Abstract
Background:
The Evaluation of Final Feasible Effect of Ultra Control Training and Sensitization (EFFECTUS) study is aimed at implementing global cardiovascular (CV) risk management in Italy.
Hypothesis:
To evaluate the impact of diabetes mellitus (DM) on attitudes and preferences for clinical management of global CV risk among physicians treating diabetic or nondiabetic patients.
Methods:
Involved physicians were asked to submit data into a study‐designed case‐report form, covering the first 10 adult outpatients consecutively seen in May 2006. All available clinical data were centrally analyzed for global CV risk assessment and CV risk profile characterization. Patients were stratified according to the presence or absence of DM.
Results:
Overall, 1078 physicians (27% female, ages 50 ± 7 y) collected data of 9904 outpatients (46.5% female, ages 67 ± 9 y), among whom 3681 (37%) had a diagnosis of DM at baseline. Diabetic patients were older and had higher prevalence of obesity, hypertension, dyslipidemia, and associated CV diseases than nondiabetic individuals (P<0.001). They had higher systolic blood pressure, total cholesterol, triglycerides, and creatinine levels, but lower high‐density lipoprotein cholesterol levels than nondiabetic patients (P<0.001). Higher numbers of blood pressure and lipid‐lowering drugs and antiplatelet agents were used in diabetic than in nondiabetic patients (P<0.001).
Conclusions:
The EFFECTUS study confirmed higher CV risk and more CV drug prescriptions in diabetic than in nondiabetic patients. Presence of DM at baseline significantly improved clinical data collection. Such an approach, however, was not paralleled by a better control of global CV risk profile, which was significantly worse in the former than in the latter group. © 2011 Wiley Periodicals, Inc.
This work has been supported by an unconditioned educational grant by Merck Sharp & Dohme, Italy, for data collection and analysis. The authors have no other funding, financial relationships, or conflicts of interest to disclose.
Introduction
Diabetes mellitus (DM) affects approximately 100 million persons worldwide. In view of the increasing prevalence of unfavorable lifestyle habits (eg, smoking, physical inactivity, and high‐caloric diet) and associated clinical conditions (obesity, atherogenic dyslipidemia, and hypertension), it is likely that its incidence will further and dramatically rise in both Western and developing countries in the next decades.
Nowadays, both general practitioners and specialized physicians are encountering many of these patients in their routine clinical practice, thus having the opportunity to substantially reduce the global burden of disease related to DM and glucose abnormalities.1, 2 Diabetic patients have, in fact, higher susceptibility than nondiabetic individuals to develop major cardiovascular (CV) events, such as myocardial infarction, stroke, and CV death, and non‐CV mortality.3, 4 Because CV diseases represent the main causes of death and disability in people with DM, physicians must recognize the key role of this clinical condition to promptly stratify and timely treat these patients. Evidence has, in fact, demonstrated that a therapeutic approach based on global CV risk management may effectively reduce the burden of CV disease in diabetic patients.5, 6
The Evaluation of Final Feasible Effect of Ultra Control Training and Sensitization (EFFECTUS) program is a multicenter, observational study designed to raise awareness about global CV risk management among physicians operating in daily clinical practice in Italy.7 A large and representative population of physicians distributed throughout Italy provides information on patients at risk followed in different clinical settings and areas. In this population, in fact, we recently demonstrated high prevalence of CV risk factors, including DM, irrespective of the clinical settings in which patients were followed (cardiologists, diabetologists, and general practitioners),7 as well as a significantly higher prevalence of major CV risk factors, mostly DM, in southern regions than in northern and central areas of Italy.8 In a further analysis, we were also able to demonstrate that a more intensive recording of clinical data was paralleled by a better adherence to guidelines, suggesting that accuracy in recording translates into better management of patients at risk in the daily clinical practice.9
In the present analysis, we aimed to examine the influence of DM on the clinical management of Italian outpatients at CV risk, based on clinical data already available from their own physicians. Therefore, the primary aim of this prespecified analysis is to evaluate the potential impact of DM on CV risk management among physicians involved in the EFFECTUS program, operating in their routine clinical practice.
