ABSTRACT
Background
Patients with type 2 diabetes and macroalbuminuria generally experience progressive glomerular filtration rate (GFR) decline despite angiotensin-converting enzyme inhibition (ACEI) and blood pressure (BP) control but this therapy generally stabilizes GFR in those without macroalbuminuria. Cigarette smoking exacerbates GFR decline in patients with type 2 diabetes and macroalbuminuria despite ACEI and BP control; whether this therapy prevents nephropathy progression in nonmacroalbuminuric type 2 diabetic smokers is unknown.
Methods
We determined the course of urine excretion of indices of renal injury that distinguished patients with type 2 diabetes with and without macroalbuminuria but with normal plasma creatinine who were prospectively followed 6 months while receiving ACEI and BP control. We compared this course in nonsmokers and smokers with normo-, micro-, and macroalbuminuria (n = 157) and in response to smoking cessation in a separate cohort (n = 80) with microalbuminuria.
Results
Urine excretion of transforming growth factor β-1 (UTGFβV) increased in macroalbuminuric but not in nonmacroalbuminuric nonsmokers and UTGFβV rate was higher in smokers than nonsmokers within each albuminuria group. In the separate microalbuminuric cohort, the rate of UTGFβV change for quitting smokers was not different from nonsmokers (0.093 versus −0.123 ng/g of creatine/week, P = not significant) but that for nonquitting smokers (0.970) was higher than nonsmokers (P = 0.017).
Conclusions
Patients with type 2 diabetes who are at high risk compared with low risk for nephropathy progression have progressive renal injury as measured by increasing UTGFβV. Cigarette smoking exacerbates renal injury in type 2 diabetes despite BP control and ACEI, but its cessation in those with microalbuminuria ameliorates the progressive renal injury caused by continued smoking.
KEY INDEXING TERMS
The nephropathy of type 2 diabetes is the leading cause of end-stage renal disease (ESRD) in the United States
1.
but fortunately develops in only a minority of patients with diabetics. Before glomerular filtration rate (GFR) declines, diabetics who develop renal failure experience a progressive increase in urine albumin excretion (UAE) from normal through microalbuminuria to macroalbuminuria.2.
This indolent course before GFR declines provides the opportunity for preventive therapy in diabetics at increased renal failure risk. Type 2 diabetics with early nephropathy indicated by microalbuminuria are at increased renal failure risk,- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
2.
, - Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
3.
, 4.
, 5.
but blood pressure (BP) control, including angiotensin-converting enzyme inhibition (ACEI), generally prevents progression to more advanced nephropathy.3.
, 5.
, 6.
By contrast, BP control and ACEI generally slow but do not stop progression toward ESRD of more advanced type 2 diabetic nephropathy indicated by macroalbuminuria.3.
, 4.
, 7.
Consequently, current renoprotection therapy most effectively prevents renal failure caused by type 2 diabetic nephropathy when instituted before macroalbuminuria ensues, making patients with type 2 diabetes and microalbuminuria an important target group in preventing ESRD.Cigarette smoking (CS) is associated with nephropathy progression in patients with type 2 diabetes and macroalbuminuria
5.
, 6.
despite conventional renoprotection therapy, such as BP control and ACEI.6.
, 7.
Although CS is a predictor of nephropathy progression in diabetes,6.
its predictive power is interrelated with and not independent of UAE. Specifically, UAE but not CS independently predicts progression of nephropathy in type 2 diabetes and its predictive power seems to be mediated through increased UAE.7.
Because CS is associated with increased UAE in diabetes6.
, 7.
, 8.
, 9.
, 10.
, 11.
, 12.
despite BP control and ACEI,6.
, 7.
CS in type 2 diabetes might convert early to more advanced nephropathy, indicated by progression from microalbuminuria to macroalbuminuria, as suggested in a retrospective analysis,13.
and might do so despite BP control and ACEI. We determined a pattern of urine excretion of indices of renal injury that was associated with progressive compared with nonprogressive nephropathy in patients with type 2 diabetes undergoing BP control and ACEI. We hypothesized that CS exacerbates and its cessation ameliorates this pattern in patients with type 2 diabetes and microalbuminuria who are undergoing BP control and ACEI.Patients and Methods
The 5-year follow-up protocol in our previous studies
6.
, 7.
showed that CS was associated with faster progression of macroalbuminuric nephropathy of type 2 diabetes7.
despite BP control and ACEI and that its power to predict nephropathy progression was interrelated with and not independent of UAE.6.
These previous studies led to the current hypothesis that CS converts nephropathy from nonprogressive to progressive in type 2 diabetes. To begin testing this hypothesis, we sought an outcome that might manifest within a shorter time frame in groups of patients with type 2 diabetes in whom our previous studies had shown subsequent progressive nephropathy compared with those who had not, as measured by a decline in calculated GFR.6.
We chose changes in urine indices of renal injury as that parameter and arbitrarily chose 6 months as the time frame over which subjects would be followed. Consequently, the objectives of this prospective observational and interventional study were to determine (1) the excretion pattern for urine indices of renal injury that distinguish progressive (macroalbuminuric) from nonprogressive (microalbuminuric) nephropathy in patients with type 2 diabetes undergoing BP control and ACEI; and (2) whether CS and its cessation influenced this pattern. In our previous studies, the risk for GFR decline was much higher in subjects with urine albumin-to-creatinine ratios (alb/cr) >300 than those with lower values.6.
Despite this urine alb/cr “breakpoint” of 300 determined in our earlier studies, we used the previously published alb/cr criteria2.
of <20, 20 to 200, and >200 to group recruited subjects as normoalbuminuria, microalbuminuria, and macroalbuminuria, respectively. We hypothesized that changes in UAE measured as alb/cr would distinguish nonprogressive from progressive nephropathy because changes in UAE reliably indicate the degree of nephropathy in diabetes, its course, and its response to interventions.- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
14.
, 15.
