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The Prognostic Significance of Diabetes in Patients Diagnosed With Peripheral Arterial Disease
CANADIAN JOURNAL OF DIABETES
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The Prognostic Significance of Diabetes in Patients Diagnosed With Peripheral Arterial Disease Kristen Migliaccio-Walle1 BS, Khajak J. Ishak2 PhD, Irina Proskorovsky2 BSc, J. Jaime Caro1,3 MCDM FRCPC FACP Caro Research Institute, Concord, Massachusetts, United States Caro Research Institute, Montreal, Quebec, Canada 3 Division of General Internal Medicine and Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada 1 2
A B S T R A C T OBJECTIVE
To evaluate the impact of diabetes on outcomes in patients with peripheral arterial disease (PAD). METHODS
Outcomes in 16 440 PAD patients from Saskatchewan, Canada (1985 to1995) were compared by diabetes status. Patient history and characteristics were available back to January 1980; follow-up to December 2000. Proportional hazards analyses measured the effect of diabetes on mortality and incidence of myocardial infarction (MI) and stroke in patients with PAD. Times to hospitalization were also calculated. R E S U LT S
One-quarter (23.9%) of patients had diabetes. Mortality was 37% higher among these patients and hazards of MI and ischemic stroke were also substantially higher (hazard ratios >1.50). Patients with diabetes were hospitalized more frequently and earlier regardless of cause. Hospitalization rates were 50 to 100% higher among patients with diabetes. CONCLUSIONS
Diabetes in patients with PAD is associated with substantially higher rates of morbidity and mortality.
R É S U M É OBJECTIF
Évaluer les répercussions du diabète sur le devenir des patients atteints d’artériopathie périphérique (AP). MÉTHODES
Le devenir de 16 440 patients atteints d’AP de la Saskatchewan, Canada (1985 à 1995) a été comparé selon que les patients étaient diabétiques ou non. Les dossiers des patients contenaient leurs antécédents et leurs caractéristiques depuis janvier 1980 et les données du suivi jusqu’à décembre 2000. Des analyses des hasards proportionnels ont mesuré l’effet du diabète sur la mortalité et l’incidence de l’infarctus du myocarde (IM) et de l’accident vasculaire cérébral chez les patients atteints d’AP. On a aussi calculé le délai de survenue de l’hospitalisation. R É S U LTAT S
Le quart (23,9 %) des patients étaient diabétiques. Le taux de mortalité a été de 37 % supérieur chez ces patients et les risques d’IM et d’accident ischémique cérébral étaient aussi considérablement supérieurs (rapports des risques > 1,50). Les patients diabétiques ont été hospitalisés plus souvent et plus tôt pour diverses causes. Les taux d’hospitalisation ont été de 50 à 100 % plus élevés chez les patients diabétiques. CONCLUSION
Le diabète chez les patients atteints d’AP est associé à des taux considérablement supérieurs de morbidité et de mortalité. Address for correspondence: Kristen Migliaccio-Walle Caro Research Institute 336 Baker Avenue Concord, Massachusetts United States 01742 Telephone: (978) 371-1660 Fax: (978) 371-2445 E-mail: [email protected]
M OT S C L É S
risque de manifestation, hospitalisation, mortalité, artériopathie périphérique, pronostic
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
impact of diabetes in pad 141 K E Y WO R D S
Event risk, hospitalization, mortality, peripheral arterial disease, prognosis INTRODUCTION Atherosclerotic disease of the peripheral arteries produces pain, discomfort and exercise limitation (1-3). It can lead to increasingly serious complications requiring surgical intervention (4,5) and can even result in death (6-8), yet it has not received the same level of attention as myocardial infarction (MI) or stroke. Estimates of the prevalence of peripheral arterial disease (PAD) range from <5% in younger age groups to >20% in the elderly (9-14). Advancing age, male gender, a history of diabetes and smoking are associated with a higher risk of PAD (15,16). Patients experience the frequently painful symptoms associated with this diagnosis, yet management is often less aggressive than for acute atherothrombotic diseases such as MI and stroke (17). Diabetes is known to impact negatively on the prognosis of patients with MI (18,19) and stroke (20), and is a major risk factor for the development of macrovascular disease, including disease in the limb arteries (21-24). Despite the increasing awareness that patients with diabetes are at a substantially increased risk of morbidity, mortality and hospitalization (25-29), the influence of diabetes on the course of patients with PAD is poorly understood. It is not known empirically whether diabetes raises the risk of complications in patients with PAD or the extent to which it increases mortality. These are important aspects for determining prognosis, and helping patients and their families make decisions regarding treatment. This paper examines whether diabetes substantially affects the prognosis of patients with PAD. METHODS Study population Saskatchewan Health, the government department that oversees healthcare in this western Canadian province, maintains 10 databases that track all formulary outpatient prescriptions, physician services, hospitalizations and vital statistics for approximately 1 million residents covered by provincial health insurance.These databases can be linked electronically using unique patient identifiers (30). These healthcare databases were used to identify patients with a diagnosis of PAD and to obtain information on the course of their disease over subsequent years. Residents of the province ≥21 years of age diagnosed with PAD between January 1, 1985 and December 31, 1995 (index period) were eligible. First Nations peoples are not included in the Saskatchewan Health databases because this potentially high-risk group’s health costs are covered by the federal government. No exclusion criteria were specified. Patients with PAD were identified using the International
