Department of Medicine, Division of Nephrology, The Ottawa Hospital, Ottawa, Canada.
Department of Medicine, Division of Endocrinology, University of Ottawa, Ottawa, Canada.
Syst Rev. 2019 Jun 22;8(1):147. doi: 10.1186/s13643-019-1052-2.
Obesity is increasing globally. Chronic kidney disease (CKD) is strongly associated with obesity. Kidney function is commonly estimated with equations using creatinine (such as CKD-EPI equation) which is a product of muscle metabolism. Decisions about categorizing CKD, planning modality of renal replacement therapies, and adjusting dosages of medications excreted by the kidneys are done using these equations. However, it is not well appreciated that creatinine-based equations may not accurately estimate kidney function in obese individuals. We plan a systematic review of diagnostic studies which will compare estimating equations to actual measured kidney function.
We will systematically search electronic bibliographic databases including MEDLINE, EMBASE, and the Cochrane Library with no restrictions on language or specific dates. The search terms will be adapted for the different databases using a combination of Medical Subject Heading and relevant keywords contained in titles and abstracts. Our preliminary search strategy using Cochrane, MEDLINE, and EMBASE databases have identified 190, 1246, and 1660 citations, respectively. For all studies selected, we will extract information on general study characteristics, study participant (age, sex, ethnicity, weight, height, BMI, BSA), type and protocol of reference standard utilized, the index test studied, the methodology of measurement of index test, categories of GFR, the proportion of eGFR within 10, 20, 30, 40, and 50% of measured GFR, and bias between eGFR and measured GFR. If the quality of methods and risk of bias are adequate, we will perform a meta-analysis. We will assess the heterogeneity using the χ and the I statistics to examine whether the estimates from studies included could be pooled. Sensitivity and multivariate meta-regression analyses will be performed to assess the effects of clinical factors and socio-demographic characteristics reported in included studies on the meta-analytic estimates. All analysis will be performed using the Comprehensive Meta-analysis software.
This systematic review might help to inform clinicians on the best equation to use in patients with obesity and CKD for staging of CKD and for medication dosing. If no equation is deemed suitable, this review will form a basis for future studies of GFR in obese individuals.
PROSPERO CRD42018104345.
肥胖在全球范围内呈上升趋势。慢性肾脏病(CKD)与肥胖密切相关。通常使用基于肌酐的公式(如 CKD-EPI 公式)来估算肾功能,肌酐是肌肉代谢的产物。CKD 的分类、肾脏替代治疗方式的规划以及通过肾脏排泄的药物剂量的调整都是基于这些公式进行的。然而,人们并没有充分认识到,基于肌酐的公式可能无法准确估算肥胖个体的肾功能。我们计划对诊断研究进行系统评价,将比较估算公式和实际测量的肾功能。
我们将系统地检索电子文献数据库,包括 MEDLINE、EMBASE 和 Cochrane 图书馆,不限制语言或特定日期。检索词将根据不同的数据库进行调整,使用 Medical Subject Heading 和标题及摘要中包含的相关关键词的组合。我们使用 Cochrane、MEDLINE 和 EMBASE 数据库进行的初步检索策略分别确定了 190、1246 和 1660 条引文。对于所有入选的研究,我们将提取研究的一般特征、研究参与者(年龄、性别、种族、体重、身高、BMI、BSA)、参考标准的类型和方案、所研究的指标检验、指标检验的测量方法、肾小球滤过率(GFR)的类别、eGFR 在实测 GFR 的 10%、20%、30%、40%和 50%范围内的比例以及 eGFR 与实测 GFR 之间的偏差等信息。如果方法的质量和偏倚风险足够,我们将进行荟萃分析。我们将使用 χ 2 和 I 2 统计量评估异质性,以检查纳入研究的估计值是否可以合并。将进行敏感性分析和多元荟萃回归分析,以评估纳入研究中报告的临床因素和社会人口统计学特征对荟萃分析估计值的影响。所有分析都将使用 Comprehensive Meta-analysis 软件进行。
这项系统评价可能有助于向临床医生提供在肥胖和 CKD 患者中用于 CKD 分期和药物剂量调整的最佳公式。如果没有合适的公式,本综述将为肥胖个体 GFR 的未来研究奠定基础。
PROSPERO CRD42018104345。