Because we used UAE level to select and group subjects as described, we sought additional markers of renal injury. We chose urine excretion of transforming growth factor β1 (TGF β) and type IV collagen because each are experimental markers of nephropathy in diabetes.16.
, 17.
, 18.
, 19.
The first study phase determined the pattern of changes in the excretion indices of renal injury that distinguished progressive from nonprogressive nephropathy. The second phase examined the influence of smoking cessation on this pattern. Each study phase lasted 6 months. Our Institutional Review Board approved the protocol for these studies.Candidates for recruitment had type 2 diabetes as determined by their primary care physician and by current guidelines,
20.
hypertension as determined by their primary care physician, and normal plasma creatinine (Pcr) concentrations (<1.4 and <1.2 mg/dL for men and women, respectively). Candidate patients had to have a recorded urinalysis within the past 6 months and no evidence of secondary hypertension, pregnancy, or malignancy. We excluded those with known primary renal disease or findings consistent with primary renal disease (such as ≥3 red blood cells per high-powered field or red blood cell casts). Because very poor glycemic and BP control can each worsen albuminuria,2.
recruitment was limited to patients with type 2 diabetes with hemoglobin A1c ≤8.0% and with mean BP ≤120. Each subject had a morning “clean-catch” urinalysis by a nephrologist in which albumin and creatinine concentration was measured using the Sigma Diagnostics creatinine kit (Sigma Diagnostics, St. Louis, MO) as done previously.- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
6.
, 7.
Patients with albumin (milligrams) to creatinine (grams) ratios < 20 were “normoalbuminuric,” those with ratios ≥20 but <200 were “microalbuminuric,” and those with ratios ≥200 were “macroalbuminuric.”2.
Because patients with diabetes and micro- and macroalbuminuria should receive ACEI if tolerated,- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
2.
we excluded patients from the study who did not tolerate ACEI. We used ACEI as the preferred antihypertensive agents in normoalbuminuric patients with type 2 diabetes who needed an additional antihypertensive agent for BP control. We enrolled only those normoalbuminuric patients with type 2 diabetes who tolerated ACEI antihypertensive therapy. We treated microalbuminuric, hypertensive patients with type 2 diabetes toward BP ≤130/85 mm Hg- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
2.
, - Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
21.
and macroalbuminuric hypertensive patients with type 2 diabetes toward 125/75 mm Hg.2.
Normoalbuminuric patients with type 2 diabetes were treated toward a BP of 130/85 mm Hg.- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
21.
If subjects were already on ACEI when recruited, they were enrolled after 4 more weeks of this therapy. If they had been on ACEI <4 weeks, the protocol called for them to enroll after 4 weeks of ACEI. No recruited subjects fit this particular criterion. If they were not on ACEI at recruitment, they started ACEI (usually enalapril because it was our long-acting formulary ACE) and enrolled 4 weeks later. Of the 157 subjects enrolled for the first phase of the study to determine the pattern of urine excretion of indices of renal injury that was associated with progression, 52 (33%) had not been on ACEI and were begun upon enrollment into the study. Of the 80 subjects enrolled for the subsequent smoking cessation phase, 51 (64%) had not been on ACEI and were begun at study enrollment. As stated, renoprotection therapy, such as BP control and ACEI, generally prevents nephropathy progression in microalbuminuric but not in macroalbuminuric type 2 diabetic nephropathy.
3.
, 4.
, 5.
, 6.
, 7.
Nevertheless, unpublished observations from our previous studies6.
showed no alb/cr increase after 5 years of follow-up in nonsmoking patients with type 2 diabetes and microalbuminuria (91.8 ± 16.6 to 99.4; P = 0.176 by paired t test; n = 14) but an increase in smokers despite the same renoprotection therapy (176.7 ± 5.9 to 236.8 ± 20.6; P = 0.009 by paired t test; n = 8). In addition, a retrospective analysis of patients with type 2 diabetes showed a higher rate of progression from micro- to macroalbuminuria in smokers than in nonsmokers.13.
Because of the pivotal importance of the microalbuminuria stage of type 2 diabetic nephropathy as discussed and these data suggesting CS-induced nephropathy progression in microalbuminuria despite BP control and ACEI, we limited recruitment for the smoking cessation phase to patients with type 2 diabetes with microalbuminuria.Smokers must have smoked a minimum 10 cigarettes/day for ≥1 year. Those smoking fewer cigarettes each day and/or who had smoked for less than 1 year were excluded. Nonsmokers must not have smoked for at least 1 year before recruitment. For the smoking cessation phase, smokers received 8 weeks of daily transdermal nicotine (14-mg patch) and twice-daily bupropion (150-mg tablets) with 12 weekly outpatient sessions of substance abuse counseling, similar to a previously reported protocol.
22.
Our protocol differed from this previous one in that it used 12 instead of 9 weeks of substance abuse counseling, which has proved more effective in our experience. We used self-reporting to determine medication compliance. Five of the 38 smokers reported side effects from the nicotine patch, and 3 continued it after the daily dose was reduced to 7 mg. The 2 remaining subjects could not continue the nicotine patch despite reduced dose but maintained bupropion and counseling. None reported stopping bupropion. Smokers attended 405 of 444 (91%) of scheduled counseling sessions. Smoking cessation was determined by decrease in serum and urine levels of cotinine, a nicotine metabolite,23.
because biochemical markers more accurately determine smoking cessation than self-reporting24.
and cotinine is superior to other biochemical markers for this purpose.25.
