ARDS patients (all P < 0.05). Multivariate analysis demonstrated that severe ARDS [odd ratio (OR)=12.77, 95% confidence interval (CI) 11.63-15.39, P < 0.001] and RDW > 15.0% (OR=2.01, 95%CI 1.02-3.94, P < 0.043) were the independent risk factors of the 50 d-mortality rate in ARDS patients. Conclusions RDW elevation is correlated with the severity of disease and 50 d-mortality rate in ARDS patients following renal transplantation. RDW can serve as a clinical parameter to predict the prognosis of ARDS patients after renal transplantation.
- Red cell volume distribution width (RDW) /
- Acute respiratory distress syndrome (ARDS) /
- Renal transplantation /
- Pulmonary infection /
- Prognosis /
- Predictor /
- Organ donation after citizen's death /
- Septicopyemia

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图 1 两组ARDS患者的Kaplan-Meier生存曲线

Figure 1. Kaplan-Meier survival curves of patients with ARDS in two groups

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表 1 两组患者一般临床资料的比较

Table 1. Comparison of baseline characteristics of the patients between two groups

项目	RDW正常组（n=68）	RDW升高组（n=38）	P值
年龄（x±s, 岁）	39±11	42±13	< 0.17
性别[n（%）]			< 0.43
男	55（81）	33（87）
女	13（19）	05（13）
体质量（x±s, kg）	56±90	58±11	< 0.31
感染类型[n（%）]			< 0.50
细菌	32（47）	23（61）
病毒	19（28）	05（13）
真菌	06（9）0	3（8）
其他	11（16）	07（18）
SOFA评分（x±s, 分）	4.7±1.7	6.6±2.2	< 0.01
重度ARDS[n（%）]	26（38）	15（40）	< 0.90
C反应蛋白[M(Q), mg/L]	13（4~54）	17（6~50）	< 0.54
降钙素原[M(Q), ng/L]	0.78（0.24~4.39）	1.35（0.47~8.63）	< 0.31
血清肌酐[M(Q), μmol/L]	143（114~203）0	194（129~348）0	< 0.05
白蛋白（x±s, g/L）	32±60	32±60	< 0.98
血红蛋白（x±s, g/L）	105±200	87±19	< 0.01
白细胞计数[M(Q), ×109/L]	11（7~14）	10（6~15）	< 0.59
血小板计数（x±s, ×109/L）	190±840	122±79	< 0.01
中性粒细胞/淋巴细胞[M(Q)]	15（9~28）	14（9~24）	< 0.69
血小板分布宽度（x±s, %）	15.4±2.70	15.9±2.60	< 0.29
血小板平均容积（x±s, fL）	11.4±1.50	11.3±1.30	< 0.83

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表 2 两组患者不良事件发生率的比较

Table 2. Comparison of the occurrence rate of adverse outcome in patients between two groups

[n(%)]
不良事件	RDW正常组（n=68）	RDW升高组（n=38）	P值
死亡（50 d内）	23(34)	23(61)	0.008
有创通气	44(65)	28(74)	0.340
血培养阳性	15(22)	12(32)	0.280
感染性休克	15(22)	19(50)	0.003

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表 3 ARDS患者50 d内死亡风险因素分析

Table 3. The univariate and multivariate analysis on risk of death of ARDS patients in 50 d

因素	单因素		多因素
因素	OR（95%CI）	P值	OR（95%CI）	P值
血红蛋白 < 100 g/L	2.32（1.29~4.17）	< 0.005	1.36（0.70~2.63）	< 0.360
血清肌酐 > 133 μmol/L	2.10（1.14~3.85）	< 0.017	1.65（0.85~3.23）	< 0.140
血小板计数 < 100×10⁹/L	2.08（1.13~3.81）	< 0.019	1.01（0.49~2.07）	< 0.980
重度ARDS	3.02（1.68~5.46）	< 0.001	12.77（11.63~15.39）	< 0.001
RDW > 15.0%	2.50（1.40~4.16）	< 0.002	2.01（1.02~3.94）	< 0.043