Methods
Methodology of the Study
The methodology of the study has been previously described.7 Briefly, EFFECTUS is an educational project, structured in 2 distinct phases, with the first phase designed to evaluate prevalence of major CV risk factors and the second phase to establish the potential influence of an educational intervention on global CV risk management among physicians operating in the clinical practice in Italy. The study conformed to the Declaration of Helsinki and its subsequent modifications, and was authorized by the reference Ethical Committee. The confidentiality of the data was carefully and strictly protected. Written consent to participate to the educational program was obtained by all involved physicians, and the confidentiality of patient demographic and clinical data was carefully preserved.
Physician Recruitment
Participants involved in the program were randomly selected to have a representative sample of physicians from a community of medical doctors who shared some specific features.7 Each of the 20–24 regional referral centers invited 60 physicians per region (35 general practitioners, 10 diabetologists, and 15 cardiologists) to participate in this survey, for a total of 1400 individual physicians. Following their acceptance, participating physicians were asked to report specific, relevant clinical data extracted from their clinical records from the first 10 consecutive adult Caucasian outpatients age >50 years, whatever the reason they referred to their own attending physicians. The entire data collection was completed by participants on‐site and then delivered to the data collection center by online access to remote database. At each study site, collection data was conducted throughout 1 week during May 2006. Physicians who completed the program did not receive any compensation for their participation.
Data Collection
Medical history and lifestyle habits were assessed by means of a standardized questionnaire. Information was obtained on current drug therapy for hypertension, dyslipidemia, DM, and other CV diseases, as well as any concomitant medication. Anthropometric parameters, clinic systolic and diastolic blood pressure (BP) levels, serum lipids, blood glucose, and glycated hemoglobin (HbA1c) levels were extracted from available clinical records and generally not exceeding 12 months. Information from electrocardiogram (ECG), echocardiogram, carotid or peripheral vascular ultrasonography, fundus oculi examination, microalbuminuria test, and exercise stress test were also recorded by physicians, when available. Thus, all clinical parameters were derived only from personal outpatient visits and not from previous medical records.
Data Analysis
Available data were reported into a study‐designed case‐report form and were centrally analyzed for global CV risk evaluation and CV risk profile characterization. Normal values of clinic and metabolic parameters were defined according to current international guidelines. In particular, systolic and diastolic BP control was defined as BP ≤140/90 mm Hg,10 total cholesterol ≤190 mg/dL,11 high‐density lipoprotein cholesterol (HDL‐C) ≥40 mg/dL in men and ≥50 mg/dL in women,12, 13 triglycerides ≤150 mg/dL,12, 13 and fasting glucose levels ≤126 mg/dL.14 When available, normal HbA1c levels were defined as ≤75%.14, 15, 16
Statistical Analysis
The data were entered into Microsoft Access for Windows (Microsoft, Redmond, WA). Continuous variables were expressed as mean ± SD and discrete variables as number and percentage. Patient data were analyzed using a mixed model with group as fixed effect and physicians fitted as random, so that possible differences in data across physicians could be considered. Data were entered into a database (Microsoft Access) and statistical analyses were performed with R (R Foundation for Statistical Computing, Vienna, Austria). Because of the large sample size, the comparisons were considered relevant for P values <0.001.
Results
The EFFECTUS program involved 1078 physicians and 9904 outpatients, among whom 3681 (37%) had a diagnosis of DM at baseline. General characteristics of physicians and patients involved in the EFFECTUS program are reported in Table 1. A vast proportion of physicians were male, middle‐aged, and general practitioners, uniformly distributed throughout the whole of Italy. Outpatients enrolled by this cohort of physicians were stratified into 2 groups, according to the purpose of the present analysis.
Table 1.
