Figures
Abstract
Introduction
Appropriate algorithms for the prediction of cardiovascular risk are strongly suggested in clinical practice, although still controversial. In type 2 diabetes mellitus (T2DM), the beneficial effect of phosphodiesterase (PDE)-5 inhibitors is demonstrated on endothelial function but not on the estimation of cardiovascular risk.
Aim
To study whether the chronic Vardenafil administration to men with T2DM influences variables correlated with the predicted long-term cardiovascular risk calculated by different validated algorithms.
Methods
Per-protocol analysis of a longitudinal, prospective, randomized, placebo-controlled, double-blind, investigator-started, clinical trial. 54 male patients affected by T2DM were assigned to study (26patients) and control-group (28patients), respectively. The study included a treatment phase (24weeks) (Vardenafil/placebo 10mg twice-daily) and a follow-up phase (24weeks). Three time points were considered: baseline(V0), end of treatment(V1) and end of the study(V2). Parameters evaluated: endothelial health-related parameters and cardiovascular risk, assessed by calculating the Framingham (coronary hart disease [CHD], myocardial infarction [MI], stroke and cardiovascular disease [CVD]), ASSIGN and CUORE equations.
Results
Predicted cardiovascular risk at ten years resulted different using the three algorithms chosen, without differences between study and control groups and among visits. IL-6 was directly related to CHD, CVD and CUORE scores at V1 and with MI and STROKE at V2. Similarly, hs-CRP was directly related to CHD, MI, STROKE and CUORE only at V1 in the study group. Testosterone serum levels were inversely related to CHD and MI at V1 in study group.
Discussion
The predicted cardiovascular risk is different depending on the algorithm chosen. Despite no predictive risk reduction after six months of treatment, a possible effect of Vardenafil could be hypothesized through its action on inflammation markers reduction and through restoration of normal testosterone levels.
Citation: Santi D, Locaso M, Granata AR, Trenti T, Roli L, Pacchioni C, et al. (2018) Could chronic Vardenafil administration influence the cardiovascular risk in men with type 2 diabetes mellitus? PLoS ONE 13(6): e0199299. https://doi.org/10.1371/journal.pone.0199299
Editor: Maria Ida Maiorino, Seconda Universita degli Studi di Napoli, ITALY
Received: October 27, 2017; Accepted: May 31, 2018; Published: June 28, 2018
Copyright: © 2018 Santi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the paper and its Supporting Information files.
Funding: This study was not directly funded, but authors received a grant from "Progetti di Rilevante Interesse Nazionale" (PRIN).
Competing interests: The authors have declared that no competing interests exist.
Introduction
Predictability of coronary heart diseases (CHD) is one of the major challenge in clinical practice [1–4]. Cardiology societies worldwide recommend the use of appropriate predictive algorithms for identification of patients at high cardiovascular risk [5–10]. The Framingham Heart study provided the first and best known example of such equations, created in 1991 thanks to a large North American population-based trial [11]. This algorithm is used to calculate the cardiovascular risk at ten years with the final aim to decide if a preventive treatment is needed [11]. A number of algorithms have been proposed in the following years, considering the population-specific risk and evaluating different large population-based cohorts. For the Italian population, in 2000, the CUORE score was created to evaluate the risk of coronary deaths [12–14]. These algorithms represent the only largely evaluated method to consider this risk in a cohort of patients.
Type 2 diabetes mellitus is one of the major risk factors of CHD [15]. Indeed, diabetes increases the long-term cardiovascular risk to the level observed in non-diabetic patients with prior myocardial infarction [16]. Diet, exercise, anti-diabetic drugs and bariatric surgery approaches have been studied for their effectiveness in reducing cardiovascular events, which is generally independent on their glucose-lowering effect [15]. In this clinical setting, despite the validation of multiple diabetes-specific and general population-based cardiovascular risk assessment models, the cardiovascular risk estimation remains approximate [17]. Moreover, the management of diabetic men does not always consider prediction of cardiovascular risk in the treatment selection.
