Literature DB >> 31236280

Characteristics of Adults With Type 2 Diabetes Mellitus by Category of Chronic Kidney Disease and Presence of Cardiovascular Disease in Alberta Canada: A Cross-Sectional Study.

Marcello Tonelli1, Natasha Wiebe2, Jean-Francois Richard3, Scott W Klarenbach2, Brenda R Hemmelgarn1.   

Abstract

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with an excess risk of cardiovascular disease (CVD) and chronic kidney disease (CKD). Although CVD, CKD, and use of antihyperglycemic treatments are all key drivers of the costs and consequences experienced by people with diabetes, no recent Canadian data describe these characteristics among adults with diabetes.
OBJECTIVE: To describe prevalence of CVD, CKD, and use of antihyperglycemic treatments among adults with diabetes.
DESIGN: Retrospective population-based, cross-sectional study.
SETTING: Alberta, Canada. PATIENTS: All adults with T2DM as of March 31, 2017. MEASUREMENTS: We described the demographic and clinical characteristics by CKD stage and CVD status and type. CKD stage was categorized according to international guidelines and based on estimated glomerular filtration rate (eGFR) and severity of albuminuria.
METHODS: Clinical and demographic characteristics were defined using provincial administrative data; medication use was based on data from the provincial drug plan. Additional analyses examined subgroups based on demographic characteristics, clinical characteristics, and medication use.
RESULTS: There were 260 903 participants, all of whom had T2DM. Median age was 64 years; 53.6% were male; and 10.9% lived in rural communities. Median duration of diabetes was 7.7 years. Half of the participants had A1C <7%. Overall, 33.0% had CKD; among these most had eGFR <60 mL/min/1.73 m2; 11.1%, 5.6%, and 2.9% had CKD stages 3a, 3b, and 4/5, respectively. The overall prevalence of CVD (prior myocardial infarction, stroke/transient ischemic attack, or peripheral artery disease) was 22.5%; prevalence increased in parallel with the presence of CKD: 14.4%, 28.8%, 35.7%, 44.3%, and 50.9% for stages 1, 2, 3a, 3b, and 4/5, respectively. Prescriptions for antihyperglycemic medications were more common in people with CKD as compared with those without. However, the use of all antihyperglycemic medications except insulin and meglitinide was progressively lower in the presence of more severe CKD. LIMITATIONS: The study is based on administrative data; therefore, the findings could be influenced by measurement error (eg, accuracy of diagnostic and procedural codes and prescription drug codes used).
CONCLUSIONS: These findings will be useful to policy makers seeking to understand the burden of diabetes-related kidney disease as well as the potential budget implications and potential clinical benefits of expanded use of antihyperglycemic use in this population.

Entities:  

Keywords:  antihyperglycemic medication; chronic kidney disease; diabetes; elderly

Year:  2019        PMID: 31236280      PMCID: PMC6572900          DOI: 10.1177/2054358119854113

Source DB:  PubMed          Journal:  Can J Kidney Health Dis        ISSN: 2054-3581


What was known before

Diabetes-related kidney disease is common and is associated with adverse health outcomes.

What this adds

This study provides population-based estimates of the demographic and clinical characteristics of Alberta patients with type 2 diabetes mellitus by stage of kidney disease and history of cardiovascular disease, including a detailed examination of the number and type of antihyperglycemic agents prescribed in this population. These findings will be useful to those seeking to understand the burden of diabetes-related kidney disease and its treatment.

Introduction

Diabetes mellitus affects more than 400 million people worldwide, and the prevalence of diabetes is growing rapidly, especially for type 2 diabetes mellitus (T2DM) and in low- and middle-income countries.[1-3] T2DM is associated with an excess risk of microvascular and macrovascular complications including cardiovascular disease (CVD) and chronic kidney disease (CKD). The simultaneous presence of T2DM and CKD is associated with future risk for cardiovascular events that is similar to people with prior myocardial infarction[4] as well as a heightened risk for hypoglycemia, compared with people with diabetes but no CKD. Besides the excess risk of CVD events, a key clinical consequence of CKD is progressive kidney function loss—which is associated with adverse outcomes, high health care costs, and the possibility that chronic renal replacement (dialysis or kidney transplantation) will be required.[5] Because CVD and CKD are both key drivers of the costs and consequence experienced by people with diabetes, information on the prevalence of these conditions would be potentially useful to policy makers seeking to project the future resources and personnel needed to provide health services for this high-risk group. However, no recent Canadian data describe the population burden of diabetic kidney disease among adults with diabetes (or its pharmacological treatment) by stage of CKD and level of estimated glomerular filtration rate (eGFR). The current study describes the demographic and clinical characteristics of patients with T2DM by CKD stage and CVD status and type. Our primary objective was to provide cross-sectional population-based estimates of the distribution (prevalence) of CKD stage among prevalent Albertan adults with T2DM. Additional subgroup analyses examined how this prevalence varies by demographic characteristics, clinical characteristics, and medication use. We also examined the number and type of antihyperglycemic agents currently used by stage of CKD and type of CVD.

Methods

This retrospective population-based cross-sectional study is reported according to the STROBE guidelines.[6] The institutional review boards at the Universities of Alberta (Pro00053469) and Calgary (REB16-1575) approved this study. This is a study of administrative data without any intervention. No study participants were placed at risk as a result of the study. Informed consent was not required.

Data Sources and Cohort

We used the Alberta Kidney Disease Network database, which incorporates data from Alberta Health (AH; the provincial health ministry) including physician claims, hospitalizations, and ambulatory care utilization; Alberta pharmaceutical network data; and the clinical laboratories in Alberta. This database has been widely used[4,7,8] because of its population-based coverage of a geographically defined area, including demographic characteristics, health services utilization, and clinical outcomes. Additional information on the database is available elsewhere, including the validation of selected data elements and the standardization and calibration of serum creatinine assays.[9] All adults 18 years of age and older registered with AH were included in the database; all Alberta residents are eligible for insurance coverage by AH and >99% participate in coverage. The database was used to assemble a cohort of adults (18 years and older) with T2DM who resided in Alberta on March 31, 2017 (index date). Patients with type 1 diabetes mellitus (International Classification of Diseases, Ninth Revision [ICD-9] code: 250.x1 and 250.x3) in any of their previous records were excluded.

Diabetes Mellitus and Comorbidities

T2DM and comorbidities were defined using a previously published framework using validated algorithms as applied to Canadian physician claims data, each of which had positive predictive values ≥70% as compared with a gold standard measure such as chart review.[10] Conditions included T2DM,[11] chronic heart failure,[12,13] dementia,[12,13] depression,[12,13] myocardial infarction,[14] peripheral artery disease (PAD),[15] and stroke or transient ischemic attack (TIA).[16] Each participant was classified with respect to the presence or absence of these 7 chronic conditions (lookback extended as far as April 1994 where records were available).[17] Detailed methods for classifying comorbidity status and the specific algorithms used are found elsewhere.[10] Myocardial infarctions were included in our definition of coronary artery disease (CAD) along with percutaneous coronary intervention (ICD-9 procedures codes: 36.01, 36.02, 36.05, 36.06, and CCI 1.IJ.50, 1.IJ.57.GQ, 1.IL.35) and coronary artery bypass grafting (ICD-9 procedures codes: 36.1, 36.2, and CCI 1.IJ.76). Cardiovascular disease was defined as CAD, PAD, and stroke/TIA.