Classification of Diseases (ICD-9) codes 440, 440.2 or 443.9. If the broad 3-digit code 443 coincided with documentation of prescription for pentoxifylline, it was also included based on the assumption that all patients who received this prescription were diagnosed with PAD (31). The date of first diagnosis of PAD (index diagnosis) was taken as the date of entry into the study (index date). Either hospital admission or physician visit was accepted (depending on where the diagnosis was initially recorded). Medical history was available back to January 1, 1980, and follow-up was complete through March 2000, or until a patient could no longer be followed due to emigration or death. Patients were classified into 2 groups: those with a history of diabetes at the time of the index diagnosis; and those without diabetes, if they had no history of diabetes prior to diagnosis of PAD.Amongst patients without diabetes, followup was censored (i.e., discontinued) upon diagnosis of diabetes in patients who had a recorded diagnosis of diabetes after the index diagnosis. Medical history prior to the date of the index diagnosis was also examined to identify other conditions of interest: atrial fibrillation, angina, heart failure, treatment of hypercholesterolemia, hypertension, ischemic stroke, MI and transient ischemic attack (TIA). Data on smoking history or laboratory values were not available in these databases. Mortality Survival in each group was established using the KaplanMeier method, and was calculated from the date of PAD diagnosis to either the date of death, the date patient was censored or the last follow-up date available.The overall survival curves were compared using log-rank and Wilcoxon tests. Differences in overall mortality were also quantified by hazard ratios (HR) and the corresponding 95% confidence intervals (CI). Proportional hazards models were used to evaluate the impact of other potential determinants. The assumption of proportionality of the effect of diabetes was verified by including interactions between indicators of diabetes and time. Morbidity Morbidity was examined with respect to hospitalizations for major cardiovascular (CV) events (ischemic stroke and MI) identified using ICD-9 codes (433.x to 434.x and 436.x for ischemic stroke; 410.x for MI). Event rates were defined as the total number of hospitalizations divided by the patient time accumulated (i.e. hospitalizations per patient-year of follow-up) in each of 8 time periods: 4 time periods in year 1 CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
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(30 days, 60 days, months 3 to 6, months 7 to 12) and years 2 to 5. For patients who suffered >1 type of event in a period, each occurrence contributed independently to the appropriate type (i.e., stroke or MI) with the corresponding follow-up time to each event calculated. Hospitalization CV-related and all-cause hospitalizations were examined in patients with and without diabetes. A hospitalization was considered CV-related if the primary diagnosis was ischemic stroke, TIA, MI, stable or unstable angina, heart failure or a complication of PAD. Hospitalization occurrence was estimated for each of the time periods defined above as the proportion of patients hospitalized and as the rate of hospitalization (hospitalizations per patient-year of followup) for each type of hospitalization over time.The time until first hospitalization after index diagnosis of PAD was estimated for each hospitalization type using standard failuretime analyses (32), and the impact of diabetes was examined using Kaplan-Meier methods.To determine the effect of diabetes on total hospitalization rates, admissions occurring in 9 discrete time periods were evaluated: first 3 months, months
4 to 6, months 7 to 12, years 2 through 5 and every 5 years thereafter, through year 15. RESULTS A cohort of 16 440 patients with a first diagnosis of PAD was identified during the index period (1985 to 1995). Three patients were excluded from the analysis for administrative reasons (e.g. exit date recorded prior to index date). Of the remaining 16 437 patients, one-quarter (23.9%) had a documented history of diabetes upon entry into the cohort. Mean follow-up was slightly shorter among patients with diabetes (5.9 vs. 6.8 years in patients without diabetes). Patients with and without diabetes were comparable in terms of age and sex, but other risk factors were significantly more prevalent among patients with diabetes (Table 1). Mortality A significantly greater proportion of patients with diabetes died during the study period (69.0 vs. 50.2% p<0.0001) (Figure 1). The median survival of patients without diabetes was 9.6 years vs. 5.6 years in patients with diabetes. Controlling for other risk factors of death in a proportional
Table 1. Patient characteristics and medical history at time of diagnosis of PAD
Mean follow-up, years (±SD) Mean age, years (±SD) Male, n (%) Qualifying diagnosis of PAD in hospital, n (%)
Diabetes n=3172
No diabetes n=13 265
p value
5.9 (4.2)
6.8 (4.5)
<0.0001
68.6 (8.2)
66.9 (9.4)
<0.0001
1866 (58.8)
7162 (54.0)
<0.0001
490 (15.5)
1168 (8.8)
<0.0001
Medical history Atrial fibrillation, n (%)
<0.0001 215 (6.8)
647 (4.9)
<0.0001
Angina, n (%)
1233 (38.9)
4213 (31.8)
<0.0001
Heart failure, n (%)
1055 (33.3)
3121 (23.5)
<0.0001
275 (8.7)
853 (6.4)
<0.0001
2147 (67.7)
7405 (55.8)
<0.0001
Ischemic stroke, n (%)
508 (16.0)
1601 (12.1)
<0.0001
MI, n (%)
657 (20.7)
2211 (16.7)
<0.0001
TIA, n (%)
457 (14.4)
1759 (13.3)
0.089
Hypercholesterolemia, n (%) Hypertension, n (%)
MI = myocardial infarction PAD = peripheral arterial disease SD = standard deviation TIA = transient ishemic stroke
impact of diabetes in pad 143
Morbidity MI occurred in 9.8% of patients with diabetes compared to 6.4% (p<0.0001) of those without diabetes; ischemic stroke occurred in 10.5% and 6.9% (p<0.0001), respectively. Similarly, a history of diabetes was associated with higher rates of MI and ischemic strokes throughout follow-up (Table 2). Ischemic strokes occurred more frequently than MI in the first 3 months of the study, regardless of diabetes status (Table 3). However, the 2 events occurred at fairly similar rates within each group over time, with the exception of the 3- to 6-month time period in which stroke occurred more frequently than MI among patients without diabetes. In the 6- to 12-month period, strokes occurred more frequently than MI among patients with diabetes. Diabetes was associated with significantly increased risk for MI (1.56 [1.37–1.78] and ischemic stroke 1.52 [1.33–1.72]. For both MI and
ischemic stroke, the estimate of the effect of diabetes did not vary substantially over time. Hospitalizations The proportion of patients hospitalized at least once for any cause was 89.3% among those with diabetes compared with 82.3% of those without diabetes (p<0.0001). Hospitalizations for CV events occurred in 46.8% of patients with diabetes vs. Figure 1. Survival following diagnosis of PAD by diabetes status 100 90
Diabetes
80 Proportion alive (%)
hazards model (Table 2), there was a 37% increase (95% CI, 31–44%) in the hazard of death for patients with diabetes. There were no serious departures from the assumption of proportional hazards in these analyses, suggesting that the increase in risk among patients with diabetes was relatively stable over time. In addition to diabetes, significant predictors of death included age (continuous), male gender, atrial fibrillation, heart failure, hypercholesterolemia and prior ischemic stroke (Table 2).