General Characteristics and Prevalence of Major Cardiovascular Risk Factors and Associated Clinical Conditions in the Overall Population and in Subgroups of Patients With and Without Diabetes Mellitus
| Overall Population (n = 9904) | Diabetic Patients (n = 3681) | Nondiabetic Patients (n = 6223) | P Value | |
|---|---|---|---|---|
| Physicians | <0.001 | |||
| General practitioners, n (%) | 7722 (78) | 2454 (67) | 5268 (85) | |
| Cardiologists, n (%) | 1303 (13) | 444 (12) | 859 (14) | |
| Diabetologists, n (%) | 879 (9) | 783 (21) | 96 (2) | |
| Italian macro‐areas | <0.001 | |||
| North, n (%) | 3219 (33) | 1152 (31) | 2067 (33) | |
| Central, n (%) | 3652 (37) | 1239 (34) | 2413 (39) | |
| South, n (%) | 3033 (31) | 1290 (35) | 1743 (28) | |
| Patient characteristics | ||||
| Patients, n (%) | 9904 (100) | 3681 (37) | 6223 (63) | <0.001 |
| Male, n (%) | 5300 (54) | 1971 (54) | 3329 (53) | 0.96 |
| Age (y) | 66.9 ± 9.2 | 67.4 ± 8.8 | 66.6 ± 9.4 | <0.001 |
| BMI (kg/m2) | 28 ± 5 | 29 ± 5 | 27 ± 4 | <0.001 |
| Waist circumference (cm) | 99 ± 16 | 102 ± 15 | 96 ± 15 | <0.001 |
| Obesity, n (%) | 2504 (25) | 1318 (36) | 1186 (19) | <0.001 |
| Physical activity, n (%) | 2922 (30) | 1084 (29) | 1838 (30) | 0.044 |
| Family history of CV disease, n (%) | 2884 (29) | 1235 (34) | 1649 (26) | <0.001 |
| Smoking, n (%) | 3324 (34) | 1233 (33) | 2091 (34) | 0.008 |
| Hypertension, n (%) | 7436 (75) | 2929 (80) | 4507 (72) | <0.001 |
| SBP (mm Hg) | 138 ± 15 | 140 ± 15 | 137 ± 15 | <0.001 |
| DBP (mm Hg) | 82 ± 8 | 82 ± 8 | 81 ± 8 | 0.051 |
| Dyslipidemia, n (%) | 5873 (59) | 2682 (73) | 3191 (51) | <0.001 |
| Total cholesterol (mg/dL) | 212 ± 40 | 207 ± 41 | 215 ± 39 | <0.001 |
| HDL‐C (mg/dL) | 52 ± 14 | 50 ± 13 | 54 ± 14 | <0.001 |
| LDL‐C (mg/dL) | 131 ± 37 | 126 ± 37 | 135 ± 36 | <0.001 |
| TG (mg/dL) | 155 ± 74 | 165 ± 86 | 148 ± 64 | <0.001 |
| Fasting glucose (mg/dL) | 121 ± 41 | 152 ± 46 | 98 ± 13 | <0.001 |
| Ischemic heart disease, n (%) | 2633 (27) | 1192 (32) | 1441 (23) | <0.001 |
| Previous MI | 1218 (12) | 521 (14) | 697 (11) | <0.001 |
| Angina | 767 (8) | 332 (9) | 435 (7) | 0.004 |
| Coronary revascu‐ larization | 882 (9) | 353 (10) | 529 (9) | 0.10 |
| Ischemic cerebral disease, n (%) | 1102 (11) | 529 (14) | 573 (9) | <0.001 |
| Stroke | 262 (3) | 130 (4) | 132 (2) | 0.009 |
| TIA | 444 (4) | 185 (5) | 259 (4) | 0.24 |
| Carotid artery disease | 420 (4) | 200 (5) | 220 (4) | 0.001 |
| PAD, n (%) | 1247 (13) | 712 (19) | 535 (9) | <0.001 |
| Serum Cr (mg/dL) | 1.05 ± 0.35 | 1.09 ± 0.41 | 1.01 ± 0.29 | <0.001 |
Abbreviations: BMI, body mass index; Cr, creatinine; CV, cardiovascular; DBP, diastolic blood pressure; HbA1c, glycated hemoglobin; HDL‐C, high‐density lipoprotein cholesterol; LDL‐C; low‐density lipoprotein cholesterol; MI, myocardial infarction; PAD, peripheral artery disease; SBP, systolic blood pressure; TG, triglycerides; TIA, transient ischemic attack. P<0.001 vs nondiabetic patients.
