Email Alert | RSS

Journal of Peking University (Health Sciences) ›› 2022, Vol. 54 ›› Issue (5): 1056-封三. doi: 10.19723/j.issn.1671-167X.2022.05.036

Previous Articles    

Chronic kidney disease in community: Current state for screening and management

Ling-yi XU1,2,Miao HUI1,2,Shu-hong ZHU2,3,Zhao YANG1,2,Meng-rui LI1,2,Hong-yu YANG1,2,Xi-zi ZHENG1,2,Ji-cheng LV1,2,*(),Li YANG1,2,*()   

  1. 1. Renal Division, Peking University First Hospital; Institute of Nephrology, Peking University; Key Laboratory of Renal Disease, Ministry of Health of China; Key Laboratory of CKD Prevention and Treatment, Ministry of Education of China; Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences; Beijing 100034, China
    2. Joint Laboratory of Community Intelligent Health Management, Beijing 10034, China
    3. Health Intelligence Research Center of Beijing Xicheng District, Beijing 100053, China
  • Received:2022-06-22 Online:2022-10-18 Published:2022-10-14
  • Contact: Ji-cheng LV,Li YANG E-mail:jichenglv75@gmail.com;li.yang@bjmu.edu.cn
  • Supported by:
    the Beijing Outstanding Young Scientist Program(BJJWZYJH01201910001006);the Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences(2020-JKCS-009);the PKU-Baidu Fund(2020BD026);the PKU-Baidu Fund(2020BD044);the Beijing Nova Program(2021051);the CAMS Innovation Fund for Medical Sciences(2019-I2M-5-046);the Capital's Funds for Health Improvement and Research(首发2022-1-4071)

RICH HTML

 25   

PDF (PC)

162

Abstract:

Objective: To understand the current state and problem of screening and management of chronic kidney disease (CKD) in the community, and to explore the improving strategies. Methods: We established a community-CKD integrated data science platform based on medical information from 79 community health centers, in Xicheng District, Beijing. Patients who referred to 79 community health centers from 21 June 2015 to 20 November 2021 were retrospectively included in this study using the CKD data platform. The monitoring of the indicator of kidney injury, risk factor control, medicine use and device configuration in community were assessed in the study. Results: In the study, 70.6% of the population were identified with high risk of CKD in the total 374 498 individuals who referred to the community health centers. Hypertension (62.3%), coronary heart disease (43.3%) and diabetes (30.4%) were the most common risk factors in high-risk CKD population. Only 17.2% of the patients with high risk of CKD were screened for kidney injury including at least one serum creatine (Scr) or albuminuria test, among which 10 992 (24.2%) individuals were defined as CKD. 22.7% (11 338/49 908) of the total patients with kidney screening in community were defined as CKD, of whom, 42.6% and 46.1% were identified by estimated glomerular filtration rate (eGFR) < 60 mL/(min·1.73 m2) and abnormalities of urinary proteins, respectively. The overall CKD detection rate in the community was 5.2% (19 299/374 498), and the miss-diagnosis rate of CKD was 38.1%. Of the 79 community health centers, 13 (16.5%) were equipped with ACR testing device, and eGFR was reported directly in 66 (83.5%) centers. Altogether 60.3% and 99.7% of the community CKD patients achieved glucose control and blood pressure control, respectively, and 59.3% of the CKD patients who had proteinuria was treated with renin-angiotensin-aldosterone system (RAAS) inhibitors. Conclusion: High-risk CKD population account for a substantial proportion of patients who refer to the community. Early screening, prevention and management of CKD in the community are of great importance to improve the prognosis and decrease the burden of CKD. It's essential to establish a screening and monitoring system, strengthen standardized management and clinician training for improving the ability of CKD management in the community.

Key words: Chronic kidney disease, Community health services, Disease management, Health education

CLC Number: 

  • R692

Figure 1

Flow diagram of 374 498 patients in 79 community health centers CKD, chronic kidney disease."

