Abstract
BackgroundThere is concern that not all cases of chronic kidney disease (CKD) are known to general practitioners, leading to an underestimate of its true prevalence. We carried out this study to develop a model to predict the prevalence of CKD using a large English primary care dataset which includes previously undiagnosed cases of CKD.MethodsCross-sectional analysis of data from the Quality Improvement in CKD trial, a representative sample of 743 935 adults in England aged 18 and over. We created multivariable logistic regression models to identify important predictive factors.ResultsA prevalence of 6.76% was recorded in our sample, compared to a national prevalence of 4.3%. Increasing age, female gender and cardiovascular disease were associated with a significantly increased prevalence of CKD (p < 0.001 for all). Age had a complex association with CKD. Cardiovascular disease was a stronger predictive factor in younger than in older patients. For example, hypertension has an odds ratio of 2.02 amongst patients above average and an odds ratio of 3.91 amongst patients below average age.ConclusionIn England many cases of CKD remain undiagnosed. It is possible to use the results of this study to identify areas with high levels of undiagnosed CKD and groups at particular risk of having CKD.Trial registrationCurrent Controlled Trials ISRCTN: ISRCTN56023731. Note that this study reports the results of a cross-sectional analysis of data from this trial.
Highlights
There is concern that not all cases of chronic kidney disease (CKD) are known to general practitioners, leading to an underestimate of its true prevalence
The primary aim of the Quality improvement in chronic kidney disease (QICKD) trial is to compare quality improvement interventions aimed at lowering systolic blood pressure in patients with CKD in primary care; ethical approval has been given for secondary analyses of the data
The Pay for performance (P4P) indicator in England gives a prevalence of CKD of 4.3% [4], we reported a prevalence of 6.76%, suggesting that over a third of people with CKD are not known to their general practices (GP)
Summary
There is concern that not all cases of chronic kidney disease (CKD) are known to general practitioners, leading to an underestimate of its true prevalence. We carried out this study to develop a model to predict the prevalence of CKD using a large English primary care dataset which includes previously undiagnosed cases of CKD. Chronic Kidney Disease (CKD) is largely asymptomatic [1]. Within England, CKD is included in a national payfor-performance (P4P) scheme for chronic disease. There are existing models that may be used to estimate the prevalence of CKD for an area [5,6,7,8]. These models all have limitations: none of them use data from English patients and none check for interactions between variables. We used routinely collected data and a novel method to identify patients with CKD that has not been identified under the P4P scheme [9]
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