As shown in Table 1, diabetic patients were predominantly followed by general practitioners rather than by specialist cardiologists and diabetologists, although the specialists have a significantly higher proportion of diabetic patients than nondiabetic individuals in their routine practice, as expected. On average, diabetic outpatients were older and had a higher global CV risk profile than nondiabetic individuals. In fact, they were more obese (P<0.001), having higher body mass index (BMI) (P<0.001) and waist circumference (P<0.001). Also, they had a higher prevalence of family history of CV disease (P<0.001), hypertension (P<0.001), and dyslipidemia (P<0.001), as well as ischemic heart disease (previous MI, P<0.001), cerebrovascular disease, and both peripheral and carotid vascular disease (P<0.001, for both).
Arterial hypertension represented by far the most frequent concomitant CV risk factor both in diabetic and in nondiabetic patients, followed by dyslipidemia and obesity, all of which were significantly more prevalent in the former than in the latter group, as shown in Figure 1. Systolic BP levels were higher in diabetic outpatients than those recorded in nondiabetic individuals (P<0.001), whereas diastolic BP levels did not show any significant difference. It should also be noted that systolic BP levels were on average in the high‐normal range, which confers a high added CV risk in the presence of DM and irrespective of other concomitant CV risk factors or signs of organ damage, according to current BP stratification proposed by European guidelines.10 As expected, both fasting glucose and HbA1c levels were higher in the diabetic than in the nondiabetic group (P<0.001). In addition, HDL‐C levels were lower, whereas triglycerides were higher in diabetic outpatients as compared with nondiabetic individuals (P<0.001, for both), thus suggesting the presence of an impaired metabolic profile like that described for the metabolic syndrome.12, 13 On the contrary, total and low‐density lipoprotein cholesterol (LDL‐C) levels were higher in nondiabetic patients than in diabetic ones (P<0.001, for both). Finally, serum creatinine levels were higher in the diabetic than in the nondiabetic group (P<0.001). Of note, with the only exception of fasting glucose and HbA1c levels, all these parameters were in the normal or in the upper‐normal thresholds, according to current international guidelines.14, 15, 16
Figure 1.
Prevalence of major CV risk factors hypertension, dyslipidemia, obesity, and smoking in the overall population and in subgroups of patients with and without DM. P<0.001 vs nondiabetic patients. Abbreviations: CV, cardiovascular; DM, diabetes mellitus.
Figure 2 illustrates prevalence of patients showing normal values of major CV risk factors at baseline, including BP, total cholesterol and HDL‐C, triglycerides, and fasting glucose and HbA1c levels. According to different prevalence of hypertension, dyslipidemia, and obesity between the 2 prespecified groups, baseline normal BP levels were less frequently reported in diabetic outpatients than in nondiabetic individuals (P<0.001), who also showed higher proportions of individuals having normal levels for both HDL‐C (P<0.001) and triglycerides (P<0.001). In particular, a high‐risk metabolic pattern, as defined by “atherogenic dyslipidemia” (ie, low levels of HDL‐C, high values of triglycerides, and glucose abnormalities), seems to be more prevalent in diabetic outpatients than in nondiabetic individuals. Finally, normal fasting glucose levels were obviously less prevalent in diabetic patients than in nondiabetic ones (P<0.001). The same findings were observed with regard to normal HbA1c levels, which were less frequently reported in diabetic outpatients than in nondiabetic individuals (P<0.001). This latter analysis, however, should be limited by the fact that availability of this parameter largely differed between the 2 predefined groups (n = 2736 in the overall population sample, n = 2172 in diabetic patients, and n = 564 in nondiabetic individuals).
Figure 2.