No diabetes
70 60 50 40 30 20 10 0
0
1
2
3
4
5
6
7 8 9 10 11 12 13 14 15 Time (years)
PAD = peripheral arterial disease
Table 2. Hazard ratios of death, MI and ischemic stroke by risk factors* Death
MI
Ischemic stroke
Age at index diagnosis (per year)
1.08 (1.08, 1.09)
1.03 (1.02, 1.03)
1.04 (1.04, 1.05)
Male gender
1.26 (1.21, 1.32)
1.62 (1.43, 1.84)
1.23 (1.09, 1.38)
History of diabetes
1.37 (1.31, 1.44)
1.56 (1.37, 1.78)
1.52 (1.33, 1.72)
History of atrial fibrillation
1.17 (1.08, 1.27)
—
1.62 (1.31, 1.99)
—
1.50 (1.32, 1.71)
—
History of heart failure
1.90 (1.81, 1.99)
—
1.25 (1.10, 1.43)
Hypercholesterolemia treatment
0.77 (0.70, 0.85)
—
—
—
1.15 (1.01, 1.30)
1.43 (1.27, 1.62)
1.56 (1.48, 1.65)
1.30 (1.10, 1.54)
2.13 (1.84, 2.47)
History of MI
—
1.64 (1.42, 1.89)
—
History of TIA
—
—
1.37 (1.18, 1.59)
History of angina
History of hypertension History of ischemic stroke
These equations represent the final equations, which excluded factors that were not significant, as these can introduce noise and reduce the precision of the estimates. Blank cells indicate that these variables were not included in the final equations *Hazard ratios (95% CI) obtained from proportional hazards analyses MI = myocardial infarction TIA = transient ischemic attack
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
CANADIAN JOURNAL OF DIABETES
144 Table 3. Rate of hospitalizations due to MI and ischemic stroke by diabetes status and time since index diagnosis* Ischemic stroke
MI Time
No diabetes
Diabetes
No diabetes
Diabetes
Months 0–3
0.022
0.033
0.029
0.046
Months 3–6
0.014
0.024
0.022
0.023
Months 6–12
0.018
0.029
0.018
0.035
Years 1–2
0.014
0.029
0.015
0.027
Years 2–3
0.011
0.024
0.014
0.022
Years 3–4
0.011
0.017
0.013
0.028
Years 4–5
0.013
0.021
0.012
0.017
Years 5–10
0.013
0.025
0.013
0.025
Years 10+
0.015
0.022
0.013
0.027
*Expressed as number of hospitalizations per patient-year calculated in each time period MI = myocardial infarction
Proportion hospitalized (%)
32.0% of those without diabetes (p<0.0001). The time to among patients with diabetes (p<0.001) (Figure 3).The rates first hospitalization for any cause and CV events is shown in were highest for both groups during the first few months. Figure 2 and Table 4. More than half (56.8%) of patients with Rates stabilized after the first year at approximately 50 diabetes were hospitalized at least once for any cause within hospitalizations per 100 person-years due to any cause, and the first year vs. 42.1% of patients without diabetes 9 hospitalizations per 100 person-years due to CVD events (p<0.0001). By the end of 5 years, 88.3% of patients with for people without diabetes. Rates among patients with diadiabetes and 76.7% of patients without diabetes had been betes stabilized around 84 hospitalizations per 100 personhospitalized at least once (p<0.0001). These differences years and 17 per 100 person-years for any cause and CVD became less prominent over time, but at the end of the 10th events, respectively. All-cause hospitalizations occurred 60% year the cumulative hospitalization rate among patients with more frequently in the group with diabetes, while the CV diabetes was still higher than in patients without diabetes hospitalization rate was approximately double. (96.4 vs. 90.5%, p<0.0001). Patients with diabetes were Hospitalizations by cause and diabetes status over time are almost twice as likely as those without diabetes to be hospiFigure 2. Time to first hospitalization for talized at least once in the first year for CV causes (18.6 vs. any cause or for CV events by 10.9%, p<0.0001) (Figure 2).The CV-related hospitalization diabetes status rate remained higher in the diabetes group than in the nondi100 abetes group over the long term: 42.7 vs. 25.6%, respectiveAny cause 90 ly, were hospitalized by year 5 (p<0.0001) and 60.7 vs. 80 40.3%, respectively, by year 10 (p<0.0001). 70 Among patients hospitalized at least once, half of those with diabetes were hospitalized within the first 6 months of follow60 CVD events up (median time: 0.6 years [Table 4]), while half of those 50 without diabetes survived past 1 year without a hospitalization. 40 Once a hospitalization occurred, the time from the first to 30 Diabetes second hospitalization was not affected by diabetes status. 20 No diabetes Similarly, time to first CV hospitalization was shorter among 10 patients with diabetes, but subsequent time to hospitalization 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 was comparable in patients with and without diabetes. Time (years) The overall rate of hospitalization (i.e. for all admissions, not just the first) remained noticeably and consistently higher CVD = cardiovascular disease
impact of diabetes in pad 145 Table 4. Time to first hospitalization, and time from first to second hospitalization for any cause and for CV event by diabetes status Mean±SD Minimum
25th percentile
Median
75th Maximum percentile
Hospitalization for any cause Time to first hospitalization, years No diabetes
2.1±2.7
0.003
0.2
1.0
2.9
15.6
Diabetes
1.5±2.1
0.003
0.1
0.6
1.9
15.1
No diabetes
1.5±2.1
0.003
0.2
0.6
2.0
14.9
Diabetes
1.1±1.7
0.000
0.1
0.5
1.5
13.1
No diabetes
3.5±3.4
0.003
0.6
2.3
5.5
15.9
Diabetes
2.8±3.0
0.003
0.5
1.8
4.3
13.9
No diabetes
1.8±2.4
0.003
0.2
0.7
2.5
14.8
Diabetes
1.5±1.9
0.003
0.2
0.7
2.1
12.1
Time from first to second hospitalization, years
Hospitalization for CV event Time to first hospitalization, years
Time from first to second hospitalization, years
CV = cardiovascular SD = standard deviation
DISCUSSION Administrative databases such as those obtained from Saskatchewan Health provide a convenient way to study a large number of patients over long periods of time in actual practice settings. Patients in this cohort were followed for up to 15 years in such a setting.To our knowledge, this is the first large-scale study to study the impact of diabetes on the prognosis (mortality, morbidity and hospitalization) of patients with PAD in an actual practice setting. Patients in this cohort who were diagnosed with PAD and concurrent diabetes had a significantly poorer prognosis than patients without diabetes. Diabetes was associated with a 37% increase in mortality, a 56% increase in the risk of MI and a 52% increase in the risk of ischemic stroke.Whether PAD is simply a marker of disease severity and advanced stage of disease or whether the 2 conditions interact to worsen the prognosis is unclear. Nonetheless, physicians must be aware of the increased risk implied by this comorbid condition.
The presence of diabetes in PAD patients also increased resource use. Following a diagnosis of PAD, patients who also had diabetes were hospitalized more frequently and earlier Figure 3. Hospitalizations over time for any cause and for CV events by diabetes status* 180
Rate (per 100 patient-years)
shown in Figure 4. CV events were a more common reason for hospitalization among patients with diabetes in every time period (p<0.005 for all time periods).The difference was primarily attributable to a higher proportion of other CV diagnoses rather than more frequent MI or ischemic strokes.
