Abstract
Purpose
Diabetes mellitus is a risk factor for the development and progression of chronic kidney disease (CKD). However, the association of prediabetes with adverse kidney outcomes is uncertain.
Methods
We performed a secondary analysis of the Systolic Blood Pressure Intervention Trial (SPRINT), including 9361 participants without diabetes at baseline. We categorized participants according to fasting glucose level as having impaired fasting glucose [≥100 mg/dL (≥5.6 mmol/L)] or normoglycemia [<100 mg/dL (<5.6 mmol/L)]. Unadjusted and adjusted proportional hazards models were fitted to estimate the association of impaired fasting glucose (vs normoglycemia) with a composite outcome of worsening kidney function [≥30% decrease in estimated glomerular filtration rate (eGFR) to <60 mL/min/1.73 m2 in participants without baseline CKD; ≥50% decrease in eGFR or need for long-term dialysis/kidney transplantation in participants with CKD] or incident albuminuria (doubling of urinary albumin/creatinine ratio from <10 mg/g to >10 mg/g). These outcomes were also evaluated separately and according to CKD status at baseline.
Results
Participants’ mean age was 67.9 ± 9.4 years, 35.5% were female, and 31.4% were black. The median follow-up was 3.3 years, and 41.8% had impaired fasting glucose. Impaired fasting glucose was not associated with higher rates of the composite outcome [hazard ratio (HR): 0.97; 95% CI: 0.8 to 1.16], worsening kidney function (HR: 1.02; 95% CI: 0.75 to 1.37), or albuminuria (HR: 0.98; 95% CI: 0.78 to 1.23). Similarly, there was no association of impaired fasting glucose with outcomes according to baseline CKD status.
Conclusions
Impaired fasting glucose at baseline was not associated with the development of worsening kidney function or albuminuria in participants of SPRINT.
In patients with high cardiovascular risk, impaired fasting glucose was not associated with a higher incidence of CKD, worsening kidney function, or incident albuminuria compared with normoglycemia.
Diabetes mellitus (DM) is a major global health problem, affecting 14.3% of adults in the United States (1) with type 2 DM accounting for the majority of adult cases (2). DM in general is known to be a major risk factor for the development and progression of chronic kidney disease (CKD) and albuminuria (3), and it remains the predominant cause of end-stage renal disease (ESRD) in the United States (4). Both CKD and DM are associated with an increased risk for cardiovascular (CV) events and death (5), with their coexistence associated with a multiplicative risk (6).
Diabetes is generally thought to develop along a spectrum from normoglycemia to abnormal glycemia, with an intervening period of “prediabetes” (i.e., abnormal glucose concentrations that do not meet the diagnostic criteria for diabetes). According to the recommendations of the American Diabetes Association (7), prediabetes is defined by impaired fasting glucose [fasting plasma glucose level of 100 to 125 mg/dL (5.6 to 6.9 mmol/L)], impaired glucose tolerance [2-hour plasma glucose value between 140 and 199 mg/dL (between 7.8 and 11.0 mmol/L) after a 75-g oral glucose tolerance test], or HbA1c value of 5.7% to 6.4%. As with DM in general, the worldwide prevalence of prediabetes is increasing, with more than 470 million people expected to have this condition by 2030 (8). Although the presence of prediabetes is associated with higher CV risk, the association of prediabetes with development of CKD is less clear (9–12). The large number of nondiabetic participants, baseline determination of fasting plasma glucose level, detailed documentation, and follow-up of the Systolic Blood Pressure Intervention Trial (SPRINT) provided a unique opportunity to assess the association of impaired fasting glucose with adverse renal outcomes. We hypothesized that the presence of baseline impaired fasting glucose would be associated with a higher risk of worsening kidney function, CKD, and incident albuminuria.
Research Design and Methods
Study design and population
We performed a secondary analysis of SPRINT data to evaluate the association of impaired fasting glucose with adverse renal outcomes. SPRINT was a multicenter, randomized, controlled trial including 9361 patients aged ≥50 years with hypertension and an increased risk of CV events. Increased CV risk was defined by the presence of at least one of the following: clinical or subclinical CV disease; CKD, defined by an estimated glomerular filtration rate (eGFR) of 20 to 59 mL/min/1.73 m2; a 10-year risk of CV disease of 15% or greater on the basis of the Framingham risk score; or age ≥75 years. Patients with DM or prior stroke were excluded. Detailed inclusion and exclusion criteria have been published (13). Eligible participants were randomly assigned to a systolic blood pressure target of <140 mm Hg (standard treatment) or <120 mm Hg (intensive treatment). The study was approved by the institutional review board at each participating study site, and written informed consent was obtained from all participants. The intervention was stopped early after a median follow-up of 3.26 years owing to a significantly lower rate of the primary composite outcome in the intensive-treatment group (13). The data for this analysis were obtained as a part of the SPRINT Data Analysis Challenge (14).