Percentage of patients achieving recommended targets of major CV risk factors, including BP (<140/90 mm Hg), TOT‐C (<200 mg/dL), HDL‐C (>40 mg/dL in males and >50 mg/dL in females), TG (<200 mg/dL), glucose (fasting glucose <126 mg/dL), and HbA1c (<7.0%), showing levels in the overall population and in subgroups of patients with and without DM. Baseline clinical data on HbA1c were available in different proportions of patients included in the analysis. In particular, 1381 (50%) patients had HbA1c <7% in the overall population sample (n = 2736), 852 (39%) in the diabetic subgroup (n = 2.172), and 529 (94%) in the nondiabetic subgroup (564). P<0.001 vs nondiabetic patients. Abbreviations: BP, blood pressure; CV, cardiovascular; HDL‐C, high‐density lipoprotein cholesterol; TG, triglycerides; TOT‐C, total cholesterol.
Among markers of organ‐damage detection and evaluation (online Table), the presence of DM seems to provide a favorable impact on global CV risk stratification, as ECG, echocardiogram, carotid and abdominal Doppler ultrasound, microalbuminuria test, exercise stress test, and fundus oculi examination all were more frequently prescribed in diabetic outpatients than in nondiabetic individuals (P<0.001 for all comparisons).
As shown in Table 2, no significant differences were found regarding smoking cessation, as expected by a balanced distribution of smoking habit between the 2 groups. At the same time, diet and physical activity were more often prescribed to diabetic than to nondiabetic outpatients (P<0.001), according to the higher prevalence of obesity and metabolic abnormalities in the former than in the latter group. Despite the lower proportions of patients having normal BP levels at baseline, antihypertensive drugs were generally more commonly prescribed in diabetic patients than in nondiabetic individuals (P<0.001). In particular, angiotensin‐converting enzyme inhibitors, angiotensin II receptor blockers, calcium antagonists, diuretics, and nitrates were more often prescribed in diabetic outpatients than in nondiabetic individuals (P<0.001). At the same time, lipid‐lowering agents, including statins, fibrates, cholesterol absorption inhibitors, and omega‐3 fatty acids, were more frequently prescribed in diabetic than in nondiabetic outpatients (P<0.001). Of note, although the percentage of outpatients showing normal levels for both total and LDL‐C was significantly lower in the former than in the latter group, diabetic patients failed to achieve the same level of HDL‐C and triglyceride control than that achieved by nondiabetic individuals, thus leaving a vast proportion of diabetic patients at high residual risk of developing major CV events. Antiplatelet agents (mostly aspirin and ticlopidine) were more often prescribed to diabetic than to nondiabetic outpatients (P<0.001), and this would be probably related to the higher proportion of outpatients with ischemic heart diseases and cerebrovascular or peripheral artery diseases in the former than in the latter group.
Table 2.