Phosphodiesterase (PDE)-5 inhibitors are approved for erectile dysfunction and for pulmonary hypertension. These drugs act controlling the intra-cellular degradation rate of second messengers, such as cyclic guanosine monophosphate (cGMP) [18]. Consequently, PDE-5 inhibitors improve vasodilation, through the nitric oxide (NO)-dependent cGMP increase [19, 20]. This vasodilator effect has been studied at cardiovascular level, evaluating the cardiac output in case of chronic congestive heart failure [21], the remodelling action on the cardiac muscle cells, as well as the inhibition of platelet aggregation [22]. All these effects are due to the restoration of the physiologic equilibrium between mediators of vasoconstriction and vasodilation, inhibiting the catabolism of cGMP and enhancing NO levels [23]. These endothelial function improvements could reduce atherogenesis and vascular complications of diabetes mellitus [23]. Despite an increasing evidence of these beneficial effects [24], no studies so far evaluated whether PDE-5 inhibitors administration influences the long-term cardiovascular risk prediction in diabetic patients.
In this study we assessed whether the chronic Vardenafil administration to men with type 2 diabetes mellitus could reduce the long-term estimated cardiovascular risk, using validated algorithms. Since no specific algorithm to predict cardiovascular risk in diabetic men is commonly accepted as the reference method so far, three different equations were used and compared.
Materials and methods
Study design
This is a secondary, retrospective, analysis of a recent longitudinal, prospective, randomized, placebo-controlled, double-blind, investigator-started, clinical trial described in detail earlier [25]. Briefly, we enrolled 54 patients with diagnosis of type 2 diabetes mellitus made within 5 years before enrollment, and with erectile dysfunction but no previous use of PDE-5 inhibitors (Fig 1). The study lasted from 2008 to 2014. Patients were randomized using the permuted block method and assigned to the study or control group, in which Vardenafil (10 mg twice daily) or placebo were administered, respectively [25]. Patients were followed for one year, considering six months of therapy and six months of treatment withdrawal. During the year of trial, each patient was evaluated ten times, 8 during the treatment phase and 2 during the follow-up [25]. During each visit, a blood sample was taken after an overnight fast and biochemical and endothelial health-related parameters were evaluated and reported in our previous paper [25]. Here, we used biochemical parameters and clinical history of the patients to calculate the cardiovascular risk using three different validated algorithms. In particular, using a per-protocol analysis, we considered three visits carried out six months away: baseline (V0), end of treatment (V1) and end of the study (V2).
Cardiovascular risk assessment
The cardiovascular risk was calculated using three appropriate validated algorithms available in the literature. First, the Framingham algorithm [11] was used, which considers the four following outcome risks: CHD, myocardial infarction (MI), stroke and cardiovascular disease (CVD). Second, the ASSIGN equation and the CUORE score were used as alternative tools to cardiovascular risk calculation. The ASSIGN risk score derives from the Scottish Heart Health Extended cohort study, which includes several cohorts with more than 6000 men aged between 30 and 74 years [26]. The CUORE risk score [27–29] derives from a study including a combination of 11 Italian cohorts with more than 6800 men aged between 35 and 69 years [14].
Overall, these three tools predict the cardiovascular risk considering age, sex, total cholesterol, HDL, diabetes mellitus, smoking habit and systolic pressure.
Cardiovascular and biochemical parameters
The calculated cardiovascular risk was evaluated in association with markers of endothelial health. In particular, we considered ultrasonography parameters, such as flow mediated dilation (FMD) [30, 31], and biochemical markers, such as interleukin (IL)-6, intercellular adhesion molecule (ICAM)-1, vascular cell adhesion molecule (VCAM)-1, high sensitivity C-reactive protein (hs-CRP), endothelin (ET)-1 and testosterone serum levels.
