Data Collection and Variables
Two medical students performed the chart reviews and recorded the following variables when available: age, weight, sex, serum creatinine level, hemoglobin A1C (Hb A1C) level, proteinuria on urinalysis testing, blood pressure, total serum cholesterol, and whether a microalbuminuria test was recommended and, if performed, the results. Race was not included because the patient charts do not consistently note the patient’s race. Also, because care is often shared between attending and resident physicians, we did not include the physician training level as a variable in our analysis.
To determine whether patients were on ACEI or ARB therapy, we searched the electronic medical record database for all medications in the previous 5 years. The medical record used during this period required all prescriptions to be entered before a printed version could be generated, so we could determine if a drug had been used in the past. Although this system overlooked prescriptions that might be called in to a pharmacy and not documented in the record, it captured every prescription written by a physician in the practice. When an ACEI or ARB was used, we examined whether the medication had been started before screening was indicated or after a microalbuminuria test was performed.
We searched the laboratory section of the electronic medical record and also the hospital patient database to determine if the hospital laboratory had performed the test. Searching the hospital database would indicate if the test was performed by any other clinician (eg, an endocrinologist) or in another setting (eg, inpatient) in the university medical center. Whether a microalbuminuria test was recommended was recorded, with the returned value (if available) and the date the test was recommended. We considered values greater than 20 mg per L positive for microalbuminuria. Protein-uria tests were considered positive if they returned a 1+ protein or greater result. We also recorded whether the subject was on an ACEI or ARB therapy, and if so at what date it had been prescribed.
To minimize inter-rater variability, the 2 medical students each reviewed a pilot sample of the same 20 charts. Data were compared and differences between the auditors were reviewed to standardize definitions of data elements. After standardization, sets of 10 different charts were selected, and the process was repeated until the data from 40 consecutive charts were recorded identically by both students.
Analysis
When comparing mean values, we performed a Student t test to determine statistical significance. A chi-square test was done to determine statistical significance when comparing proportions. A P value of <.05 was determined to be statistically significant.
Results
Of the 278 eligible patients, 44 (16%) had a urinalysis with 1+ or greater protein result at baseline; 18 (41%) of these were already taking an ACEI or ARB drug. In patients without previous evidence of proteinuria, 51 (18%) patients were using ACEI or ARB therapy. This left 183 patients (66%) who had no evidence of renal disease and who were not using ACEI or ARB therapy and therefore were the prime candidates for microalbuminuria screening Figure 1.
When we examined the demographics and clinical variables of these 3 groups, we found that patients with proteinuria or who were already using drug treatment were older and had higher systolic and diastolic blood pressures than those who were not. Unexpectedly, we also found that patients with existing proteinuria had lower Hb A1C levels than patients in the other 2 categories.
Of these prime candidates for screening, only 31 (17%) received at least 1 microalbuminuria test between 1995 and 1999. The rate of screening in this group was no different from those who were taking an ACEI or ARB drug (16%, P=.83) or already had gross proteinuria (18%, P=.84).
When we examined the patients who were most likely to benefit from screening and looked at demographic or clinical factors that might influence whether a screening test was performed, we found that patients who received microalbuminuria testing were very similar to those who did not. The only difference we found was that patients who received screening had lower systolic blood pressures than those who were not screened. Weight, age, Hb A1C levels, and cholesterol levels were not predictors of being screened for microalbuminuria Table 2.
Because of the low rates of microalbuminuria screening for patients who were eligible and the relatively frequent use of screening in patients who already had evidence of gross proteinuria, we were interested in what clinicians did when a microalbuminuria test result was positive. In the group without evidence of proteinuria and not using ACEI or ARB therapy, 10 of the 31 patients who received screening for microalbuminuria tested positive. However, only 4 (40%) were placed on ACE inhibitor or ARB therapy.