All subjects submitted a morning urine specimen for cotinine, creatinine, albumin, TGF β, and type IV collagen at 1-week intervals at 3 points: study entry, 12 weeks (ie, after completion of medication and substance abuse counseling), and 24 weeks. Each subject also provided serum for cotinine and creatinine at the same time intervals. Twenty-five of the 38 smokers (66%) and 40 of the 43 (93%) nonsmokers completed all protocol visits and provided all required urine and blood samples at the indicated times. In preliminary studies, the highest urine and plasma cotinine of nonsmokers was about 10% of the lowest respective value among smokers. Consequently, smokers considered to have been successful at smoking cessation (“quitters”) were those whose urine and plasma cotinine at 12 and 24 weeks were ≤10% of their respective 1-week values. All other smokers were nonquitters. Nonsmokers were to be dropped from the analysis if plasma or urine cotinine levels at 12 or 24 weeks were greater than or equal to twice their 1-week values but none were dropped for this reason. The study coordinator or clinic nurse measured BP as described.
6.
No dietary instructions beyond standard diabetic recommendations for 20% of caloric intake as protein were given. Smokers admitted to no tobacco other than cigarettes.Analytical Methods
Plasma/Urine Creatinine
We measured plasma/urine creatinine using the Sigma Diagnostics creatinine kit and urine albumin as done previously.
7.
Urine TGF-β
Urine concentration of TGF β was measured using the quantitative sandwich enzyme immunoassay technique as described previously.
16.
The results were expressed as nanograms per gram of creatinine.Urine Type IV Collagen
Urine type IV collagen was measured with competitive indirect enzyme-linked immunosorbent assay as described previously,
18.
and we subjected urine samples and antihuman collagen IV antibody to overnight preincubation to enhance sensitivity to detection limit <1 ng/mL. Results were expressed in micrograms per gram of creatinine.Statistical Methods
The goal of the first phase of this analysis was to compare changes over time in urine excretion of albumin, TGF β, and type IV collagen (Ucoll) factored per gram of urine creatinine among nonsmokers with macroalbuminuria to those with microalbuminuria and normoalbuminuria. Previous studies from this laboratory
6.
showed that among patients with type 2 diabetes undergoing BP control and ACEI, those with macroalbuminuria generally had a progressive decline in calculated GFR, but those with microalbuminuria and normoalbuminuria did not. The current strategy was to identify a pattern of urine excretion of these parameters of renal injury that distinguished patients with type 2 diabetes and macroalbuminuria whom previous studies showed generally had progressive nephropathy from those with microalbuminuria and normoalbuminuria who generally did not have progressive nephropathy. The second phase of the analysis used 2 strategies to determine the effect of cigarette smoking on the identified pattern of excretion of renal injury parameters. We first did a cross-sectional comparison of smokers and nonsmokers within the respective albuminuria group. We then longitudinally examined effects of smoking cessation compared with continued smoking on this pattern in patients with type 2 diabetes with microalbuminuria.Observations over time were clustered within subjects, and data for some subjects were incomplete. Multilevel regression models enabled us to use data from every subject, including those with incomplete data, to contribute information regarding the pattern of the response. These models also made it possible to account for any correlations induced by clustering. The regression models were fitted to the data by an iterative procedure (restricted iterated generalized least squares) that converges to maximum likelihood estimates.
26.
For each kidney function parameter, the average trajectory over the 24 weeks of the study was fitted by a straight line segment, along with appropriate confidence bounds. For the first phase and the cross sectional comparison, we chose the coefficients of the model to reflect differences in intercept and slope in each of the 6 albuminuria and smoking subgroups. We compared the averages at week 1 and the rates of change for each outcome variable between the 6 subgroups with the use of χ2 tests (square of the standardized coefficient or Wald statistic). All tests were two-sided and conducted at the 5% level, and all confidence intervals were reported at 95% level. No adjustment was made for multiple tests. Statistical calculations were accomplished using MLwiN version 1.2025.
and Stata version 7.26.
For the longitudinal portion of the second phase, we compared changes in the 3 injury parameters among nonsmokers, smokers unsuccessful at smoking cessation (nonquitters), and smokers successful at smoking cessation (quitters) with microalbuminuria. As part of the multilevel analysis, the trajectory of alb/cr, TGFβ/cr, and Ucoll/cr was calculated for each subject for the course of study. The average trajectory for each study group was then calculated with appropriate confidence bounds. In this way, we compared rates of trajectory changes for alb/cr, TGFβ/cr, and Ucoll/cr among the 3 groups with the use of χ2.
tests of change in −2ln(likelihood). All tests were carried out at the 5% level and all confidence intervals were reported at 95% level. No adjustment was made for multiple tests. Statistical calculations were accomplished using MLwiN version 1.20- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
27.
and Stata version 7.26.
Results
Table 1 shows initial characteristics of the 3 albuminuria groups and subsequent descriptions of smoking and nonsmoking subjects within each albuminuria group. Table 2 shows week 1 values predicted by the models for each of the 3 indices of kidney injury according to albuminuria group and smoking status. This table compares smokers with nonsmokers within each of the 3 albuminuria groups. TGFβ/cr was higher in smokers compared with nonsmokers with macroalbuminuria but not in the remaining albuminuria groups. Ucoll/cr was higher in smokers than nonsmokers with microalbuminuria and macroalbuminuria but not in those with normoalbuminuria. Table 3 shows differences in week 1 indices of kidney injury among albuminuria groups of the same smoking status. TGFβ/cr was higher in the macroalbuminuric than the remaining albuminuria groups among both nonsmokers and smokers. By contrast, there was no identifiable pattern of differences for Ucoll/cr. The difference in predicted alb/cr at week 1 among normo-, micro-, and macroalbuminuria is not shown in Table 3 for either nonsmokers or smokers because these groups were selected according to alb/cr. By contrast, the rate of change of alb/cr determined during the 6-month follow-up was not considered in defining the groups, allowing this parameter to be compared among groups as done in Table 4, Table 5.