Assessment of CKD

We assessed the presence of CKD based on measurements of eGFR and albuminuria. Stage of CKD was based on the participant’s most recent evaluated outpatient GFR within 18 months before the index date: >90 mL/min/1.73 m2 together with moderate or greater albuminuria (stage 1), 60 to 89 mL/min/1.73 m2 together with moderate or greater albuminuria (stage 2), 45 to 59 mL/min/1.73 m2 (stage 3a), 30 to 44 mL/min/1.73 m2 (stage 3b), and <30 mL/min/1.73 m2 (stages 4 and 5, with or without renal replacement therapy). People without stage 1 to 5 CKD were considered not to have CKD. eGFR was calculated using the CKD Epidemiology Collaboration (CKD-EPI) equation. Albuminuria (if available) was captured using the participant’s most recent outpatient measurement within 18 months before the index date using either the albumin:creatinine ratio (ACR), the protein:creatinine ratio (PCR), and the dipstick. A PCR assessment was used when ACR was not available, and dipstick results were used when PCR was not available. Measurements were categorized as follows: missing, none/mild (ACR <3 mg/mmol, PCR <15 mg/mmol, dipstick negative/trace), moderate (ACR 3-30 mg/mmol, PCR 15-50 mg/mmol, dipstick 1+), severe (ACR 31-220 mg/mmol, PCR 51-350 mg/mmol, dipstick 2+ and 3+), and nephrotic range (ACR >220 mg/mmol, PCR >350 mg/mmol, dipstick ≥4+). Participants with missing values for albuminuria were considered not to have albuminuria when categorizing CKD stage. We also did analyses that categorized participants in terms of eGFR only (ie, without consideration of albuminuria, using the same eGFR thresholds as above: >90, 60-89, 45-59, 30-44 and <30 mL/min/1.73 m2).

Other Variables and Antihyperglycemic Agents

Demographic variables included age, gender, urban or rural residence, duration of diabetes, laboratory measurements (glycated hemoglobin [A1C] and low-density lipoprotein cholesterol [LDL-C]), body mass index (BMI), and utilization of antihyperglycemic agents. The laboratory measurements were the most recent outpatient measures within 18 months on the index date. We identified participants with BMI ≥35 kg/m2 as in our prior work.[18] Use of an antihyperglycemic agent was defined as at least one prescription for an antidiabetic agent with a duration of at least 30 days within 18 months of the index date. Available agents were categorized into treatment classes: biguanide (metformin), dipeptidyl peptidase-4 (DPP-4) inhibitors (linagliptin, saxagliptin, sitagliptin), glucagon-like peptide-1 (GLP-1) receptor agonists (dulaglutide, exenatide, liraglutide), insulin, meglitinides (nateglinide, repaglinide), sodium-glucose cotransporter type 2 (SGLT-2) inhibitors (canagliflozin, dapagliflozin, empagliflozin), sulfonylureas (chlorpropamide, glibenclamide, gliclazide, glimepiride, tolbutamide), and other agents (acarbose, orlistat, pioglitazone, rosiglitazone). Fixed dose combinations comprised of 2 antihyperglycemic agents were also included if they were available in Alberta.

Statistical Analyses

We did analyses with Stata MP 15·1 (www.stata.com) and reported descriptive statistics—counts and percentages, or medians and interquartile range (IQR), as appropriate. Multiple subgroups were explored: primarily CKD stage and prior CVD (CAD, PAD, and stroke/TIA) but also A1C (<7%, 7%-8%, 8.1%-9%, >9%).

Results

Characteristics of Study Participants

Participant flow is shown in Supplemental Figure S1; 3 481 650 individuals were excluded since they did not have T2DM and a further 56 653 were excluded as they did not have an eGFR measurement in the 18 months prior to the index date, leaving 260 903 participants in the cohort. The median age of the cohort of adults with T2DM was 64 years. There were slightly more men than women with T2DM (53.6% vs 46.4%), and 10.9% lived in rural communities (towns with <10 000 people). The median duration of T2DM was 7.7 years and 8.1% did not have A1C outpatient measurement in the prior 18 months. In those with measured A1C, slightly more than half (55.3%) had A1C <7%. Median eGFR was 83 mL/min/1.73 m2 and median LDL-C was 2.1 mmol/L. Albuminuria was not measured in 15.3% of the participants. In those with measured albuminuria, 19.9% had moderate-to-nephrotic range albuminuria. There were 12.9% of participants with a prior stroke or TIA, 11.7% with chronic depression, 10.6% with heart failure, 10.5% with CAD, 4.9% with dementia, and 3.4% with PAD. The distribution of antihyperglycemic medication use was as follows: 48.0% biguanides (all of which were metformin), 15.2% insulin, 14.4% sulfonylureas (90.9% of which were gliclazide), 11.8% DPP-4 inhibitors, 7.6% SGLT2 inhibitors, 3.7% meglitinides (all of which were repaglinide), 2.4% GLP-1 receptor agonists, and 1.9% use from other classes.

CKD Stage

Overall, 33.0% had CKD and 67.0% did not. Among those classified as having CKD, the majority had eGFR <60 mL/min/1.73 m2 (Table 1); 5.6% and 2.9% had advanced CKD, stages 3b and 4/5, respectively. Among those with CKD, age 65 years or older (15.4% vs 2.5%), women (9.3% vs 7.9%), rural participants (9.3% vs 8.5%; Table 2), participants with BMI ≥35 kg/m2 (10.1% vs 8.8%), severe albuminuria (34.9% vs 12.2% moderate vs 5.0% none/mild; Table 3), chronic heart failure (29.8% vs 6.0%; Table 4), and dementia (23.9% vs 7.7%) were all more likely to be associated with advanced CKD (stage 3b, 4, or 5) as compared with less advanced stages (1, 2, or 3a). As expected, duration with T2DM was longer for those with advanced CKD compared with those with stage 1, 2, or 3a CKD (13.3 vs 9.3 years; Table 3) and LDL-C was lower (1.8 vs 1.9 mmol/L). Stage 1 and 2 CKD was most common in participants with A1C >9% (Table 5); however, A1C level per se was not clearly associated with more advanced CKD.
Table 1.

CKD Stage, Prior CVD, and A1C Overall and by Age and Gender.

