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帮助全科医生评估肾功能下降患者的肾脏轨迹图表:一项随机案例研究。

Kidney trajectory charts to assist general practitioners in the assessment of patients with reduced kidney function: a randomised vignette study.

机构信息

Institute for Evidence-Based Healthcare, Bond University, Robina, Queensland, Australia

School of Rural Medicine, University of New England, Armidale, New South Wales, Australia.

出版信息

BMJ Evid Based Med. 2022 Oct;27(5):288-295. doi: 10.1136/bmjebm-2021-111767. Epub 2021 Dec 21.

DOI:10.1136/bmjebm-2021-111767
PMID:34933932
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9510425/
Abstract

OBJECTIVE

To investigate the decisional impact of an age-based chart of kidney function decline to support general practitioners (GPs) to appropriately interpret estimated glomerular filtration rate (eGFR) and identify patients with a clinically relevant kidney problem.

DESIGN AND SETTING

Randomised vignette study PARTICIPANTS: 372 Australian GPs from August 2018 to November 2018.

INTERVENTION

GPs were given two patient case scenarios: (1) an older woman with reduced but stable renal function and (2) a younger Aboriginal man with declining kidney function still in the normal range. One group was given an age-based chart of kidney function to assist their assessment of the patient (initial chart group); the second group was asked to assess the patients without the chart, and then again using the chart (delayed chart group).

MAIN OUTCOME MEASURES

GPs' assessment of the likelihood-on a Likert scale-that the patients had chronic kidney disease (CKD) according to the usual definition or a clinical problem with their kidneys.

RESULTS

Prior to viewing the age-based chart GPs were evenly distributed as to whether they thought case 1-the older woman-had CKD or a clinically relevant kidney problem. GPs who had initial access to the chart were less likely to think that the older woman had CKD, and less likely to think she had a clinically relevant problem with her kidneys than GPs who had not viewed the chart. After subsequently viewing the chart, 14% of GPs in the delayed chart group changed their opinion, to indicate she was unlikely to have a clinically relevant problem with her kidneys.Prior to viewing the chart, the majority of GPs (66%) thought case 2-the younger man-did not have CKD, and were evenly distributed as to whether they thought he had a clinically relevant kidney problem. In contrast, GPs who had initial access to the chart were more likely to think he had CKD and the majority (72%) thought he had a clinically relevant kidney problem. After subsequently viewing the chart, 37% of GPs in the delayed chart group changed their opinion to indicate he likely had a clinically relevant problem with his kidneys.

CONCLUSIONS

Use of the chart changed GPs interpretation of eGFR, with increased recognition of the younger male patient's clinically relevant kidney problem, and increased numbers classifying the older female patient's kidney function as normal for her age. This study has shown the potential of an age-based kidney function chart to reduce both overdiagnosis and underdiagnosis.

摘要

目的

探讨基于年龄的肾功能下降图表对支持全科医生(GP)适当解读估算肾小球滤过率(eGFR)和识别有临床相关肾脏问题的患者的决策影响。

设计和设置

2018 年 8 月至 11 月,对澳大利亚的 372 名全科医生进行随机案例研究。

参与者

澳大利亚的 372 名全科医生。

干预措施

为两组患者提供两种病例情况:(1)肾功能减退但稳定的老年女性,(2)肾功能正常但仍在下降的年轻原住民男性。一组使用基于年龄的肾功能图表来协助评估患者(初始图表组);另一组被要求在没有图表的情况下评估患者,然后再次使用图表(延迟图表组)。

主要观察指标

GP 根据常用定义或肾脏临床问题,对患者患有慢性肾脏病(CKD)的可能性(用李克特量表评估)。

结果

在查看基于年龄的图表之前,对于案例 1(老年女性)是否患有 CKD 或肾脏有临床相关问题,GP 的看法大致相同。与未查看图表的 GP 相比,先查看图表的 GP 不太可能认为老年女性患有 CKD,也不太可能认为她的肾脏有临床相关问题。在随后查看图表后,延迟图表组的 14%的 GP 改变了他们的意见,认为她不太可能有肾脏的临床相关问题。在查看图表之前,大多数 GP(66%)认为案例 2(年轻男性)没有 CKD,并且在是否认为他有肾脏临床相关问题上意见分歧。相比之下,先查看图表的 GP 更有可能认为他患有 CKD,大多数(72%)认为他有肾脏临床相关问题。在随后查看图表后,延迟图表组的 37%的 GP 改变了他们的意见,认为他可能有肾脏的临床相关问题。

结论

图表的使用改变了 GP 对 eGFR 的解读,增加了对年轻男性患者肾脏临床相关问题的认识,同时增加了将老年女性患者的肾功能归类为与其年龄相关的正常功能的数量。本研究表明,基于年龄的肾功能图表具有减少过度诊断和漏诊的潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/ef41cb100b58/bmjebm-2021-111767f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/4c5fa9e528c9/bmjebm-2021-111767f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/bbcfd1fd8d10/bmjebm-2021-111767f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/e81099306b2c/bmjebm-2021-111767f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/c327fe815cf4/bmjebm-2021-111767f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/ef41cb100b58/bmjebm-2021-111767f05.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/4c5fa9e528c9/bmjebm-2021-111767f01.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/bbcfd1fd8d10/bmjebm-2021-111767f02.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/e81099306b2c/bmjebm-2021-111767f03.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/c327fe815cf4/bmjebm-2021-111767f04.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/281f/9510425/ef41cb100b58/bmjebm-2021-111767f05.jpg

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