Table 1Characteristics of Prospectively Followed Patients with Type 2 Diabetes, Nonsmokers and Smokers, None of Whom Underwent Smoking Cessation Intervention, Categorized by Albuminuria
| Normoalbuminuria (n = 45) | Microalbuminuria (n = 34) | Macroalbuminuria (n = 78) | ||||
|---|---|---|---|---|---|---|
| Age (years) | 52.4 ± 1.9 | 49.1 ± 2.0 | 47.6 ± 1.5 | |||
| Sex (% male) | 56 | 53 | 55 | |||
| Ethnicity (% Black/Hispanic/White) | 38/51/11 | 29/59/12 | 21/62/17 | |||
| Body weight (kg) | 86.4 ± 1.6 | 85.8 ± 1.8 | 86.1 ± 1.3 | |||
| Diabetes duration (years) | 4.2 ± 0.9 | 4.4 ± 1.0 | 8.9 ± 1.4 | |||
| Plasma creatinine (mg/dL) | 0.89 ± 0.09 | 0.91 ± 0.11 | 0.92 ± 0.12 | |||
| Nonsmokers (n = 27) | Smokers (n = 18) | Nonsmokers (n = 15) | Smokers (n = 19) | Nonsmokers (n = 46) | Smokers (n = 32) | |
| Mean BP (mm Hg) | ||||||
| Initial | 98.1 ± 1.8 | 99.01.9 | 100.9 ± 1.9 | 100.8 ± 2.0 | 102.7 ± 2.0 | 104.8 ± 2.1 |
| Follow-up | 94.0 ± 1.7 | 93.11.7 | 92.7 ± 1.7 | 92.4 ± 1.6 | 93.8 ± 1.6 | 92.6 ± 1.5 |
| Hemoglobin A1c (%) | ||||||
| Initial | 7.4 ± 0.1 | 7.5 ± 0.1 | 7.4 ± 0.1 | 7.6 ± 0.1 | 7.5 ± 0.1 | 7.5 ± 0.1 |
| Follow-up | 7.1 ± 0.1 | 7.1 ± 0.1 | 7.0 ± 0.1 | 7.2 ± 0.1 | 7.1 ± 0.1 | 7.2 ± 0.1 |
| Plasma cotinine μg/mL) | 2.6 ± 0.8 | 334 ± 32 | 2.2 ± 0.7 | 327 ± 29 | 2.5 ± 0.8 | 358 ± 37 |
| Urine cotinine (μg/g of creatinine) | 69 ± 8 | 4108 ± 319 | 78 ± 9 | 3987 ± 301 | 98 ± 11 | 4697 ± 441 |
Table 2Week 1 Values Predicted by the Models for the Indices of Kidney Injury by Smoking Status and Albuminuria Group
| Nonsmokers | Smokers | |||||
|---|---|---|---|---|---|---|
| Normo | Micro | Macro | Normo | Micro | Macro | |
| Alb/cr | ||||||
| Predicted at week 1 | 7.504 | 38.410 | 522.810 | 8.849 | 38.428 | 568.207 |
| SE | 19.035 | 26.501 | 15.159 | 23.974 | 23.931 | 18.462 |
| p vs nonsmokers | NA | NA | NA | 0.969 | 0.999 | 0.057 |
| TGFβ/cr | ||||||
| Predicted at week 1 | 42.028 | 35.003 | 58.825 | 39.794 | 36.561 | 68.406 |
| SE | 2.607 | 3.550 | 2.030 | 3.321 | 3.247 | 2.440 |
| p vs nonsmokers | NA | NA | NA | 0.597 | 0.746 | 0.003 |
| Ucoll/cr | ||||||
| Predicted at week 1 | 16.214 | 13.403 | 16.623 | 15.709 | 18.997 | 19.856 |
| SE | 0.651 | 0.890 | 0.509 | 0.824 | 0.814 | 0.613 |
| p vs nonsmokers | NA | NA | NA | 0.631 | <0.001 | <0.001 |
Smokers are compared with nonsmokers within each albuminuria group. NA, comparison not applicable.
Table 3Differences in Week 1 Indices of Kidney Injury among Albuminuria Groups, Separated by Smoking Status
| Nonsmokers | Smokers | |||||
|---|---|---|---|---|---|---|
| Micro vs Normo | Macro vs Normo | Macro vs Micro | Micro vs Normo | Macro vs Normo | Macro vs Micro | |
| Alb/cr | ||||||
| Difference | 30.906 | 515.306 | 484.400 | 29.579 | 559.358 | 529.779 |
| SE | 32.629 | 24.334 | 30.530 | 33.874 | 30.259 | 30.225 |
| p | NA | NA | NA | NA | NA | NA |
| TGFβ/cr | ||||||
| Difference | −7.025 | 16.797 | 23.822 | −3.233 | 28.612 | 31.845 |
| SE | 4.404 | 3.304 | 4.089 | 4.645 | 4.121 | 4.062 |
| p | 0.111 | <0.001 | <0.001 | 0.486 | <0.001 | <0.001 |
| Ucoll/cr | ||||||
| Difference | −2.811 | 0.409 | 3.220 | 3.288 | 4.147 | 0.859 |
| SE | 1.103 | 0.826 | 1.025 | 1.158 | 1.027 | 1.019 |
| p | 0.011 | 0.621 | 0.002 | 0.005 | <0.001 | 0.399 |
p = 2-sided p-value for hypothesis c = 0 (χ2, 1 df); NA, comparison not appropriate because categories were formed using baseline alb/cr.