PopulationOverallAge, yearsGender
<65≥6565-74≥75FemaleMale
Overall260 903139 568121 33566 47254 863121 129139 774
No CKD, eGFR174 920 (67.0)110 014 (78.8)64 906 (53.5)42 307 (63.6)22 599 (41.2)82 540 (68.1)92 380 (66.1)
 >90 mL/min/1.73 m281 383 (31.2)70 238 (50.3)11 145 (9.2)10 172 (15.3)973 (1.8)40 052 (33.1)41 331 (29.6)
 60-89 mL/min/1.73 m293 537 (35.9)39 776 (28.5)53 761 (44.3)32 135 (48.3)21 626 (39.4)42 488 (35.1)51 049 (36.5)
CKD stage
 115 519 (5.9)13 205 (9.5)2314 (1.9)2100 (3.2)214 (0.4)6298 (5.2)9221 (6.6)
 219 168 (7.3)7615 (5.5)11 553 (9.5)6727 (10.1)4826 (8.8)6749 (5.6)12 419 (8.9)
 3a29 069 (11.1)5140 (3.7)23 929 (19.7)9633 (14.5)14 296 (26.1)14 336 (11.8)14 733 (10.5)
 3b14 698 (5.6)1871 (1.3)12 827 (10.6)3792 (5.7)9035 (16.5)7580 (6.3)7118 (5.1)
 4/57529 (2.9)1723 (1.2)5806 (4.8)1913 (2.9)3893 (7.1)3626 (3.0)3903 (2.8)
Prior CVD[a]58 595 (22.5)17 541 (12.6)41 054 (33.8)18 448 (27.8)22 606 (41.2)22 201 (18.3)36 394 (26.0)
 CAD27 395 (10.5)7916 (5.7)19 479 (16.1)9381 (14.1)10 098 (18.4)6948 (5.7)20 447 (14.6)
 PAD8772 (3.4)2140 (1.5)6632 (5.5)2844 (4.3)3788 (6.9)3360 (2.8)5412 (3.9)
 Stroke/TIA33 733 (12.9)9557 (6.8)24 176 (19.9)9747 (14.7)14 429 (26.3)15 420 (12.7)18 313 (13.1)
A1C
 <7%132 620 (50.8)66 885 (47.9)65 735 (54.2)35 368 (53.2)30 367 (55.4)64 482 (53.2)68 138 (48.7)
 7%-8%56 533 (21.7)29 226 (20.9)27 307 (22.5)15 804 (23.8)11 503 (21.0)24 017 (19.8)32 516 (23.3)
 8.1%-9%24 369 (9.3)14 210 (10.2)10 159 (8.4)6093 (9.2)4066 (7.4)9883 (8.2)14 486 (10.4)
 >9%26 352 (10.1)18 493 (13.3)7859 (6.5)5129 (7.7)2730 (5.0)10 827 (8.9)15 525 (11.1)
 Missing21 029 (8.1)10 754 (7.7)10 275 (8.5)4078 (6.1)6197 (11.3)11 920 (9.8)9109 (6.5)
eGFR 60-89 mL/min/1.73 m2 & CVD26 506 (10.2)6849 (4.9)19 657 (16.2)10 028 (15.1)9629 (17.6)9354 (7.7)17 152 (12.3)
eGFR <60 mL/min/1.73 m2 & CVD20 726 (7.9)2583 (1.9)18 143 (15.0)5614 (8.4)12 529 (22.8)8897 (7.3)11 829 (8.5)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack.

Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported.

Table 2.

CKD Stage, Prior CVD and A1C by Region and BMI.

PopulationRegionBMI, kg/m2
UrbanRural<35≥35Missing
Overall232 44128 462169 68263 29627 925
No CKD, eGFR156 322 (67.3)18 598 (65.3)113 608 (67.0)40 549 (64.1)20 763 (74.4)
 >90 mL/min/1.73 m272 589 (31.2)8794 (30.9)49 971 (29.4)19 407 (30.7)12 005 (43.0)
 60-89 mL/min/1.73 m283 733 (36.0)9804 (34.4)63 637 (37.5)21 142 (33.4)8758 (31.4)
CKD stage
 113 737 (5.9)1782 (6.3)8957 (5.3)4015 (6.3)2547 (9.1)
 217 068 (7.3)2100 (7.4)12 407 (7.3)4858 (7.7)1903 (6.8)
 3a25 739 (11.1)3330 (11.7)19 833 (11.7)7507 (11.9)1729 (6.2)
 3b12 950 (5.6)1748 (6.1)9932 (5.9)4036 (6.4)730 (2.6)
 4/56625 (2.9)904 (3.2)4945 (2.9)2331 (3.7)253 (0.9)
Prior CVD[a]51 563 (22.2)7032 (24.7)40 554 (23.9)15 919 (25.2)2122 (7.6)
 CAD23 901 (10.3)3494 (12.3)19 160 (11.3)7614 (12.0)621 (2.2)
 PAD7834 (3.4)938 (3.3)5975 (3.5)2613 (4.1)184 (0.7)
 Stroke/TIA29 836 (12.8)3897 (13.7)23 293 (13.7)8973 (14.2)1467 (5.3)
A1C
 <7%119 175 (51.3)13 445 (47.2)87 795 (51.7)32 281 (51.0)12 544 (44.9)
 7%-8%50 315 (21.6)6218 (21.8)36 374 (21.4)13 399 (21.2)6760 (24.2)
 8.1%-9%21 421 (9.2)2948 (10.4)15 057 (8.9)6219 (9.8)3093 (11.1)
 >9%22 848 (9.8)3504 (12.3)15 687 (9.2)6525 (10.3)4140 (14.8)
 Missing18 682 (8.0)2347 (8.2)14 769 (8.7)4872 (7.7)1388 (5.0)
eGFR 60-89 mL/min/1.73 m2 & CVD23 373 (10.1)3133 (11.0)18 795 (11.1)6721 (10.6)990 (3.5)
eGFR <60 mL/min/1.73 m2 & CVD18 269 (7.9)2457 (8.6)14 290 (8.4)5854 (9.2)582 (2.1)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; BMI = body mass index; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack.

Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported.

Table 3.

CKD Stage, Prior CVD, and A1C by Duration of T2DM Years, LDL-C, and Albuminuria.