Exposures
Participants were categorized into two groups according to fasting plasma glucose level at randomization, using the American Diabetes Association cutoff of 100 mg/dL (5.6 mmol/L) (15). Participants with a fasting plasma glucose level ≥100 mg/dL (≥5.6 mmol/L) were classified as having impaired fasting glucose; those with fasting plasma glucose level <100 mg/dL (<5.6 mmol/L) were classified as being normoglycemic. We excluded participants with missing data on fasting plasma glucose level at the randomization visit and those with missing data on all the renal outcomes evaluated (n = 40).
Study outcomes
The composite renal outcome was defined by worsening kidney function or incident albuminuria, both as prespecified in SPRINT. In participants without CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of ≥30% to a value of <60 mL/min/1.73 m2 on two consecutive laboratory determinations collected at 3-month intervals. In participants with CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of ≥50% or the development of ESRD requiring long-term dialysis or kidney transplantation. Incident albuminuria was defined for all study participants by a doubling of the urinary albumin/creatinine ratio from <10 mg/g at baseline to >10 mg/g during follow-up. The increase in urinary albumin/creatinine ratio had to be observed at two visits at least 3 months apart. As a secondary analysis, we evaluated the association of impaired fasting glucose with all-cause mortality. Medical records were obtained for documentation of clinical events and were reviewed by investigators masked to treatment assignment. At-risk time was considered to begin at the time of randomization. Participants were followed up until the occurrence of the outcomes of interest, censoring (date of last event ascertainment), or study completion.
Study data
Detailed definitions of the variables used in SPRINT were previously reported (16). Briefly, trained study personnel collected sociodemographic characteristics at baseline using structured interviews. Clinical and laboratory evaluations were performed every 3 months thereafter. The blood samples were centrifuged and shipped on ice to the central laboratory. Fasting plasma glucose level was measured in serum using the hexokinase method on a Roche analyzer. Four racial/ethnic groups were considered: non-Hispanic white, non-Hispanic black, Hispanic, and other race or ethnicity. Blood pressure was measured with an automated measurement system (Model 907; Omron Healthcare). A mean of three blood pressure measurements at an office visit while the patient was seated and after 5 minutes of quiet rest was considered. Body mass index (BMI) was calculated as the body weight in kilograms divided by the square of height in meters.
Statistical analysis
Continuous variables were examined graphically and recorded as means (±SDs) for normally distributed data or as medians (with interquartile ranges) for nonnormally distributed data. Comparisons were made using t tests or Wilcoxon rank sum tests as appropriate. Categorical variables were examined by frequency distribution and recorded as proportions. Comparisons were made using the χ2 test.
Log-rank tests were used to compare Kaplan-Meier estimates for survival curves in the two treatment groups in a time-to-first-event analysis. Hazard ratios (HRs) and 95% CIs were estimated with a Cox proportional-hazards model, with stratification according to center. Initially, unadjusted models were fitted. Subsequently, multivariable models that adjusted for baseline age, sex, race (black, Hispanic, white, or other), smoking status (current, former/never), systolic blood pressure, prior CV disease, BMI, statin use, aspirin use, and trial treatment arm were fitted. The presence of effect modification for prespecified variables (age, sex, and treatment group) was assessed by inclusion of the relevant cross-product terms in adjusted models, with performance of the likelihood ratio test. We also analyzed the outcomes of interest in the prespecified subgroups of baseline CKD status (with or without CKD at baseline).
We performed two sensitivity analyses. First, we performed all the previously described analyses after excluding SPRINT participants who had a baseline fasting plasma glucose level ≥126 mg/dL (≥7.0 mmol/L), the cutoff for a diagnosis of diabetes (n = 295). Second, we performed all the previously described analyses, using a more stringent cutoff of ≥110 mg/dL (≥6.1 mmol/L) to define impaired fasting glucose as recommended by some organizations, including the World Health Organization (17). Two-sided P values <0.05 were considered statistically significant. All statistical analyses were performed using Stata software, version 14.2 (StataCorp).
Results
Baseline characteristics
A total of 9321 participants were analyzed, of whom 3897 (41.8%) had impaired fasting glucose and 5424 (58.2%) had normoglycemia. The mean age of the cohort was 67.9 ± 9.4 years; 35.5% were female, and 31.4% were black. At baseline, participants with impaired fasting glucose tended to be younger; were more likely to be male, white, and current smokers; were more likely to have prior CV disease, higher BMI, higher fasting triglyceride levels, and higher eGFR; and were more likely to be using a statin, aspirin, and a higher number of antihypertensive agents. Participants with impaired fasting glucose were also more likely to have lower systolic and diastolic blood pressure, lower total cholesterol, and lower high-density lipoprotein levels. There were no significant differences between groups according to baseline fasting glucose status (Table 1).
Table 1.