Table 4Comparisons of Rates of Change over 24 Weeks for Indices of Kidney Injury by Smoking Status and Albuminuria Group
| Nonsmokers | Smokers | |||||
|---|---|---|---|---|---|---|
| Normo | Micro | Macro | Normo | Micro | Macro | |
| Alb/cr | ||||||
| Rate of change | 0.095 | -0.003 | 11.627 | -0.061 | 0.663 | 28.162 |
| SE | 2.051 | 2.909 | 1.683 | 2.903 | 2.478 | 2.073 |
| p vs zero | 0.963 | >0.999 | <0.001 | 0.983 | 0.789 | <0.001 |
| p vs nonsmokers | NA | NA | NA | 0.965 | 0.862 | <0.001 |
| TGFß/cr | ||||||
| Rate of change | -0.085 | -0.162 | 0.664 | 0.980 | 1.022 | 1.345 |
| SE | 0.248 | 0.343 | 0.194 | 0.359 | 0.313 | 0.234 |
| p vs zero | 0.732 | 0.637 | 0.001 | 0.006 | 0.001 | <0.001 |
| p vs nonsmokers | NA | NA | NA | 0.015 | 0.011 | 0.025 |
| Ucoll/cr | ||||||
| Rate of change | 0.083 | 0.072 | 0.092 | -0.080 | 0.134 | 0.111 |
| SE | 0.067 | 0.093 | 0.053 | 0.096 | 0.081 | 0.064 |
| p vs zero | 0.215 | 0.439 | 0.083 | 0.405 | 0.098 | 0.083 |
| p vs nonsmokers | NA | NA | NA | 0.164 | 0.615 | 0.819 |
NA, comparison not applicable.
Table 5Comparisons of Rates of Change over 24 Weeks for Indices of Kidney Injury by Smoking Status and Albuminuria Group
| Nonsmokers | Smokers | |||||
|---|---|---|---|---|---|---|
| Macro vs Normo | Macro vs Normo | Micro vs Macro | Macro vs Normo | Macro vs Normo | Micro vs Micro | |
| Alb/cr | ||||||
| Difference | −0.098 | 11.532 | 11.630 | 0.724 | 28.223 | 27.499 |
| SE | 3.559 | 2.653 | 3.361 | 3.817 | 3.567 | 3.231 |
| p | 0.978 | <0.001 | 0.001 | 0.850 | <0.001 | <0.001 |
| TGFβ/cr | ||||||
| Difference | −0.077 | 0.749 | 0.826 | 0.042 | 0.365 | 0.323 |
| SE | 0.423 | 0.315 | 0.394 | 0.476 | 0.429 | 0.391 |
| p | 0.856 | 0.017 | 0.036 | 0.930 | 0.394 | 0.409 |
| Ucoll/cr | ||||||
| Difference | −0.011 | 0.009 | 0.020 | 0.214 | 0.191 | −0.023 |
| SE | 0.115 | 0.085 | 0.107 | 0.126 | 0.115 | 0.103 |
| p | 0.924 | 0.916 | 0.852 | 0.088 | 0.098 | 0.824 |
p, 2-sided p-value for hypothesis Difference = 0 (χ2, 1 df.)
Table 4 shows the rates of change (slope of the regression lines) during the 24-week follow-up period for the indices of kidney injury by albuminuria group and smoking status. Alb/cr increased during follow-up in macroalbuminuric subjects (ie, the slope of the regression line was positive and different from zero), and the rate of increase (slope) was higher in smokers compared with nonsmokers within this albuminuria group. By contrast, alb/cr did not change (ie, slope not different from zero) in nonsmokers or smokers with microalbuminuria and normoalbuminuria, and there were no differences in rates of change for alb/cr between nonsmokers and smokers of the same albuminuria group. TGFβ/cr increased during follow-up in only the macroalbuminuric group among nonsmokers but did so in each albuminuria group of smokers. The rate of TGFβ/cr change was higher in smokers than nonsmokers for each albuminuria group. There were no changes in Ucoll/cr for any group during follow-up.
Table 5 compares rates of change of kidney injury indices among albuminuria groups of the same smoking status. The alb/cr rate of change was higher in subjects with macroalbuminuria than both micro- and normoalbuminuria within nonsmokers and smokers. The TGFβ/cr rate of change was higher in those with macroalbuminuria than with micro- and normoalbuminuria among nonsmokers but not among smokers. There was no difference in the rate of Ucoll/cr among groups.
In Table 2, Table 3, Table 4, Table 5 together, 66 different statistical tests are reported, so the probability of a type I error is increased far beyond the nominal α = 0.05. Consequently, we looked for patterns of “significant” tests that might provide insights to pursue in the subsequent phase exploring the influence of smoking-cessation. Of the 3 examined indices of urine indices, the most consistent pattern was noted for TGFβ/cr. Specifically, (1) TGFβ/cr progressively increased in nonsmoking subjects with macroalbuminuria but not in those with micro- or normoalbuminuria and (2) smokers had greater rates of TGFβ/cr change than nonsmokers within the same albuminuria group. Our previous long-term studies showed that nonsmokers with macroalbuminuria but not those with micro- or normoalbuminuria experienced progressive nephropathy manifest by increasing albuminuria and decreasing GFR despite BP control and ACEI.
6.
The present shorter-term studies again show that nonsmoking patients with type 2 diabetes and macroalbuminuria have progressively increased alb/cr. In addition, importantly, the present studies show that the subjects with macroalbuminuria have a progressive increase in TGFβ/cr, but those with micro- and normoalbuminuria do not. Furthermore, the present studies show that smokers compared with nonsmokers have increased rates of change for TGFβ/cr within each albuminuria group. This pattern is illustrated in Figure 1, which compares the multilevel regression models of TGFβ/cr among the 3 albuminuria groups within smokers and nonsmokers (Figure 1A) and between smokers and nonsmokers within each of the 3 albuminuria groups (Figure 1B).
Figure 1Composite trajectories for multilevel regression models for urine excretion over 24 weeks as indicated on the abscissa of nanograms of TGF β factored per gram of creatinine (TGFβ/cr) for the 6 groups of patients with type 2 diabetes categorized by level of albuminuria and smoking status. (A) Comparison of TGFβ/cr trajectories among normo-, micro-, and macroalbuminuria within smokers and nonsmokers. (B) Rearrangement of the same subject groups to compare nonsmokers and smokers within subjects with normo-, micro-, and macroalbuminuria.