PopulationDuration of T2DM, yearsLDL-C, mmol/LAlbuminuria
None/mildModerateSevere/nephroticMissing
Overall260 903203 770168 81637 09414 95540 038
No CKD, eGFR6.8 (3.1, 11.9)2.2 (1.6, 2.9)143 729 (85.1)0 (0.0)0 (0.0)31 191 (77.9)
 >90 mL/min/1.73 m25.8 (2.6, 10.5)2.3 (1.7, 3.0)67 309 (39.9)0 (0.0)0 (0.0)14 074 (35.2)
 60-89 mL/min/1.73 m27.6 (3.6, 12.9)2.1 (1.6, 2.9)76 420 (45.3)0 (0.0)0 (0.0)17 117 (42.8)
CKD stage
 16.8 (3.1, 12.0)2.1 (1.6, 2.9)0 (0.0)12 580 (33.9)2939 (19.7)0 (0.0)
 29.9 (4.9, 15.7)1.9 (1.4, 2.6)0 (0.0)14 796 (39.9)4372 (29.2)0 (0.0)
 3a10.4 (5.4, 16.1)1.9 (1.4, 2.6)16 685 (9.9)5180 (14.0)2425 (16.2)4779 (11.9)
 3b12.5 (6.8, 18.1)1.8 (1.3, 2.4)6717 (4.0)3154 (8.5)2409 (16.1)2418 (6.0)
 4/515.1 (8.6, 20.4)1.8 (1.3, 2.4)1685 (1.0)1384 (3.7)2810 (18.8)1650 (4.1)
Prior CVD[a]
 Yes10.1 (5.1, 16.1)1.7 (1.3, 2.4)32 538 (19.3)9865 (26.6)5327 (35.6)10 865 (27.1)
 No7.1 (3.2, 12.6)2.2 (1.6, 2.9)136 278 (80.7)27 229 (73.4)9628 (64.4)29 173 (72.9)
Prior CAD
 Yes10.2 (5.2, 16.3)1.6 (1.2, 2.1)15 066 (8.9)4996 (13.5)2573 (17.2)4760 (11.9)
 No7.5 (3.4, 13.0)2.2 (1.6,2.9)153 750 (91.1)32 098 (86.5)12 382 (82.8)35 278 (88.1)
Prior PAD
 Yes11.1 (5.4, 17.4)1.8 (1.3, 2.4)4215 (2.5)1490 (4.0)1113 (7.4)1954 (4.9)
 No7.6 (3.5, 13.3)2.1 (1.6, 2.8)164 601 (97.5)35 604 (96.0)13 842 (92.6)38 084 (95.1)
Prior Stroke/TIA
 Yes10.4 (5.3, 16.3)1.9 (1.4, 2.5)18 665 (11.1)5448 (14.7)3093 (20.7)6527 (16.3)
 No7.4 (3.4, 12.9)2.1 (1.6, 2.9)150 151 (88.9)31 646 (85.3)11 862 (79.3)33 511 (83.7)
A1C
 <7%6.3 (2.8, 11.4)2.2 (1.6, 2.9)92 454 (54.8)15 031 (40.5)5382 (36.0)19 753 (49.3)
 7%-8%9.6 (4.8, 15.5)1.9 (1.4, 2.6)36 935 (21.9)9771 (26.3)3645 (24.4)6182 (15.4)
 8.1%-9%10.9 (5.8, 16.9)2.0 (1.5, 2.7)14 647 (8.7)4868 (13.1)2149 (14.4)2705 (6.8)
 >9%9.8 (4.9,15.8)2.2 (1.6,3.0)13 971 (8.3)6303 (17.0)2974 (19.9)3104 (7.8)
 Missing6.8 (3.2, 11.8)2.5 (1.9, 3.2)10 809 (6.4)1121 (3.0)805 (5.4)8294 (20.7)
eGFR 60-89 mL/min/1.73 m2 & CVD9.4 (4.7, 15.1)1.8 (1.3, 2.4)16 321 (9.7)4108 (11.1)1402 (9.4)4675 (11.7)
eGFR <60 mL/min/1.73 m2 & CVD12.7 (6.8, 18.6)1.7 (1.2, 2.3)9053 (5.4)4045 (10.9)3405 (22.8)4223 (10.5)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; T2DM = type 2 diabetes mellitus; LDL-C = low-density lipoprotein cholesterol; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; IQR = interquartile range.

Prior CVD is any CAD, PAD, or stroke/TIA. N (%) or medians (IQR) are reported as appropriate.

Table 4.

CKD Stage, Prior CVD, and A1C, by Chronic Heart Failure, Dementia, and Depression.

PopulationChronic heart failureDementiaDepression
YesNoYesNoYesNo
Overall27 600233 30312 901248 00230 524230 379
No CKD, eGFR10 351 (37.5)164 569 (70.5)5792 (44.9)169 128 (68.2)20 933 (68.6)153 987 (66.8)
 >90 mL/min/1.73 m22619 (9.5)78 764 (33.8)1258 (9.8)80 125 (32.3)10 272 (33.7)71 111 (30.9)
60-89 mL/min/1.73 m27732 (28.0)85 805 (36.8)4534 (35.1)89 003 (35.9)10 661 (34.9)82 876 (36.0)
CKD stage
 1768 (2.8)14 751 (6.3)229 (1.8)15 290 (6.2)1833 (6.0)13 686 (5.9)
 22463 (8.9)16 705 (7.2)965 (7.5)18 203 (7.3)1902 (6.2)17 266 (7.5)
 3a5783 (21.0)23 286 (10.0)2831 (21.9)26 238 (10.6)3253 (10.7)25 816 (11.2)
 3b4720 (17.1)9978 (4.3)2050 (15.9)12 648 (5.1)1710 (5.6)12 988 (5.6)
 4/53515 (12.7)4014 (1.7)1034 (8.0)6495 (2.6)893 (2.9)6636 (2.9)
Prior CVD [a] 15 973 (57.9)42 622 (18.3)6554 (50.8)52 041 (21.0)7790 (25.5)50 805 (22.1)
 CAD9769 (35.4)17 626 (7.6)2172 (16.8)25 223 (10.2)2760 (9.0)24 635 (10.7)
 PAD2987 (10.8)5785 (2.5)1175 (9.1)7597 (3.1)1293 (4.2)7479 (3.2)
 Stroke/TIA8605 (31.2)25 128 (10.8)5056 (39.2)28 677 (11.6)5341 (17.5)28 392 (12.3)
A1C
 <7%13 267 (48.1)119 353 (51.2)6307 (48.9)126 313 (50.9)16 043 (52.6)116 577 (50.6)
 7%-8%5709 (20.7)50 824 (21.8)2191 (17.0)54 342 (21.9)5265 (17.2)51 268 (22.3)
 8.1%-9%2690 (9.7)21 679 (9.3)1023 (7.9)23 346 (9.4)2638 (8.6)21 731 (9.4)
 >9%2560 (9.3)23 792 (10.2)949 (7.4)25 403 (10.2)3363 (11.0)22 989 (10.0)
 Missing3374 (12.2)17 655 (7.6)2431 (18.8)18 598 (7.5)3215 (10.5)17 814 (7.7)
eGFR 60-89 mL/min/1.73 m2 & CVD5694 (20.6)20 812 (8.9)2645 (20.5)23 861 (9.6)3310 (10.8)23 196 (10.1)
eGFR <60 mL/min/1.73 m2 & CVD8696 (31.5)12 030 (5.2)3350 (26.0)17 376 (7.0)2651 (8.7)18 075 (7.8)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; CAD = coronary artery disease; eGFR = estimated glomerular filtration rate; PAD = peripheral artery disease; TIA = transient ischemic attack.

Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported.

Table 5.

CKD Stage and Prior CVD, by A1C.

PopulationA1C
<7%7-8%8.1-9%>9%Missing
Overall132 62056 53324 36926 35221 029
No CKD, eGFR93 935 (70.8)36 219 (64.1)14 583 (59.8)15 010 (57.0)15 173 (72.2)
 >90 mL/min/1.73 m240 589 (30.6)16 813 (29.7)7594 (31.2)9238 (35.1)7149 (34.0)
 60-89 mL/min/1.73 m253 346 (40.2)19 406 (34.3)6989 (28.7)5772 (21.9)8024 (38.2)
CKD stage
 15219 (3.9)3634 (6.4)2226 (9.1)3976 (15.1)464 (2.2)
 27862 (5.9)5172 (9.1)2499 (10.3)3006 (11.4)629 (3.0)
 3a15 105 (11.4)6508 (11.5)2668 (10.9)2206 (8.4)2582 (12.3)
 3b7112 (5.4)3299 (5.8)1500 (6.2)1330 (5.0)1457 (6.9)
 4/53387 (2.6)1701 (3.0)893 (3.7)824 (3.1)724 (3.4)
Prior CVD[a]28 863 (21.8)12 755 (22.6)5677 (23.3)5595 (21.2)5705 (27.1)
 CAD12 907 (9.7)6464 (11.4)2928 (12.0)2790 (10.6)2306 (11.0)
 PAD4241 (3.2)1787 (3.2)858 (3.5)810 (3.1)1076 (5.1)
 Stroke/TIA17 001 (12.8)6939 (12.3)3034 (12.5)3103 (11.8)3656 (17.4)
eGFR 60-89 mL/min/1.73 m2 & CVD13 901 (10.5)5673 (10.0)2354 (9.7)2135 (8.1)2443 (11.6)
eGFR <60 mL/min/1.73 m2 & CVD9840 (7.4)4589 (8.1)2142 (8.8)1859 (7.1)2296 (10.9)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack.

Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported.

CKD Stage, Prior CVD, and A1C Overall and by Age and Gender. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack. Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported. CKD Stage, Prior CVD and A1C by Region and BMI. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; BMI = body mass index; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack. Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported. CKD Stage, Prior CVD, and A1C by Duration of T2DM Years, LDL-C, and Albuminuria. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; T2DM = type 2 diabetes mellitus; LDL-C = low-density lipoprotein cholesterol; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; IQR = interquartile range. Prior CVD is any CAD, PAD, or stroke/TIA. N (%) or medians (IQR) are reported as appropriate. CKD Stage, Prior CVD, and A1C, by Chronic Heart Failure, Dementia, and Depression. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; CAD = coronary artery disease; eGFR = estimated glomerular filtration rate; PAD = peripheral artery disease; TIA = transient ischemic attack. Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported. CKD Stage and Prior CVD, by A1C. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; A1C = glycated hemoglobin; eGFR = estimated glomerular filtration rate; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack. Prior CVD is any CAD, PAD, or stroke/TIA. N (%) are reported. The prevalences of the different eGFR categories were 96 902 (37%), 112 705 (43%), 29 069 (11%), 14 698 (6%), and 7529 (3%) for eGFR >90, 60-89, 45-59, 30-44, and <30 mL/min/1.73 m2, respectively (Supplemental Table S1). Figure 1 shows prevalence of antihyperglycemic class use by CKD stage. Biguanides, followed by insulin, sulfonylureas, and DPP-4 inhibitors were the drug classes most frequently used by participants with CKD stages 1 through 3b. In participants with CKD stage 4/5, insulin followed by biguanides, sulfonylureas, meglitinides, and DPP-4 inhibitors were most frequently used.
Figure 1.

Any use of antihyperglycemic classes by CKD stage.

Note. CKD = chronic kidney disease; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1. Other includes Acarbose, Orlistat, Pioglitazone, and Rosiglitazone. Any participant can be counted in more than one class of antihyperglycemic agent.

Any use of antihyperglycemic classes by CKD stage. Note. CKD = chronic kidney disease; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1. Other includes Acarbose, Orlistat, Pioglitazone, and Rosiglitazone. Any participant can be counted in more than one class of antihyperglycemic agent.

Cardiovascular Disease

Three quarters of the participants had no prior CVD (Table 1). In those with prior CVD, stroke/TIA was the most frequent (12.9%) followed by CAD (10.5%) then PAD (3.4%). Participants 65 years or older (33.8% vs 12.6%), men (26.0% vs 18.3%), rural participants (24.7% vs 22.2%), participants with BMI ≥35 kg/m2 (25.2% vs 23.9%), severe albuminuria (35.6% vs 26.6% moderate vs 19.3% none/mild; Table 3), chronic heart failure (57.9% vs 18.3%; Table 4), dementia (50.8% vs 21.0%), and depression (25.5% vs 22.1%) were more likely to have prior CVD. Duration of T2DM was longer (10.1 vs 7.1 years; Table 3) and LDL-C was lower (1.7 vs 2.2 mmol/L) for those with prior CVD. The prevalence of prior CVD was highest in participants with A1C 8.1% to 9% (Table 5). A1C level per se was not clearly associated with a prior history of CVD. The prevalence of any CVD, CAD, PAD, or stroke/TIA was 14.4%, 6.8%, 2.0%, 7.7% for stage 1, 28.8%, 14.4%, 4.3%, 15.6% for stage 2, 35.7%, 17.2%, 5.6%, 21.2% for stage 3a, 44.3%, 21.7%, 8.1%, 27.0% for stage 3b, and 50.9%, 23.6%, 15.2%, 30.2% for stage 4/5 CKD, respectively. Figure 2 shows prevalence of antihyperglycemic class use by prior CVD. Biguanides, followed by insulin, sulfonylureas, DPP-4 inhibitors, SGLT2 inhibitors, and meglitinides were the classes most frequently used by participants with prior CVD.
Figure 2.

Any use of antihyperglycemic classes by prior CVD.

Note. CVD = cardiovascular disease; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1. Other includes Acarbose, Orlistat, Pioglitazone, and Rosiglitazone. Any participant can be counted in more than one class of antihyperglycemic agent.

Any use of antihyperglycemic classes by prior CVD. Note. CVD = cardiovascular disease; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1. Other includes Acarbose, Orlistat, Pioglitazone, and Rosiglitazone. Any participant can be counted in more than one class of antihyperglycemic agent. Figure 3 and Table 6 show use of antihyperglycemic class use by CKD stage and prior CVD. Supplemental Tables S2 and S3 show use of monotherapy and antihyperglycemic agent use alone or in combination, respectively, as a function of CKD stage. Use of DPP-4 inhibitors tended to be higher for people with CKD than without, but use became progressively less common in parallel with lower eGFR. Similar findings were observed for all other agents except for insulin and meglitinide monotherapy and in combination, which was more common at lower eGFR. Supplemental Table S4 shows antihyperglycemic agent use alone or in combination, respectively, as a function of prior CVD.
Figure 3.

Use of antihyperglycemic classes by CKD stage and prior CVD.

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack.

Table 6.

Anti-Hyperglycemic Class by CKD Stage and Prior CVD.