IL-6 was measured on plasma samples by the Human IL-6 Quantikine ELISA Kit (R&D Systems Europe, Ltd. Abingdon OX14 3NB, UK). ICAM-1 and VCAM-1 were measured on serum samples, diluted 1:2, using the bead-based multiplex assay for Luminex platform (R&D Systems Inc kit code LXSAH, Minneapolis, US). Hs-CRP and ET-1 were measured with the BN™ II System instrument (Siemens) through a specific automated nephelometric assay (CardioPhase® hsCRP, Dada Behring Inc. Newark, DE 19714 US). Testosterone was analyzed by liquid-chromatography, tandem mass-spectometry (LC/MS-MS) (Shimadzu Nexera UHPLC with Shimadzu LCMS-8050 triple quadrupole) with the Pelkin Elmer kit (Wallac OY, Turku, Finland), using serum samples obtained at each visit. Other routine assays were performed using commercially available kits.
Ethics
The local Ethics Committee of the University of Modena and Reggio Emilia, Italy, approved the study protocol. Patient informed consent was obtained and patients were appropriately insured. The study was registered according to European study registration rules (EudraCT: 2009-014137-25), and on ClinicalTrials.gov (Identification number NCT02219646)
Statistical analysis
Statistical analysis was performed through the “per protocol” method. According to the not-normal distribution of variables, evaluated at Kolmogorov-Smirnov test, the differences of risk scores were evaluated comparing study and control groups using Mann-Whitney test at each visit. The score change during the study protocol was evaluated through Wilcoxon-rank test in both groups. Moreover, at each visit, the risk change compared to previous visit was calculated. Finally, each risk was evaluated after adjustment for blood pressure and total, HDL and LDL cholesterol. The correlation among the risk scores and other parameters was evaluated using Spearman’s Rho.
Finally, multivariate analyses were performed to detect possible predictors of cardiovascular risks. Thus, stepwise, linear, multiple regression analyses were performed using each risk score as dependent variable and age, body mass index, glucose, glycated haemoglobin, microalbuminuria, hs-CRP, IL-6, ET-1, ICAM-1, VCAM-1, fibrinogen, FMD and testosterone as independent variables. Each independent variable entered the analysis step by step. In these analyses lipid profile and blood pressures have not been considered as dependent variables, since they are included in the algorithms used for cardiovascular risk calculation. All multiple regression analyses were performed in the study group.
Statistical analysis was performed using the ‘Statistical Package for the Social Sciences’ software for Macintosh (version 21.0; SPSS Inc., Chicago, IL). For all comparisons, p values < 0.05 were considered statistically significant.
Results
Fifty-four diabetic men were enrolled, 26 in the study and 28 in the control group. Excluding drop-outs, 20 patients in the study and 25 in the control group were finally evaluated. Patients enrolled were similar at baseline for each parameter investigated, as previously reported (Table 1) [25].
The basal cardiovascular risk at ten years was different using the three algorithms chosen (p = 0.004), ranging from 12.10±9.30% for the CUORE equation, to 14.86±7.55% for the Framingham CHD score, to 21.48±7.48% for the ASSIGN equation. At V0, no differences between study and control groups were found for CHD, MI, stroke, CVD, ASSIGN and CUORE scores (Table 2). Similarly, no differences were found at V1 (CHD p = 0.405, MI p = 0.372, stroke p = 0.759, CVD p = 0.407, ASSIGN p = 0.708 and CUORE p = 0.668) and V2 (CHD p = 0.455, MI p = 0.327, stroke p = 0.425, CVD p = 0.336, ASSIGN p = 0.809 and CUORE p = 0.661). No differences among visits were found, considering separately the study (CHD p = 0.767, MI p = 0.755, stroke p = 0.903, CVD p = 0.862, ASSIGN p = 0.417 and CUORE p = 0.962) and control (CHD p = 0.806, MI p = 0.849, stroke p = 0.981, CVD p = 0.951, ASSIGN p = 0.194 and CUORE p = 0.999) group. Similarly, no changes were observed after adjustment for cholesterol and blood pressure.