To further examine the influence of CS on the pattern of urine excretion of the indices of renal injury, including TGFβ/cr, we prospectively examined the effects of smoking cessation in a separate set of patients with type 2 diabetes with microalbuminuria. Table 6 shows the baseline characteristics of these subjects, among whom smokers underwent smoking cessation intervention. Of the 37 smokers who completed the protocol, 8 claimed to have completely stopped smoking at both the 12- and 24-week time points. Of the 29 subjects who claimed continued smoking, none had any subsequent urine or plasma cotinine levels ≤ 10% of their respective 1-week value. Among the 8 claiming not to be smoking, 5 had urine and plasma cotinine measurements at both 12 and 24 weeks that were less than 10% of the 1-week value, thereby satisfying the preassigned criteria (see Methods) for smoking cessation. No 12- or 24-week blood or urine cotinine level in the remaining 3 subjects who claimed not to be smoking was less than 10% of the respective 1-week value. Indeed, cotinine levels for these patients were similar to those claiming continued smoking. Because these 3 smokers did not fit the preassigned criteria to be labeled as quitters, they were counted as nonquitters in the analysis. Figure 2 displays plasma and urine cotinine concentrations for these 2 groups of smokers (nonquitters and quitters) and for nonsmokers during follow-up.
Table 6Baseline Characteristics of Prospectively Followed Patients with Type 2 Diabetes with Initial Microalbuminuria among Whom Smokers Underwent Smoking Cessation Intervention
| Nonsmokers (n = 43) | Nonquitters (n = 32) | Quitters (n = 5) | |
|---|---|---|---|
| Male | 44% | 50% | 40% |
| % Black/Hispanic/White | 7/77/16 | 9/78/13 | 0/60/40 |
| Subjects on BP meds at recruitment | 84% | 76% | 80% |
| Subjects on ACEI at recruitment | 40% | 33% | 40% |
| Age (years) | 54.5 ± 12.2 | 48.1 ± 12.5 | 49.8 ± 10.3 |
| Diabetes duration (years) | 7.1 ± 7.5 | 4.6 ± 4.8 | 4.2 ± 4.4 |
| Systolic BP (mm Hg) | 133.0 ± 20.2 | 130.5 ± 16.2 | 133.0 ± 4.7 |
| Diastolic BP (mm Hg) | 79.1 ± 7.9 | 76.5 ± 7.8 | 74.0 ± 10.3 |
| Mean BP (mm Hg) | 97.0 ± 10.3 | 94.5 ± 9.3 | 93.7 ± 8.2 |
| Hemoglobin A1c (%) | 7.0 ± 0.6 | 7.1 ± 0.5 | 7.1 ± 0.5 |
| Plasma creatinine (mg/dL) | 0.9 ± 0.1 | 0.9 ± 0.1 | 0.9 ± 0.1 |
| Urine albumin (mg/g of creatinine) | 17.74 ± 22.20 | 20.03 ± 19.91 | 22.12 ± 4.70 |
| Urine TGF β (ng/g of creatinine) | 33.71 ± 24.26 | 37.43 ± 27.05 | 42.20 ± 21.26 |
| Urine type IV collagen (μg/g of creatinine) | 14.04 ± 7.10 | 17.05 ± 5.74 | 20.02 ± 2.91 |
| Urine cotinine (μg/g of creatinine) | 80.28 ± 65.74 | 4501± 2117 | 3028 ± 1510 |
| Plasma Cotinine (μg/ml) | 2.64 ± 5.81 | 347 ± 175 | 245 ± 95.4 |
| Cigarette packs/day | 1.38 ± 0.78 | 0.95 ± 0.45 | |
| Cigarette packs/day × years | 36.57 ± 24.60 | 26.20 ± 13.14 |
BP, blood pressure; Alb/cr, urine albumin-to-creatinine ratio; TGF β, transforming growth factor β. Conversion factor from the listed conventional to international units is 88.4 for plasma creatinine (to micromoles/liter).
Figure 2Plasma (top) and urine (bottom) cotinine levels during follow-up in nonsmokers, smokers not successful at quitting despite smoking cessation intervention (nonquitters), and smokers successful at smoking cessation (quitters).
Composite group trajectories for alb/cr, urine TGF β/cr, and Ucoll/cr derived from multilevel analysis are shown in Figure 3. The alb/cr analysis shows that there was a difference in the rates of increase of this parameter (P = 0.05) among the 3 groups. The most likely source of this difference was between the rates for quitting versus nonquitting smokers (−0.554 versus 0.553 alb/cr/week, P = 0.021) because the rate for nonsmokers (0.116 alb/cr/week) was not different from the value for either nonquitters or quitters. The analysis for TGFβ/cr shows that there was a difference in the rates of increase of TGFβ/cr among the 3 groups (P = 0.01). The most likely source of this difference was between the rates for nonquitting smokers and nonsmokers (0.970 versus −0.123 TGF β/cr/week (P = 0.017), because the rate for quitting smokers (0.093) was not different from the 2 remaining groups. The analysis for rate of change of Ucoll/cr shows no difference in trajectories among the 3 groups (P = 0.458). In summary, quitting smokers had lower rates of alb/cr change than nonquitting smokers and had rates of TGFβ/cr change comparable with those of nonsmokers.
Figure 3Composite trajectories (solid lines) with 95% confidence limits (dotted lines) for the multilevel analysis of the indicated parameter for nonsmokers, smokers not successful at quitting despite smoking cessation intervention (nonquitters), and smokers who successfully quit in response to the intervention (quitters). Alb/cr and TGF β/cr are as in previous figures and Ucoll is expressed in micrograms of urine type IV collagen factored per gram of creatinine. For the alb/cr plots, the zero for the abscissa is represented by a dotted line to show that the lower boundary of the 95% confidence interval crosses the true abscissa for the quitters during the indicated period of follow-up. For all plots, excretion as described is on the ordinate and the follow-up in weeks is on the abscissa.
Discussion
We tested the hypothesis that CS exacerbates renal injury despite BP control and ACEI in patients with type 2 diabetes with early nephropathy defined by microalbuminuria and normal plasma creatinine. Standard renoprotection therapy with BP control and ACEI generally prevents progression of early to advanced (macroalbuminuria) nephropathy with its much higher risk for renal failure. Patients with type 2 diabetes and macroalbuminuria previously shown to have progressive albuminuria and GFR decline despite BP control and ACEI
3.
