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Original Investigation |

Association Between Glycemic Control and Adverse Outcomes in People With Diabetes Mellitus and Chronic Kidney Disease:  A Population-Based Cohort Study FREE

Sabin Shurraw, MD; Brenda Hemmelgarn, MD, PhD; Meng Lin, MSc; Sumit R. Majumdar, MD, MSc; Scott Klarenbach, MD, MSc; Braden Manns, MD, MS; Aminu Bello, MD, PhD; Matthew James, MD, PhD; Tanvir Chowdhury Turin, MD, PhD; Marcello Tonelli, MD, SM; for the Alberta Kidney Disease Network
[+] Author Affiliations

Author Affiliations: Divisions of Nephrology, University of Alberta, Edmonton (Drs Shurraw, Majumdar, Klarenbach, Bello, and Tonelli and Mr Lin), and University of Calgary, Foothills Medical Centre, Calgary (Drs Hemmelgarn, Manns, James, and Turin), Alberta, Canada.

Group Information: A list of members of the Alberta Kidney Disease Network can be found at http://www.akdn.info/.


Arch Intern Med. 2011;171(21):1920-1927. doi:10.1001/archinternmed.2011.537.
Text Size: A A A
Published online

Background Better glycemic control as reflected by lower hemoglobin A1c (HbA1c) level may prevent or slow progression of nephropathy in people with diabetes mellitus (DM). Whether a lower HbA1c level improves outcomes in people with DM and chronic kidney disease (CKD) is unknown.

Methods From all people with serum creatinine measured as part of routine care in a single Canadian province from 2005 through 2006, we identified those with CKD based on laboratory data (estimated glomerular filtration rate [eGFR], <60.0 mL/min/1.73 m2]) and DM using a validated algorithm applied to hospitalization and claims data. Patients were classified based on their first HbA1c measurement; Cox regression models were used to assess independent associations between HbA1c level and 5 study outcomes (death, progression of kidney disease based on a doubling of serum creatinine level, or new end-stage renal disease [ESRD], cardiovascular events, all-cause hospitalization).

Results We identified 23 296 people with DM and an eGFR lower than 60.0 mL/min/1.73 m2. The median HbA1c level was 6.9% (range, 2.8%-20.0%), and 11% had an HbA1c value higher than 9%. Over the median follow-up period of 46 months, 3665 people died, and 401 developed ESRD. Regardless of baseline eGFR, a higher HbA1c level was strongly and independently associated with excess risk of all 5 outcomes studied (P < .001 for all comparisons). However, the association with mortality was U-shaped, with increases in the risk of mortality apparent at HbA1c levels lower than 6.5% and higher than 8.0%. The increased risk of ESRD associated with a higher HbA1c level was attenuated at a lower baseline eGFR (P value for interaction, <.001). Specifically, among those with an eGFR of 30.0 to 59.9 mL/min/1.73 m2, the risk of ESRD was increased by 22% and 152% in patients with HbA1c levels of 7% to 9% and higher than 9%, respectively, compared with patients with an HbA1c level lower than 7% (P < .001), whereas corresponding increases were 3% and 13%, respectively, in those with an eGFR of 15.0 to 29.9 mL/min/1.73 m2.

Conclusions A hemoglobin A1c level higher than 9% is common in people with non–hemodialysis-dependent CKD and is associated with markedly worse clinical outcomes; lower levels of HbA1c (<6.5%) also seemed to be associated with excess mortality. The excess risk of kidney failure associated with a higher HbA1c level was most pronounced among people with better kidney function. These findings suggest that appropriate and timely control of HbA1c level in people with DM and CKD may be more important than previously realized, but suggest also that intensive glycemic control (HbA1c level <6.5%) may be associated with increased mortality.