Considering the change of each cardiovascular risk estimation from V0 to V1 and from V1 to V2, no differences were found between study and control group.
Endothelial health-related parameters
We previously demonstrated that chronic Vardenafil treatment significantly decreases IL-6 serum levels [25]. Here, we found that IL-6 was not related to cardiovascular risk estimated at baseline. However, IL-6 was directly related to CHD, CVD and CUORE scores at V1 (Table 3). These correlations remained statistically significant after treatment withdrawal (V2) for MI and STROKE (Table 3).
Hs-CRP was not related to cardiovascular risk scores at V0 in both study and control groups (Table 4). However, a significant direct relationship was found at V1 between hs-CRP and CHD, MI, STROKE, CVD and CUORE only in the study group (Table 4). The significant correlation between hs-CRP and CHD remained at V2 (Table 4). Interestingly, the direct correlation between hs-CRP and CHD was found also in the control group at V1 and V2 (Table 4).
ET-1, ICAM-1, VCAM-1 and FMD did not correlate with any of the cardiovascular risk estimations considered, neither in the study, nor in the control group. Similarly, no correlations were found between cardiovascular risk estimation and glycemia-related parameters, such as serum glucose levels, glycated haemoglobin and microalbuminuria. Finally, the score at erectile function domain of international index of erectile function (IIEF)-15 did not correlate with estimated cardiovascular risk scores in any group.
Gonadal status
Testosterone serum levels were not related to any of the estimated cardiovascular risk scores at V0 in either groups. However, at V1, a significant, inverse relationship between testosterone and CHD and MI was found only in the study group (Table 5).
Considering gonadal status, we previously demonstrated that 13 of patients enrolled (24%) were hypogonadal at baseline, according to the cut-off limit (10.4 nmol/L) proposed by the Endocrine Society [32]. In these men, total testosterone serum levels significantly improved in the study compared to the control group and across visits [25]. Here, we further strengthen the association between testosterone and cardiovascular risk. Indeed, considering 7 hypogonadal men treated with Vardenafil, the inverse relationship at V1 was confirmed between testosterone and CHD, MI, CVD and ASSIGN (Table 5). On the contrary, no relationship was found in the non-hypogonadal men (Table 5).
Multivariate analyses
By multivariate analyses, some significant results were detected. First, considering CHD as dependent variable, the following equation (p = 0.007) was found: CHD = 12.873+6.178*(hs-CRP). hs-CRP entered also in the second model (p = 0.009), in which the ASSIGN score was used as dependent variable: ASSIGN = 9.355+39–019*(hs-CRP). These results pinpoint variables are correlated with these parameters which enter in the prediction of cardiovascular risk, although a direct relationship was not previously pointed out. On the other hand, considering the CUORE score as dependent variable, IL-6 entered the model (p = 0.009) as follows: CUORE = 3.454+2560*(IL-6).
Discussion
Here, we retrospectively evaluated the effect of chronic Vardenafil administration on the estimation of cardiovascular risk in diabetic men. To the best of our knowledge, this is the first trial giving the opportunity of evaluating the effect of PDE-5 inhibitors on prediction of cardiovascular risk in patients with type 2 diabetes mellitus. In spite of the beneficial effect of chronic Vardenafil administration on several endothelial health-related parameters [25], no significant change in the prediction of cardiovascular risk was found using three different algorithms. Of the variables used in these algorhytms, neither cholesterol, nor blood pressure are directly influenced by Vardenafil administration, as previously demonstrated [25].