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参考文献(27)

[1]	Shorr AF, Abbott KC, Agadoa LY. Acute respiratory distress syndrome after kidney transplantation: epidemiology, risk factors, and outcomes[J]. Crit Care Med, 2003, 31(5): 1325-1330. doi: 10.1097/01.CCM.0000053645.38356.A6
[2]	Canet E, Osman D, Lambert J, et al. Acute respiratory failure in kidney transplant recipients: a multicenter study[J]. Crit Care, 2011, 15(2): R91. DOI: 10.1186/cc10091.
[3]	Zhang P, Ye Q, Wan Q, et al. Mortality predictors in recipients developing acute respiratory distress syndrome due to pneumonia after kidney transplantation[J]. Ren Fail, 2016, 38(7): 1082-1088. DOI: 10.1080/0886022X.2016.1184938.
[4]	Förhécz Z, Gombos T, Borgulya G, et al. Red cell distribution width in heart failure: prediction of clinical events and relationship with markers of ineffective erythropoiesis, inflammation, renal function, and nutritional state[J]. Am Heart J, 2009, 158(4): 659-666. DOI: 10.1016/j.ahj.2009.07.024.
[5]	Tonelli M, Sacks F, Arnold M, et al. Relation between red blood cell distribution width and cardiovascular event rate in people with coronary disease[J]. Circulation, 2008, 117(2): 163-168. doi: 10.1161/CIRCULATIONAHA.107.727545
[6]	Ani C, Ovbiagele B. Elevated red blood cell distribution width predicts mortality in persons with known stroke[J]. J Neurol Sci, 2009, 277(1/2): 103-108. DOI: 10.1016/j.jns.2008.10.024.
[7]	Allen LA, Felker GM, Mehra MR, et al. Validation and potential mechanisms of red cell distribution width as a prognostic marker in heart failure[J]. J Card Fail, 2010, 16(3): 230-238. DOI: 10.1016/j.cardfail.2009.11.003.
[8]	Braun E, Kheir J, Mashiach T, et al. Is elevated red cell distribution width a prognostic predictor in adult patients with community acquired pneumonia?[J]. BMC Infect Dis, 2014, 14: 129. DOI: 10.1186/1471-2334-14-129.
[9]	Ku NS, Kim HW, Oh HJ, et al. Red blood cell distribution width is an independent predictor of mortality in patients with gram-negative bacteremia[J]. Shock, 2012, 38(2): 123-127. DOI: 10.1097/SHK. 0b013e31825e2a85.
[10]	Lee JH, Chung HJ, Kim K, et al. Red cell distribution width as a prognostic marker in patients with community-acquiredpneumonia[J]. Am J Emerg Med, 2013, 31(1): 72-79. DOI: 10.1016/j.ajem.2012.06.004.
[11]	Jo YH, Kim K, Lee JH, et al. Red cell distribution width is a prognostic factor in severe sepsis and septic shock[J]. Am J Emerg Med, 2013, 31(3): 545-548. DOI: 10.1016/j.ajem.2012.10.017.
[12]	Lorente L, Martín MM, Abreu-González P, et al. Red blood cell distribution width during the first week is associated with severity and mortality in septic patients[J]. PLoS One, 2014, 9(8): e105436. DOI: 10.1371/journal.pone.0105436.
[13]	ARDS Definition Task Force, Ranieri VM, Rubenfeld GD, et al. Acute respiratory distress syndrome: the Berlin definition[J]. JAMA, 2012, 307(23): 2526-2533. DOI: 10.1001/jama.2012.5669.
[14]	Sun Q, Liu ZH, Chen J, et al. An aggressive systematic strategy for acute respiratory distress syndrome caused by severe pneumonia after renal transplantation[J]. Transpl Int, 2006, 19(2): 110-116. doi: 10.1111/tri.2006.19.issue-2