Baseline Characteristics of Study Participants According to Fasting Glucose Status
| Normoglycemia (n = 5424) | Impaired Fasting Glucose (n = 3897) | P Valuea | |
|---|---|---|---|
| Age, y | 68.1 ± 9.6 | 67.6 ± 9.2 | 0.02 |
| Female sex, n (%) | 2155 (39.7) | 1152 (29.6) | <0.001 |
| Race or ethnic group, n (%) | <0.001 | ||
| Non-Hispanic white | 2997 (55.3) | 2387 (61.3) | |
| Non-Hispanic black | 1764 (32.5) | 1021 (26.2) | |
| Hispanic | 565 (10.4) | 413 (10.6) | |
| Other | 98 (1.8) | 76 (2.0) | |
| Baseline blood pressure, mm Hg | |||
| Systolic | 140.2 ± 15.7 | 138.9 ± 15.4 | <0.001 |
| Diastolic | 78.5 ± 11.9 | 77.7 ± 12.0 | 0.001 |
| Antihypertensive agents, (n) | 2 (1–2) | 2 (1–3) | <0.001 |
| Cardiovascular disease, n (%) | 1046 (19.3) | 823 (21.1) | 0.03 |
| Body mass index, kg/m2 | 29.1 ± 5.7 | 30.9 ± 5.6 | <0.001 |
| Fasting plasma glucose level | <0.001 | ||
| mg/dL | 91 ± 6 | 110 ± 13 | |
| mmol/L | 5.1 ± 0.3 | 6.1 ± 0.7 | |
| Fasting total cholesterol level | <0.001 | ||
| mg/dL | 191 ± 41 | 188 ± 41 | |
| mmol/L | 4.9 ± 1.1 | 4.9 ± 1.1 | |
| Fasting HDL cholesterol level | <0.001 | ||
| mg/dL | 55 ± 15 | 50 ± 13 | |
| mmol/L | 1.4 ± 0.4 | 1.3 ± 0.3 | |
| Fasting total triglyceride level | <0.001 | ||
| mg/dL | 100 (73–137) | 116 (84–166) | |
| mmol/L | 1.1 (0.8–1.5) | 1.3 (0.9–1.9) | |
| Statin use, n (%) | 2213 (41.1) | 1832 (47.3) | <0.001 |
| Aspirin use, n (%) | 2682 (49.6) | 2064 (53.0) | 0.001 |
| Current smoker, n (%) | 2177 (40.1) | 1784 (45.8) | <0.001 |
| eGFR, mL/min/1.73 m2 | 71.3 ± 20.9 | 72.4 ± 20.2 | 0.01 |
| Chronic kidney disease, n (%) | 1576 (29.1) | 1069 (27.4) | 0.09 |
| Albumin/creatinine ratio, mg/g | 9.4 (5.7–21.3) | 9.5 (5.6–21.5) | 0.67 |
Values for continuous variables are given as mean ± SD or median (25th–75th percentile).
Abbreviation: HDL, high-density lipoprotein.
P values refer to a test for difference (t test for normally distributed continuous variables; Wilcoxon rank sum for nonnormally distributed continuous variables; and χ2 test for categorical variables) according to impaired fasting glucose vs normoglycemia.
Association of impaired fasting glucose with renal outcomes
The median (25th to 75th percentile) follow-up was 3.3 (2.8 to 3.8) years. The composite renal outcome occurred in 221 individuals (5.7%) with impaired fasting glucose and 314 (5.8%) with normoglycemia at baseline. Worsening kidney function occurred in 79 individuals (2.0%) with impaired fasting glucose and 114 (2.1%) with normoglycemia at baseline. Among the 4619 participants at risk of developing albuminuria as prespecified in SPRINT, this outcome occurred in 147 individuals with impaired fasting glucose (7.6% of those at risk and 3.8% of all participants) and 203 individuals with normoglycemia at baseline (7.5% of those at risk and 3.7% of all participants).
Impaired fasting glucose was not associated with higher rates of the composite renal outcome, worsening kidney function, or albuminuria in either unadjusted or adjusted analyses (Fig.1; Table 2). There was no evidence for effect modification of the composite renal outcome according to randomized treatment assignment (Pinteraction = 0.98), sex (Pinteraction = 0.17), or age (Pinteraction = 0.15). Similarly, there was no evidence for effect modification of worsening kidney function (Pinteraction = 0.38) or albuminuria (Pinteraction = 0.74) according to randomized treatment assignment. The results of the analysis according to subgroup of randomized treatment assignment are presented in an online repository (18).
Figure 1.
(A) Composite renal outcome, (B) worsening kidney function, and (C) incident albuminuria by fasting glucose status. The composite renal outcome was defined by worsening kidney function or incident albuminuria. In participants without CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 30% or more to a value of <60 mL/min/1.73 m2. In participants with CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 50% or more or the development of ESRD requiring long-term dialysis or kidney transplantation. Incident albuminuria was defined for all study participants by a doubling of the ratio of urinary albumin to creatinine from <10 mg/g at baseline to >10 mg/g during follow-up.
Table 2.
