The assessment of kidney function by general practitioners in Australian patients with type 2 diabetes (NEFRON‐2)

Abstract

Objective: To examine factors influencing the identification of kidney impairment in patients with type 2 diabetes in Australian primary care. Design, setting and participants: 348 general practitioner investigators were asked to estimate kidney function and its severity in 10–15 consecutively presenting patients with type 2 diabetes (n = 3893). They were then asked, for each patient, whether they routinely estimated kidney function. No instruction was provided on how kidney function should be estimated or categorised. Data were collected between April and September 2005. Main outcome measures: Kidney function estimated by the Cockcroft–Gault equation using clinical and laboratory data provided by the GP; estimates of kidney function made by the GP. Results: In 24% of the patients with type 2 diabetes, their GP routinely estimated kidney function. However, few of these patients had impaired kidney function or risk factors for kidney disease. There was a good statistical correlation between the estimates made by GPs and the data‐derived estimates (R2 = 0.72). GPs identified patients with data‐derived estimates of kidney function < 60 mL/min in over 83% of cases, with a specificity of 90%. Impaired kidney function was reported by GPs in 34.4% of men and 36.4% of women. These figures were discordant with function categorisation using both GP estimates and data‐derived values, overlapping in half of the patients. Despite GPs’ ability to assess creatinine clearance, “raw” (unstandardised) serum creatinine levels inappropriately influenced the perception of impairment of kidney function. Conclusion: GPs can accurately assess kidney function, without reporting of estimated glomerular filtration rate (eGFR). However, even in patients at increased risk of chronic kidney disease, routine estimates are seldom made. Our findings underline the value of the recent initiative recommending automatic reporting of eGFR in Australia.

The management of diabetes in indigenous Australians from primary care

“…Data and informed consent were obtained from 3893 adults with type 2 diabetes. The clinical characteristics of this cohort have been previously published[ 6 , 7 ], and are similar to that observed in other Australian studies of patients with type 2 diabetes. Briefly, patient had a mean age of 66 years and a median duration of diagnosed diabetes of six years.…”

“…The recruitment of investigators and sample selection are described in detail elsewhere [ 6 , 7 ] and are briefly summarised below. Expressions of interest (EOIs) were invited via a mailing from all (18810) registered GPs across all jurisdictions in Australia in February 2005.…”

“…In the event of investigator withdrawal from the study, the geographically closest, but not previously selected, EOI was approached as a potential replacement. The final investigators recruited had a mean age, gender distribution, professional qualifications and number of sessions per week that was not significantly different to that recorded for the all registered general practitioners in Australia [ 6 , 7 ].…”

Nonalbuminuric Renal Impairment in Type 2 Diabetic Patients and in the General Population (National Evaluation of the Frequency of Renal Impairment cO-existing with NIDDM [NEFRON] 11)

“…Investigator selection and its representation of practitioners in Australia is described elsewhere (3,8). In brief, 500 randomly selected investigators were requested to provide data on 10–15 consecutively presenting adult patients with established type 2 diabetes.…”

Assessment and management of hypertension in patients with type 2 diabetes

“…Investigator selection and its representation of general practitioners in Australia is described in detail elsewhere. 3,4 Briefly, 500 randomly selected investigators were requested to provide clinical data on 10-15 consecutively presenting adult patients with established type 2 diabetes attending the GPs practice between April and September 2005 (approximately 2 years after the DEMAND study), irrespective of the reason for the visit. This dataset also captured demographic information, including age, sex, ethnicity, history of diabetic complications, medication usage, smoking and relevant family history, together with details of physical examination and results from the most recent blood tests and laboratory urinalysis.…”