Absolute Levels of Blood Pressure, Glucose, and Lipid and Renal Profile in the Overall Population and in Subgroups of Patients With and Without Diabetes Mellitus
| Overall Population (n = 9904) | Diabetic Patients (n = 3681) | Nondiabetic Patients (n = 6223) | P Value | |
|---|---|---|---|---|
| Lifestyle recommendations, n (%) | ||||
| Smoking cessation | 3962 (40) | 1541 (42) | 2421 (39) | 0.55 |
| Diet | 7091 (72) | 2861 (78) | 4230 (68) | <0.001 |
| Physical activity | 6528 (66) | 2641 (72) | 3887 (62) | <0.001 |
| Antihypertensive drugs, n (%) | 7864 (79) | 3106 (84) | 4758 (76) | <0.001 |
| ACE inhibitors | 4825 (49) | 2035 (55) | 2790 (45) | <0.001 |
| β‐Blockers | 2138 (22) | 798 (22) | 1340 (22) | 0.81 |
| ARBs | 2186 (22) | 953 (26) | 1233 (20) | <0.001 |
| Calcium antagonists | 2335 (24) | 1010 (27) | 1325 (21) | <0.001 |
| Diuretics | 3192 (32) | 1264 (34) | 1928 (31) | <0.001 |
| Digoxin | 378 (4) | 178 (5) | 200 (3) | 0.004 |
| Nitrates | 1195 (12) | 547 (15) | 648 (10) | <0.001 |
| Antidiabetic drugs, n (%) | 3021 (31) | 3021 (82) | 0 (0) | — |
| Glitazones | 238 (2) | 238 (6) | 0 (0) | — |
| Insulin | 799 (8) | 799 (22) | 0 (0) | — |
| Metformin | 1928 (19) | 1928 (52) | 0 (0) | — |
| Secretagogues | 551 (6) | 551 (15) | 0 (0) | — |
| Others | 323 (3) | 323 (9) | 0 (0) | — |
| Lipid‐lowering agents, n (%) | 4312 (44) | 2035 (55) | 2277 (37) | <0.001 |
| Fibrates | 166 (2) | 91 (2) | 75 (1) | <0.001 |
| Cholesterol absorption inhibitors | 64 (0.6) | 31 (0.8) | 33 (0.5) | <0.001 |
| Omega‐3 | 847 (9) | 373 (10) | 474 (8) | <0.001 |
| Statins | 3892 (39) | 1848 (50) | 2044 (33) | <0.001 |
| Antiarrhythmic drugs, n (%) | 443 (4) | 168 (5) | 275 (4) | 0.88 |
| Anticoagulant agents, n (%) | 446 (5) | 196 (5) | 250 (4) | 0.007 |
| Antiplatelet agents, n (%) | 4333 (44) | 2010 (55) | 2323 (37) | <0.001 |
| Aspirin | 3461 (35) | 1634 (44) | 1827 (29) | <0.001 |
| Clopidogrel | 260 (3) | 103 (3) | 157 (3) | 0.50 |
| Ticlopidine | 733 (7) | 336 (9) | 397 (6) | <0.001 |
| Other drugs, n (%) | 1728 (17) | 534 (15) | 1194 (19) | <0.001 |
Abbreviations: ACE, angiotensin‐converting enzyme; ARB, angiotensin II receptor blocker; BP, blood pressure; HbA1c, glycated hemoglobin; HDL, high‐density lipoprotein; LDL, low‐density lipoprotein.
Data are expressed as mean ± SD.
P < 0.001 vs nondiabetic patients.
Finally, physicians treating diabetic patients paid more attention to collecting information on global CV risk profile than physicians treating nondiabetic individuals (data not shown). In particular, they recorded information on BP levels, glucose and lipid profile, creatinine levels, lifestyle changes, and CV drugs in a higher proportion of their outpatients compared with the other group of physicians (P<0.001). In addition, information on major CV risk factors, organ damage, and associated clinical conditions was more frequently recorded by physicians treating diabetic patients than by the other group of physicians (P<0.001), thus confirming a closer attention to global CV risk stratification in the presence of DM.
Discussion
The purpose of the EFFECTUS program was to provide updated information on prevalence of major CV risk factors and physicians' attitudes on global CV risk management in a large population sample of daily clinical practice of general practitioners, cardiologists, and diabetologists in Italy. The present study reports data collected in the cross‐sectional phase of this program, based on clinical information derived from the whole population sample of 9904 subjects observed by 1078 physicians, a large and age‐ and gender‐representative sample of the Italian outpatient population.
In the present analysis, we are able to highlight some important differences not only in the distribution and detection of major CV risk factors, but in the clinical management and therapeutic approaches adopted by physicians in the presence or absence of DM at baseline observation. Among the large number of data made available by this analysis, some specific aspects deserve discussion.
