Controlling the ABCs of diabetes in clinical practice: A community-based endocrinology practice experience

diabetes research and clinical practice 80 (2008) 89–95

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Controlling the ABCs of diabetes in clinical practice: A community-based endocrinology practice experience§ Swarna Varma a,*, Laura L. Boyle a, Manu R. Varma a, Gretchen A. Piatt b a b

Pittsburgh Endocrinology and Diabetes Associates, Bridgeville, PA, United States University of Pittsburgh Diabetes Institute, Pittsburgh, PA, United States

article info

abstract

Article history:

Aims: Determine A1C, blood pressure (BP), and total cholesterol (TC) (Diabetes ABCs) control

Received 11 October 2007

in a community-based endocrinology practice (CBEP) and compare levels to national

Accepted 30 October 2007

averages. Additionally, determine patient factors associated with ABC control.

Published on line 21 December 2007

Methods: A retrospective chart audit of 395 consecutive patients seen for diabetes management was conducted for years 2000–2004 to examine levels of control of the ABCs. Multi-

Keywords:

variate models were used to determine patient factors associated with control.

Diabetes

Results: Significantly more patients met the goal of A1C <7% in the CBEP compared to

Clinical practice

national estimates (CBEP: 47.1% vs. NHANES 1999–2000: 37%, p = 0.003). Similar patterns

ABC goals

were observed for BP (CBEP: 53.2% vs. NHANES 1999–2000: 35.8%, p < 0.0001), TC (CBEP: 82% vs. NHANES 1999–2000: 48.2%, p < 0.0001), and all three ABCs (CBEP: 22%, vs. NHANES 1999– 2000: 7.3%, p < 0.0001). The proportion of patients meeting all three ABC goals in the CBEP increased significantly over time ( p < 0.0001). Multivariate models demonstrated that patients not needing insulin ( p < 0.0001), and taking fewer BP ( p < 0.0001), and cholesterol-lowering medications ( p < 0.02) were significantly more likely to have ABCs in control. Conclusions: Attainment of ABC goals is feasible in a CBEP and can be achieved at rates higher than national averages. Attention to factors that affect these goals is warranted. # 2007 Elsevier Ireland Ltd. All rights reserved.

1.

Introduction

The current diabetes epidemic affects nearly 20.8 million individuals in the United States [1], with the prevalence expected to increase to 48.3 million by 2050 [2]. Each year, thousands of individuals suffer from diabetes-related complications leading to increased morbidity and diabetes-related mortality. Landmark trials have tested the efficacy of intensive diabetes management in preventing or delaying micro and macrovascular diabetes complications. These trials established that control of A1C, blood pressure (BP), and cholesterol §

(ABCs of diabetes) can significantly delay or prevent diabetesrelated complications [3–9]. Despite numerous programs and efforts that target the attainment of ABC goals [10,11], translating the results of these trials into clinical practice remains a challenge. National data demonstrate that only a small fraction of adults meet the established guidelines for control of the ABCs [12–15]. The National Health and Nutrition Examination Survey (NHANES) 1999–2002 demonstrated that only half of individuals with diabetes met the goal of A1C <7% [12]. Additionally, only one-third of the population achieved BP <130/85 mmHg and LDLc <100 mg/dL [13,15]. A mere 7% of the population met all three ABC goals [15]. While a number of

Data previously presented at the American Diabetes Association 66th Annual Scientific Sessions, Washington, DC, 2006. * Corresponding author at: 1370 Washington Pike, Suite L8, Bridgeville, PA 15017, United States. Tel.: +1 412 221 4740; fax: +1 412 221 5620. E-mail address: [email protected] (S. Varma). 0168-8227/$ – see front matter # 2007 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.diabres.2007.10.029

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diabetes research and clinical practice 80 (2008) 89–95

reports using population-based samples have been published that describe attainment of ABC control [15–17], there remains little data on goal attainment in the clinical practice setting. Moreover, if ABC goals are met, it is important to characterize factors that are related to the observed improvements so that clinical care can be tailored to meet individual needs [15]. We therefore sought to determine the levels of, and factors related to, ABC control in a community-based endocrinology practice (CBEP), and compare the levels to national averages.

2.