Figures in this Article

Diabetes mellitus (DM) and chronic kidney disease (CKD) are potent independent risk factors for cardiovascular (CV) events and progression to end-stage renal disease (ESRD).1,2 Patients with both conditions are therefore at exceedingly high risk of adverse events, and diabetic nephropathy is the most common cause of ESRD in North America, accounting for approximately 40% of patients undergoing incident dialysis.3,4 Given projected increases in the prevalence of DM in developing countries, the global burden of diabetic kidney disease is expected to increase dramatically in the coming decades.5

Targeting hemoglobin A1c (HbA1c) values lower than 7% slows progression of diabetic kidney disease, including both the onset of microalbuminuria and progression to overt nephropathy.6,7 (To convert HbA1c to a proportion of total hemoglobin, multiply by 0.01.) However, the link between intensive glycemic control and CV events or all-cause mortality is more complex and still debated.8 For example, one recent trial demonstrated that targeting HbA1c levels lower than 6% increased mortality in higher-risk patients with type 2 DM.9

Despite the importance of diabetic kidney disease, the impact of glycemic control on outcomes in patients with DM and CKD is unknown because most trials of glycemic control have excluded those with reduced glomerular filtration rate (GFR). Indeed, while current National Kidney Foundation's Kidney Disease Outcomes Quality Initiative guidelines10(pS62) suggest a target HbA1c level of 7% “for all diabetic patients with or without chronic kidney disease,” very little evidence supports this recommendation.

We designed this study to determine whether HbA1c level is independently associated with important clinical outcomes, such as all-cause mortality, CV events, hospitalizations, and kidney failure, in people with DM and stage 3 to 4 CKD. We hypothesized that an increased HbA1c level would be associated with an increased risk of all adverse outcomes.

SETTING AND PARTICIPANTS

Data from the Alberta Kidney Disease Network11 (Canada) and the provincial health ministry (Alberta Health and Wellness) were used for this study. From all outpatients older than 18 years who had their serum creatinine level measured in Alberta at least once between January 1, 2005, and December 31, 2006, we selected those with an eGFR of 15.0 to 59.9 mL/min/1.73 m2 and DM. We estimated GFR using the Modification of Diet in Renal Disease (MDRD) study equation because it is the most widely used formula and is recommended by current guidelines.10 We identified DM using validated algorithms (2 physician billing claims in a 2-year period or 1 hospital discharge ever with a diagnosis of DM, excluding gestational DM).12 Of 32 555 people with DM and an eGFR of 15.0 to 59.9 mL/min/1.73 m2, we excluded 436 people (1%) with ESRD receiving hemodialysis or transplantation before their first creatinine measurement in 2005 or 2006 (their index date), those without HbA1c measurements during the 6-month period after the first eGFR index date (8041 [25%]), and those of First Nations origin (782 [2%]); because we did not have complete data for this population. Patients were classified into 3 groups based on their first HbA1c measurement during the study period: HbA1c level lower than 7%; HbA1c level of 7% to 9%; and HbA1c level greater than 9%. Comorbidity was assessed by using physician claims and hospitalization data together with validated algorithms13 for the variables listed in Table 1. The median household income for each postal code was obtained using data from the 2006 Canadian census.14

Table Graphic Jump LocationTable 1. Demographic and Clinical Characteristics, by Baseline Hemoglobin A1c Levela
OUTCOMES

The primary outcome for this study was all-cause mortality. All-cause mortality, dates of hospitalization, first hospitalization for CV events (myocardial infarction, stroke, coronary revascularization, heart failure requiring hospitalization), and the date of first renal replacement therapy for people who developed ESRD were determined by linkage to the provincial health ministry and the provincial renal databases. Coronary revascularization (percutaneous coronary intervention or coronary artery bypass graft surgery) was identified by procedure codes from records of hospitalizations; myocardial infarction, stroke, and heart failure were based on most responsible diagnosis for hospitalizations using validated algorithms.1517 Progression of kidney disease was based on a sustained doubling in serum creatinine value18 and defined only for participants with at least 2 serum creatinine values; participants whose serum creatinine value doubled from baseline but then declined to less than twice the original value on a subsequent measurement were not considered to have experienced disease progression.