Antihyperglycemic agentsPrior CVDNo CKD, eGFRCKD Stage
>60>9060-89123a3b4/5
DPP-4 inhibitor: Linagliptin, saxagliptin, sitagliptinAny CVD3142 (10.4)1118 (12.2)2024 (9.6)392 (17.6)822 (14.9)1131 (10.9)727 (11.2)310 (8.1)
CAD1602 (11.7)522 (13.5)1080 (11.0)188 (18.0)445 (16.1)577 (11.6)396 (12.4)166 (9.4)
PAD327 (8.9)101 (10.1)226 (8.4)52 (17.2)94 (11.3)158 (9.7)131 (11.0)68 (6.0)
Stroke/TIA1587 (9.3)576 (11.1)1011 (8.5)195 (16.3)400 (13.4)599 (9.7)393 (9.9)163 (7.2)
None15 768 (10.9)8038 (11.1)7730 (10.7)2283 (17.2)2354 (17.2)2382 (12.7)1148 (14.0)425 (11.5)
GLP-1 receptor agonist: Dulaglutide, exenatide, liraglutideAny CVD581 (1.9)296 (3.2)285 (1.4)101 (4.5)124 (2.3)129 (1.2)62 (1.0)20 (0.5)
CAD270 (2.0)120 (3.1)150 (1.5)47 (4.5)66 (2.4)75 (1.5)38 (1.2)5 (0.3)
PAD54 (1.5)29 (2.9)25 (0.9)9 (3.0)16 (1.9)16 (1.0)9 (0.8)5 (0.4)
Stroke/TIA312 (1.8)171 (3.3)141 (1.2)58 (4.8)54 (1.8)58 (0.9)35 (0.9)14 (0.6)
None3824 (2.6)2280 (3.2)1544 (2.1)597 (4.5)409 (3.0)336 (1.8)120 (1.5)19 (0.5)
Insulin: Any insulinAny CVD4299 (14.3)1544 (16.9)2755 (13.1)686 (30.7)1521 (27.6)1916 (18.5)1540 (23.7)1156 (30.2)
CAD2097 (15.4)715 (18.5)1382 (14.1)337 (32.2)836 (30.2)1015 (20.3)849 (26.7)582 (32.8)
PAD594 (16.2)190 (19.0)404 (15.1)100 (33.0)245 (29.5)338 (20.7)298 (25.0)311 (27.3)
Stroke/TIA2347 (13.7)842 (16.2)1505 (12.6)363 (30.3)789 (26.4)1043 (16.9)840 (21.2)647 (28.5)
None17 137 (11.8)9287 (12.9)7850 (10.8)2699 (20.3)2860 (20.9)3105 (16.6)1745 (21.3)1082 (29.3)
Insulin: Insulin monotherapyAny CVD701 (4.3)259 (5.0)442 (4.0)80 (4.9)219 (5.6)363 (6.3)414 (11.5)586 (32.6)
CAD279 (3.5)83 (3.5)196 (3.6)28 (3.5)104 (5.1)185 (6.3)212 (11.4)295 (33.8)
PAD129 (7.0)43 (8.2)86 (6.5)11 (5.6)41 (7.2)79 (8.9)93 (15.5)174 (37.7)
Stroke/TIA427 (4.9)170 (6.0)257 (4.3)50 (5.8)126 (6.2)205 (6.3)244 (11.8)324 (31.8)
None4295 (5.8)2730 (7.4)1565 (4.2)466 (5.4)417 (4.5)489 (4.5)398 (8.2)496 (26.0)
Insulin: Insulin in combinationAny CVD3657 (22.5)1312 (25.1)2345 (21.2)617 (37.8)1323 (34.0)1591 (27.5)1143 (31.8)580 (32.3)
CAD1848 (23.4)647 (26.9)1201 (21.8)316 (39.4)743 (36.5)849 (28.7)644 (34.7)292 (33.4)
PAD474 (25.8)149 (28.5)325 (24.7)92 (46.7)209 (36.9)266 (30.0)207 (34.4)138 (29.9)
Stroke/TIA1948 (22.1)683 (24.0)1265 (21.2)316 (36.8)672 (33.0)863 (26.6)607 (29.4)330 (32.4)
None13 100 (17.6)6719 (18.1)6381 (17.0)2296 (26.6)2477 (26.6)2653 (24.5)1363 (28.2)606 (31.7)
Biguanide: MetforminAny CVD14 661 (48.7)4702 (51.5)9959 (47.4)1481 (66.4)3480 (63.2)4984 (48.0)2663 (40.9)599 (15.6)
CAD7241 (53.1)2230 (57.8)5011 (51.3)747 (71.3)1846 (66.8)2553 (51.2)1382 (43.4)302 (17.0)
PAD1597 (43.5)442 (44.3)1155 (43.2)176 (58.1)488 (58.8)720 (44.1)411 (34.5)114 (10.0)
Stroke/TIA7820 (45.6)2499 (48.0)5321 (44.6)764 (63.7)1808 (60.5)2794 (45.3)1522 (38.4)345 (15.2)
None66 734 (46.1)32 721 (45.3)34 013 (46.9)7836 (59.0)8495 (62.2)9603 (51.4)3838 (46.9)831 (22.5)
Sodium-glucose linked transporter 2 (SGLT2) inhibitor:Canagliflozin, dapagliflozin, empagliflozinAny CVD2184 (7.2)901 (9.9)1283 (6.1)306 (13.7)526 (9.5)494 (4.8)152 (2.3)17 (0.4)
CAD1146 (8.4)421 (10.9)725 (7.4)162 (15.5)292 (10.6)283 (5.7)81 (2.5)11 (0.6)
PAD230 (6.3)91 (9.1)139 (5.2)31 (10.2)71 (8.6)73 (4.5)31 (2.6)4 (0.4)
Stroke/TIA1085 (6.3)476 (9.1)609 (5.1)154 (12.8)249 (8.3)242 (3.9)80 (2.0)8 (0.4)
None11 439 (7.9)6370 (8.8)5069 (7.0)1872 (14.1)1496 (11.0)1044 (5.6)245 (3.0)33 (0.9)
Sulfonylurea:Glibenclamide, gliclazide, glimepirideAny CVD4102 (13.6)1325 (14.5)2777 (13.2)504 (22.6)1100 (20.0)1579 (15.2)1011 (15.5)367 (9.6)
CAD2093 (15.3)676 (17.5)1417 (14.5)261 (24.9)574 (20.8)876 (17.6)525 (16.5)181 (10.2)
PAD421 (11.5)125 (12.5)296 (11.1)55 (18.2)144 (17.3)209 (12.8)149 (12.5)83 (7.3)
Stroke/TIA2145 (12.5)681 (13.1)1464 (12.3)251 (20.9)561 (18.8)818 (13.3)592 (14.9)219 (9.6)
None18 135 (12.5)6370 (8.8)5069 (7.0)2642 (19.9)2904 (21.3)3156 (16.9)1498 (18.3)493 (13.3)
Meglitinide:RepaglinideAny CVD1065 (3.5)295 (3.2)770 (3.7)116 (5.2)338 (6.1)497 (4.8)445 (6.8)431 (11.2)
CAD522 (3.8)137 (3.5)385 (3.9)51 (4.9)170 (6.1)248 (5.0)232 (7.3)185 (10.4)
PAD132 (3.6)36 (3.6)96 (3.6)20 (6.6)47 (5.7)71 (4.3)74 (6.2)129 (11.3)
Stroke/TIA589 (3.4)158 (3.0)158 (3.0)62 (5.2)193 (6.5)289 (4.7)266 (6.7)243 (10.7)
None3753 (2.6)8892 (12.3)9243 (12.7)566 (4.3)659 (4.8)850 (4.5)593 (7.2)419 (11.3)
CombinationsAny CVD8701 (28.9)3037 (33.3)5664 (27.0)1149 (51.5)2494 (45.3)3307 (31.8)2078 (31.9)816 (21.3)
CAD4412 (32.4)1470 (38.1)2942 (30.1)584 (55.8)1352 (48.9)1756 (35.2)1127 (35.4)417 (23.5)
PAD948 (25.8)296 (29.7)652 (24.4)140 (46.2)353 (42.5)493 (30.2)340 (28.6)192 (16.8)
Stroke/TIA4583 (26.7)1594 (30.6)2989 (25.0)593 (49.4)1266 (42.3)1776 (28.8)1146 (28.9)458 (20.1)
None39 044 (27.0)19 924 (27.6)19 120 (26.4)5745 (43.2)5955 (43.6)6251 (33.5)2902 (35.4)958 (25.9)
Other:Acarbose, orlistat, pioglitazone, rosiglitazoneAny CVD486 (1.6)165 (1.8)321 (1.5)44 (2.0)125 (2.3)192 (1.8)110 (1.7)45 (1.2)
CAD198 (1.5)57 (1.5)141 (1.4)15 (1.4)50 (1.8)82 (1.6)48 (1.5)24 (1.4)
PAD51 (1.4)17 (1.7)34 (1.3)9 (3.0)19 (2.3)30 (1.8)18 (1.5)9 (0.8)
Stroke/TIA293 (1.7)102 (2.0)191 (1.6)25 (2.1)74 (2.5)109 (1.8)64 (1.6)25 (1.1)
None2519 (1.7)1043 (1.4)1476 (2.0)253 (1.9)380 (2.8)520 (2.8)264 (3.2)92 (2.5)