Association of Impaired Fasting Glucose vs Normoglycemia With Outcomes
| Outcome | Normoglycemia | Impaired Fasting Glucose | Hazard Ratio (95% CI) |
|---|---|---|---|
| No. of Events/No. at Risk (%) | |||
| Composite adverse renal outcomea | 314/5424 (5.8) | 221/3897 (5.7) | |
| Unadjusted model | 0.95 (0.80–1.14) | ||
| Adjusted model | 0.97 (0.81–1.16) | ||
| Worsening kidney functionb | 114/5424 (2.1) | 79/3897 (2.0) | |
| Unadjusted model | 0.91 (0.68–1.22) | ||
| Adjusted model | 1.02 (0.75–1.37) | ||
| Incident albuminuriac | 203/2691 (7.5) | 147/1928 (7.6) | |
| Unadjusted model | 1.01 (0.81–1.25) | ||
| Adjusted model | 0.98 (0.78–1.23) | ||
Adjusted model: age, sex, race, smoking status, systolic blood pressure, prior cardiovascular disease, body mass index, statin use, aspirin use, and trial treatment arm.
Defined by worsening kidney function or incident albuminuria.
In participants without CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 30% or more to a value of <60 mL/min/1.73 m2. In participants with CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 50% or more or the development of ESRD requiring long-term dialysis or kidney transplantation.
Defined for all study participants by a doubling of the ratio of urinary albumin/creatinine from <10 mg/g at baseline to >10 mg/g during follow-up.
There was no association of impaired fasting glucose with adverse renal outcomes in the sensitivity analyses that excluded participants with baseline fasting plasma glucose level ≥126 mg/dL, consistent with the main analyses (Table 3). Similarly, when the World Health Organization definition of impaired fasting glucose was assessed, no significant association of impaired fasting glucose with any adverse renal outcomes was found (Table 4).
Table 3.
Association of Impaired Fasting Glucose vs Normoglycemia With Outcomes [Excluding Patients With Fasting Plasma Glucose Level ≥126 mg/dL (≥7.0 mmol/L) at Baseline]
| Outcome | Normoglycemia | Impaired Fasting Glucose | Unadjusted Hazard Ratio | Adjusted Hazard Ratioa |
|---|---|---|---|---|
| No. of Events/No. at Risk (%) | ||||
| Composite adverse renal outcomeb | 314/5424 (5.8) | 198/3602 (5.5) | 0.93 (0.78–1.12) | 0.94 (0.78–1.14) |
| Worsening kidney functionc | 114/5424 (2.1) | 70/3602 (1.9) | 0.88 (0.65–1.19) | 0.98 (0.72–1.34) |
| Incident albuminuriad | 203/2691 (7.5) | 133/1796 (7.4) | 0.98 (0.78–1.23) | 0.96 (0.76–1.21) |
Adjusted model: age, sex, race, smoking status, systolic blood pressure, prior cardiovascular disease, body mass index, statin use, aspirin use, and trial treatment arm.
Defined by worsening kidney function or incident albuminuria.
In participants without CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 30% or more to a value of <60 mL/min/1.73 m2. In participants with CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 50% or more or the development of ESRD requiring long-term dialysis or kidney transplantation.
Defined for all study participants by a doubling of the ratio of urinary albumin/creatinine from <10 mg/g at baseline to >10 mg/g during follow-up.
Table 4.
Association of Impaired Fasting Glucose vs Normoglycemia With Outcomes Using the WHO Definition [Fasting Plasma Glucose ≥110 mg/dL (≥6.1 mmol/L)]
| Outcome | Normoglycemia | Impaired Fasting Glucose | Unadjusted Hazard Ratio | Adjusted Hazard Ratioa |
|---|---|---|---|---|
| No. of Events/No. at Risk (%) | ||||
| Composite adverse renal outcomeb | 439/7847 (5.6) | 96/1474 (6.5) | 1.14 (0.92–1.43) | 1.17 (0.93–1.47) |
| Worsening kidney functionc | 157/7847 (2.0) | 36/1474 (2.4) | 1.18 (0.82–1.70) | 1.28 (0.88–1.86) |
| Incident albuminuriad | 288/3903 (7.4) | 62/716 (8.7) | 1.19 (0.90–1.57) | 1.21 (0.90–1.61) |
Adjusted model: age, sex, race, smoking status, systolic blood pressure, prior cardiovascular disease, body mass index, statin use, aspirin use, and trial treatment arm.
Defined by worsening kidney function or incident albuminuria.
In participants without CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 30% or more to a value of <60 mL/min/1.73 m2. In participants with CKD at baseline, worsening kidney function was defined by a decrease in the eGFR of 50% or more or the development of ESRD requiring long-term dialysis or kidney transplantation.
Defined for all study participants by a doubling of the ratio of urinary albumin/creatinine from <10 mg/g at baseline to >10 mg/g during follow-up.
Association of impaired fasting glucose with renal outcomes according to CKD status at baseline
Among participants without CKD at baseline (n = 6676), 164 (2.5%) developed a ≥30% decrease in eGFR to <60 mL/min/1.73 m2, and 242 (of 3593; 6.7%) developed incident albuminuria. In participants with CKD at baseline (n = 2645), 29 (1.1%) presented with a ≥50% decrease in eGFR, long-term dialysis, or kidney transplantation, and 108 (of 1026; 10.5%) developed incident albuminuria. There were no significant differences in the unadjusted or adjusted effect estimates according to the presence or absence of CKD at baseline (Table 5).
Table 5.
