Suppr超能文献

透析前慢性肾脏病的患病率、社会人口学特征及合并健康状况:来自曼尼托巴慢性肾脏病队列的结果

Prevalence, socio-demographic characteristics, and comorbid health conditions in pre-dialysis chronic kidney disease: results from the Manitoba chronic kidney disease cohort.

作者信息

Chartier Mariette J, Tangri Navdeep, Komenda Paul, Walld Randy, Koseva Ina, Burchill Charles, McGowan Kari-Lynne, Dart Allison

机构信息

Manitoba Centre for Health Policy, Department of Community Health Sciences, University of Manitoba, Winnipeg, Canada.

Chronic Disease Innovation Centre, Seven Oaks General Hospital, Department of Medicine and Community Health Sciences, Max Rady College of Medicine, University of Manitoba, Winnipeg, Canada.

出版信息

BMC Nephrol. 2018 Oct 10;19(1):255. doi: 10.1186/s12882-018-1058-3.

Abstract

BACKGROUND

Chronic Kidney Disease (CKD) is common and its prevalence has increased steadily over several decades. Monitoring of rates and severity of CKD across populations is critical for policy development and resource planning. Administrative health data alone has insufficient sensitivity for this purpose, therefore utilizing population level laboratory data and novel methodology is required for population-based surveillance. The aims of this study include a) develop the Manitoba CKD Cohort, b) estimate CKD prevalence, c) identify individuals at high risk of progression to kidney failure and d) determine rates of comorbid health conditions.

METHODS

Administrative health and laboratory data from April 1996 to March 2012 were linked from the data repository at the Manitoba Centre for Health Policy. Prevalence was estimated using three methods: a) all CKD cases in administrative and laboratory databases; b) all CKD cases captured only through the laboratory data; c) and the capture-recapture method. Patients were stratified by risk by estimated Glomerular Filtration Rate (eGFR) and albuminuria based on Kidney Disease Improving Global Outcomes (KDIGO) criteria. For comorbid health conditions, the counts were modelled using a Generalized Linear Model (GLM).

RESULTS

The Manitoba CKD Cohort consisted of 55,876 people with CKD. Of these, 18,342 were identified using administrative health data, 27,393 with laboratory data, and 10,141 people were identified in both databases. The CKD prevalence was 5.6% using the standard definition, 10.6% using only people captured by the laboratory data and 10.6% using the capture-recapture method. Of the identified cases, 46% were at high risk of progression to end-stage kidney disease (ESKD), 41% were at low risk and 13% were not classified, due to unavailable laboratory data. High risk cases had a higher burden of comorbid conditions.

CONCLUSION

This study reports a novel methodology for population based CKD surveillance utilizing a combination of administrative health and laboratory data. High rates of CKD at risk of progression to ESKD have been identified with this approach. Given the high rates of comorbidity and associated healthcare costs, these data can be used to develop a targeted and comprehensive public health surveillance strategy that encompass a range of interrelated chronic diseases.

摘要

背景

慢性肾脏病(CKD)很常见,其患病率在几十年间稳步上升。监测不同人群中CKD的发病率和严重程度对于政策制定和资源规划至关重要。仅行政健康数据在此目的上敏感性不足,因此基于人群的监测需要利用人群层面的实验室数据和新方法。本研究的目的包括:a)建立曼尼托巴CKD队列;b)估计CKD患病率;c)识别有进展至肾衰竭高风险的个体;d)确定合并健康状况的发生率。

方法

将1996年4月至2012年3月的行政健康和实验室数据从曼尼托巴健康政策中心的数据存储库中进行关联。患病率采用三种方法估计:a)行政和实验室数据库中的所有CKD病例;b)仅通过实验室数据捕获的所有CKD病例;c)捕获-再捕获法。根据改善全球肾脏病预后(KDIGO)标准,患者按估计的肾小球滤过率(eGFR)和蛋白尿进行风险分层。对于合并健康状况,使用广义线性模型(GLM)对计数进行建模。

结果

曼尼托巴CKD队列由55,876名CKD患者组成。其中,通过行政健康数据识别出18,342人,通过实验室数据识别出27,393人,两个数据库中均识别出10,141人。使用标准定义时CKD患病率为5.6%,仅使用实验室数据捕获的人群时为10.6%,使用捕获-再捕获法时为10.6%。在已识别的病例中,46%有进展至终末期肾病(ESKD)的高风险,41%为低风险,13%因实验室数据不可用未分类。高风险病例合并症负担更高。

结论

本研究报告了一种利用行政健康和实验室数据相结合的基于人群的CKD监测新方法。通过这种方法已识别出有进展至ESKD风险的高CKD发病率。鉴于高合并症发生率和相关医疗费用,这些数据可用于制定涵盖一系列相关慢性病的有针对性且全面的公共卫生监测策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2543/6180583/7f130e2e0484/12882_2018_1058_Fig1_HTML.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验