The scientific literature demonstrates beneficial effects of PDE-5 inhibitors on cardiac remodelling [33], symptoms of coronary artery diseases [34] and hemodynamic parameters [35]. These effects were evaluated in specific clinical conditions, e.g. heart failure, myocardial infarction, stroke and hypertension [36]. In diabetes mellitus only endothelial health-related parameters were evaluated after PDE-5 inhibitors treatment [24]. We previously confirmed the beneficial effect of chronic Vardenafil administration on endothelial parameters, suggested by a IL-6 reduction and a FMD increase [25]. Whether this beneficial effect could influence the long-term cardiovascular risk in type 2 diabetes mellitus is not known. Here we do not test the cardiovascular risk of our patients but whether the prediction of this risk changes under chronic PDE-5 inhibitor treatment for six months. This parameter does not change. However, the improvement of endothelial health-related parameters resulting from chronic Vardenafil administration opens the possibility of a stronger effect of this treatment of the predicted cardiovascular risk using longer treatment duration.
A direct relationship between hs-CRP and cardiovascular risk scores is found in study group at V1, although hs-CRP did not change over time and after Vardenafil administration, as previously reported [25]. This result suggests that hs-CRP could have an important role on the parameters used in the prediction of cardiovascular risk. On the contrary, other endothelial health-related parameters, which are strongly influenced by Vardenafil administration (e.g. FMD) [25], are not related to the estimated cardiovascular risk scores. These relationships suggest that cardiovascular risk predicted by validated tools seems to be mostly related to inflammation markers, rather than to vasodilator parameters. As a confirmation, multivariate analyses highlight the hs-CRP and IL-6 role in the prediction of cardiovascular risk. Thus, since the PDE-5 inhibitors anti-inflammatory effect was proven by previous results, we might expect them to exert a protective role on cardiovascular risk provided the treatment is sufficiently long. However, the clinical use of these drugs for this purpose is not indicated so far and properly designed, longer and well-powered clinical trials are needed to better understand long-term survival of these patients after longer chronic treatment. In this context, the role of sphingosine-1-phosphate is widely proposed and a possible combined effect with PDE-5 inhibitors could be evaluated in the near future [37, 38].
Finally, cardiovascular risk predicted by validated algorithms seems to be influenced by total testosterone serum levels. In particular, CHD and MI are inversely related to testosterone after Vardenafil administration. This correlation is further confirmed considering only diabetic men with hypogonadism at baseline. Since chronic Vardenafil administration improves testosterone serum levels in hypogonadal diabetic men [25], this might be another way by which gonadal function improvement results in a beneficial effect on cardiovascular health. Therefore, the overall protective role of PDE-5 inhibitors on cardiovascular health might be mediated by both inflammatory markers decrease and gonadal function improvement.
A large number of cardiovascular risk calculators have been developed and validated so far, the first and widely used tool being represented by the Framingham score [11], which however, suffers of a number of pitfalls. Indeed, it is well demonstrated that the use of this calculator for deciding whether preventive therapy is needed or not could lead to under-treatment with a consequent socio-economic burden increase [39]. Thus, other equations have been developed and validated in different population-based cohorts. Although these algorithms should provide overlapping scores, we found different percentages of the estimated cardiovascular risk at ten years considering the same group of patients, ranging from 12% for the CUORE score, to 22% for the ASSIGN equation. Thus, our results confirm the discrepancy in the risk prediction obtained by different algorithms and how to generalize the risk score obtained by these calculators remains the main challenge in this field. Moreover, the clinical use of these algorithms must consider the characteristics of the population in which the tool has been validated. Admittedly, our study, which was not designed to assess the cardiovascular risk and solve these discrepancies, is bases on a low number of patients enrolled and relatively short-term treatment therapy length to investigate appropriately the effects of PDE-5 inhibitors. However, our retrospective analysis gives some hints, which could be useful for the design of future prospective studies in cardiovascular prevention in diabetic patients and for the identification of the best predictive tool in this setting.