STATISTICAL ANALYSIS

Baseline characteristics stratified by HbA1c level were given as means or proportions. Poisson regression models (including the number of days at risk as offset) were used for hospitalization rate analyses. Cox proportional hazards models were used for time-to-event analyses, stratified by health service regions. The proportional hazards assumption was tested using log-negative-log survival plots. All models to assess association between HbA1c levels and outcomes were adjusted for the following potential confounders: age, sex, index eGFR, individual health insurance premium level (a marker of individual-level income), median neighborhood income, comorbidity, and residence location. Because services available to Albertans with CKD may differ by residence location, we did Poisson regression using robust estimates of variance, defining the cluster (grouping) variable by the health region. Because remote residence location was associated with adverse outcomes in patients with CKD, and to further account for any effect of residence location on outcomes, we adjusted both Cox and Poisson models for distance between each patient's residence and the closest nephrologist as previously described.19,20 We used a restricted cubic spline function with 3 knots to allow for a nonlinear association between the clinical outcomes and HbA1c level. Statistical significance was set at P = .05, and all statistical tests were 2 sided. Censoring occurred with death, first event of interest in analyses of nonfatal events, disenrollment from the health plan, or end-of-study date (March 31, 2009).

We also performed several sensitivity analyses. First, we explored the potential effect of misclassification of HbA1c level by using the mean value of all measurements made during the 6-month exposure period to reclassify HbA1c categories. Second, we considered HbA1c level as a continuous rather than a categorical variable. Third, we considered baseline eGFR as a continuous variable in a similar manner. Fourth, we considered HbA1c level as a time-dependent covariate using all available HbA1c values prior to the date of each adverse outcome.

The institutional review boards for the Universities of Alberta and Calgary approved the study. Analyses were performed using SAS (version 9.2; SAS Institute Inc, Cary, North Carolina) and Stata SE (version 10.1; StataCorp LP, College Station, Texas) software.

Characteristics of the 23 296 participants by HbA1c level are shown in Table 1; a comparison between included and excluded participants is shown in eTable 1. Overall, 21 155 participants had stage 3 CKD (eGFR, 30.0-59.9 mL/min/1.73 m2), and 2141 had stage 4 CKD (eGFR, 15.0-29.9 mL/min/1.73 m2). As shown in Table 1, people with a higher HbA1c level were younger, more likely to be male, and had lower socioeconomic status.

The distribution of HbA1c levels in study participants with stage 3 and stage 4 CKD is shown in Figure 1 and as a function of eGFR in the eFigure. During the median follow-up period (3.8 years [range, 1-51 months]), 16% of patients died, 49% were hospitalized, 16% had any CV event (3% stroke, 5% myocardial infarction, 8% acute heart failure), 6% had sustained doubling of serum creatinine value, and 2% developed ESRD.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Histogram of observed hemoglobin A1c (HbA1c) values in people with stage 3 to 4 chronic kidney disease. The superimposed spline plot shows the adjusted risk of all-cause mortality as a function of HbA1c level. The solid black line represents the adjusted hazard ratio (HR) of all-cause mortality associated with a given HbA1c level higher than 9% compared with a level lower than 6.5%. The shaded area represents the 95% CIs. Models were adjusted for age, sex, index estimated glomerular filtration rate, individual health insurance premium level, median neighborhood income, comorbidity, and residence location. To convert HbA1c to a proportion of total hemoglobin, multiply by 0.01.

RELATION BETWEEN HbA1c LEVEL AND ALL-CAUSE MORTALITY

For both stage 3 and stage 4 CKD, there was an increased risk of death associated with higher levels of HbA1c (P value for trend <.001 for both comparisons). Compared with an HbA1c level lower than 7%, an HbA1c level higher than 9% was associated with significantly higher mortality among people with stage 3 and 4 CKD (adjusted hazard ratio [HR], 1.35; 95% CI, 1.21-1.50); the magnitude of the increased risk was similar for stage 3 and stage 4 CKD when considered separately (Table 2 and Table 3). A test for interaction between stage of CKD and HbA1c level and the risk of mortality was nonsignificant (P = .72).

Table Graphic Jump LocationTable 2. Adjusted Risk of Adverse Outcomes Among People With Stage 3 CKD, by Baseline HbA1c Level
Table Graphic Jump LocationTable 3. Adjusted Risk of Adverse Outcomes Among People With Stage 4 CKD, by Baseline HbA1c Level
RELATION BETWEEN HbA1c LEVEL AND NONFATAL EVENTS

Similar findings were observed for each of myocardial infarction, stroke, and heart failure, as well as CV events in aggregate and all-cause hospitalization: a graded independent increase in risk was observed at higher levels of HbA1c in all analyses and remained significant for stage 3 and stage 4 CKD separately in 4 stratified analyses (Table 2 and Table 3). Tests for interaction between stage of CKD and the risk of these events were all nonsignificant (P = .49, .89, .07, .30, and .34, respectively).

