目的 构建并应用维持性血液透析患者衰弱风险预测模型。方法 采用前瞻性研究设计,选取2020年3月—2022年4月在浙江省某三级甲等医院接受维持性血液透析治疗的876例患者作为研究对象,其中2020年3月—2021年7月为建模组（n=491）,2021年8月—2022年4月为验证组（n=385）。采用单因素和多因素Logistic回归分析维持性血液透析患者衰弱的危险因素,建立风险预测模型并绘制列线图。采用Hosmer-Lemeshow拟合优度检验、受试者操作特征曲线下面积（area under curve,AUC）评价模型临床预测效果,采用Bootstrap抽样法对模型进行内部验证。结果 共226例患者（25.80%）发生衰弱,其中建模组123例（25.05%）,验证组103例（26.75%）。年龄（OR=3.553）、日常生活活动能力（OR=37.804）、脑卒中史（OR=16.434）、血清白蛋白（OR=4.197）、C反应蛋白（OR=2.633）及血肌酐（OR=2.201）6个影响因素构建预测模型。建模组Hosmer-Lemeshow拟合优度检验χ2=5.667,P=0.772,AUC为0.955[95%CI（0.936,0.974）],灵敏度89.7%,特异度87.7%,约登指数为0.774,内部验证C-statistic统计量值为0.950。验证组Hosmer-Lemeshow拟合优度检验χ2=44.085,P=1.362,AUC为0.914[95%CI（0.882,0.946）],灵敏度85.5%,特异度85.4%,约登指数为0.709,准确度为73.5%。结论 维持性血液透析患者衰弱风险预测模型能较好地可视化预测患者衰弱的发生风险,为医护人员早期识别和干预提供支持。
Objective To develop predictive model of frailty risk prediction in maintenance hemodialysis patients. Methods Prospective study design was adopted,a total of 876 patients who received hemodialysis in a tertiary class A hospital in Zhejiang Province from March 2020 to April 2022 were recruited,including March 2020 to July 2021 as the modeling group（n=491）and August 2021 to April 2022 as the validation group（n=385）. Univariate and multivariate logistic regression were used to analyze the risk factors of frailty in maintenance hemodialysis patients,and we established a risk prediction model and to draw a nomogram. Hosmer-Lemeshow test and area under receiver operating characteristic were used to evaluate the clinical prediction effect of the model. The bootstrap method sampling method was used to internally validate the model. Results 226 patients（25.80%）had frailty,123（25.05%）in the modeling group and 103（26.75%）in the validation group. Six influencing factors,including age（OR=3.553）,activities of daily living（OR=37.804）,history of stroke（OR=16.434）,serum albumin（OR=4.197）,C-reactive protein（OR=2.633）,and serum creatinine（OR=2.201）,were used to construct the prediction model. In the modeling group,Hosmer-Lemeshow goodness-of-fit test showed χ2=5.667,P=0.772,the AUC was 0.955[95%CI（0.936,0.974）],the sensitivity was 89.7%,the specificity was 87.7%,the Youden index was 0.774,and internal validation C-statistic value was 0.950. In the validation group,Hosmer-Lemeshow goodness-of-fit test showed χ2=44.085,P=1.362,the AUC was 0.914[95%CI（0.882,0.946）],the sensitivity was 85.5%,the specificity was 85.4%,the Youden index was 0.709,and the accuracy was 73.5%. Conclusion The risk prediction model of frailty in maintenance hemodialysis patients can better visually predict the occurrence risk of frailty in patients,providing support for the early identification and intervention of medical staff.
[1] Monardo P,Lacquaniti A,Campo S,et al.Updates on hemodialysis techniques with a common denominator:the personalization of the dialytic therapy[J]. Semin Dial,2021,34(3):183-195.
[2] Yadla M,John J,Mummadi M.A study of clinical assessment of frailty in patients on maintenance hemodialysis supported by cashless government scheme[J]. Saudi J Kidney Dis Transpl,2017,28(1):15.
[3] Nixon AC,Bampouras TM,Pendleton N,et al.Frailty and chronic kidney disease:current evidence and continuing uncertainties[J]. Clin Kidney J,2018,11(2):236-245.
[4] Jiang XX,Li DT,Shen W,et al.In-hospital outcomes of patients on maintenance dialysis with frailty:10-year results from the US national inpatient sample database[J]. J Ren Nutr,2020,30(6):526-534.
[5] Takeuchi H,Uchida HA,Kakio Y,et al.The prevalence of frailty and its associated factors in Japanese hemodialysis patients[J]. Aging Dis,2018,9(2):192-207.
[6] 吴淑琳,宋洁,肖萍,等. 维持性血液透析患者衰弱发生率及影响因素的系统评价[J]. 中华护理教育,2021,18(4):352-357.
Wu SL,Song J,Xiao P,et al.Systematic review of frailty prevalence and its influencing factors in patients with maintenance hemodialysis[J]. Chin J Nurs Educ,2021,18(4):352-357.
[7] 上海慢性肾脏病早发现及规范化诊治与示范项目专家组. 慢性肾脏病筛查诊断及防治指南[J]. 中国实用内科杂志,2017,37(1):28-34.