Table 1

Baseline characteristics of high-risk and CKD patients in community health centers"

Items Total population(n=374 498) High-risk patients(n=264 514) CKD patients(n=19 299)
Male 159 320 (42.5) 120 242 (45.5) 8 925 (46.2)
Age/years 58±16 65±12 67±12
BMI/(kg/m2) 24 (22, 26) 24 (23, 27) 25 (23, 27)
Insurance 304 951 (81.4) 229 141 (86.6) 18 228 (94.5)
Diabetes 80 455 (21.5) 80 455 (30.4) 9 788 (50.7)
Hypertension 164 851 (44.0) 164 851 (62.3) 15 719 (81.4)
MI 64 (0) 64 (0) 12 (0.1)
CHD 114 662 (30.6) 114 662 (43.3) 13 101 (67.9)
HF 1 966 (0.5) 1 966 (0.7) 344 (1.8)
COPD 3 333 (0.9) 3 213 (1.2) 514 (2.7)
Cancer 4 606 (1.2) 4 606 (1.7) 470 (2.4)
Follow-up/years 1.9±1.6 2.3±1.5 3.4±1.4

Figure 2

Distribution of risk factor of comorbidity in high-risk CKD population in community CKD, chronic kidney disease; CHD, coronary heart disease; HT, hypertension; DM, diabetes mellitus."

Figure 3

Detection rate of CKD in high-risk CKD population in community CKD, chronic kidney disease; Non-CKD, high-risk patients without CKD; New CKD, CKD occurred after identified as a high-risk group; Old CKD, CKD has occurred when identified as a high-risk group."

Table 2

Evaluating of risk factors and complications of CKD patients  n (%) "