Association of Impaired Fasting Glucose vs Normoglycemia With Outcomes According to Chronic Kidney Disease Status at Baseline
| Normoglycemia | Impaired Fasting Glucose | Hazard Ratio (95% CI) | |
|---|---|---|---|
| No. of Events/No. at Risk (%) | |||
| Participants without CKD at baseline | |||
| Composite adverse renal outcomea | 229/3848 (6.0) | 169/2828 (6.0) | |
| Unadjusted model | 0.98 (0.80–1.21) | ||
| Adjusted model | 1.00 (0.81–1.23) | ||
| ≥30% reduction in eGFR to <60 mL/min/1.73 m2 | 96/3848 (2.5) | 68/2828 (2.4) | |
| Unadjusted model | 0.90 (0.65–1.23) | ||
| Adjusted model | 1.02 (0.73–1.41) | ||
| Incident albuminuriab | 136/2071 (6.7) | 106/1522 (7.0) | |
| Unadjusted model | 1.09 (0.83–1.42) | ||
| Adjusted model | 1.05 (0.80–1.39) | ||
| Participants with CKD at baseline | (n = 1576) | (n = 1069) | |
| Composite adverse renal outcomea | 85/1576 (5.4) | 52/1069 (4.9) | |
| Unadjusted model | 0.85 (0.59–1.23) | ||
| Adjusted model | 0.86 (0.59–1.26) | ||
| ≥50% reduction in eGFR, long-term dialysis, or kidney transplantation | 10/1576 (0.6) | 11/1069 (1.0) | |
| Unadjusted model | 0.80 (0.37–1.74) | ||
| Adjusted model | 0.92 (0.41–2.06) | ||
| Incident albuminuriab | 67/620 (10.8) | 41/406 (10.1) | |
| Unadjusted model | 0.91 (0.59–1.39) | ||
| Adjusted model | 0.90 (0.57–1.40) | ||
Adjusted model: age, sex, race, smoking status, systolic blood pressure, prior cardiovascular disease, body mass index, statin use, aspirin use, and trial treatment arm.
Defined by worsening kidney function or incident albuminuria.
Defined for all study participants by a doubling of the ratio of urinary albumin/creatinine from <10 mg/g at baseline to >10 mg/g during follow-up.
Association of impaired fasting glucose with all-cause mortality
Impaired fasting glucose was not associated with an increased risk for mortality in either unadjusted analysis (HR: 0.93; 95% CI: 0.75 to 1.16) or adjusted analysis (HR: 0.96; 95% CI: 0.77 to 1.20). Furthermore, there was no evidence for effect modification of mortality according to the presence or absence of CKD at baseline (Pinteraction = 0.40) or randomized treatment assignment (Pinteraction = 0.70).
Conclusions
In our post hoc analysis of participants of the SPRINT trial, impaired fasting glucose at baseline was not associated with a higher incidence of CKD, worsening kidney function, or incident albuminuria in comparison with normoglycemia.
Previous studies evaluating the association of prediabetes with kidney disease have shown contradictory results (8–11, 19–26). Most studies suggesting a higher risk of kidney disease in patients with prediabetes are cross-sectional (21, 23–26), with obvious limitations in estimating temporal associations. One of the largest studies reporting a positive association of prediabetes with greater risk of CKD was a meta-analysis of 185,452 individuals (mainly Asian and white). Over 835,146 person-years of follow-up, the authors reported a modest increased risk of CKD development (HR: 1.12; 95% CI: 1.02 to 1.21) (11). However, the analyses were limited by significant heterogeneity across studies and limited ability to adjust for potentially confounding variables (11). Our finding of no association of impaired fasting glucose with renal outcomes is consistent with a study of 12,808 participants aged ≥20 years. Over a median follow-up of >10 years, both diabetes and hypertension were associated with an increased risk of CKD, whereas neither prediabetes nor prehypertension (individually or combined) was associated with an increased risk of CKD (12). Furthermore, in an analysis of 2398 participants in the Framingham Heart Study offspring cohort, which had a median follow-up of 7.0 years, neither impaired fasting glucose nor impaired glucose tolerance was associated with CKD development after adjustment for potential confounders (10). Of note, these studies did not include time-updated analyses, and most patients in the Framingham cohort had low to moderate CV risk, whereas patients included in the SPRINT trial were at higher risk for CV events.
In this study, impaired fasting glucose was not associated with all-cause mortality. Previous studies have had contradictory results regarding this association. Although most found increased mortality among patients with prediabetes (27–30), others found no association with mortality (31, 32). It should be noted that most previous studies that found an association between prediabetes and all-cause mortality included participants at low or moderate CV risk. The fact that all participants included in SPRINT had a higher baseline CV risk raises the possibility that impaired fasting glucose may not be associated with additional risk for mortality among those who are already at higher risk for CV events.