Methods

We identified 395 consecutive patients seen in consultation for diabetes management in a CBEP. In order to be included in the analyses, a patient had to have 2 A1C, BP, and TC measurements respectively. All patients were 18 years or older with a diabetes diagnosis before or during calendar year 2004. Patients were referred to the CBEP after inpatient consultation, from primary care physicians, and through self-referral. Demographic, anthropometric, metabolic, and medication data were collected for each patient’s office visits over 5 years (2000–2004) as part of routine clinical care.

on the endocrinologist’s clinical judgment and were individualized and adjusted for each patient. Patients using oral agents were instructed to record blood glucose levels 2 times daily using a similar grid system. All patients were encouraged to contact the CBEP at least once per week for adjustments to their treatment regimen. Instructions for preventing and treating hypoglycemia were given [26] and glucose monitoring prior to driving or operating equipment was encouraged. Angiotensin-converting enzyme (ACE) inhibitors [27–29] and angiotensin receptor blockers (ARBs) [30–34] were preferentially used for BP control or for treatment of nephropathy. Statins were used in patients with elevated LDL levels, whenever possible, for their cardiovascular protective effects [35–37]. Combination drug therapy was used when appropriate. Office follow-up was scheduled in 1–2 months for individuals not meeting all ABC goals, until goals were met, and every 3–4 months for individuals who met all goals. Patients were encouraged to have laboratory work completed 8–10 days prior to their office visit so results could be discussed during the visit.

2.2. 2.1.

Measures and study outcomes

CBEP patient management

A physical exam was conducted at each visit. Principles of basal/bolus therapy were applied to patients on subcutaneous insulin, insulin pumps, or combination of insulin and oral agents, to target both fasting and postprandial hyperglycemia [18–22]. Similar concepts were simulated for patients on secretagogues, leading to use of meglitinides whenever accepted by the patient. Thiazolidinediones and biguanides were used to decrease insulin resistance whenever not contraindicated [23,24]. Physician charting used a grid system, with medical problems and corresponding actions (prescribing or adjusting medications, instructions on diet, exercise, ordering appropriate labs and referrals to other specialists) in parallel columns. Diabetes type and duration, A1C, BP, cholesterol results, and a complete review of systems were noted at each visit. During the office visit, simplified handouts detailing demonstrated risk reductions for microvascular and macrovascular complications were given to patients and discussed with them. Additionally, patients received a grocery shopping guide that included healthy food choices focusing on a low-fat, low-glycemic, high fiber diet [25]. Patients were also encouraged to increase physical activity as feasible based on their health status. A ‘‘team of four’’ philosophy (patient, family members, physician, and support staff working together) was used to achieve ABC goals. Insulin-requiring patients were instructed to record blood glucose levels 2–4 times daily to visualize diurnal and nocturnal patterns. Directions were given on a single sheet for basal therapies and bolus doses, using a baseline dose along with instructions for correction doses according to a simple sliding scale. Based on activity and food intake, instructions were given. Similar principles were applied to insulin pump therapy [20]. All insulin adjustments were based

All patients had height, weight, and BP measured according to standard clinical practice methods. A1C and lipids were collected as part of routine clinical care in the local hospital or commercial lab, and medication usage was noted from patient charts. Combination medications were separated into their individual components for purposes of classification. Self-monitoring of blood glucose was captured as part of routine care. Primary outcomes included the proportion of subjects with an A1C <7%, BP <130/80 mmHg, and total cholesterol (TC) <200 mg/dL. Secondary outcomes included the proportion of subjects with LDLc <100 mg/dL and the proportion of subjects with all ABCs (A1C, BP, and TC) in control. The University of Pittsburgh Institutional Review Board approved the study protocol for data analysis.

2.3.

Statistical analysis

Laboratory and medication data from all time points were used in the analyses. Measures of central tendency (e.g. proportions, means, standard deviations, etc.) were used for descriptive analyses. Student’s t-tests and Pearson’s chisquare tests were used in determining significant differences between groups. In determining if the proportion of subjects meeting ABC goals increased over time, a chi-square test for trend was used. Multivariate associations with A1C <7%, BP <130/80 mmHg, and TC <200 mg/dL were examined using forward logistic regression. Explanatory variables chosen for inclusion were not limited based on statistical significance but were based on literature review and analyses previously conducted in addition to the current analyses. Age, gender, race, insulin use, and BMI were forced into the A1C model. These covariates plus number of BP and cholesterol-lowering medications were forced into the BP and TC models respectively. Each outcome variable was a separate multivariate model. Multivariate analysis to examine associations

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diabetes research and clinical practice 80 (2008) 89–95

with achievement of all three ABCs, as a whole, was not performed due to the small number of patients achieving all three outcomes. All analyses were conducted using SAS v.8.2, Cary, North Carolina.

statistically significant differences were apparent in the proportion of males (CBEP: 59.2% vs. NHANES 1999–2000: 50%, p = 0.02) and non-Hispanic whites (CBEP: 92.7% vs. NHANES 1999–2000: 59.8%, p < 0.0001), but not in mean age (CBEP: 60.4 vs. NHANES 1999–2000: 59.3, p = 0.27) [14].