Shanghai Chronic Kidney Disease Early Detection and Standardized Diagnosis and Treatment and Demonstration Project Expert Group. Guideline for screening,diagnosis,prevention and treatment of chronic kidney disease[J]. Chin J Pract Intern Med,2017,37(1):28-34.
[8] Riley RD,Ensor J,Snell KIE,et al.Calculating the sample size required for developing a clinical prediction model[J]. BMJ,2020,368:m441.
[9] Fried LP,Tangen CM,Walston J,et al.Frailty in older adults:evidence for a phenotype[J]. J Gerontol A Biol Sci Med Sci,2001,56(3):M146-M156.
[10] Lawton MP,Brody EM.Assessment of older people:self-maintaining and instrumental activities of daily living[J]. Gerontologist,1969,9(3):179-186.
[11] Fu WJ,Zhang AH,Ma LN,et al.Severity of frailty as a significant predictor of mortality for hemodialysis patients:a prospective study in China[J]. Int J Med Sci,2021,18(14):3309-3317.
[12] Iyasere OU,Brown EA,Johansson L,et al.Quality of life and physical function in older patients on dialysis:a comparison of assisted peritoneal dialysis with hemodialysis[J]. Clin J Am Soc Nephrol,2016,11(3):423-430.
[13] Fukuma S,Shimizu S,Shintani A,et al.Development and validation of a prediction model for loss of physical function in elderly hemodialysis patients[J]. Nephrol Dial Transplant,2018,33(8):1452-1458.
[14] Cai GL,Ying JP,Pan MY,et al.Development of a risk prediction nomogram for sarcopenia in hemodialysis patients[J]. BMC Nephrol,2022,23(1):319.
[15] 黄国海,许少英,李绪城. 维持性血液透析患者的生存预后及其风险预测模型的构建[J]. 临床肾脏病杂志,2023,23(4):320-325.
Huang GH,Xu SY,Li XC.Survival analysis and risk predic-tive model of maintenance hemodialysis patients[J]. J Clin Nephrol,2023,23(4):320-325.
[16] 应金萍,蔡根莲,潘梦燕,等. 维持性血液透析患者衰弱表型对日常生活活动能力的影响[J]. 中华肾脏病杂志,2021,37(8):639-646.
Ying JP,Cai GL,Pan MY,et al.Effect of frailty phenotype on activities of daily living in maintenance hemodialysis patients[J]. Chin J Nephrol,2021,37(8):639-646.
[17] Watanabe T,Kutsuna T,Suzuki Y,et al.Perceived difficulty in activities of daily living and survival in patients receiving maintenance hemodialysis[J]. Int Urol Nephrol,2021,53(1):177-184.
[18] Shah B,Jagtap P,Sarmah D,et al.Cerebro-renal interaction and stroke[J]. Eur J Neurosci,2021,53(4):1279-1299.
[19] Shih CJ,Ou SM,Chao PW,et al.Risks of death and stroke in patients undergoing hemodialysis with new-onset atrial fibrillation:a competing-risk analysis of a nationwide cohort[J]. Circulation,2016,133(3):265-272.
[20] 应金萍,蔡根莲,项雪佳,等. 维持性血液透析患者并发脑梗死的危险因素分析[J]. 中华危重症医学杂志(电子版),2021,14(3):206-212.
Ying JP,Cai GL,Xiang XJ,et al.Risk factors of cerebral infarction in patients undergoing maintenance hemodialysis[J]. Chin J Crit Care Med Electron Ed,2021,14(3):206-212.
[21] Mutevelić-Turković A,Resić H,Roljić BČ,et al.The frailty phenotype in hemodialysis patients and its association with biochemical markers of mineral bone disorder,inflammation and nutrition[J]. Revue Roumaine De Med Interne,2022,60(1):42-48.
[22] Sahathevan S,Khor BH,Ng HM,et al.Understanding development of malnutrition in hemodialysis patients:a narrative review[J]. Nutrients,2020,12(10):3147.
[23] 周丹,张芃,张照英,等. 维持性血液透析尿毒症患者外周血MCP-1、TNF-α、IL-6和hs-CRP水平对血管通路功能的影响[J]. 临床误诊误治,2018,31(2):91-94.
Zhou D,Zhang P,Zhang ZY,et al.Effects of MCP-1,TNF-α,IL-6 and Hs-CRP levels in peripheral blood on function of vascular access in treat-ment of patients with maintenance hemodialysis[J]. Clin Misdiagnosis Mistherapy,2018,31(2):91-94.
[24] Hanna RM,Ghobry L,Wassef O,et al.A practical approach to nutrition,protein-energy wasting,sarcopenia,and cachexia in patients with chronic kidney disease[J]. Blood Purif,2020,49(1/2):202-211.
[25] 杜晓菊,张海林,尹丽霞,等. 维持性血液透析患者骨骼肌质量下降预测模型的构建及对护理工作的启示[J]. 中华护理杂志,2021,56(4):496-501.
Du XJ,Zhang HL,Yin LX,et al.Establishment and enlighten-ment of a predictive model for decreased skeletal muscle mass in maintenance hemodialysis patients[J]. Chin J Nurs,2021,56(4):496-501.