, 4.
, 6.
had increasing UTGFβV despite this standard renoprotection therapy. By contrast, normoalbuminuric patients and patients with type 2 diabetes and microalbuminuria undergoing the same renoprotective therapy did not. CS increased UTGFβV in patients with type 2 diabetes at all albuminuria levels, consistent with progressive renal injury. Smoking cessation compared with continued smoking ameliorated the UTGFβV increase, consistent with amelioration of progressive renal injury. These data support that CS exacerbates renal injury in type 2 diabetes despite BP control and ACEI at each of the 3 levels of albuminuria examined. Furthermore, these data support the idea that smoking compared with nonsmoking patients with type 2 diabetes with early nephropathy (microalbuminuria) are at higher risk of progressing to advanced nephropathy (macroalbuminuria) with its greater risk of renal failure. The data further support that smoking cessation avoids nephropathy progression in patients with type 2 diabetes and microalbuminuria with BP control and ACEI and thereby reduces the risk for subsequent renal failure. Longer studies are needed to directly determine whether CS increases the risk for patients with type 2 diabetes and microalbuminuria to progress to macroalbuminuria despite BP control and ACEI and if smoking cessation prevents this progression.Progressive GFR decline in type 2 diabetic nephropathy is preceded by a progressive increase in UAE from normoalbuminuria through microalbuminuria to macroalbuminuria.
2.
BP control and ACEI generally stops further nephropathy progression in patients with type 2 diabetes with microalbuminuria.- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
3.
, 6.
, 6.
By contrast, this conventional renoprotection therapy slows but does not stop nephropathy progression in patients with type 2 diabetes and macroalbuminuria.3.
, 4.
, 7.
Consequently, patients with type 2 diabetes with microalbuminuria constitute an important group to target with renoprotection therapy because they are at increased risk for subsequent renal failure,2.
yet standard renoprotection therapy with BP control and ACEI generally prevents further nephropathy progression. Because increased UAE is a reliable indicator of the presence and degree of nephropathy in diabetes,- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
13.
, 14.
and CS increases UAE in type 2 diabetes4.
, 6.
, 7.
and did so despite BP control and ACEI in a post hoc analysis of the microalbuminuric cohort from a previous study,6.
CS might exacerbate nephropathy progression in patients with type 2 diabetes and microalbuminuria despite BP control and ACEI. The present studies show that patients with type 2 diabetes and macroalbuminuria who generally experience progressive nephropathy despite BP control and ACEI were distinguished from those with normoalbuminuria and microalbuminuria by increasing UTGFβV, consistent with progressive nephropathy. CS increased UTGFβV in all albuminuria groups, and its cessation ameliorated the increase in a separate cohort of patients with type 2 diabetes and microalbuminuria, all of whom were treated with BP control and ACEI. These data support the concept that CS exacerbates progressive renal injury in normoalbuminuric patients and patients with type 2 diabetes and microalbuminuria despite currently recommended renoprotective therapy. Thus, CS might increase the risk of progression from normoalbuminuria to microalbuminuria and from microalbuminuria to macroalbuminuria despite therapy that generally prevents nephropathy progression in patients with type 2 diabetes and microalbuminuria. Encouragingly, the data suggest that smoking cessation in patients with type 2 diabetes and microalbuminuria stops the progressive renal injury induced by CS.All subjects in these studies were patients with type 2 diabetes, the single largest group of patients with ESRD,
1.
and so the conclusions are limited to this group pending similar studies in patients with type 1 diabetes. Nevertheless, CS is also associated with increased UAE in type 1 diabetes11.
and smoking cessation is associated with reduced UAE in patients with type 1 diabetes.12.
The BP goal in these previous studies was <140/90, and it was not reported how many were on ACEI. Consequently, it is not clear whether the patients of this previous study were receiving what is currently considered to be optimal renoprotection therapy. By contrast, all subjects (type 2) of the present studies were on ACEI and their BP goal was 130/85 or lower, as currently recommended.2.
Despite what is currently considered to be optimal renoprotection therapy, CS was associated with nephropathy progression in our previous studies of patients with type 2 diabetes and macroalbuminuria- Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
6.
, 7.
and in the cohort of these subjects with microalbuminuria, as stated earlier. The present studies confirm the previous studies and support the concept that smoking cessation ameliorates this CS-induced exacerbation of nephropathy progression. Together, these studies suggest that CS exacerbates nephropathy progression in type 2 diabetes despite current renoprotective therapy, such as BP control and ACEI, and that smoking cessation in those with microalbuminuria ameliorates further progression.Smoking cessation was determined using urine cotinine excretion because biochemical markers more accurately determine smoking cessation than self-reporting,
24.
and cotinine is superior to other biochemical markers for this purpose.25.
The successful smoking cessation rate 6 months after enrollment in the present studies was 14% (5 of 37) but would have been 22% (8 of 37) had self-reporting been the sole criterion. Nevertheless, this smoking cessation rate was lower than the 26% rate obtained using a similar smoking cessation protocol and urine cotinine excretion to identify quitters.24.
Table 6 shows that nonquitters smoked more cigarettes per day, and Figure 2 shows that they had higher plasma and urine cotinine levels, although neither difference was significant. The moderate single-dose nicotine patch used in the present studies might have been less effective for smoking cessation in heavier smokers, as suggested previously,28.
and might have contributed to the comparatively low rate of smoking cessation.Although patients with diabetes and microalbuminuria are termed “at risk” for established nephropathy indicated by macrolbuminuria,
2.
, - Bennett P.H.
- Haffner S.
- Kasiske B.L.
- et al.
Screening and management of microalbuminuria in patients with diabetes mellitus: recommendations to the Scientific Advisory Board of the National Kidney Foundation from an ad hoc committee of the Council on Diabetes Mellitus of the National Kidney Foundation.