RELATION BETWEEN HbA1c LEVEL AND PROGRESSIVE KIDNEY FUNCTION LOSS

We also observed independent and statistically significant relationships between higher HbA1c level and the risk of a sustained doubling of serum creatinine or the development of ESRD (P value for trend <.001 for both comparisons). For doubling of creatinine, there was no significant interaction according to stage of CKD (P = .65). The magnitude of the increased risk for ESRD associated with higher HbA1c levels seemed lower for those with stage 4 CKD at baseline, compared with those with stage 3 CKD (P value for interaction <.001): among those with stage 4 CKD, the risk of ESRD was increased by 3% and 13% in patients with HbA1c levels of 7% to 9% and higher than 9%, respectively, compared with patients with HbA1c levels lower than 7% (P < .001; Table 3); corresponding findings for those in stage 3 were 22% and 152%, respectively (Table 2).

SENSITIVITY ANALYSES

Because of suggestions that both high and low values of HbA1c might be harmful,9,21 we performed additional analyses that used nonlinear splines to examine the association between adverse outcomes and HbA1c level modeled as a continuous variable. We observed a U-shaped relation between HbA1c level and mortality, and visual inspection of these plotted data suggested 2 inflection points: there was a significant increase in risk when HbA1c values were higher than 8% and when they were lower than 6.5% (Figure 1). There was no evidence of increased risk for myocardial infarction, stroke, heart failure, or ESRD at lower levels of HbA1c (data not shown).

EFFECT MODIFICATION OF BASELINE eGFR ON ASSOCIATION BETWEEN HbA1c LEVEL AND OUTCOMES

We tested for interactions between baseline HbA1c level and baseline eGFR (as a continuous variable) on the risk of the clinical outcomes. None were statistically significant except for analyses related to ESRD (P = .02). Therefore, we modeled the association between HbA1c level and the risk of ESRD as a continuous variable and found a direct relation between the excess risk associated with higher HbA1c level and baseline eGFR (Figure 2).

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Association between hemoglobin A1c (HbA1c) and risk of end-stage renal disease (ESRD) modeled as a spline function of baseline glomerular filtration rate. The solid black line represents the adjusted hazard ratio (HR) of ESRD associated with an HbA1c level higher than 9% compared with a level lower than 7%, modeled as a function of estimated glomerular filtration rate (eGFR). The shaded area represents the 95% CIs. Models were adjusted for age, sex, index eGFR, individual health insurance premium level, median neighborhood income, comorbidity, and residence location. To convert HbA1c to a proportion of total hemoglobin, multiply by 0.01.

ALTERNATIVE METHODS OF CLASSIFYING HbA1c LEVEL STATUS

In primary analyses, only the first HbA1c value during the study period was included to represent overall glycemic control. To reduce the risk that our results were influenced by misclassification, we repeated all analyses using the mean of all measurements made during the exposure period to classify participants with respect to HbA1c level. Results of these analyses were very similar to those of the primary analyses; the magnitude of the association between higher HbA1c levels and the risk of adverse outcomes seemed similar or stronger, and all tests for trend remained significant (P < .001 for all comparisons). Finally, we repeated analyses using HbA1c level as a time-varying covariate, and all results were very similar to those in the primary analysis (eTable 2 and eTable 3).