160
Diabetes
140
No diabetes
120 100
Any cause
80 60 40
CVD events
20 0
0
1
2
3
4
5
6 7 8 Time (years)
9
10
11
12
13
*Expressed as hospitalizations per 100 patient-years of follow-up p<0.001for comparisons between “diabetes” and “no diabetes” CVD = cardiovascular disease
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
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100 90 80 70 60 50 40 30 20
Year 1
Year 2
Year 3
Ischemic stroke
Year 4
MI
Year 5
Years 6-10
Other CVD
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
0
Diabetes
10 No diabetes
Proportion of all hospitalizations (%)
Figure 4. Proportion of all hospitalizations due to MI, ischemic stroke, other CV event or other cause over time by diabetes status*
≥11 years
Other
*p≤0.005 for all time periods CVD = cardiovascular disease MI = myocardial infarction
than those without diabetes: the rate of all-cause hospitalizations was 60% higher and the rate of CV hospitalizations was almost double. Differences in hospitalization rates between the groups were apparent immediately after the diagnosis of PAD and were maintained throughout the study period. Thus, interventions to prevent complications and other disease-related admissions to hospital would likely offset much or all of their treatment costs. There are some limitations to this study.The definition of the populations and identification of events relied on the accuracy of the ICD-9 codes submitted to Saskatchewan Health. Validation work has indicated a low error rate overall, and even lower for CV events (30). Given the comprehensive and universal nature of the healthcare system in Saskatchewan and the lack of healthcare alternatives, the vast majority of residents seek care within the system, providing a closed data source. Moreover, with the global hospital budgets in Canada there is no reimbursement incentive to alter coding.Another limitation is that patients were required to have a recorded diagnosis of PAD, potentially resulting in a cohort with more advanced disease than might be obtained based on reporting of the ankle-brachial index, for example, which was not available. Similarly, only patients with a recorded diagnosis of diabetes were included.The observed prevalence of diabetes in patients with PAD (23.9%) in this analysis is lower than that reported in the literature (33 to 45%) (12,33). Patients in this study were selected on the first documented diagnosis of PAD within the index period; thus, it is expected that one-
third of patients would also have a diagnosis of diabetes (12). One potential reason for the difference is that this study relied on reporting from physicians to identify prevalent patients; if the criteria were expanded to include documentation of a prescription for an antihyperglycemic agent, for example, the number of patients with comorbid diabetes would likely increase. Finally, clinical data such as laboratory and other test results, smoking, family history and blood pressure, are not available in the Saskatchewan Health databases. Thus, these potentially relevant factors could not be considered in the selection criteria or analyses. Knowledge of these factors could have provided more detail, but would not likely have altered the overall findings. To our knowledge, this is the only comprehensive study that has examined the impact of comorbid diabetes on resource utilization, morbidity and mortality in patients diagnosed with PAD for over a decade in an actual practice setting.The results show that patients with PAD and concurrent diabetes are at substantially increased risk, even when other risk factors are taken into account.These data are intended to complement the knowledge base, which increasingly indicates that PAD is an important component of the spectrum of atherothrombotic disease (9-12,26,27). The results of this study indicate that diabetes and concurrent PAD are associated with an increased risk of morbidity and mortality. ACKNOWLEDGEMENTS This study is based on de-identified data provided by the Saskatchewan Department of Health. The interpretation and conclusions contained herein do not necessarily represent those of the Government of Saskatchewan or the Saskatchewan Department of Health. AUTHOR DISCLOSURES This work was supported in part by a grant from SanofiSynthelabo and Bristol-Myers Squibb to Caro Research.The grantors collaborated in helping set the specifications for the analyses, but had no role in methodological decisions or interpretation of results. Grantors were permitted to review and comment on this manuscript, but were explicitly forbidden from exerting any editorial control. AUTHOR CONTRIBUTIONS KMW designed the study, and participated in the data analyses and writing of the paper. KJI led the analyses and participated in writing the paper. IP conducted the analyses and helped write the paper. JJC designed the study, and participated in the data analyses and writing of the paper. REFERENCES 1. Elhadd TA, Robb R, Jung RT, et al. Pilot study of prevalence of asymptomatic peripheral arterial occlusive disease in patients with diabetes attending a hospital clinic. Practical Diabetes Int. 1999;16:163-166.
impact of diabetes in pad 147 2. Langer RD, Ho E, Denenberg JO, et al. Relationships between symptoms and venous disease: the San Diego population study. Arch Intern Med. 2005;165:1420-1444. 3. McDermott MM, Liu K, Greenland P, et al. Functional decline in peripheral arterial disease: associations with the ankle brachial index and leg symptoms. JAMA. 2004;292:453-461. 4. Froehlich JB, Mukherjee D, Avezum A, et al. Association of peripheral artery disease with treatment and outcomes in acute coronary syndromes. The Global Registry of Acute Coronary Events (GRACE). Am Heart J. 2006;151:1123-1238. 5. Nicoloff AD, Taylor LM, Sexton GJ, et al. Relationship between site of initial symptoms and subsequent progression of disease in a prospective study of atherosclerosis progression in patients receiving long-term treatment for symptomatic peripheral arterial disease. JVasc Surg. 2002;35:38-47. 6. Criqui MH, Langer RD, Fronek A, et al. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med. 1992;326:381-386. 7. Feringa HH, Bax JJ, van Waning VH, et al.The long-term prognostic value of the resting and post exercise ankle-brachial index. Arch Intern Med. 2006;166:529-535. 8. O’Hare AM, Katz R, Shlipak MG, et al. Mortality and cardiovascular risk across the ankle-arm index spectrum: results from the Cardiovascular Health Study. Circulation. 2006; 113:388-393. 9. Hirsch AT, Haskal ZJ, Hertzer NR, et al. ACC/AHA 2005 Practice guidelines for the management of patients with peripheral arterial disease (lower extremity, renal, mesenteric, and abdominal aortic). Circulation. 2006;113:e463-e654. 10. Pasternak RC, Criqui MH, Benjamin EJ, et al. Atherosclerotic vascular disease conference. Writing group I: Epidemiology. Circulation. 2004;109:2605-2612. 11. Selvin E, Erlinger TP. Prevalence and risk factors for peripheral arterial disease in the United States. Results from the National Health and Nutrition Examination Survey, 19992000. Circulation. 2004;110:738-743. 12. Hirsch AT, Criqui MH, Treat-Jacobson D, et al. Peripheral arterial disease detection, awareness and treatment in primary care. JAMA. 2001;286:1317-1324. 13. Criqui MH. Systematic atherosclerosis risk and the mandate for intervention in atherosclerotic peripheral arterial disease. Am J Cardiol. 2001;88(suppl 2):43J-47J. 14. Weitz JI, Byrne J, Clagett P, et al. Diagnosis and treatment of chronic arterial insufficiency of the lower extremities: A critical review. Circulation. 1996;94:3026-3049. 15. Price PF, Mowbray PI, Lee AJ, et al. Relationship between smoking and cardiovascular risk factors in the development of peripheral arterial disease and coronary artery disease. Eur Heart J. 1999;20:344-353. 16. McDermott MM, Greenland P, Liu K, et al. Leg symptoms in peripheral arterial disease: Associated clinical characteristics and functional impairment. JAMA. 2001;286:1599-1606. 17. McDermott MM, Hanh EA, Greenland P, et al. Atherosclerotic risk factor reduction in peripheral arterial
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31.