3.

Results

3.2.

3.1.

Population characteristics

Overall, the proportion of subjects achieving goals in the CBEP significantly surpassed national estimates (Fig. 1). Significant disparities emerged in the proportion of subjects achieving goal levels for A1C (CBEP: 47.1% vs. NHANES 1999–2000: 37%, p = 0.003), BP (CBEP: 53.2% vs. NHANES 1999–2000: 35.8%, p < 0.0001), TC (CBEP: 82% vs. NHANES 1999–2000: 48.2%, p < 0.0001), and all three ABCs (CBEP: 22%, vs. NHANES 1999– 2000: 7.3%, p < 0.0001) [14]. When NHANES was updated for 1999–2002, similar patterns were observed for BP (CBEP: 53.2% vs. NHANES 1999–2002: 39.6%, p < 0.0001) and LDLc (CBEP:

Demographic and clinical characteristics are presented in Table 1. The CBEP population included individuals with both type 1 (15.9%) and type 2 (84.1%) diabetes. The average age was 60.4 years. The majority were male (59.2%), non-Hispanic white (92.7%), and currently being treated with glucose (99.8%), BP (92.9%), or cholesterol (87.1%) lowering medication (Table 1). When the CBEP patients were compared to the 1999–2000 NHANES cohort to determine generalizability,

Achievement of the ABCs

Table 1 – Demographic, clinical characteristics and medication use of the community-based endocrinology practice cohort (n = 395) Mean (S.D.) or % (n) Age (years) Duration (years) Gender (% male) Race (% non-Hispanic white) Type of diabetes (% type 1) Insulin (% yes) BMI A1C Blood pressure (mm Hg) Systolic blood pressure Diastolic blood pressure Total cholesterol (mg/dL) LDLc (mg/dL)

Range

60.4 11.2 59.2 92.7 15.9 63.8 33.1 7.4

(14.8) (9.0) (231) (355) (61) (252) (8.7) (1.5)

20–89 1–44 – – – – 18–61 4.7–13.8

128.9 73.3 173.8 93.6

(10) (6.5) (41.2) (29.4)

104–173 50–98 88–437.7 27–273

Antihypertensive medication (% yes) Glucose-lowering medication (% yes) Lipid lowering medication (% yes)

92.9 (367) 99.8 (394) 87.1 (344)

– – –

Glucose-lowering medications Insulin Thiazolidinediones Sulfonylureas Meglitinitdes Biguanides Alpha glucosidase inhibitors

60.2 40.7 20.8 54.3 17.3 6.3

(238) (161) (82) (214) (68) (25)

– – – – – –

Blood pressure-lowering medications ACE inhibitors ARBs Beta blockers Alpha-adrenergic blockers Alpha agonists Calcium channel blockers Vasodilators Diuretics

46.3 (183) 37.3 (147) 26.5 (105) 5.1 (20) 0.91 (4) 31 (122) 0.73 (3) 28.1 (111)

– – – – – – – –

Cholesterol-lowering medications Statins Fibrates Bile acid binding Cholesterol absorption inhibitor Nicotinic acid

63.4 12.9 2.5 13.5 0.7

– – – – –

(250) (51) (10) (53) (3)

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diabetes research and clinical practice 80 (2008) 89–95

control overall (r = 0.04, p = 0.18) or when stratified by insulin use (insulin use: r = 0.03, p = 0.34; no insulin use: r = 0.04, p = 0.44). Patient weight remained steady through the study period (data not shown), despite tight levels of glycemic control.

3.3.2.

Fig. 1 – Comparison of the proportion of subjects meeting recommended levels of control in a community-based endocrinology practice to NHANES 1999–2000.

68.8% vs. NHANES 1999–2002: 36%, p < 0.0001); however, the proportion of subjects achieving goal was similar to the national estimate for A1C (CBEP: 47.1% vs. NHANES 1999–2002: 49.8%) [12]. Additionally, the proportion of patients meeting all ABC goals in the CBEP increased significantly over time, from 12.4% in 2000 to 23.6% in 2004 ( p < 0.0001).

3.3.

Factors associated with achievement of the ABCs

3.3.1.