We studied data from almost 24 000 adults with DM and stage 3 to 4 CKD (eGFR, 15.0-59.9 mL/min/1.73 m2) treated in a universal health care system within a single Canadian province. In contrast to findings from patients with kidney failure,2224 we found strong and independent associations between higher levels of HbA1c and multiple clinically relevant outcomes, including mortality, CV events, hospitalization, and progression to kidney failure. These relations remained significant after controlling for multiple potential confounders, were observed in both stage 3 and stage 4 CKD, and were robust to a variety of sensitivity analyses. Consistent with findings from trials in the general population with DM,9,25 we also found that levels of HbA1c greater than 8.0% as well as levels lower than 6.5% were associated with increased mortality. Furthermore, our results suggest that many previous analyses that have considered HbA1c values of less than 6% to 7% as a homogenous reference group may have systematically underestimated the strength of association between elevated HbA1c levels and adverse events.26,27 Thus, our results have both clinical and scientific implications with respect to studies of glycemic control and adverse events.

Better glycemic control does help to prevent nephropathy and other microvascular complications of DM in people without CKD. For example, in patients with type 1 DM, the Diabetes Control and Complications Trial (DCCT) showed that a target HbA1c level of 7% (vs 9%) over 9 years reduced the risk of microalbuminuria and macroalbuminuria by 34% and 56%, respectively.6 The DCCT-EDIC (Epidemiology of Diabetes Interventions and Complications) study followed patients for another 8 years after DCCT closeout and showed evidence of so-called legacy effects with respect to glycemic control: ongoing benefits in terms of developing microalbuminuria or macroalbuminuria as well as a significant 75% reduction in the risk of incident “renal failure” (creatinine level >177 μmol/L; to convert to conventional units, divide by 88.4).28 Similarly, the UK Prospective Diabetes Study (UKPDS) showed that more intensive glycemic control (HbA1c level of 7.0% vs 7.9%) in patients newly diagnosed as having type 2 DM was associated with significant and sustained reductions in the risk of microalbuminuria, macroalbuminuria, and doubling of serum creatinine level over a 10-year period.7 Based on trials such as these, most guidelines have extrapolated broadly and recommend an HbA1c target level of 7.0% for patients with CKD, even though this population has been specifically excluded from the seminal trials of glycemic control for type 1 or type 2 DM.10,29

Since the risk of adverse events such as hypoglycemia may be greater at lower levels of kidney function,30 some have suggested that more liberal target levels for glycemic control may be appropriate for people with CKD,31 especially since microvascular damage has already occurred. Although better glycemic control was associated with lower risk of all-cause mortality irrespective of baseline kidney function, we found that the association between better glycemic control and decreased risk of ESRD was attenuated at lower levels of baseline eGFR. We speculate that this finding may represent a “point of no return” for kidney function—beyond which better glycemic control may simply not be enough to prevent progressive kidney function loss.

In contrast to data on microvascular outcomes, the link between better glycemic control and macrovascular outcomes in the general population of patients with DM is less clear. Long-term follow-up from DCCT and UKPDS suggest that more intensive glycemic control may reduce the risk of CV events and death.25,28 However, 2 recent trials found that HbA1c target levels below 6.5% led to increased CV mortality9 or no reduction in CV events32 in people with type 2 DM. Our findings of higher risk associated with both lower and higher levels of HbA1c are broadly consistent with these results and suggest that there is little evidence of benefit with respect to macrovascular events when HbA1c levels are much below 7.0%. That said, to our knowledge, there are no prior studies addressing the potential benefits or harms of better glycemic control on macrovascular outcomes in people with stage 3 or 4 CKD. As with participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial, it is plausible that patients with DM and CKD who are treated to an HbA1c level lower than 6.5% might experience iatrogenic harm owing to serious hypoglycemic events or too precipitous a fall in average glucose.9

Our current findings contrast with those of previous studies in patients undergoing hemodialysis, several of which show little or no association between HbA1c level and mortality.21-23 While these studies were not designed to explain the mechanism mediating the association between glycemic control and outcomes, one might speculate that competing causes of mortality in patients undergoing hemodialysis may attenuate any such association. In addition, the largest such study found that higher levels of HbA1c were associated with increased mortality in patients undergoing hemodialysis33 after adjustment for markers of malnutrition or chronic inflammation. Although it is possible that residual confounding by these characteristics have influenced our findings, the malnutrition-inflammation syndrome is substantially less common in patients with milder forms of CKD, such as those in the current study.34,35 Perhaps for these reasons, our findings seem more similar to the association between HbA1c level and outcomes in the general population than in people with hemodialysis-dependent kidney failure.