Prediabetes may be considered part of the continuum from normoglycemia to hyperglycemia with a greater associated risk of complications. Prediabetes raises short-term absolute risk of type 2 DM by threefold to 10-fold (33), and people with diabetes are vulnerable to multiple and complex medical complications, including CKD development and progression to ESRD (15, 34). In addition, prediabetes is frequently associated with comorbidities, particularly hypertension, that are also important risk factors for CKD (35). However, DM is diagnosed on the basis of glucose levels that have been associated with higher risk of development of end-organ complications (34). Thus, it is possible that the pathophysiological mechanisms involved in the renal adverse outcomes observed in DM may not be present at the glycemic levels in prediabetes. In this regard, it is interesting to note that plasma glucose levels in prediabetes are similar to the actual therapeutic targets for patients with DM, which have been associated reduced risk of renal outcomes (35, 36). It is also possible that lifestyle interventions are more frequently recommended for patients with prediabetes than for normoglycemic participants, eventually minimizing the risk of adverse kidney outcomes. In fact, early identification and treatment of prediabetes has been shown to potentially reduce or delay the progression to DM and related CV and microvascular disease (34).
Regarding the strengths of our study, we performed a secondary analysis of a large multicenter, randomized, controlled trial with rigorous data collection. The presence of detailed information about the participants allowed adjustment for several biologically plausible confounders in a group of individuals with high CV risk. There are, however, limitations of this analysis, which include the observational nature of a post hoc study, the potential for residual confounding despite performance of adjusted models, and the potential lack of power to detect significant associations in subgroups. Impaired fasting glucose was defined on the basis of a single measure of fasting glucose level at baseline, and time-updated measures of glycemic control and comorbid disease were not available. Although sensitivity analyses using a different fasting plasma glucose cutoff were consistent with our primary results, we cannot exclude the possibility of differing risks if prediabetes status had been based on HbA1c levels and/or oral glucose tolerance tests and if time-updated glycemic measurements had been available. Furthermore, the risk for adverse renal outcomes with impaired fasting glucose may have been higher if the follow-up had been longer. The limitations of the current data set include the absence of insulin levels, markers of insulin resistance, and detailed information on time-updated eGFR and albuminuria, which precluded the performance of more granular analyses.
In summary, in this post hoc analysis of the SPRINT trial, impaired fasting glucose was not associated with a higher incidence of CKD, incident albuminuria, or worsening kidney function. Future studies examining time-updated glycemic status with longer duration of follow-up are needed to examine the longitudinal renal risks of prediabetes.
Acknowledgments
The authors acknowledge the patients who participated in the SPRINT trial and the organizers of the SPRINT Data Analysis Challenge of The New England Journal of Medicine.
Financial Support: The SPRINT trial was sponsored by the National Heart, Lung, and Blood Institute (NHLBI), with cosponsorship by the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, and the National Institute on Aging. F.R.M. is supported by the National Institute of Diabetes and Digestive and Kidney Diseases grant K23DK102511. No funding was received for the completion of the current study.
Author Contributions: J.S.N., M.B.V., L.L., and R.B.B. jointly conceived the study, performed the literature search, developed the analytical strategy, did the statistical analysis, and jointly contributed to the first draft. R.M., C.V.D., A.O., D.C., and F.R.M. revised the draft and approved the final version of the manuscript. Each author contributed important intellectual content during manuscript drafting or revision. J.S.N., M.B.V., L.L., R.B.B., R.M., and C.V.D. are the guarantors of this work and, as such, had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.
Disclosure Summary: The authors declare that there are no conflicts of interest relevant to this article.
Glossary
Abbreviations:
- BMI
body mass index
- CKD
chronic kidney disease
- CV
cardiovascular
- DM
diabetes mellitus
- eGFR
estimated glomerular filtration rate
- ESRD
end-stage renal disease
- HR
hazard ratio
- SPRINT
Systolic Blood Pressure Intervention Trial
Parts of this study were presented in abstract form at the 20th European Congress of Endocrinology, Barcelona, Spain, 19‒22 May 2018.