The strength of the present study relies on the study design of the original trial (prospective, double blind, placebo controlled), which provided the longest treatment duration with a PDE-5 inhibitor and follow-up phase published so far. Admittedly, however, the treatment duration is at the same time a potential limit for the parameter investigated here. Indeed, cardiovascular risk is predicted at ten years and longer treatment durations might be necessary to influence this parameter. Finally, the low number of patients represents another important limit.
In conclusion, despite six-months of chronic Vardenafil administration do not change cardiovascular risk prediction, a beneficial effect of PDE-5 inhibitors on cardiovascular health, via the previously demonstrated action on inflammatory markers is suggested. Similarly, the PDE-5 inhibitors effect in restoring normal gonadal function seems to influence the prediction of long term cardiovascular risk. Longer duration of chronic PDE-5 inhibitors treatment should be evaluated in the near future.
References
- 1. Liao Y, McGee DL, Cooper RS, Sutkowski MB. How generalizable are coronary risk prediction models? Comparison of Framingham and two national cohorts. American heart journal. 1999;137(5):837–45. Epub 1999/04/30. pmid:10220632.
- 2. Menotti A, Keys A, Blackburn H, Kromhout D, Karvonen M, Nissinen A, et al. Comparison of multivariate predictive power of major risk factors for coronary heart diseases in different countries: results from eight nations of the Seven Countries Study, 25-year follow-up. Journal of cardiovascular risk. 1996;3(1):69–75. Epub 1996/02/01. pmid:8783033.
- 3. Hense HW, Schulte H, Lowel H, Assmann G, Keil U. Framingham risk function overestimates risk of coronary heart disease in men and women from Germany—results from the MONICA Augsburg and the PROCAM cohorts. European heart journal. 2003;24(10):937–45. Epub 2003/04/26. pmid:12714025.
- 4. Brindle P, Emberson J, Lampe F, Walker M, Whincup P, Fahey T, et al. Predictive accuracy of the Framingham coronary risk score in British men: prospective cohort study. BMJ (Clinical research ed). 2003;327(7426):1267. Epub 2003/12/04. pmid:14644971; PubMed Central PMCID: PMCPMC286248.
- 5. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47. Epub 1998/05/29. pmid:9603539.
- 6. Jackson R. Guidelines on preventing cardiovascular disease in clinical practice. BMJ (Clinical research ed). 2000;320(7236):659–61. Epub 2000/03/11. pmid:10710556; PubMed Central PMCID: PMCPMC1117692.
- 7. Prevention of coronary heart disease in clinical practice. Recommendations of the Second Joint Task Force of European and other Societies on coronary prevention. European heart journal. 1998;19(10):1434–503. Epub 1998/11/20. pmid:9820987.
- 8. McKenney JM. Update on the National Cholesterol Education Program Adult Treatment Panel III guidelines: getting to goal. Pharmacotherapy. 2003;23(9 Pt 2):26S–33S. Epub 2003/10/04. pmid:14524636.
- 9. Assmann G, Cullen P, Schulte H. Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Munster (PROCAM) study. Circulation. 2002;105(3):310–5. Epub 2002/01/24. pmid:11804985.
- 10. Conroy RM, Pyorala K, Fitzgerald AP, Sans S, Menotti A, De Backer G, et al. Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project. European heart journal. 2003;24(11):987–1003. Epub 2003/06/06. pmid:12788299.
- 11. Anderson KM, Odell PM, Wilson PW, Kannel WB. Cardiovascular disease risk profiles. American heart journal. 1991;121(1 Pt 2):293–8. Epub 1991/01/01. pmid:1985385.
- 12. Menotti A, Lanti M, Puddu PE, Kromhout D. Coronary heart disease incidence in northern and southern European populations: a reanalysis of the seven countries study for a European coronary risk chart. Heart (British Cardiac Society). 2000;84(3):238–44. Epub 2000/08/24. pmid:10956281; PubMed Central PMCID: PMCPMC1760967.
