蛛网膜下腔出血患者发生急性肾损伤的危险因素分析
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摘要
目的:分析蛛网膜下腔出血(SAH)患者急性肾损伤(AKI)的发病率及相关危险因素。方法:收集2015年1月至2016年12月武汉大学中南医院神经重症监护室(NICU)中自发性SAH患者,回顾性收集患者一般资料。应用改善全球肾脏病预后组织(KDIGO)的AKI诊断及分期标准,比较AKI组与非AKI组临床资料的差异。采用二分类Logistic回归方程分析SAH患者发生AKI的危险因素。通过绘制受试者工作特征(ROC)曲线,评估各危险因素的预测价值。结果:356例SAH患者中83例发生AKI,发病率为23. 3%,AKI1到AKI3期分别有58例(16. 3%)、12例(3. 4%)、13例(3. 7%)。Logistic回归结果提示:利尿剂(OR=1. 983,95%CI:1. 054～3. 732)、APACHEⅡ评分(OR=1. 224,95%CI:1. 165～1. 285)是SAH患者发生AKI的独立危险因素;纳入SAH患者中75例死亡,AKI组的病死率明显高于非AKI组(59. 0%比9. 5%,OR=13. 69,95%CI:7. 55～24. 84,P<0. 001)。APACHEⅡ评分预测SAH患者发生AKI的ROC曲线下面积最大(AUC=0. 843,P<0. 001),具有较好的准确性。结论:在SAH患者中AKI发生率较高;AKI的发生显著增加患者死亡率,患者入院时APACHEⅡ评分是预测患者发生AKI的最佳预测因子。
Objective: To analyze the incidence and related risk factors of acute kidney injury(AKI) in patients after subarachnoid hemorrhage(SAH).Methods: The patients with spontaneous SAH in the Neurological Intensive Care Unit(NICU) of Zhongnan Hospital of Wuhan University from January2015 to December 2016 were screened out. Based on the KDIGO-AKI criteria, these patients were classified into two groups: NAKI group(patients without AKI) and AKI group. The clinical data of patients were collected retrospectively. The clinical characteristics of patients with AKI and non -AKI were compared. Logistic regression model was used to analyze the risk factors of AKI, and then the receiver operating characteristic curve(ROC) was used to evaluate the predictive value of risk factors.Results: A total of 83(23. 3%) patients developed AKI, and the incidence of AKI stage 1 to 3 were16. 3%, 3. 4%, and 3. 7%, respectively. Logistic regression suggested that independent risk factors of AKI were hydragogue(OR=1. 983,95%CI:1. 054-3. 732) and APACHE Ⅱ scores(OR=1. 224,95%CI: 1. 165 - 1. 285). The total mortality of SAH patients was 21%, and the mortality of AKI group was significantly higher than that of NAKI group(59. 0% vs 9. 5%, OR=13. 69, 95%CI: 7. 55-24. 84, P<0. 001). For predicting AKI, APACHEⅡ scores displayed an excellent areas under the ROC curve(AUC=0. 843, P<0. 001).Conclusion: The incidence of AKI is higher in patients with SAH. AKI significantly increases the hospital mortality, which is an important factor affecting the prognosis of SAH patients. The APACHEⅡ scores is the best predictor of AKI among subarachnoid hemorrhagic patients.
Objective: To analyze the incidence and related risk factors of acute kidney injury(AKI) in patients after subarachnoid hemorrhage(SAH).Methods: The patients with spontaneous SAH in the Neurological Intensive Care Unit(NICU) of Zhongnan Hospital of Wuhan University from January2015 to December 2016 were screened out. Based on the KDIGO-AKI criteria, these patients were classified into two groups: NAKI group(patients without AKI) and AKI group. The clinical data of patients were collected retrospectively. The clinical characteristics of patients with AKI and non -AKI were compared. Logistic regression model was used to analyze the risk factors of AKI, and then the receiver operating characteristic curve(ROC) was used to evaluate the predictive value of risk factors.Results: A total of 83(23. 3%) patients developed AKI, and the incidence of AKI stage 1 to 3 were16. 3%, 3. 4%, and 3. 7%, respectively. Logistic regression suggested that independent risk factors of AKI were hydragogue(OR=1. 983,95%CI:1. 054-3. 732) and APACHE Ⅱ scores(OR=1. 224,95%CI: 1. 165 - 1. 285). The total mortality of SAH patients was 21%, and the mortality of AKI group was significantly higher than that of NAKI group(59. 0% vs 9. 5%, OR=13. 69, 95%CI: 7. 55-24. 84, P<0. 001). For predicting AKI, APACHEⅡ scores displayed an excellent areas under the ROC curve(AUC=0. 843, P<0. 001).Conclusion: The incidence of AKI is higher in patients with SAH. AKI significantly increases the hospital mortality, which is an important factor affecting the prognosis of SAH patients. The APACHEⅡ scores is the best predictor of AKI among subarachnoid hemorrhagic patients.
引文
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[9] Tujjar O, Belloni I, Hougardy JM,et al. Acute kidney injury after subarachnoid hemorrhage[J]. J Neurosurg Anesthesiol,2017,29(2):140-149.