Note. CKD = chronic kidney disease; CVD = cardiovascular disease; eGFR = estimated glomerular filtration rate; DPP-4 = dipeptidyl peptidase-4; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; GLP-1 = glucagon-like peptide-1; SGLT2 = sodium-glucose linked transporter 2. N (%) are reported.

Use of antihyperglycemic classes by CKD stage and prior CVD. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; DPP-4 = dipeptidyl peptidase-4; SGLT2 = sodium glucose co-transporter 2; GLP-1 = glucagon-like peptide 1; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack. Anti-Hyperglycemic Class by CKD Stage and Prior CVD. Note. CKD = chronic kidney disease; CVD = cardiovascular disease; eGFR = estimated glomerular filtration rate; DPP-4 = dipeptidyl peptidase-4; CAD = coronary artery disease; PAD = peripheral artery disease; TIA = transient ischemic attack; GLP-1 = glucagon-like peptide-1; SGLT2 = sodium-glucose linked transporter 2. N (%) are reported.

A1C Management

About half of the participants had A1C <7% (Table 1): participants 65 years and older (54.2% vs 47.9%), women (53.2% vs 48.7%), urban participants (51.3% vs 47.2%), no/mild albuminuria (54.8% vs 40.5% moderate vs 36.0% severe), and depression (52.6% vs 50.6%) were more likely to have A1C <7%. Participants younger than 65 years (13.3% vs 6.5%), men (11.1% vs 8.9%), rural participants (12.3% vs 9.8%), participants with BMI ≥35 kg/m2 (10.3% vs 9.2%), severe albuminuria (19.9% vs 17.0% moderate vs 8.3% none/mild; Table 3), and depression (11.0% vs 10.0%) were more likely to have A1C >9%. The level of A1C control was not clearly associated with duration of T2DM, or with LDL-C level (Table 3).

Discussion

This population-based study of 260 903 adult residents of Alberta provides detailed estimates of the prevalence of T2DM as a function of CVD and CKD status, including use of antihyperglycemic medications and a detailed assessment of common comorbidities. There were 6 key findings in this population of people with diabetes, nearly half of whom were aged ≥65 years. First, approximately one third of people with diabetes had CKD and nearly two-thirds had eGFR<90 mL/min/1.73 m.[2] In most cases, CKD was associated with reduced eGFR, although a minority (13.3% of the total study population) had abnormal albuminuria with eGFR ≥60 mL/min/1.73 m2. Second, about one quarter of people with diabetes had known CVD, with stroke or TIA being most common and PAD being least common. Third, among people with diabetes there was a strong relation between kidney disease and atherosclerosis, with the burden of all types of CVD increasing in parallel with the severity of CKD. Fourth, the use of all antihyperglycemic medications was more common in people with CKD as compared with those without. However, the use of all antihyperglycemic medications except insulin and meglitinide was progressively lower in the presence of more severe CKD. Fifth, biguanide (metformin) use was relatively common (19.0%) even among people with stage 4/5 CKD, in whom its use is not recommended.[19] And sixth, the use of newer antihyperglycemic agents such as DPP-4 inhibitors and SGLT2 inhibitors was <20% at every stage of CKD, especially at lower levels of eGFR. For example, the prevalence of SGLT2 inhibitors was 5.3% in people with stage 3a CKD (eGFR 45-59.9 mL/min/1.73 m2). Given that SGLT2 inhibitors may reduce the risk of future cardiovascular events and progressive kidney function loss, patients with CKD may be an attractive population for targeted use of these agents. However, it is possible that use of these newer agents is already higher now than it was in 2017. Among those in whom A1C was measured, more than half (55.3%) had values <7%.

Previous Work

A previous population-based study explored health care use among 569 384 adults with diabetes in Ontario, Canada.[20] The prevalence of CKD stage by eGFR is not reported, but can be calculated from the numbers in the article; the prevalence of CKD was 35.2%, 44.6%, 17.2%, and 2.3% for >90, 60-89, 30-59, and <30 mL/min/1.73 m2, respectively, which is very similar to the results of our study. Our article extends the findings from the Ontario study by including results related to albuminuria and by including detailed information on antihyperglycemic medication use. A previous report from the Canadian Health Measures Survey used eGFR and albuminuria to identify the presence of CKD, and suggested that the prevalence of CKD in the general Canadian population during 2007-2009 was 12.5%[21]; the higher prevalence observed in the current population is consistent with the known status of diabetes as a major risk factor for CKD. A recent study from the US National Health and Nutrition Examination Survey (NHANES) 2007-2014[22] demonstrated that the prevalences of stage 3a, 3b, and 4 or 5 CKD among people with diabetes were 12.5%, 5.3%, and 2.2%, respectively, similar to the 11.1%, 5.6%, and 2.9% observed in the current study. These findings are generally similar to the prevalences of the same CKD stages reported among a population of Spanish patients seen in primary care clinics (11.6%, 5.2%, and 1.2%, respectively)[23]; the lower proportion of more severe CKD in the latter study may reflect the discharge of such patients from primary care settings to nephrology subspecialty practices. Our study also reports on the total prevalence of mildly reduced eGFR (60-89.9 mL/min/1.73 m2), most cases of which do not constitute CKD because of the absence of albuminuria. Specifically, of the 112 705 people in the current study with eGFR 60 to 89.9 mL/min/1.73 m2, only 19 168 (17.0%) had CKD. We did not identify prior studies describing secular trends in the prevalence of CKD among Canadian patients with diabetes. However, studies from the United States suggest that the prevalence of CKD among US patients with diabetes has been approximately stable from 2007 to 2012.[24]

Limitations

This study has several important strengths, including its large size, population-based design, and its use of eGFR and albuminuria to classify participants with respect to CKD status. However, the study also has several limitations that should be considered when interpreting results. First, like all studies based on administrative data, the findings could be influenced by measurement error (eg, accuracy of diagnostic and procedural codes and prescription drug codes used). Second, this analysis was based on data from patients treated in a single Canadian province, and so might not be representative of Canadians living in other provinces where the burden of disease, management practices, or reimbursement status may vary. Third, we used administrative data to identify people with diabetes. The algorithm that we used has 80% sensitivity and 86% positive predictive value for type 1 and type 2 diabetes, although we excluded patients with any claim for type 1 diabetes, which may have slightly altered these diagnostic characteristics of the algorithm. Nonetheless, because no algorithm is perfectly sensitive and because not all cases of diabetes have been identified in clinical practice, our data likely underestimate the true prevalence of T2DM in Alberta. Fourth, not all Alberta patients had assessments of albuminuria, and thus our findings underestimate the true prevalence of CKD among those with diabetes. Finally, we required all patients to have a minimum of 1 year of medical records available prior to their last encounter in the database, which could also have influenced the generalizability of our findings.