- 13. Menotti A, Farchi G, Seccareccia F. The prediction of coronary heart disease mortality as a function of major risk factors in over 30 000 men in the Italian RIFLE pooling Project. A comparison with the MRFIT primary screenees. The RIFLE research group. Journal of cardiovascular risk. 1994;1(3):263–70. Epub 1994/10/01. pmid:7621307.
- 14. Ferrario M, Chiodini P, Chambless LE, Cesana G, Vanuzzo D, Panico S, et al. Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation. International journal of epidemiology. 2005;34(2):413–21. Epub 2005/01/22. pmid:15659467.
- 15. Naito R, Miyauchi K. Coronary Artery Disease and Type 2 Diabetes Mellitus. International heart journal. 2017;58(4):475–80. Epub 2017/07/19. pmid:28717115.
- 16. Haffner SM, Lehto S, Ronnemaa T, Pyorala K, Laakso M. Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction. The New England journal of medicine. 1998;339(4):229–34. Epub 1998/07/23. pmid:9673301.
- 17. Santilli F, Pignatelli P, Violi F, Davi G. Aspirin for primary prevention in diabetes mellitus: from the calculation of cardiovascular risk and risk/benefit profile to personalised treatment. Thrombosis and haemostasis. 2015;114(5):876–82. Epub 2015/08/08. pmid:26245672.
- 18. Bender AT, Beavo JA. Cyclic nucleotide phosphodiesterases: molecular regulation to clinical use. Pharmacological reviews. 2006;58(3):488–520. Epub 2006/09/14. pmid:16968949.
- 19. Corbin JD. Mechanisms of action of PDE5 inhibition in erectile dysfunction. International journal of impotence research. 2004;16 Suppl 1:S4–7. Epub 2004/06/30. pmid:15224127.
- 20. Rosen RC, Kostis JB. Overview of phosphodiesterase 5 inhibition in erectile dysfunction. The American journal of cardiology. 2003;92(9A):9M–18M. Epub 2003/11/12. pmid:14609619.
- 21. Kapur V, Chien CV, Fuess JE, Schwarz ER. The relationship between erectile dysfunction and cardiovascular disease. Part II: The role of PDE-5 inhibition in sexual dysfunction and cardiovascular disease. Reviews in cardiovascular medicine. 2008;9(3):187–95. Epub 2008/10/28. pmid:18953278.
- 22. Dunkern TR, Hatzelmann A. The effect of Sildenafil on human platelet secretory function is controlled by a complex interplay between phosphodiesterases 2, 3 and 5. Cellular signalling. 2005;17(3):331–9. Epub 2004/11/30. pmid:15567064.
- 23. Milani E, Nikfar S, Khorasani R, Zamani MJ, Abdollahi M. Reduction of diabetes-induced oxidative stress by phosphodiesterase inhibitors in rats. Comparative biochemistry and physiology Toxicology & pharmacology: CBP. 2005;140(2):251–5. Epub 2005/05/24. pmid:15907769.
- 24. Santi D, Giannetta E, Isidori AM, Vitale C, Aversa A, Simoni M. THERAPY OF ENDOCRINE DISEASE: Effects of chronic use of phosphodiesterase inhibitors on endothelial markers in type 2 diabetes mellitus: a meta-analysis. European journal of endocrinology / European Federation of Endocrine Societies. 2015;172(3):R103–R14. Epub 2014/10/04. pmid:25277671.
- 25. Santi D, Granata AR, Guidi A, Pignatti E, Trenti T, Roli L, et al. Six months of daily treatment with Vardenafil improves parameters of endothelial inflammation and of hypogonadism in male patients with type 2 diabetes and erectile dysfunction: a randomized, double-blind, prospective trial. European journal of endocrinology / European Federation of Endocrine Societies. 2016. Epub 2016/01/23. pmid:26792933.