References and Notes
- 1. Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and trends in diabetes among adults in the United States, 1988-2012. JAMA. 2015;314(10):1021–1029. [DOI] [PubMed] [Google Scholar]
- 2. Xu G, Liu B, Sun Y, Du Y, Snetselaar LG, Hu FB, Bao W. Prevalence of diagnosed type 1 and type 2 diabetes among US adults in 2016 and 2017: population based study. BMJ. 2018;362:k1497. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Anders H-J, Huber TB, Isermann B, Schiffer M. CKD in diabetes: diabetic kidney disease versus nondiabetic kidney disease. Nat Rev Nephrol. 2018;14(6):361–377. [DOI] [PubMed] [Google Scholar]
- 4. Saran R, Li Y, Robinson B, Ayanian J, Balkrishnan R, Bragg-Gresham J, Chen JT, Cope E, Gipson D, He K, Herman W, Heung M, Hirth RA, Jacobsen SS, Kalantar-Zadeh K, Kovesdy CP, Leichtman AB, Lu Y, Molnar MZ, Morgenstern H, Nallamothu B, O'Hare AM, Pisoni R, Plattner B, Port FK, Rao P, Rhee CM, Schaubel DE, Selewski DT, Shahinian V, Sim JJ, Song P, Streja E, Kurella Tamura M, Tentori F, Eggers PW, Agodoa LY, Abbott KC. US Renal Data System 2014 annual data report: epidemiology of kidney disease in the United States. Am J Kidney Dis. 2015;66(1 Suppl 1):Svii, S1–S305. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Chawla LS, Eggers PW, Star RA, Kimmel PL. Acute kidney injury and chronic kidney disease as interconnected syndromes. N Engl J Med. 2014;371(1):58–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6. Chang Y-T, Wu J-L, Hsu C-C, Wang J-D, Sung J-M. Diabetes and end-stage renal disease synergistically contribute to increased incidence of cardiovascular events: a nationwide follow-up study during 1998-2009. Diabetes Care. 2014;37(1):277–285. [DOI] [PubMed] [Google Scholar]
- 7. American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2019. Diabetes Care. 2019;42(Suppl 1):S13–S28. [DOI] [PubMed] [Google Scholar]
- 8. Tabák AG, Herder C, Rathmann W, Brunner EJ, Kivimäki M. Prediabetes: a high-risk state for diabetes development. Lancet. 2012;379(9833):2279–2290. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Thomas G, Sehgal AR, Kashyap SR, Srinivas TR, Kirwan JP, Navaneethan SD. Metabolic syndrome and kidney disease: a systematic review and meta-analysis. Clin J Am Soc Nephrol. 2011;6(10):2364–2373. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Fox CS, Larson MG, Leip EP, Meigs JB, Wilson PWF, Levy D. Glycemic status and development of kidney disease: the Framingham Heart Study. Diabetes Care. 2005;28(10):2436–2440. [DOI] [PubMed] [Google Scholar]
- 11. Echouffo-Tcheugui JB, Narayan KM, Weisman D, Golden SH, Jaar BG. Association between prediabetes and risk of chronic kidney disease: a systematic review and meta-analysis. Diabet Med. 2016;33(12):1615–1624. [DOI] [PubMed] [Google Scholar]
- 12. Derakhshan A, Bagherzadeh-Khiabani F, Arshi B, Ramezankhani A, Azizi F, Hadaegh F. Different combinations of glucose tolerance and blood pressure status and incident diabetes, hypertension, and chronic kidney disease. J Am Heart Assoc. 2016;5(8):e003917. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Wright JT Jr, Williamson JD, Whelton PK, Snyder JK, Sink KM, Rocco MV, Reboussin DM, Rahman M, Oparil S, Lewis CE, Kimmel PL, Johnson KC, Goff DC Jr, Fine LJ, Cutler JA, Cushman WC, Cheung AK, Ambrosius WT; SPRINT Research Group. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med. 2015;373(22):2103–2116. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Burns NS, Miller PW. Learning what we didn’t know: the SPRINT data analysis challenge. N Engl J Med. 2017;376(23):2205–2207. [DOI] [PubMed] [Google Scholar]
- 15. American Diabetes Association. 2. Classification and diagnosis of diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S13–S27. [DOI] [PubMed] [Google Scholar]
- 16. Systolic Blood Pressure Intervention Trial (SPRINT) Protocol version 4.0. Available at: www.sprinttrial.org/public/Protocol_Current.pdf. Accessed 10 January 2019.
- 17. World Health Organization, International Diabetes Foundation. 2. Classification and Diagnosis of Diabetes: Standards of Medical Care in Diabetes 2019. Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia. 2006. Available at: www.who.int/diabetes/publications/Definition%20and%20diagnosis%20of%20diabetes_new.pdf. Accessed on 10 January 2019.
- 18. Bigotte Vieira M, Neves JS, Leitão L, Baptista RB, Magriço R, Viegas Dias C, Oliveira A, Carvalho D, Mc Causland FR. Data from: Impaired fasting glucose and chronic kidney disease, albuminuria, or worsening kidney function: a secondary analysis of SPRINT. Harvard Dataverse Digital Repository. Deposited 12 April 2019. 10.7910/DVN/KNGSVZ. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Melsom T, Mathisen UD, Ingebretsen OC, Jenssen TG, Njølstad I, Solbu MD, Toft I, Eriksen BO. Impaired fasting glucose is associated with renal hyperfiltration in the general population. Diabetes Care. 2011;34(7):1546–1551. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Fujita H, Narita T, Ito S. Abnormality in urinary protein excretion in Japanese men with impaired glucose tolerance. Diabetes Care. 1999;22(5):823–826. [DOI] [PubMed] [Google Scholar]