32. 33.
disease: Results of a national physician survey. J Gen Intern Med. 2002;17:895-904. Carnethon MR, Lynch EB, Dyer AR, et al. Comparison of risk factors of cardiovascular disease mortality in black and white adults. Arch Intern Med. 2006;166:1196-1202. Hirakawa Y, Masuda Y, Kuzuya M, et al. Influence of diabetes mellitus on in-hospital mortality in patients with acute myocardial infarction in Japan: A report from TAMIS-II. Diabetes Res Clin Pract. 2006;47:1-192. Liu X, Xu G, Wu W,et al. Subtypes and one-year survival of first-ever stroke in Chinese patients: The Nanjing Stroke Registry. Cerebrovasc Dis. 2006;22:130-136. Novo S. Classification, epidemiology, risk factors, and natural history of peripheral arterial disease. Diabetes Obes Metab. 2002; 4(suppl 2):S1-S6. Meijer WT, Hoes AW, Rutgers D, et al. Peripheral arterial disease in the elderly: the Rotterdam Study. Arterioscler ThrombVasc Biol. 1998;18:185-192. Hooi JD, Kester AD, Stoffers HE, et al. Incidence of and risk factors for asymptomatic peripheral arterial occlusive disease: a longitudinal study. Am J Epidemiol. 2001;153:666-672. Kallio M, Forsblom C, Groop P-H, et al. Development of new peripheral arterial occlusive disease in patients with type 2 diabetes during a mean follow-up of 11 years. Diabetes Care.2003; 26:1241-1245. Newman AB. Peripheral arterial disease: Insights from population studies of older adults. J Am Geriatr Soc. 2000;48:11571162. Migliaccio-Walle K, Caro JJ, Ishak K, et al. Costs and medical care consequences associated with the diagnosis of peripheral arterial disease. Pharmacoeconomics. 2005;23:733-742. Caro JJ, Migliaccio-Walle K, Ishak K, et al.The morbidity and mortality following a diagnosis of peripheral arterial disease: Long-term follow-up of a large database. BMC Cardiovasc Disord. 2005;5:14. Leibson CL, Ransom JE, Olson W, et al. Peripheral arterial disease, diabetes and mortality. Diabetes Care. 2004;27:28432849. Dolan NC, Liu K, Criqui MH, et al. Peripheral artery disease, diabetes, and reduced lower extremity functioning. Diabetes Care. 2002;25:113-120. Malcolm E, Downey W, Strand LM, et al. Saskatchewan Health’s linkable data bases and pharmacoepidemiology. Post Marketing Surveillance. 1993;6:175-264. Stergachis A, Sheingold S, Luce BR, et al. Medical care and cost outcomes after pentoxifylline treatment for peripheral arterial disease. Arch Intern Med. 1992;152:1220-1224. Lee ET, Wang JW. Statistical Methods for Survival Data Analysis. 3rd ed. Hoboken, NJ:Wiley-Interscience; 2003. Bhatt DL, Steg PG, Ohman EM, et al. International prevalence, recognition, and treatment of cardiovascular risk factors in outpatients with atherothrombosis. JAMA. 2006;295:180-189.
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The Prognostic Significance of Diabetes in Patients Diagnosed With Peripheral Arterial Disease Kristen Migliaccio-Walle1 BS, Khajak J. Ishak2 PhD, Irina Proskorovsky2 BSc, J. Jaime Caro1,3 MCDM FRCPC FACP Caro Research Institute, Concord, Massachusetts, United States Caro Research Institute, Montreal, Quebec, Canada 3 Division of General Internal Medicine and Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Quebec, Canada 1 2
A B S T R A C T OBJECTIVE
To evaluate the impact of diabetes on outcomes in patients with peripheral arterial disease (PAD). METHODS
Outcomes in 16 440 PAD patients from Saskatchewan, Canada (1985 to1995) were compared by diabetes status. Patient history and characteristics were available back to January 1980; follow-up to December 2000. Proportional hazards analyses measured the effect of diabetes on mortality and incidence of myocardial infarction (MI) and stroke in patients with PAD. Times to hospitalization were also calculated. R E S U LT S
One-quarter (23.9%) of patients had diabetes. Mortality was 37% higher among these patients and hazards of MI and ischemic stroke were also substantially higher (hazard ratios >1.50). Patients with diabetes were hospitalized more frequently and earlier regardless of cause. Hospitalization rates were 50 to 100% higher among patients with diabetes. CONCLUSIONS
Diabetes in patients with PAD is associated with substantially higher rates of morbidity and mortality.
R É S U M É OBJECTIF
Évaluer les répercussions du diabète sur le devenir des patients atteints d’artériopathie périphérique (AP). MÉTHODES
Le devenir de 16 440 patients atteints d’AP de la Saskatchewan, Canada (1985 à 1995) a été comparé selon que les patients étaient diabétiques ou non. Les dossiers des patients contenaient leurs antécédents et leurs caractéristiques depuis janvier 1980 et les données du suivi jusqu’à décembre 2000. Des analyses des hasards proportionnels ont mesuré l’effet du diabète sur la mortalité et l’incidence de l’infarctus du myocarde (IM) et de l’accident vasculaire cérébral chez les patients atteints d’AP. On a aussi calculé le délai de survenue de l’hospitalisation. R É S U LTAT S
Le quart (23,9 %) des patients étaient diabétiques. Le taux de mortalité a été de 37 % supérieur chez ces patients et les risques d’IM et d’accident ischémique cérébral étaient aussi considérablement supérieurs (rapports des risques > 1,50). Les patients diabétiques ont été hospitalisés plus souvent et plus tôt pour diverses causes. Les taux d’hospitalisation ont été de 50 à 100 % plus élevés chez les patients diabétiques. CONCLUSION
Le diabète chez les patients atteints d’AP est associé à des taux considérablement supérieurs de morbidité et de mortalité. Address for correspondence: Kristen Migliaccio-Walle Caro Research Institute 336 Baker Avenue Concord, Massachusetts United States 01742 Telephone: (978) 371-1660 Fax: (978) 371-2445 E-mail: [email protected]
M OT S C L É S
risque de manifestation, hospitalisation, mortalité, artériopathie périphérique, pronostic
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
impact of diabetes in pad 141 K E Y WO R D S
Event risk, hospitalization, mortality, peripheral arterial disease, prognosis INTRODUCTION Atherosclerotic disease of the peripheral arteries produces pain, discomfort and exercise limitation (1-3). It can lead to increasingly serious complications requiring surgical intervention (4,5) and can even result in death (6-8), yet it has not received the same level of attention as myocardial infarction (MI) or stroke. Estimates of the prevalence of peripheral arterial disease (PAD) range from <5% in younger age groups to >20% in the elderly (9-14). Advancing age, male gender, a history of diabetes and smoking are associated with a higher risk of PAD (15,16). Patients experience the frequently painful symptoms associated with this diagnosis, yet management is often less aggressive than for acute atherothrombotic diseases such as MI and stroke (17). Diabetes is known to impact negatively on the prognosis of patients with MI (18,19) and stroke (20), and is a major risk factor for the development of macrovascular disease, including disease in the limb arteries (21-24). Despite the increasing awareness that patients with diabetes are at a substantially increased risk of morbidity, mortality and hospitalization (25-29), the influence of diabetes on the course of patients with PAD is poorly understood. It is not known empirically whether diabetes raises the risk of complications in patients with PAD or the extent to which it increases mortality. These are important aspects for determining prognosis, and helping patients and their families make decisions regarding treatment. This paper examines whether diabetes substantially affects the prognosis of patients with PAD. METHODS Study population Saskatchewan Health, the government department that oversees healthcare in this western Canadian province, maintains 10 databases that track all formulary outpatient prescriptions, physician services, hospitalizations and vital statistics for approximately 1 million residents covered by provincial health insurance.These databases can be linked electronically using unique patient identifiers (30). These healthcare databases were used to identify patients with a diagnosis of PAD and to obtain information on the course of their disease over subsequent years. Residents of the province ≥21 years of age diagnosed with PAD between January 1, 1985 and December 31, 1995 (index period) were eligible. First Nations peoples are not included in the Saskatchewan Health databases because this potentially high-risk group’s health costs are covered by the federal government. No exclusion criteria were specified. Patients with PAD were identified using the International