Items Total CKD patients (n=19 299) CKD patients diagnosed by ICD-10 (n=11 945)
Detection rate Control rate Detection rate Control rate
Blood glucose 5 372 (27.8) 3 240 (60.3) 2 012 (16.8) 1 253 (62.3)
Blood pressure 19 191 (99.4) 19 128 (99.7) 11 903 (99.6) 11 900 (100.0)
  SBP 19 191 (99.4) 18 720 (97.5) 11 903 (99.6) 11 787 (99.0)
  DBP 19 191 (99.4) 19 025 (99.1) 11 903 (99.6) 11 864 (99.7)
Hyperkalemia 7 719 (40.0) 154 (2.0) 2 850 (23.9) 81 (2.8)
1 Zhang L , Wang F , Wang L , et al. Prevalence of chronic kidney disease in China: A cross-sectional survey[J]. Lancet, 2012, 379 (9818): 815- 822.
doi: 10.1016/S0140-6736(12)60033-6
2 Zhang L , Long J , Jiang W , et al. Trends in chronic kidney disease in China[J]. N Engl J Med, 2016, 375 (9): 905- 906.
doi: 10.1056/NEJMc1602469
3 Coresh J , Selvin E , Stevens L A , et al. Prevalence of chronic kidney disease in the United States[J]. JAMA, 2007, 298 (17): 2038- 2047.
doi: 10.1001/jama.298.17.2038
4 北京统计局. 北京区域统计年鉴2021[M]. 北京: 中国统计出版社, 2021: 9- 12.
5 Levey AS , Stevens LA , Schmid CH , et al. A new equation to estimate glomerular filtration rate[J]. Ann Intern Med, 2009, 150 (9): 604- 612.
doi: 10.7326/0003-4819-150-9-200905050-00006
6 Shlipak MG , Tummalapalli SL , Boulware LE , et al. The case for early identification and intervention of chronic kidney disease: Conclusions from a kidney disease: Improving global outcomes (KDIGO) controversies conference[J]. Kidney Int, 2021, 99 (1): 34- 47.
doi: 10.1016/j.kint.2020.10.012
7 Kidney disease: Improving global outcomes (KDIGO) CKD work group . KDIGO 2012 clinical practice guideline for the evaluation and management of chronic kidney disease[J]. Kidney Int Suppl, 2013, 3 (1): 1- 150.
doi: 10.1038/kisup.2012.73
8 上海市肾内科临床质量控制中心专家组. 慢性肾脏病早期筛查, 诊断及防治指南(2022年版)[J]. 中华肾脏病杂志, 2022, 38 (5): 453- 464.
doi: 10.3760/cma.j.cn441217-20210819-00067
9 董婷, 李建中, 吴声, 等. 苏州社区老年人慢性肾脏病筛查及共病分析[J]. 中华老年医学杂志, 2021, 40 (12): 1583- 1588.
doi: 10.3760/cma.j.issn.0254-9026.2021.12.023
10 林雅慧, 刘玉红, 王宓, 等. 社区高危人群慢性肾脏病患病率及筛查策略研究[J]. 中国实用内科杂志, 2018, 38 (12): 1169- 1172.
11 Lv J , Ehteshami P , Sarnak MJ , et al. Effects of intensive blood pressure lowering on the progression of chronic kidney disease: A systematic review and meta-analysis[J]. CMAJ, 2013, 185 (11): 949- 957.
doi: 10.1503/cmaj.121468
12 Perkovic V , Heerspink HL , Chalmers J , et al. Intensive glucose control improves kidney outcomes in patients with type 2 diabetes[J]. Kidney Int, 2013, 83 (3): 517- 523.
doi: 10.1038/ki.2012.401
13 牛娜, 董建琴, 杜雪平. 北京市基层全科医生对慢性肾脏病的认知调查[J]. 中国全科学, 2017, 20 (10): 1267- 1270.
14 赵慧颖, 黄雯, 张国娟. 各级医院非肾脏病科医生对慢性肾脏病知晓率的调查分析[J]. 中国血液净化杂, 2017, 16 (2): 100- 103.
15 Rayner HC , Baharani J , Dasgupta I , et al. Does community-wide chronic kidney disease management improve patient outcomes?[J]. Nephrol Dial Transplant, 2014, 29 (3): 644- 649.
doi: 10.1093/ndt/gft486
16 蒙陆丹, 潘松球. 社区早期肾脏病筛查现状研究[J]. 中国社区医师, 2020, 36 (28): 7- 8.
doi: 10.3969/j.issn.1007-614x.2020.28.003
17 Conway N , Adamson KA , Cunningham SG , et al. Decision support for diabetes in Scotland: Implementation and evaluation of a clinical decision support system[J]. J Diabetes Sci Technol, 2018, 12 (2): 381- 388.
doi: 10.1177/1932296817729489
18 李小玲, 贾楠, 杨长贵, 等. 临床决策支持系统辅助社区高血压患者管理的效果研究[J]. 中国循环杂志, 2019, 34 (5): 481- 485.
doi: 10.3969/j.issn.1000-3614.2019.05.011
[1] Lin MA,Jing-yi WU,Shuang-cheng LI,Peng-fei LI,Lu-xia ZHANG. Effect of modification of antihypertensive medications on the association of nitrogen dioxide long-term exposure and chronic kidney disease [J]. Journal of Peking University (Health Sciences), 2022, 54(5): 1047-1055.
[2] Xiao-wei XIE,Fen LI,Guang-hui LING,Xi XIE,Su-qing XU,Yi-yue CHEN. Development and clinical application of the health education knowledge assessment questionnaire for gout [J]. Journal of Peking University (Health Sciences), 2022, 54(4): 699-704.
[3] YANG Chao, WANG Jin-wei, YANG Yao-zheng, BAI Kun-hao, GAO Bi-xia, ZHAO Ming-hui, ZHANG Lu-xia, WU Shou-ling， WANG Fang. Impact of anemia and chronic kidney disease on the risk of cardiovascular disease and all-cause mortality among diabetic patients [J]. Journal of Peking University(Health Sciences), 2018, 50(3): 495-500.
[4] LIN Hong-bo, CHEN Yi, SHEN Peng, LI Xiao-yong,SI Ya-qin, ZHANG Du-dan, TANG Xun, GAO Pei. Incidence and risk factors of chronic kidney disease in community-based patients with diabetes [J]. Journal of Peking University(Health Sciences), 2018, 50(3): 416-421.
[5] SUN Xin-ying;GUO Yan;SUN Jing . Validation of the integration of health belief model and planned behavior theory [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 129-134.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] . [J]. Journal of Peking University(Health Sciences), 2007, 39(5): 507 -510 .
[2] . [J]. Journal of Peking University(Health Sciences), 2000, 32(4): 300 .
[3] . [J]. Journal of Peking University(Health Sciences), 2008, 40(2): 146 -150 .
[4] . [J]. Journal of Peking University(Health Sciences), 2008, 40(4): 369 -373 .
[5] . [J]. Journal of Peking University(Health Sciences), 2010, 42(2): 126 -130 .
[6] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 225 -328 .
[7] . [J]. Journal of Peking University(Health Sciences), 2001, 33(2): 181 -182 .
[8] . [J]. Journal of Peking University(Health Sciences), 2007, 39(6): 663 -665 .
[9] . [J]. Journal of Peking University(Health Sciences), 2008, 40(1): 39 -42 .
[10] . [J]. Journal of Peking University(Health Sciences), 2010, 42(6): 739 -745 .
Copyright © Journal of Peking University (Health Sciences), All Rights Reserved.
Powered by Beijing Magtech Co. Ltd