- 21. Metcalf PA, Baker JR, Scragg RK, Dryson E, Scott AJ, Wild CJ. Microalbuminuria in a middle-aged workforce: effect of hyperglycemia and ethnicity. Diabetes Care. 1993;16(11):1485–1493. [DOI] [PubMed] [Google Scholar]
- 22. Gabir MM, Hanson RL, Dabelea D, Imperatore G, Roumain J, Bennett PH, Knowler WC. Plasma glucose and prediction of microvascular disease and mortality: evaluation of 1997 American Diabetes Association and 1999 World Health Organization criteria for diagnosis of diabetes. Diabetes Care. 2000;23(8):1113–1118. [DOI] [PubMed] [Google Scholar]
- 23. Hoehner CM, Greenlund KJ, Rith-Najarian S, Casper ML, McClellan WM. Association of the insulin resistance syndrome and microalbuminuria among nondiabetic native Americans: the Inter-Tribal Heart Project. J Am Soc Nephrol. 2002;13(6):1626–1634. [DOI] [PubMed] [Google Scholar]
- 24. Plantinga LC, Crews DC, Coresh J, Miller ER III, Saran R, Yee J, Hedgeman E, Pavkov M, Eberhardt MS, Williams DE, Powe NR; CDC CKD Surveillance Team. Prevalence of chronic kidney disease in US adults with undiagnosed diabetes or prediabetes. Clin J Am Soc Nephrol. 2010;5(4):673–682. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Sun Y, Wang C, Yang W, Wang Y, Zhang X, Ma Z, Song J, Lin P, Liang K, Ma A, Zheng H, Wu J, Gong L, Wang M, Liu F, Li W, Yan F, Yang J, Wang L, Tian M, Liu J, Zhao R, Hou X, Chen L. Fasting blood glucose, but not 2-h postload blood glucose or HbA1c, is associated with mild decline in estimated glomerular filtration rate in healthy Chinese. Int Urol Nephrol. 2015;47(1):147–152. [DOI] [PubMed] [Google Scholar]
- 26. Wang XL, Lu JM, Pan CY, Tian H, Li CL. A comparison of urinary albumin excretion rate and microalbuminuria in various glucose tolerance subjects. Diabet Med. 2005;22(3):332–335. [DOI] [PubMed] [Google Scholar]
- 27. Huang Y, Cai X, Mai W, Li M, Hu Y. Association between prediabetes and risk of cardiovascular disease and all cause mortality: systematic review and meta-analysis. BMJ. 2016;355:i5953. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Rao Kondapally Seshasai S, Kaptoge S, Thompson A, Di Angelantonio E, Gao P, Sarwar N, Whincup PH, Mukamal KJ, Gillum RF, Holme I, Njølstad I, Fletcher A, Nilsson P, Lewington S, Collins R, Gudnason V, Thompson SG, Sattar N, Selvin E, Hu FB, Danesh J; Emerging Risk Factors Collaboration. Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med. 2011;364(9):829–841. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Sarwar N, Gao P, Seshasai SR, Gobin R, Kaptoge S, Di Angelantonio E, Ingelsson E, Lawlor DA, Selvin E, Stampfer M, Stehouwer CD, Lewington S, Pennells L, Thompson A, Sattar N, White IR, Ray KK, Danesh J; Emerging Risk Factors Collaboration. Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies. Lancet. 2010;375(9733):2215–2222. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Laukkanen JA, Mäkikallio TH, Ronkainen K, Karppi J, Kurl S. Impaired fasting plasma glucose and type 2 diabetes are related to the risk of out-of-hospital sudden cardiac death and all-cause mortality. Diabetes Care. 2013;36(5):1166–1171. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Deedwania P, Patel K, Fonarow GC, Desai RV, Zhang Y, Feller MA, Ovalle F, Love TE, Aban IB, Mujib M, Ahmed MI, Anker SD, Ahmed A. Prediabetes is not an independent risk factor for incident heart failure, other cardiovascular events or mortality in older adults: findings from a population-based cohort study. Int J Cardiol. 2013;168(4):3616–3622. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32. Gordon-Dseagu VLZ, Mindell JS, Steptoe A, Moody A, Wardle J, Demakakos P, Shelton NJ. Impaired glucose metabolism among those with and without diagnosed diabetes and mortality: a cohort study using Health Survey for England data. PLoS One. 2015;10(3):e0119882. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. American Diabetes Association. 5. Prevention or delay of type 2 diabetes: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S51–S54. [DOI] [PubMed] [Google Scholar]
- 34. Garber A, Handelsman Y, Einhorn D, Bergman D, Bloomgarden Z, Fonseca V, Timothy Garvey W, Gavin J III, Grunberger G, Horton E, Jellinger P, Jones K, Lebovitz H, Levy P, McGuire D, Moghissi E, Nesto RW. Diagnosis and management of prediabetes in the continuum of hyperglycemia: when do the risks of diabetes begin? A consensus statement from the American College of Endocrinology and the American Association of Clinical Endocrinologists. Endocr Pract. 2008;14(7):933–946. [DOI] [PubMed] [Google Scholar]
- 35. American Diabetes Association. 10. Microvascular complications and foot care: Standards of Medical Care in Diabetes-2018. Diabetes Care. 2018;41(Suppl 1):S105–S118. [DOI] [PubMed] [Google Scholar]
- 36. Nordwall M, Abrahamsson M, Dhir M, Fredrikson M, Ludvigsson J, Arnqvist HJ. Impact of HbA1c, followed from onset of type 1 diabetes, on the development of severe retinopathy and nephropathy: the VISS Study (Vascular Diabetic Complications in Southeast Sweden). Diabetes Care. 2015;38(2):308–315. [DOI] [PubMed] [Google Scholar]