Classification of Diseases (ICD-9) codes 440, 440.2 or 443.9. If the broad 3-digit code 443 coincided with documentation of prescription for pentoxifylline, it was also included based on the assumption that all patients who received this prescription were diagnosed with PAD (31). The date of first diagnosis of PAD (index diagnosis) was taken as the date of entry into the study (index date). Either hospital admission or physician visit was accepted (depending on where the diagnosis was initially recorded). Medical history was available back to January 1, 1980, and follow-up was complete through March 2000, or until a patient could no longer be followed due to emigration or death. Patients were classified into 2 groups: those with a history of diabetes at the time of the index diagnosis; and those without diabetes, if they had no history of diabetes prior to diagnosis of PAD.Amongst patients without diabetes, followup was censored (i.e., discontinued) upon diagnosis of diabetes in patients who had a recorded diagnosis of diabetes after the index diagnosis. Medical history prior to the date of the index diagnosis was also examined to identify other conditions of interest: atrial fibrillation, angina, heart failure, treatment of hypercholesterolemia, hypertension, ischemic stroke, MI and transient ischemic attack (TIA). Data on smoking history or laboratory values were not available in these databases. Mortality Survival in each group was established using the KaplanMeier method, and was calculated from the date of PAD diagnosis to either the date of death, the date patient was censored or the last follow-up date available.The overall survival curves were compared using log-rank and Wilcoxon tests. Differences in overall mortality were also quantified by hazard ratios (HR) and the corresponding 95% confidence intervals (CI). Proportional hazards models were used to evaluate the impact of other potential determinants. The assumption of proportionality of the effect of diabetes was verified by including interactions between indicators of diabetes and time. Morbidity Morbidity was examined with respect to hospitalizations for major cardiovascular (CV) events (ischemic stroke and MI) identified using ICD-9 codes (433.x to 434.x and 436.x for ischemic stroke; 410.x for MI). Event rates were defined as the total number of hospitalizations divided by the patient time accumulated (i.e. hospitalizations per patient-year of follow-up) in each of 8 time periods: 4 time periods in year 1 CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
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142
(30 days, 60 days, months 3 to 6, months 7 to 12) and years 2 to 5. For patients who suffered >1 type of event in a period, each occurrence contributed independently to the appropriate type (i.e., stroke or MI) with the corresponding follow-up time to each event calculated. Hospitalization CV-related and all-cause hospitalizations were examined in patients with and without diabetes. A hospitalization was considered CV-related if the primary diagnosis was ischemic stroke, TIA, MI, stable or unstable angina, heart failure or a complication of PAD. Hospitalization occurrence was estimated for each of the time periods defined above as the proportion of patients hospitalized and as the rate of hospitalization (hospitalizations per patient-year of followup) for each type of hospitalization over time.The time until first hospitalization after index diagnosis of PAD was estimated for each hospitalization type using standard failuretime analyses (32), and the impact of diabetes was examined using Kaplan-Meier methods.To determine the effect of diabetes on total hospitalization rates, admissions occurring in 9 discrete time periods were evaluated: first 3 months, months
4 to 6, months 7 to 12, years 2 through 5 and every 5 years thereafter, through year 15. RESULTS A cohort of 16 440 patients with a first diagnosis of PAD was identified during the index period (1985 to 1995). Three patients were excluded from the analysis for administrative reasons (e.g. exit date recorded prior to index date). Of the remaining 16 437 patients, one-quarter (23.9%) had a documented history of diabetes upon entry into the cohort. Mean follow-up was slightly shorter among patients with diabetes (5.9 vs. 6.8 years in patients without diabetes). Patients with and without diabetes were comparable in terms of age and sex, but other risk factors were significantly more prevalent among patients with diabetes (Table 1). Mortality A significantly greater proportion of patients with diabetes died during the study period (69.0 vs. 50.2% p<0.0001) (Figure 1). The median survival of patients without diabetes was 9.6 years vs. 5.6 years in patients with diabetes. Controlling for other risk factors of death in a proportional
Table 1. Patient characteristics and medical history at time of diagnosis of PAD
Mean follow-up, years (±SD) Mean age, years (±SD) Male, n (%) Qualifying diagnosis of PAD in hospital, n (%)
Diabetes n=3172
No diabetes n=13 265
p value
5.9 (4.2)
6.8 (4.5)
<0.0001
68.6 (8.2)
66.9 (9.4)
<0.0001
1866 (58.8)
7162 (54.0)
<0.0001
490 (15.5)
1168 (8.8)
<0.0001
Medical history Atrial fibrillation, n (%)
<0.0001 215 (6.8)
647 (4.9)
<0.0001
Angina, n (%)
1233 (38.9)
4213 (31.8)
<0.0001
Heart failure, n (%)
1055 (33.3)
3121 (23.5)
<0.0001
275 (8.7)
853 (6.4)
<0.0001
2147 (67.7)
7405 (55.8)
<0.0001
Ischemic stroke, n (%)
508 (16.0)
1601 (12.1)
<0.0001
MI, n (%)
657 (20.7)
2211 (16.7)
<0.0001
TIA, n (%)
457 (14.4)
1759 (13.3)
0.089
Hypercholesterolemia, n (%) Hypertension, n (%)
MI = myocardial infarction PAD = peripheral arterial disease SD = standard deviation TIA = transient ishemic stroke
impact of diabetes in pad 143
Morbidity MI occurred in 9.8% of patients with diabetes compared to 6.4% (p<0.0001) of those without diabetes; ischemic stroke occurred in 10.5% and 6.9% (p<0.0001), respectively. Similarly, a history of diabetes was associated with higher rates of MI and ischemic strokes throughout follow-up (Table 2). Ischemic strokes occurred more frequently than MI in the first 3 months of the study, regardless of diabetes status (Table 3). However, the 2 events occurred at fairly similar rates within each group over time, with the exception of the 3- to 6-month time period in which stroke occurred more frequently than MI among patients without diabetes. In the 6- to 12-month period, strokes occurred more frequently than MI among patients with diabetes. Diabetes was associated with significantly increased risk for MI (1.56 [1.37–1.78] and ischemic stroke 1.52 [1.33–1.72]. For both MI and
ischemic stroke, the estimate of the effect of diabetes did not vary substantially over time. Hospitalizations The proportion of patients hospitalized at least once for any cause was 89.3% among those with diabetes compared with 82.3% of those without diabetes (p<0.0001). Hospitalizations for CV events occurred in 46.8% of patients with diabetes vs. Figure 1. Survival following diagnosis of PAD by diabetes status 100 90
Diabetes
80 Proportion alive (%)
hazards model (Table 2), there was a 37% increase (95% CI, 31–44%) in the hazard of death for patients with diabetes. There were no serious departures from the assumption of proportional hazards in these analyses, suggesting that the increase in risk among patients with diabetes was relatively stable over time. In addition to diabetes, significant predictors of death included age (continuous), male gender, atrial fibrillation, heart failure, hypercholesterolemia and prior ischemic stroke (Table 2).