First of all, in our population sample, a higher proportion of diabetic patients was followed by general practitioners than by specialized physicians, mostly diabetologists. Irrespective of the clinical setting in which diabetic outpatients were followed, however, it should be highlighted that a higher prevalence of major CV risk factors and associated clinical conditions was observed among diabetic outpatients than among nondiabetic individuals (Figure 1). This distribution may confer a substantially higher global CV risk profile to diabetic patients included in our analysis than that reported in nondiabetic individuals. Diabetic patients, in fact, showed baseline normal values of major CV risk factors in significantly lower proportions than nondiabetic patients, with the only exceptions total and LDL‐C levels (Figure 2). Second, the lower control rate of major CV risk factors observed in diabetic patients than that reported in nondiabetic patients did not seem to be related to the use of diagnostic examinations for evaluating markers of organ damage. In our analysis, in fact, diabetic patients underwent advanced diagnostic examinations, including ECG, echocardiogram, carotid and abdominal Doppler ultrasound, microalbuminuria test, exercise stress test and fundus oculi examination, in significantly higher proportions than those reported in nondiabetic individuals (online Table). In order to achieve clinical outcomes, physicians often use more resources and diagnostic exams in patients with a higher CV risk profile, being the higher the risk, the lower the control rate.17, 18, 19 This is probably the reason why, in our observation, a larger number of diagnostic tests was used in diabetic as compared with nondiabetic patients. In addition, the larger use of diagnostic examinations in diabetic than in nondiabetic patients was consistent with the recommendations of current international guidelines for the clinical management of diabetes and CV diseases.14, 15, 16
The differences observed among CV and non‐CV drug prescriptions between the 2 groups, mostly antihypertensive, lipid‐lowering, and antiplatelet agents, may be related to the significantly higher prevalence of hypertension, dyslipidemia, and CV diseases among diabetic outpatients rather than in nondiabetic individuals. It should be highlighted, however, that even in this case the larger use of CV drugs in diabetic patients was not paralleled by a better control of major CV risk factors at baseline as compared with that obtained in nondiabetic individuals, thus suggesting that other aspects, beyond diabetes or glucose abnormalities, should be taken into account in the clinical management of CV disease, beyond the number of prescriptions and dosages of drugs.
Finally, the presence of DM demonstrates a favorable impact on increasing physicians' accuracy for clinical data collection and registration, confirming our previous observations.9 In a previous analysis of this database, in fact, we found that a significant increase in the proportion of patients treated according to guidelines was observed in those physicians who were more accurate in recording clinical data of their outpatients.9 In the present analysis, the presence of DM and high CV risk profile was associated with higher clinical data availability and registration of above all major CV risk factors, markers of organ damage, and associated clinical conditions as compared with that reported in nondiabetic individuals. In this latter regard, it should be also mentioned that the more careful CV risk stratification attained in diabetic patients may be linked to the fact that physicians treating diabetic patients paid more attention to collecting information on global CV risk profile, rather than the fact that diabetic patients underwent more clinical evaluations as compared with nondiabetic individuals. These discrepancies observed between the 2 groups with regard to clinical data collection and registration may represent, in our opinion, a crucial aspect that may account for different rates of normal thresholds of major CV risk factors observed in diabetic than in nondiabetic individuals in our population sample.
Conclusion
Presence of DM at baseline significantly improved clinical data availability, thus confirming a closer attention to global CV risk stratification by physicians when treating diabetic rather than nondiabetic patients. In the presence of the higher global CV risk and greater use of diagnostic tools for organ‐damage detection and evaluation, diabetic outpatients have more updated clinical data than what is reported in nondiabetic subjects, which can be translated into a more comprehensive global CV risk stratification, as recommended by current international guidelines.14, 20 Such an approach, however, was not associated with an improved global CV risk management in diabetic patients compared with nondiabetic patients enrolled in our population sample. At this time, there is limited evidence indicating that a more frequent prescription of diagnostic examinations relates to a better prognosis in patients at CV risk. Our current results may suggest the need to implement educational interventions among physicians who have a large number of diabetic outpatients in their routine clinical practice. This approach may help to improve the global CV risk stratification in both diabetic and nondiabetic patients at increased risk of developing major CV events.
Acknowledgements
Authors wish to thank the 1078 Italian physicians for their contribution to this project. The present study was endorsed by the Italian Society of Cardiovascular Prevention (SIPREC).
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