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US Renal Data System 2020 Annual Data Report: Epidemiology of Kidney Disease in the United States.《美国肾脏数据系统2020年年报:美国肾脏疾病流行病学》
Am J Kidney Dis. 2021 Apr;77(4 Suppl 1):A7-A8. doi: 10.1053/j.ajkd.2021.01.002.
2
The Kidney Failure Risk Equation for prediction of end stage renal disease in UK primary care: An external validation and clinical impact projection cohort study.用于预测英国初级保健中终末期肾病的肾衰竭风险方程:外部验证和临床影响预测队列研究。
PLoS Med. 2019 Nov 6;16(11):e1002955. doi: 10.1371/journal.pmed.1002955. eCollection 2019 Nov.
3
Development and Validation of a Pragmatic Electronic Phenotype for CKD.开发和验证用于 CKD 的实用电子表型。
Clin J Am Soc Nephrol. 2019 Sep 6;14(9):1306-1314. doi: 10.2215/CJN.00360119. Epub 2019 Aug 12.
4
Timely Referral to Outpatient Nephrology Care Slows Progression and Reduces Treatment Costs of Chronic Kidney Diseases.及时转诊至门诊肾病护理可减缓慢性肾脏病的进展并降低治疗成本。
Kidney Int Rep. 2016 Oct 14;2(2):142-151. doi: 10.1016/j.ekir.2016.09.062. eCollection 2017 Mar.
5
Risk-Based Triage for Nephrology Referrals Using the Kidney Failure Risk Equation.使用肾衰竭风险方程进行肾脏科转诊的基于风险的分诊
Can J Kidney Health Dis. 2017 Aug 9;4:2054358117722782. doi: 10.1177/2054358117722782. eCollection 2017.
6
Evaluating the feasibility of the KDIGO CKD referral recommendations.评估改善全球肾脏病预后组织(KDIGO)慢性肾脏病转诊建议的可行性。
BMC Nephrol. 2017 Jul 7;18(1):223. doi: 10.1186/s12882-017-0646-y.
7
Estimating time to ESRD using kidney failure risk equations: results from the African American Study of Kidney Disease and Hypertension (AASK).使用肾衰竭风险方程估算终末期肾病发生时间:非裔美国人肾脏疾病与高血压研究(AASK)的结果
Am J Kidney Dis. 2015 Mar;65(3):394-402. doi: 10.1053/j.ajkd.2014.07.026. Epub 2014 Oct 14.
8
A simple tool to predict end-stage renal disease within 1 year in elderly adults with advanced chronic kidney disease.一种简单的工具,可预测患有晚期慢性肾脏病的老年患者在 1 年内进入终末期肾病。
J Am Geriatr Soc. 2013 May;61(5):762-8. doi: 10.1111/jgs.12223. Epub 2013 Apr 25.
9
A predictive model for progression of chronic kidney disease to kidney failure.慢性肾脏病进展为肾衰竭的预测模型。
JAMA. 2011 Apr 20;305(15):1553-9. doi: 10.1001/jama.2011.451. Epub 2011 Apr 11.
10
A new equation to estimate glomerular filtration rate.一种估算肾小球滤过率的新公式。
Ann Intern Med. 2009 May 5;150(9):604-12. doi: 10.7326/0003-4819-150-9-200905050-00006.

基于实验室值、肾衰竭风险或两者的肾脏病转诊:使用退伍军人事务部健康系统数据的研究。

Nephrology Referral Based on Laboratory Values, Kidney Failure Risk, or Both: A Study Using Veterans Affairs Health System Data.

机构信息

Veterans Affairs Palo Alto Health Care System, Palo Alto, California; Department of Medicine, Division of Nephrology, School of Medicine, Stanford University, Stanford, California; Center for Primary Care and Outcomes Research, Stanford University, Stanford, California.

Department of Medicine, Division of Nephrology, School of Medicine, Stanford University, Stanford, California.