Am J Kidney Dis. 1995; 25: 107-112
15.
they already have parenchymal injury and should be more accurately termed “early nephropathy.”18.
Consequently, ACEI-induced stabilization of GFR and UAE in patients with type 2 diabetes and microalbuminuria3.
, 5.
, 6.
is consistent with stabilization of nephropathy rather than prevention. The stable course of alb/cr and TGFβ/cr in the nonsmokers of the present studies is therefore consistent with no further nephropathy progression that is probably related to their comparatively good BP control and to ACEI.3.
, 5.
, 6.
By contrast, progressive UAE and TGFβ/cr increase in nonquitters suggests that CS exacerbates nephropathy progression despite BP control and ACEI. CS is associated with increased UAE in type 18.
, 9.
, 10.
, 11.
, 12.
and type 26.
, 7.
, 13.
diabetes as well as with nondiabetic nephropathy.29.
The present studies show that continued CS is associated with increasing UAE and TGFβ/cr, consistent with progressive renal injury15.
, 16.
, 17.
, 18.
, 19.
in patients with diabetes and microalbuminuria despite standard renoprotection therapy as ACEI and BP control. Encouragingly, the courses of alb/cr and TGFβ/cr of quitters were comparable with the stable courses of nonsmokers, supporting no further nephropathy progression. The present studies support that smoking cessation ameliorates nephropathy progression, as indicated by increased UAE and increased urine TGF β in patients with type 2 diabetes and microalbuminuria receiving standard renoprotection therapy.The present studies show that the rate of increase of TGFβ/cr was higher in smokers than in nonsmokers in cross-sectional analysis (Figure 1) and progressively increased during prospective follow-up in nonquitters but not in quitters (Figure 3). ACEI might have contributed to the stable urine TGFβ/cr of the nonsmokers.
16.
On the other hand, cigarette smoking increases serum TGF β levels in patients with diabetes,30.
and the present studies suggest that CS can increase TGFβ/cr despite ACEI. Encouragingly, TGFβ/cr of quitters did not progressively increase, unlike the pattern for nonquitters but similar to the stable pattern of nonsmokers. Consequently, these data additionally support that smoking cessation halts and continued CS exacerbates progressive nephropathy as measured by TGFβ/cr in patients with type 2 diabetes on standard renoprotection therapy.Unlike the courses described for alb/cr and TGFβ/cr, the course of Ucoll/cr was not different among the 3 groups (Figure 3). ACEI suppresses the time-dependent increase in Ucoll/cr in patients with type 2 diabetes,
19.
so the ACEI therapy given to all subjects might have accounted for these findings. On the other hand, CS-induced exacerbation of nephropathy progression and/or smoking cessation-induced amelioration thereof might require >6 months for nephropathy progression indicated by Ucoll/cr to be manifest. Alternatively, CS-induced exacerbation of nephropathy and/or smoking cessation amelioration thereof might involve progression mechanisms that are less reflected by urine excretion of Ucoll/cr.Although the statistical analysis described strongly supports the conclusions, potential weaknesses of the present studies should be highlighted. The overall sample size was relatively small. In addition, CS addictive power and the stringent criteria for smoking cessation that relied on biochemical criteria for smoking cessation led to a small number of quitting smokers. Smokers missed more protocol visits than nonsmokers, so sample collection was less complete in this group, even though multilevel analysis (see Methods) allowed for subjects with incomplete data to be included. In addition, the progressive increase in alb/cr and TGFβ/cr described for nonquitters of the smoking-cessation cohort was mostly attributable to a minority of this group who had dramatic rises in these parameters during follow-up. These data suggest that some patients with type 2 diabetes are more susceptible to the effects of CS on the nephropathy of type 2 diabetes, and future studies will help distinguish them. We are unable to conclusively rule out factors associated with CS rather than CS itself as responsible for the study findings. Similarly, nephropathy progression in nonquitters might have been a result of less rigorous compliance with ACEI. Although we made no objective measures of medication compliance, follow-up BP was not different among the 3 groups (data not shown), supporting a comparable effect of antihypertensive therapy among subjects.
Determining the mechanism(s) by which CS exacerbates renal injury in patients with type 2 diabetes was not a goal of these studies. Nevertheless, increased oxidizing activity of body tissues, a state referred to as oxidant stress, is a phenomenon common to both diabetes
31.
and cigarette smoking.32.
Oxidant stress mediates progression of experimental diabetic nephropathy33.
and oxidant stress is exacerbated by cigarette smoking.32.
Consequently, cigarette smoking might exacerbate renal injury in diabetic nephropathy by enhancing oxidant stress.In summary, the present studies show that continued CS exacerbates the nephropathy of type 2 diabetes and that smoking cessation in those with microalbuminuria ameliorates nephropathy progression as measured by increased urine excretion of TGFβ/cr. The untoward effects of CS on these markers of kidney injury occurred in patients with type 2 diabetes despite standard renoprotection therapy. These data suggest that continued smoking exacerbates nephropathy in patients with type 2 diabetes and microalbuminuria despite standard renoprotection therapy and that smoking cessation halts nephropathy progression. The data support the contention that smoking cessation is an effective renoprotective intervention in patients with type 2 diabetes with early nephropathy indicated by microalbuminuria and who are receiving standard renoprotection therapy.
Acknowledgements
We thank the Inside Out Community Outreach Program of Lubbock, Texas, for providing the substance abuse counseling and the nursing and clerical staff of the Internal Medicine Clinic of the Department of Internal Medicine at Texas Tech University Health Sciences Center for their assistance.
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Article Info
Publication History
Accepted:
September 5,
2003
Received:
June 11,
2003
Footnotes
This work was supported by The Texas Minority Health Research and Education Grant Program, The Larry and Jane Woirhaye Memorial Endowment in Renal Research, and Texas Tech University Health Sciences center.
Identification
Copyright
© 2004 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.
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