Strengths of our study include the inclusion of a population-based cohort treated in a universal health care system. We used validated techniques to select patients with diagnosed DM and CKD, and we studied clinically relevant outcomes. Our findings were robust to multiple sensitivity analyses, and the excess risk was both statistically and clinically significant. Despite its novelty and strengths, our study also has several important limitations that deserve mention. First, this was a retrospective observation study that cannot confirm the benefit (or harm) of more intensive glycemic control or the manner in which this control is achieved. Second, while we controlled for many important clinical and demographic factors, we could not control for certain potential confounders, such as use of insulin, epoetin, or other medications; overall intensity of DM care; blood pressure control; and laboratory markers, such as hemoglobin or markers of inflammation or malnutrition. Third, we included only patients with HbA1c measured as part of their routine clinical care and not part of a study protocol. Although all patients had access to medical services in Alberta's publicly funded health care system, we may not have captured data for individuals who chose not to be tested or who were unaware of their DM status. Fourth, we used HbA1c level as our index of glycemic control. Although HbA1c level may not correlate well with measured glycemic control in the setting of kidney failure (especially when epoetin is used), this does not seem to apply to earlier stages of CKD,31 suggesting that HbA1c level is an appropriate index of glycemic control for our study population. Fifth, our definition of CKD was based on a single measurement of serum creatinine, which may have led to misclassification in some individuals. At the least, our sensitivity analyses suggest this misclassification is likely either nondifferential or at worst would tend to bias our findings to the null because of regression to the mean. Finally, we could not distinguish type 1 from type 2 DM, nor did we have any measures of the clinical severity of DM itself.

In summary, we found that both higher and lower levels of HbA1c were associated with adverse events in a large population of patients with DM and stage 3 to 4 CKD. Our findings are consistent with the hypothesis that (as in the general population of patients with DM) better glycemic control in patients with stage 3 to 4 CKD tends to improve clinical outcomes, but that overly intensive therapy (ie, HbA1c target level lower than 7%) may be harmful. This speculation requires confirmation in an adequately powered randomized trial.

Correspondence: Marcello Tonelli, MD, SM Department of Medicine, University of Alberta, 7-129 Clinical Science Bldg, 8440 112th St, Edmonton, AB T6B 2G3, Canada (mtonelli-admin@med.ualberta.ca).

Accepted for Publication: August 15, 2011.

Author Contributions: Dr Tonelli had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Bello and Tonelli. Acquisition of data: Hemmelgarn, Klarenbach, Manns, Bello, and Tonelli. Analysis and interpretation of data: Shurraw, Hemmelgarn, Lin, Majumdar, Bello, James, Turin, and Tonelli. Drafting of the manuscript: Shurraw, Hemmelgarn, Lin, Bello, and Tonelli. Critical revision of the manuscript for important intellectual content: Shurraw, Hemmelgarn, Majumdar, Klarenbach, Manns, Bello, James, and Tonelli. Statistical analysis: Shurraw, Lin, Majumdar, Bello, Turin, and Tonelli. Obtained funding: Manns. Administrative, technical, and material support: Hemmelgarn and Manns. Study supervision: Tonelli.

Financial Disclosure: None reported.

Funding/Support: This work was funded by an operating grant from the Heart and Stroke Foundation of Canada, and by an interdisciplinary team grant from the Alberta Heritage Foundation for Medical Research (AHFMR). Drs Hemmelgarn, Tonelli, Majumdar, and Klarenbach were supported by career salary awards from the AHFMR. Dr Tonelli was also supported by a Government of Canada Research Chair. Drs Hemmelgarn, Klarenbach, Manns, and Tonelli were all supported by a joint initiative between Alberta Health and Wellness and the Universities of Alberta and Calgary.

Role of the Sponsor: The funding organizations played no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of the manuscript.