No diabetes
70 60 50 40 30 20 10 0
0
1
2
3
4
5
6
7 8 9 10 11 12 13 14 15 Time (years)
PAD = peripheral arterial disease
Table 2. Hazard ratios of death, MI and ischemic stroke by risk factors* Death
MI
Ischemic stroke
Age at index diagnosis (per year)
1.08 (1.08, 1.09)
1.03 (1.02, 1.03)
1.04 (1.04, 1.05)
Male gender
1.26 (1.21, 1.32)
1.62 (1.43, 1.84)
1.23 (1.09, 1.38)
History of diabetes
1.37 (1.31, 1.44)
1.56 (1.37, 1.78)
1.52 (1.33, 1.72)
History of atrial fibrillation
1.17 (1.08, 1.27)
—
1.62 (1.31, 1.99)
—
1.50 (1.32, 1.71)
—
History of heart failure
1.90 (1.81, 1.99)
—
1.25 (1.10, 1.43)
Hypercholesterolemia treatment
0.77 (0.70, 0.85)
—
—
—
1.15 (1.01, 1.30)
1.43 (1.27, 1.62)
1.56 (1.48, 1.65)
1.30 (1.10, 1.54)
2.13 (1.84, 2.47)
History of MI
—
1.64 (1.42, 1.89)
—
History of TIA
—
—
1.37 (1.18, 1.59)
History of angina
History of hypertension History of ischemic stroke
These equations represent the final equations, which excluded factors that were not significant, as these can introduce noise and reduce the precision of the estimates. Blank cells indicate that these variables were not included in the final equations *Hazard ratios (95% CI) obtained from proportional hazards analyses MI = myocardial infarction TIA = transient ischemic attack
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
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144 Table 3. Rate of hospitalizations due to MI and ischemic stroke by diabetes status and time since index diagnosis* Ischemic stroke
MI Time
No diabetes
Diabetes
No diabetes
Diabetes
Months 0–3
0.022
0.033
0.029
0.046
Months 3–6
0.014
0.024
0.022
0.023
Months 6–12
0.018
0.029
0.018
0.035
Years 1–2
0.014
0.029
0.015
0.027
Years 2–3
0.011
0.024
0.014
0.022
Years 3–4
0.011
0.017
0.013
0.028
Years 4–5
0.013
0.021
0.012
0.017
Years 5–10
0.013
0.025
0.013
0.025
Years 10+
0.015
0.022
0.013
0.027
*Expressed as number of hospitalizations per patient-year calculated in each time period MI = myocardial infarction
Proportion hospitalized (%)
32.0% of those without diabetes (p<0.0001). The time to among patients with diabetes (p<0.001) (Figure 3).The rates first hospitalization for any cause and CV events is shown in were highest for both groups during the first few months. Figure 2 and Table 4. More than half (56.8%) of patients with Rates stabilized after the first year at approximately 50 diabetes were hospitalized at least once for any cause within hospitalizations per 100 person-years due to any cause, and the first year vs. 42.1% of patients without diabetes 9 hospitalizations per 100 person-years due to CVD events (p<0.0001). By the end of 5 years, 88.3% of patients with for people without diabetes. Rates among patients with diadiabetes and 76.7% of patients without diabetes had been betes stabilized around 84 hospitalizations per 100 personhospitalized at least once (p<0.0001). These differences years and 17 per 100 person-years for any cause and CVD became less prominent over time, but at the end of the 10th events, respectively. All-cause hospitalizations occurred 60% year the cumulative hospitalization rate among patients with more frequently in the group with diabetes, while the CV diabetes was still higher than in patients without diabetes hospitalization rate was approximately double. (96.4 vs. 90.5%, p<0.0001). Patients with diabetes were Hospitalizations by cause and diabetes status over time are almost twice as likely as those without diabetes to be hospiFigure 2. Time to first hospitalization for talized at least once in the first year for CV causes (18.6 vs. any cause or for CV events by 10.9%, p<0.0001) (Figure 2).The CV-related hospitalization diabetes status rate remained higher in the diabetes group than in the nondi100 abetes group over the long term: 42.7 vs. 25.6%, respectiveAny cause 90 ly, were hospitalized by year 5 (p<0.0001) and 60.7 vs. 80 40.3%, respectively, by year 10 (p<0.0001). 70 Among patients hospitalized at least once, half of those with diabetes were hospitalized within the first 6 months of follow60 CVD events up (median time: 0.6 years [Table 4]), while half of those 50 without diabetes survived past 1 year without a hospitalization. 40 Once a hospitalization occurred, the time from the first to 30 Diabetes second hospitalization was not affected by diabetes status. 20 No diabetes Similarly, time to first CV hospitalization was shorter among 10 patients with diabetes, but subsequent time to hospitalization 0 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 was comparable in patients with and without diabetes. Time (years) The overall rate of hospitalization (i.e. for all admissions, not just the first) remained noticeably and consistently higher CVD = cardiovascular disease
impact of diabetes in pad 145 Table 4. Time to first hospitalization, and time from first to second hospitalization for any cause and for CV event by diabetes status Mean±SD Minimum
25th percentile
Median
75th Maximum percentile
Hospitalization for any cause Time to first hospitalization, years No diabetes
2.1±2.7
0.003
0.2
1.0
2.9
15.6
Diabetes
1.5±2.1
0.003
0.1
0.6
1.9
15.1
No diabetes
1.5±2.1
0.003
0.2
0.6
2.0
14.9
Diabetes
1.1±1.7
0.000
0.1
0.5
1.5
13.1
No diabetes
3.5±3.4
0.003
0.6
2.3
5.5
15.9
Diabetes
2.8±3.0
0.003
0.5
1.8
4.3
13.9
No diabetes
1.8±2.4
0.003
0.2
0.7
2.5
14.8
Diabetes
1.5±1.9
0.003
0.2
0.7
2.1
12.1
Time from first to second hospitalization, years
Hospitalization for CV event Time to first hospitalization, years
Time from first to second hospitalization, years
CV = cardiovascular SD = standard deviation
DISCUSSION Administrative databases such as those obtained from Saskatchewan Health provide a convenient way to study a large number of patients over long periods of time in actual practice settings. Patients in this cohort were followed for up to 15 years in such a setting.To our knowledge, this is the first large-scale study to study the impact of diabetes on the prognosis (mortality, morbidity and hospitalization) of patients with PAD in an actual practice setting. Patients in this cohort who were diagnosed with PAD and concurrent diabetes had a significantly poorer prognosis than patients without diabetes. Diabetes was associated with a 37% increase in mortality, a 56% increase in the risk of MI and a 52% increase in the risk of ischemic stroke.Whether PAD is simply a marker of disease severity and advanced stage of disease or whether the 2 conditions interact to worsen the prognosis is unclear. Nonetheless, physicians must be aware of the increased risk implied by this comorbid condition.