Glycemic control

Overall, subjects who were younger (59.0 y vs. 62.3 y, p = 0.03) and currently using insulin (89.6% vs. 36.9%, p < 0.0001) were more likely to achieve an A1C <7%. Additionally, 79.7% subjects with type 1 diabetes compared to 47.7% of subjects with type 2 diabetes achieved an A1C <7% ( p < 0.0001). However, after multivariate adjustment all associations were attenuated except for insulin use. Subjects not needing insulin were significantly more likely to have an A1C <7% (OR = 0.08, 95% CI: 0.04, 0.13) (Table 2). The frequency of glucose readings <80 mg/dL was not significantly correlated with glycemic

Blood pressure

When BP control was examined, younger age was significantly associated with BP <130/80 mmHg (57.8 y vs. 63.4 y, p = 0.001), as was lower BMI (kg/m2) (32 vs. 34.4, p = 0.005). Additionally, those taking fewer BP-lowering medications were more likely to have a BP <130/80 mmHg (OR = 0.47, 95% CI: 0.38, 0.58). After multivariate adjustment, the association with age was attenuated; although significant associations remained between lower BMI (OR = 0.97, 95% CI: 0.94, 1.00) and fewer BP-lowering medications (OR = 0.48, 95% CI: 0.37, 0.64) with BP control (Table 2).

3.3.3.

Total cholesterol

Unlike BP control, older subjects were more likely to have TC <200 mg/dL (61.3% vs. 57.5%, p = 0.05). Additionally, male gender was significantly associated with attainment of TC <200 mg/dL (male: 88.2% vs. female: 77.4%, p = 0.01). After multivariate adjustment, associations remained, as older (OR = 1.0, 95% CI: 1.0, 1.1) males (OR = 0.44, 95% CI: 0.23, 0.86) on fewer cholesterol-lowering medications (OR = 0.45, 95% CI: 0.23, 0.88) were more likely to achieve a TC <200 mg/dL.

4.

Discussion

This retrospective medical chart audit provides evidence that control of the ABCs of diabetes is feasible and can be achieved in a CBEP. The CBEP results significantly surpassed national estimates [12–15] for BP and cholesterol control, and compared favorably to the results observed in landmark clinical trials for

Table 2 – Factors associated with control of the ABC goals in a community-based endocrinology practice cohort (2000– 2004) Outcome variable

Variable

b

OR

95% CI

p-Value

A1C <7% (n = 324)

Age (years) Gender Race Insulin use BMI

0.01 0.04 0.25 2.6 0.01

1.0 1.0 1.3 0.08 1.0

(0.99, 1.0) (0.6, 1.8) (0.49, 3.4) (0.04, 0.13) (0.98, 1.0)

0.19 0.90 0.61 <0.0001 0.60

Blood pressure <130/80 mmHg (n = 335)

Age (years) Gender (% male) Race (% non-Hispanic white Insulin use BMI (mean) Mean number of blood pressure lowering medications

0.01 0.44 0.56 0.25 0.03 0.72

0.99 1.56 1.75 1.28 0.97 0.48

(0.97, (0.94, (0.71, (0.78, (0.94, (0.37,

0.23 0.09 0.22 0.33 0.05 <0.0001

Total cholesterol <200 mg/dL (n = 324)

Age (years) Gender Race (% non-Hispanic white) Insulin use BMI Mean number of cholesterol-lowering medications

0.04 0.82 0.12 0.30 0.003 0.79

1.03 0.44 1.12 1.36 1.0 0.45

(1.0, 1.1) (0.23, 0.86) (0.39, 3.25) (0.75, 2.46) (0.97, 1.0) (0.23, 0.88)

Each outcome variable is a separate model. Reference group for each model is subjects who do not meet the goal level.

1.0) 2.6) 4.3) 2.1) 1.0) 0.64)