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Chen H, Cohen P, Chen S. Biased odds ratios from dichotomization of age.  Stat Med. 2007;26(18):3487-3497
PubMed   |  Link to Article
Gamble JM, Eurich DT, Marrie TJ, Majumdar SR. Admission hypoglycemia and increased mortality in patients hospitalized with pneumonia.  Am J Med. 2010;123(6):556- e11-e16
PubMed   |  Link to Article
Nathan DM, Cleary PA, Backlund JY,  et al; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study Research Group.  Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes.  N Engl J Med. 2005;353(25):2643-2653
PubMed   |  Link to Article
American Diabetes Association.  Standards of medical care in diabetes: 2011.  Diabetes Care. 2011;34:(suppl 1)  S11-S61
PubMed   |  Link to Article
Moen MF, Zhan M, Hsu VD,  et al.  Frequency of hypoglycemia and its significance in chronic kidney disease.  Clin J Am Soc Nephrol. 2009;4(6):1121-1127
PubMed   |  Link to Article
Schernthaner G, Ritz E, Schernthaner GH. Strict glycaemic control in diabetic patients with CKD or ESRD: beneficial or deadly?  Nephrol Dial Transplant. 2010;25(7):2044-2047
PubMed   |  Link to Article
Patel A, MacMahon S, Chalmers J,  et al; ADVANCE Collaborative Group.  Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes.  N Engl J Med. 2008;358(24):2560-2572
PubMed   |  Link to Article
Kalantar-Zadeh K, Kopple JD, Regidor DL,  et al.  A1C and survival in maintenance hemodialysis patients.  Diabetes Care. 2007;30(5):1049-1055
PubMed   |  Link to Article
Kopple JD, Greene T, Chumlea WC,  et al.  Relationship between nutritional status and the glomerular filtration rate: results from the MDRD study.  Kidney Int. 2000;57(4):1688-1703
PubMed   |  Link to Article
Panichi V, Migliori M, De Pietro S,  et al.  C-reactive protein and interleukin-6 levels are related to renal function in predialytic chronic renal failure.  Nephron. 2002;91(4):594-600
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Graphic Jump Location

Figure 1. Histogram of observed hemoglobin A1c (HbA1c) values in people with stage 3 to 4 chronic kidney disease. The superimposed spline plot shows the adjusted risk of all-cause mortality as a function of HbA1c level. The solid black line represents the adjusted hazard ratio (HR) of all-cause mortality associated with a given HbA1c level higher than 9% compared with a level lower than 6.5%. The shaded area represents the 95% CIs. Models were adjusted for age, sex, index estimated glomerular filtration rate, individual health insurance premium level, median neighborhood income, comorbidity, and residence location. To convert HbA1c to a proportion of total hemoglobin, multiply by 0.01.

Place holder to copy figure label and caption
Graphic Jump Location

Figure 2. Association between hemoglobin A1c (HbA1c) and risk of end-stage renal disease (ESRD) modeled as a spline function of baseline glomerular filtration rate. The solid black line represents the adjusted hazard ratio (HR) of ESRD associated with an HbA1c level higher than 9% compared with a level lower than 7%, modeled as a function of estimated glomerular filtration rate (eGFR). The shaded area represents the 95% CIs. Models were adjusted for age, sex, index eGFR, individual health insurance premium level, median neighborhood income, comorbidity, and residence location. To convert HbA1c to a proportion of total hemoglobin, multiply by 0.01.

Tables

Table Graphic Jump LocationTable 1. Demographic and Clinical Characteristics, by Baseline Hemoglobin A1c Levela
Table Graphic Jump LocationTable 2. Adjusted Risk of Adverse Outcomes Among People With Stage 3 CKD, by Baseline HbA1c Level
Table Graphic Jump LocationTable 3. Adjusted Risk of Adverse Outcomes Among People With Stage 4 CKD, by Baseline HbA1c Level