The presence of diabetes in PAD patients also increased resource use. Following a diagnosis of PAD, patients who also had diabetes were hospitalized more frequently and earlier Figure 3. Hospitalizations over time for any cause and for CV events by diabetes status* 180
Rate (per 100 patient-years)
shown in Figure 4. CV events were a more common reason for hospitalization among patients with diabetes in every time period (p<0.005 for all time periods).The difference was primarily attributable to a higher proportion of other CV diagnoses rather than more frequent MI or ischemic strokes.
160
Diabetes
140
No diabetes
120 100
Any cause
80 60 40
CVD events
20 0
0
1
2
3
4
5
6 7 8 Time (years)
9
10
11
12
13
*Expressed as hospitalizations per 100 patient-years of follow-up p<0.001for comparisons between “diabetes” and “no diabetes” CVD = cardiovascular disease
CANADIAN JOURNAL OF DIABETES. 2007;31(2):140-147.
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146
100 90 80 70 60 50 40 30 20
Year 1
Year 2
Year 3
Ischemic stroke
Year 4
MI
Year 5
Years 6-10
Other CVD
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
Diabetes
No diabetes
0
Diabetes
10 No diabetes
Proportion of all hospitalizations (%)
Figure 4. Proportion of all hospitalizations due to MI, ischemic stroke, other CV event or other cause over time by diabetes status*
≥11 years
Other
*p≤0.005 for all time periods CVD = cardiovascular disease MI = myocardial infarction
than those without diabetes: the rate of all-cause hospitalizations was 60% higher and the rate of CV hospitalizations was almost double. Differences in hospitalization rates between the groups were apparent immediately after the diagnosis of PAD and were maintained throughout the study period. Thus, interventions to prevent complications and other disease-related admissions to hospital would likely offset much or all of their treatment costs. There are some limitations to this study.The definition of the populations and identification of events relied on the accuracy of the ICD-9 codes submitted to Saskatchewan Health. Validation work has indicated a low error rate overall, and even lower for CV events (30). Given the comprehensive and universal nature of the healthcare system in Saskatchewan and the lack of healthcare alternatives, the vast majority of residents seek care within the system, providing a closed data source. Moreover, with the global hospital budgets in Canada there is no reimbursement incentive to alter coding.Another limitation is that patients were required to have a recorded diagnosis of PAD, potentially resulting in a cohort with more advanced disease than might be obtained based on reporting of the ankle-brachial index, for example, which was not available. Similarly, only patients with a recorded diagnosis of diabetes were included.The observed prevalence of diabetes in patients with PAD (23.9%) in this analysis is lower than that reported in the literature (33 to 45%) (12,33). Patients in this study were selected on the first documented diagnosis of PAD within the index period; thus, it is expected that one-
third of patients would also have a diagnosis of diabetes (12). One potential reason for the difference is that this study relied on reporting from physicians to identify prevalent patients; if the criteria were expanded to include documentation of a prescription for an antihyperglycemic agent, for example, the number of patients with comorbid diabetes would likely increase. Finally, clinical data such as laboratory and other test results, smoking, family history and blood pressure, are not available in the Saskatchewan Health databases. Thus, these potentially relevant factors could not be considered in the selection criteria or analyses. Knowledge of these factors could have provided more detail, but would not likely have altered the overall findings. To our knowledge, this is the only comprehensive study that has examined the impact of comorbid diabetes on resource utilization, morbidity and mortality in patients diagnosed with PAD for over a decade in an actual practice setting.The results show that patients with PAD and concurrent diabetes are at substantially increased risk, even when other risk factors are taken into account.These data are intended to complement the knowledge base, which increasingly indicates that PAD is an important component of the spectrum of atherothrombotic disease (9-12,26,27). The results of this study indicate that diabetes and concurrent PAD are associated with an increased risk of morbidity and mortality. ACKNOWLEDGEMENTS This study is based on de-identified data provided by the Saskatchewan Department of Health. The interpretation and conclusions contained herein do not necessarily represent those of the Government of Saskatchewan or the Saskatchewan Department of Health. AUTHOR DISCLOSURES This work was supported in part by a grant from SanofiSynthelabo and Bristol-Myers Squibb to Caro Research.The grantors collaborated in helping set the specifications for the analyses, but had no role in methodological decisions or interpretation of results. Grantors were permitted to review and comment on this manuscript, but were explicitly forbidden from exerting any editorial control. AUTHOR CONTRIBUTIONS KMW designed the study, and participated in the data analyses and writing of the paper. KJI led the analyses and participated in writing the paper. IP conducted the analyses and helped write the paper. JJC designed the study, and participated in the data analyses and writing of the paper. REFERENCES 1. Elhadd TA, Robb R, Jung RT, et al. Pilot study of prevalence of asymptomatic peripheral arterial occlusive disease in patients with diabetes attending a hospital clinic. Practical Diabetes Int. 1999;16:163-166.
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