[15]	Mao P, Wan QQ, Ye QF. Bacteria isolated from respiratory tract specimens of renal recipients with acute respiratory distress syndrome due to pneumonia: epidemiology and susceptibility of the strains[J]. Transplant Proc, 2015, 47(10): 2865-2869. DOI: 10.1016/j.transproceed.2015.10.034.
[16]	Chu L, Ye QF, Wan QQ, et al. Mortality predictors in acute respiratory distress syndrome renal transplant recipients with ESKAPE/rESKAPE pneumonia[J]. Transplant Proc, 2015, 47(8): 2450-2455. DOI: 10.1016/j.transproceed.2015.08.005.
[17]	邵明杰, 叶启发, 明英姿, 等.心脏死亡供体的移植肾功能延迟恢复的危险因素分析[J].中南大学学报(医学版), 2012, 37(10): 1045-1049. DOI: 10.3969/j.issn.1672-7347.2012.10.013. Shao MJ, Ye QF, Ming YZ, et al. Delayed graft function after DCD kidney transplantation: risk factors for and impact on transplantation[J]. J Cent South Univ(Med Sci), 2012, 37(10): 1045-1049. DOI: 10.3969/j.issn.1672-7347.2012.10.013.
[18]	Zhao W, Ge X, Sun K, et al. Acute respiratory distress syndrome after orthotopic liver transplantation[J]. J Crit Care, 2016, 31(1): 163-167. DOI: 10.1016/j.jcrc.2015.09.028.
[19]	Huang R, Yang C, Wu K, et al. Red cell distribution width as a potential index to assess the severity of hepatitis B virus-related liver diseases[J]. Hepatol Res, 2014, 44(14): E464-E470. DOI: 10.1111/hepr.12342.
[20]	Clarke K, Sagunarthy R, Kansal S. RDW as an additional marker in inflammatory bowel disease/undifferentiated colitis[J]. Dig Dis Sci, 2008, 53(9): 2521-2523. DOI: 10.1007/s10620-007-0176-8.
[21]	Geboers DG, de Beer FM, Tuip-de Boer AM, et al. Plasma suPAR as a prognostic biological marker for ICU mortality in ARDS patients[J]. Intensive Care Med, 2015, 41(7): 1281-90. Dig: 10.1007/s00134-015-3924-9. doi: 10.1007/s00134-015-3924-9
[22]	Chen C, Shi L, Li Y, et al. Disease-specific dynamic biomarkers selected by integrating inflammatory mediators with clinical informatics in ARDS patients with severe pneumonia[J]. Cell Biol Toxicol, 2016, 32(3):169-184. DOI: 10.1007/s10565-016-9322-4.
[23]	Chiari MM, Bagnoli R, De Luca PD, et al. Influence of acute inflammation on iron and nutritional status indexes in older inpatients[J]. J Am Geriatr Soc, 1995, 43(7):767-771. doi: 10.1111/jgs.1995.43.issue-7
[24]	Pierce CN, Larson DF. Inflammatory cytokine inhibition of erythropoiesis in patients implanted with a mechanical circulatory assist device[J]. Perfusion, 2005, 20(2): 83-90. doi: 10.1191/0267659105pf793oa
[25]	Ghaffari S. Oxidative stress in the regulation of normal and neoplastic hematopoiesis[J]. Antioxid Redox Signal, 2008, 10(11): 1923-1940. DOI: 10.1089/ars.2008.2142.
[26]	Ujszaszi A, Molnar MZ, Czira ME, et al. Renal function is independently associated with red cell distribution width in kidney transplant recipients: a potential new auxiliary parameter for the clinical evaluation of patients with chronic kidney disease[J]. Br J Haematol, 2013, 161(5): 715-725. DOI: 10.1111/bjh.12315.
[27]	Mucsi I, Ujszaszi A, Czira ME, et al. Red cell distribution width is associated with mortality in kidney transplant recipients[J]. Int Urol Nephrol, 2014, 46(3): 641-651. doi: 10.1007/s11255-013-0530-z