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[11] Mehta RL, Pascual MT, Soroko S, et al. Diuretics,mortality, and nonrecovery of renal function in acute re-nal failure[J]. JAMA,2002, 288(20):2 547-2 553.
[12] Wu X, Zhang W, Ren H, et al. Diuretics associated acute kidney injury:clinical and pathological analysis[J].Ren Fail,2014,36(7):1 051-1 055.
[13] Choi HW, Park HJ, Choi SY,et al. Early prediction of the severity of acute pancreatitis using radiologic and clinical scoring systems with classification tree analysis[J]. AJR Am J Roentgenol,2018,211(5):1 035-1 043.
[14] Trongtrakul K, Sawawiboon C, Wang AY, et al.Acute kidney injury in critically ill surgical patients:Epi-demiology, risk factors and outcomes[J]. Nephrology(Carlton), 2019,24(1):39-46.
[15] Zygun DA, Doig CJ, Gupta AK, et al. Non-neurologi-cal organ dysfunction in neurocritical care[J]. J Crit Care,2003, 18(4):238-244.
[16] Levey AS, James MT. Acute kidney injury[J]. Ann In-tern Med,2017,167(9):ITC66-ITC80.
[17] Hoste EA, Bagshaw SM, Bellomo R, et al. Epidemi-ology of acute kidney injury in critically ill patients:the multinational AKI-EPI study[J]. Intensive Care Med,2015,41(8):1 411-1 423.
[2] Nieuwkamp DJ, Setz LE, Algra A, et al. Changes in case fatality of aneurysmal subarachnoid haemorrhage over time, according to age, sex, and region:a meta-analysis[J]. Lancet Neurol,2009,8(7):635-642.
[3] Zacharia BE, Ducruet AF, Hickman ZL, et al. Renal dysfunction as an independent predictor of outcome after aneurysmal subarachnoid hemorrhage:a single-center cohort study[J]. Stroke,2009,40(7):2 375-2 381.
[4] Ray B, Rickert KL, Welch BG,et al. Development of contrast-induced nephropathy in subarachnoid hemor-rhage:a single center perspective[J]. Neurocrit Care,2013,19(2):150-156.
[5] Mizuno T, Sato W, Ishikawa K,et al. KDIGO(kidney disease:improving global outcomes)criteria could be a useful outcome predictor of cisplatin-induced acute kid-ney injury[J]. Oncology,2012,82(6):354-359.
[6] Fuhrman DY, Kane-Gill S, Goldstein SL,et al. Acute kidney injury epidemiology, risk factors, and outcomes in critically ill patients 16-25 years of age treated in an adult intensive care unit[J]. Ann Intensive Care, 2018,8(1):26.
[7] Lovelock CE, Rinkel GJ, Rothwell PM. Time trends in outcome of subarachnoid hemorrhage:Population-based study and systematic review[J]. Neurology,2010, 74(19):1 494-1 501.
[8] de Rooij NK, Linn FH, van der Plas JA, et al. Inci-dence of subarachnoid haemorrhage:a systematic re-view with emphasis on region, age, gender and time trends[J]. J Neurol Neurosurg Psychiatry,2007, 78(12):1 365-1 372.
[9] Tujjar O, Belloni I, Hougardy JM,et al. Acute kidney injury after subarachnoid hemorrhage[J]. J Neurosurg Anesthesiol,2017,29(2):140-149.
[10] Chen S, Li Q, Wu H,et al. The harmful effects of sub-arachnoid hemorrhage on extracerebral organs[J].Biomed Res Int,2014,2014:858496.
[11] Mehta RL, Pascual MT, Soroko S, et al. Diuretics,mortality, and nonrecovery of renal function in acute re-nal failure[J]. JAMA,2002, 288(20):2 547-2 553.
[12] Wu X, Zhang W, Ren H, et al. Diuretics associated acute kidney injury:clinical and pathological analysis[J].Ren Fail,2014,36(7):1 051-1 055.
[13] Choi HW, Park HJ, Choi SY,et al. Early prediction of the severity of acute pancreatitis using radiologic and clinical scoring systems with classification tree analysis[J]. AJR Am J Roentgenol,2018,211(5):1 035-1 043.
[14] Trongtrakul K, Sawawiboon C, Wang AY, et al.Acute kidney injury in critically ill surgical patients:Epi-demiology, risk factors and outcomes[J]. Nephrology(Carlton), 2019,24(1):39-46.
[15] Zygun DA, Doig CJ, Gupta AK, et al. Non-neurologi-cal organ dysfunction in neurocritical care[J]. J Crit Care,2003, 18(4):238-244.
[16] Levey AS, James MT. Acute kidney injury[J]. Ann In-tern Med,2017,167(9):ITC66-ITC80.
[17] Hoste EA, Bagshaw SM, Bellomo R, et al. Epidemi-ology of acute kidney injury in critically ill patients:the multinational AKI-EPI study[J]. Intensive Care Med,2015,41(8):1 411-1 423.