References

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PubMed   |  Link to Article
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Kokotailo RA, Hill MD. Coding of stroke and stroke risk factors using International Classification of Diseases, Revisions 9 and 10 Stroke. 2005;36(8):1776-1781
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Levey AS. Assessing the effectiveness of therapy to prevent the progression of renal disease.  Am J Kidney Dis. 1993;22(1):207-214
PubMed
Rucker D, Hemmelgarn BR, Lin M,  et al.  Quality of care and mortality are worse in chronic kidney disease patients living in remote areas.  Kidney Int. 2011;79(2):210-217
PubMed   |  Link to Article
Tonelli M, Manns B, Culleton B,  et al; Alberta Kidney Disease Network.  Association between proximity to the attending nephrologist and mortality among patients receiving hemodialysis.  CMAJ. 2007;177(9):1039-1044
PubMed   |  Link to Article
Johnston SS, Conner C, Aagren M, Smith DM, Bouchard J, Brett J. Evidence linking hypoglycemic events to an increased risk of acute cardiovascular events in patients with type 2 diabetes.  Diabetes Care. 2011;34(5):1164-1170
PubMed   |  Link to Article
Shurraw S, Majumdar SR, Thadhani R, Wiebe N, Tonelli M.Alberta Kidney Disease Network.  Glycemic control and the risk of death in 1,484 patients receiving maintenance hemodialysis.  Am J Kidney Dis. 2010;55(5):875-884
PubMed   |  Link to Article
Williams ME, Lacson E Jr, Wang W, Lazarus JM, Hakim R. Glycemic control and extended hemodialysis survival in patients with diabetes mellitus: comparative results of traditional and time-dependent Cox model analyses.  Clin J Am Soc Nephrol. 2010;5(9):1595-1601
PubMed   |  Link to Article
Okada T, Nakao T, Matsumoto H,  et al.  Association between markers of glycemic control, cardiovascular complications and survival in type 2 diabetic patients with end-stage renal disease.  Intern Med. 2007;46(12):807-814
PubMed   |  Link to Article
Holman RR, Paul SK, Bethel MA, Matthews DR, Neil HA. 10-year follow-up of intensive glucose control in type 2 diabetes.  N Engl J Med. 2008;359(15):1577-1589
PubMed   |  Link to Article
Chen H, Cohen P, Chen S. Biased odds ratios from dichotomization of age.  Stat Med. 2007;26(18):3487-3497
PubMed   |  Link to Article
Gamble JM, Eurich DT, Marrie TJ, Majumdar SR. Admission hypoglycemia and increased mortality in patients hospitalized with pneumonia.  Am J Med. 2010;123(6):556- e11-e16
PubMed   |  Link to Article
Nathan DM, Cleary PA, Backlund JY,  et al; Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study Research Group.  Intensive diabetes treatment and cardiovascular disease in patients with type 1 diabetes.  N Engl J Med. 2005;353(25):2643-2653
PubMed   |  Link to Article
American Diabetes Association.  Standards of medical care in diabetes: 2011.  Diabetes Care. 2011;34:(suppl 1)  S11-S61
PubMed   |  Link to Article
Moen MF, Zhan M, Hsu VD,  et al.  Frequency of hypoglycemia and its significance in chronic kidney disease.  Clin J Am Soc Nephrol. 2009;4(6):1121-1127
PubMed   |  Link to Article
Schernthaner G, Ritz E, Schernthaner GH. Strict glycaemic control in diabetic patients with CKD or ESRD: beneficial or deadly?  Nephrol Dial Transplant. 2010;25(7):2044-2047
PubMed   |  Link to Article
Patel A, MacMahon S, Chalmers J,  et al; ADVANCE Collaborative Group.  Intensive blood glucose control and vascular outcomes in patients with type 2 diabetes.  N Engl J Med. 2008;358(24):2560-2572
PubMed   |  Link to Article
Kalantar-Zadeh K, Kopple JD, Regidor DL,  et al.  A1C and survival in maintenance hemodialysis patients.  Diabetes Care. 2007;30(5):1049-1055
PubMed   |  Link to Article
Kopple JD, Greene T, Chumlea WC,  et al.  Relationship between nutritional status and the glomerular filtration rate: results from the MDRD study.  Kidney Int. 2000;57(4):1688-1703
PubMed   |  Link to Article
Panichi V, Migliori M, De Pietro S,  et al.  C-reactive protein and interleukin-6 levels are related to renal function in predialytic chronic renal failure.  Nephron. 2002;91(4):594-600
PubMed   |  Link to Article

Correspondence

April 9, 2012
Arch Intern Med. 2012;172(7):597-598. doi:10.1001/archinternmed.2012.129.
April 9, 2012
Arch Intern Med. 2012;172(7):597-598. doi:10.1001/archinternmed.2012.227.
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