0.002 0.02 0.83 0.32 0.87 0.02

diabetes research and clinical practice 80 (2008) 89–95

glycemic control, BP levels, and cholesterol parameters [3,28– 30,33–41]. Achieving glycemic control may be the most elusive of all ABC goals. Numerous factors predict and influence glycemic control including smart food choices, hypoglycemia prevention, and adjustment of glucose-lowering medication doses; however, there remains a lack of consensus on the relationship between demographic and clinical characteristics and glycemic control. Our univariate analyses support this theory as a number of demographic and clinical factors influenced glycemic control; however, after multivariate adjustment, lack of need for insulin was the only covariate that was significantly associated with achieving an A1C <7%. As insulin is often thought of as an index for disease severity, this pattern may reflect patients who are not as advanced in their disease process achieving an A1C <7%. Additionally, early, aggressive therapeutic management may have also contributed to achievement of the A1C goal in subjects not using insulin. Similar glycemic control patterns were observed during the fourth year of the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) study. Median A1C values converged to 8% when intensive insulin therapy was implemented in a real world setting [42]. As hypoglycemia and weight gain are critical factors when trying to attain glycemic control [43–45] it is important to understand their relationship as well. It is well documented that as glycemic control tightens, patients may experience weight gain and/or hypoglycemia [43–45]. Although the majority of CBEP patients achieved an A1C <7%, the frequency of blood glucose readings <80 mg/dl did not correlate with glycemic control and weight remained steady over the study period. This is in contrast to the results of the United Kingdom Prospective Diabetes Study (UKPDS) [24] and the DCCT [4] where significant weight gain occurred in the intensively treated groups. While there may be several explanations for lack of weight gain in the CBEP, we hypothesize that it may be related to different approaches to nutritional counseling and encouragement of physical activity. As studies have demonstrated significant renal [28,30,32,33] cardiovascular [28,31,38,46] and retinopathy [46] risk reduction with control of BP, examining factors related to achievement of BP goal was critical in order to tailor care to meet the needs of the patient. Significant associations between lower BMIs and fewer BP-lowering medications and BP control were observed. These associations likely reflect the need for intensive intervention in individuals with higher BMIs. Additionally, as with glycemic control, patients on fewer BP-lowering medications may not be advanced in their disease progression and therefore able to attain the BP goal. While our study did not measure the incidence of diabetes complications as the aforementioned studies did, striving to maintain BP at goal levels with medications and/or lifestyle modification may result in similar degrees of benefit. The clinical significance of the observed association between older males and TC control could be a facet of an older population. Studies demonstrate [47,48] that TC concentration decreases with age. However, the reasons for this phenomenon remain controversial. In Volpato et al.’s work [48], indicators of poor health status accounted for nearly twothirds of the crude effect of age on TC level in both men and

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women. As nearly half of our cohort was 65 or older, this phenomenon could be occurring in the CBEP. Similar to glycemic and BP control, the need for fewer lipid-lowering medications was associated with cholesterol control. Again, this may be reflective of disease severity, or perhaps the patients’ diet, or genetic predisposition. The CBEP data confirm the findings of landmark clinical trials, as well as NHANES estimates, which demonstrate the importance of achieving goal levels for A1C, BP, and cholesterol [12–15]. However, this study also adds significantly to the existing literature. It is one of the first studies, to our knowledge, which examined achievement of ABC goals in clinical practice, and more specifically in a CBEP, where specialized diabetes care is delivered. Notably, when the ABCs were examined collectively as one outcome, the proportion of subjects meeting all three goals increased significantly over time in the CBEP. This is in contrast to national estimates which have increased marginally over the past two years (personal communication, Sharon Saydah, PhD). Although only 22% of the CBEP achieved all three ABC goals, this percent is significantly higher than the 7.3% reported for the nation in NHANES [14]. Additionally, relatively little is known about what patient factors are associated with control of the ABCs. Numerous studies report that outcomes improve following interventions; however, very few report data on factors that are associated with the improvement. Our multivariate analyses help to close this gap in the literature. Several limitations may have affected the outcomes observed in this study. The primary limitation is that the data used in these analyses were from a single CBEP. Therefore, the results observed may not be generalizable to larger populations or to populations of patients not treated by an endocrinologist. When the CBEP was compared to NHANES 1999–2000 to determine generalizability, mean age was similar, however, highly significant differences emerged in race and gender, with the CBEP having nearly all non-Hispanic white subjects and significantly more males [14]. We attempted to avoid this known bias by reviewing consecutive patient charts; indeed, subjects were not chosen with an a priori hypothesis in mind. Additionally, we were not able to capture a wide variety of socioeconomic and demographic data, as these data are not typically collected in clinical practice, therefore limiting the robustness of the multivariate analyses. The results of this retrospective chart audit demonstrated that achieving goal levels for the ABCs of diabetes is feasible in a CBEP. ABC goals were achieved at rates higher than national averages with progressive increases in the proportion of patients who achieved all ABC goals over the study period. We speculate that using the CBEP model in the primary care setting, where 90% of diabetes care is delivered, could improve diabetes outcomes. A greater investment of time and resources in providing quality diabetes care, prior to the onset of complications, may lead to decreased morbidity and mortality and increased quality of life for persons with diabetes.

Acknowledgement We would like to thank Drs. David Nathan and Janice Zgibor for reviewing this manuscript.

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Conflict of interest Swarna Varma is on the speakers bureau of Eli Lilly, SanofiAventis, Novartis, Daiichi Sankyo, Glaxo Smith-Kline, Takeda, Proctor & Gamble, has received consulting fees from Amylin and NovoNordisk, and owns stock in Amylin Pharmaceuticals.

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