出版信息

Am J Kidney Dis. 2022 Mar;79(3):347-353. doi: 10.1053/j.ajkd.2021.06.028. Epub 2021 Aug 24.

DOI:10.1053/j.ajkd.2021.06.028
PMID:34450193
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9973036/
Abstract

RATIONALE & OBJECTIVE: Current guidelines for nephrology referral are based on laboratory criteria. We sought to evaluate whether nephrology referral patterns reflect current clinical practice guidelines and to estimate the change in referral volume if they were based on the estimated risk of kidney failure.

STUDY DESIGN

Observational cohort.

SETTING & PARTICIPANTS: Retrospective study of 399,644 veterans with chronic kidney disease (October 1, 2015 through September 30, 2016).

EXPOSURE

Laboratory referral criteria based on Veterans Affairs/Department of Defense guidelines, categories of predicted risk for kidney failure using the Kidney Failure Risk Equation, and the combination of laboratory referral criteria and predicted risk.

OUTCOME

Number of patients identified for referral.

ANALYTICAL APPROACH

We evaluated the number of patients who were referred and their predicted 2-year risk for kidney failure. For each exposure, we estimated the number of patients who would be identified for referral.

RESULTS

There were 66,276 patients who met laboratory indications for referral. Among these patients, 11,752 (17.7%) were referred to nephrology in the following year. The median 2-year predicted risk of kidney failure was 1.5% (interquartile range, 0.3%-4.7%) among all patients meeting the laboratory referral criteria. If referrals were restricted to patients with a predicted risk of ≥1% in addition to laboratory indications, the potential referral volume would be reduced from 66,276 to 38,229 patients. If referrals were based on predicted risk alone, a 2-year risk threshold of 1% or higher would identify a similar number of patients (72,948) as laboratory-based criteria with median predicted risk of 2.3% (interquartile range, 1.4%-4.6%).

LIMITATIONS

Missing proteinuria measurements.

CONCLUSIONS

The current laboratory-based guidelines for nephrology referral identify patients who are, on average, at low risk for progression, most of whom are not referred. As an alternative, referral based on a 2-year kidney failure risk exceeding 1% would identify a similar number of patients but with a higher median risk of kidney failure.

摘要

背景与目的

目前肾脏病学转诊的指南基于实验室标准。我们试图评估肾脏病学转诊模式是否反映了当前的临床实践指南,并估计如果基于肾功能衰竭的估计风险,转诊量会发生怎样的变化。

研究设计

观察性队列研究。

设置与参与者

2015 年 10 月 1 日至 2016 年 9 月 30 日期间,399644 名患有慢性肾脏病的退伍军人的回顾性研究。

暴露

基于退伍军人事务部/国防部指南的实验室转诊标准、使用肾脏病衰竭风险方程预测的肾功能衰竭风险类别,以及实验室转诊标准和预测风险的组合。

结局

确定转诊的患者数量。

分析方法

我们评估了被转诊的患者数量及其 2 年内肾功能衰竭的预测风险。对于每种暴露,我们估计了被识别出需要转诊的患者数量。

结果

有 66276 名患者符合实验室转诊指征。在这些患者中,有 11752 名(17.7%)在随后的一年中被转诊到肾脏病科。所有符合实验室转诊标准的患者中,中位数 2 年肾功能衰竭预测风险为 1.5%(四分位距,0.3%4.7%)。如果将转诊限制在除实验室指征外,预测风险≥1%的患者中,潜在的转诊量将从 66276 人减少到 38229 人。如果仅根据预测风险进行转诊,2 年风险阈值为 1%或更高,将与基于实验室标准的标准识别出相同数量的患者(72948 人),中位预测风险为 2.3%(四分位距,1.4%4.6%)。

局限性

蛋白尿测量值缺失。

结论

目前基于实验室的肾脏病学转诊指南确定了处于进展低风险的患者,其中大多数未被转诊。作为替代方法,基于 2 年内肾功能衰竭风险超过 1%的转诊标准将识别出相似数量的患者,但肾功能衰竭的中位风险更高。