Conclusion

In summary, this study reports on the demographic and clinical characteristics of Alberta patients with T2DM by CKD stage and CVD status and type, including a detailed examination of the number and type of antihyperglycemic agents prescribed in this population. These findings will be useful to clinicians, researchers, and policy makers seeking to understand the burden of diabetes-related kidney disease as well as the budget implications and potential clinical benefits of expanded use of antihyperglycemic use in this population. Click here for additional data file. Supplemental material, Supplemental_Figures_and_tables for Characteristics of Adults With Type 2 Diabetes Mellitus by Category of Chronic Kidney Disease and Presence of Cardiovascular Disease in Alberta Canada: A Cross-Sectional Study by Marcello Tonelli, Natasha Wiebe, Jean-Francois Richard, Scott W. Klarenbach and Brenda R. Hemmelgarn in Canadian Journal of Kidney Health and Disease
  23 in total

1.  The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies.

Authors:  Erik von Elm; Douglas G Altman; Matthias Egger; Stuart J Pocock; Peter C Gøtzsche; Jan P Vandenbroucke
Journal:  Lancet       Date:  2007-10-20       Impact factor: 79.321

2.  Assessing validity of ICD-9-CM and ICD-10 administrative data in recording clinical conditions in a unique dually coded database.

Authors:  Hude Quan; Bing Li; L Duncan Saunders; Gerry A Parsons; Carolyn I Nilsson; Arif Alibhai; William A Ghali
Journal:  Health Serv Res       Date:  2008-08       Impact factor: 3.402

3.  Risk of coronary events in people with chronic kidney disease compared with those with diabetes: a population-level cohort study.

Authors:  Marcello Tonelli; Paul Muntner; Anita Lloyd; Braden J Manns; Scott Klarenbach; Neesh Pannu; Matthew T James; Brenda R Hemmelgarn
Journal:  Lancet       Date:  2012-06-19       Impact factor: 79.321

4.  Coding of stroke and stroke risk factors using international classification of diseases, revisions 9 and 10.

Authors:  Rae A Kokotailo; Michael D Hill
Journal:  Stroke       Date:  2005-07-14       Impact factor: 7.914

5.  Diabetes in Ontario: determination of prevalence and incidence using a validated administrative data algorithm.

Authors:  Janet E Hux; Frank Ivis; Virginia Flintoft; Adina Bica
Journal:  Diabetes Care       Date:  2002-03       Impact factor: 19.112

6.  Coding algorithms for defining comorbidities in ICD-9-CM and ICD-10 administrative data.

Authors:  Hude Quan; Vijaya Sundararajan; Patricia Halfon; Andrew Fong; Bernard Burnand; Jean-Christophe Luthi; L Duncan Saunders; Cynthia A Beck; Thomas E Feasby; William A Ghali
Journal:  Med Care       Date:  2005-11       Impact factor: 2.983

7.  The contribution of chronic kidney disease to the global burden of major noncommunicable diseases.

Authors:  William G Couser; Giuseppe Remuzzi; Shanthi Mendis; Marcello Tonelli
Journal:  Kidney Int       Date:  2011-10-12       Impact factor: 10.612

8.  A multicenter study of the coding accuracy of hospital discharge administrative data for patients admitted to cardiac care units in Ontario.

Authors:  Peter C Austin; Paul A Daly; Jack V Tu
Journal:  Am Heart J       Date:  2002-08       Impact factor: 4.749

9.  Diabetes mellitus, fasting blood glucose concentration, and risk of vascular disease: a collaborative meta-analysis of 102 prospective studies.

Authors:  N Sarwar; P Gao; S R Kondapally Seshasai; R Gobin; S Kaptoge; E Di Angelantonio; E Ingelsson; D A Lawlor; E Selvin; M Stampfer; C D A Stehouwer; S Lewington; L Pennells; A Thompson; N Sattar; I R White; K K Ray; J Danesh
Journal:  Lancet       Date:  2010-06-26       Impact factor: 202.731

10.  Overview of the Alberta Kidney Disease Network.

Authors:  Brenda R Hemmelgarn; Fiona Clement; Braden J Manns; Scott Klarenbach; Matthew T James; Pietro Ravani; Neesh Pannu; Sofia B Ahmed; Jennifer MacRae; Nairne Scott-Douglas; Kailash Jindal; Robert Quinn; Bruce F Culleton; Natasha Wiebe; Richard Krause; Laurel Thorlacius; Marcello Tonelli
Journal:  BMC Nephrol       Date:  2009-10-19       Impact factor: 2.388

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  4 in total

1.  Underuse of cardiorenal protective agents in high-risk diabetes patients in primary care: a cross-sectional study.

Authors:  Robin Hao; Tyler Myroniuk; Taylor McGuckin; Donna Manca; Denise Campbell-Scherer; Darren Lau; Roseanne O Yeung
Journal:  BMC Prim Care       Date:  2022-05-24

2.  A retrospective observational population-based study to assess the prevalence and burden of illness of type 2 diabetes with an estimated glomerular filtration rate < 90 mL/min/1.73 m2 in Ontario, Canada.

Authors:  Wally Rapattoni; David Zante; Marko Tomas; Varun Myageri; Shane Golden; Prerna Grover; Ali Tehrani; Brad Millson; Sheldon W Tobe; Jennifer B Rose
Journal:  Diabetes Obes Metab       Date:  2021-01-13       Impact factor: 6.577

3.  Healthy food prescription incentive programme for adults with type 2 diabetes who are experiencing food insecurity: protocol for a randomised controlled trial, modelling and implementation studies.

Authors:  Dana Lee Olstad; Reed Beall; Eldon Spackman; Sharlette Dunn; Lorraine L Lipscombe; Kienan Williams; Richard Oster; Sara Scott; Gabrielle L Zimmermann; Kerry A McBrien; Kieran J D Steer; Catherine B Chan; Sheila Tyminski; Seth Berkowitz; Alun L Edwards; Terry Saunders-Smith; Saania Tariq; Naomi Popeski; Laura White; Tyler Williamson; Mary L'Abbé; Kim D Raine; Sara Nejatinamini; Aruba Naser; Carlota Basualdo-Hammond; Colleen Norris; Petra O'Connell; Judy Seidel; Richard Lewanczuk; Jason Cabaj; David J T Campbell
Journal:  BMJ Open       Date:  2022-02-15       Impact factor: 2.692

4.  Systematic Review and Meta-Analysis of Renin-Angiotensin-Aldosterone System Blocker Effects on the Development of Cardiovascular Disease in Patients With Chronic Kidney Disease.

Authors:  Katsunori Yanai; Kenichi Ishibashi; Yoshiyuki Morishita
Journal:  Front Pharmacol       Date:  2021-07-02       Impact factor: 5.810

  4 in total

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