- 26. Woodward M, Brindle P, Tunstall-Pedoe H. Adding social deprivation and family history to cardiovascular risk assessment: the ASSIGN score from the Scottish Heart Health Extended Cohort (SHHEC). Heart (British Cardiac Society). 2007;93(2):172–6. Epub 2006/11/09. pmid:17090561; PubMed Central PMCID: PMCPMC1861393.
- 27. Giampaoli S, Palmieri L, Chiodini P, Cesana G, Ferrario M, Panico S, et al. [The global cardiovascular risk chart]. Italian heart journal Supplement: official journal of the Italian Federation of Cardiology. 2004;5(3):177–85. Epub 2004/05/01. pmid:15116861.
- 28. Donfrancesco C, Palmieri L, Vanuzzo D, Panico S, Ferrario MM, Cesana G, et al. [The CUORE Project: preliminary analysis for the updating of the cardiovascular risk charts and individual scores]. Giornale italiano di cardiologia (2006). 2010;11(5 Suppl 3):20S–4S. Epub 2010/10/01. pmid:20879474.
- 29. Palmieri L, Panico S, Vanuzzo D, Ferrario M, Pilotto L, Sega R, et al. [Evaluation of the global cardiovascular absolute risk: the Progetto CUORE individual score]. Annali dell'Istituto superiore di sanita. 2004;40(4):393–9. Epub 2005/04/09. pmid:15815105.
- 30. Corretti MC, Anderson TJ, Benjamin EJ, Celermajer D, Charbonneau F, Creager MA, et al. Guidelines for the ultrasound assessment of endothelial-dependent flow-mediated vasodilation of the brachial artery: a report of the International Brachial Artery Reactivity Task Force. Journal of the American College of Cardiology. 2002;39(2):257–65. Epub 2002/01/15. pmid:11788217.
- 31. Heiss C, Lauer T, Dejam A, Kleinbongard P, Hamada S, Rassaf T, et al. Plasma nitroso compounds are decreased in patients with endothelial dysfunction. Journal of the American College of Cardiology. 2006;47(3):573–9. Epub 2006/02/07. pmid:16458138.
- 32. Bhasin S, Cunningham GR, Hayes FJ, Matsumoto AM, Snyder PJ, Swerdloff RS, et al. Testosterone therapy in men with androgen deficiency syndromes: an Endocrine Society clinical practice guideline. The Journal of clinical endocrinology and metabolism. 2010;95(6):2536–59. Epub 2010/06/09. pmid:20525905
- 33. Giannetta E, Isidori AM, Galea N, Carbone I, Mandosi E, Vizza CD, et al. Chronic Inhibition of cGMP phosphodiesterase 5A improves diabetic cardiomyopathy: a randomized, controlled clinical trial using magnetic resonance imaging with myocardial tagging. Circulation. 2012;125(19):2323–33. Epub 2012/04/13. pmid:22496161.
- 34. Fox KM, Thadani U, Ma PT, Nash SD, Keating Z, Czorniak MA, et al. Sildenafil citrate does not reduce exercise tolerance in men with erectile dysfunction and chronic stable angina. European heart journal. 2003;24(24):2206–12. Epub 2003/12/09. pmid:14659772.
- 35. Andersen MJ, Ersboll M, Axelsson A, Gustafsson F, Hassager C, Kober L, et al. Sildenafil and diastolic dysfunction after acute myocardial infarction in patients with preserved ejection fraction: the Sildenafil and Diastolic Dysfunction After Acute Myocardial Infarction (SIDAMI) trial. Circulation. 2013;127(11):1200–8. Epub 2013/02/15. pmid:23406672.
- 36. Pofi R, Gianfrilli D, Badagliacca R, Di Dato C, Venneri MA, Giannetta E. Everything you ever wanted to know about phosphodiesterase 5 inhibitors and the heart (but never dared ask): How do they work? Journal of endocrinological investigation. 2015. Epub 2015/07/06. pmid:26142740.
- 37. Feuerborn R, Becker S, Poti F, Nagel P, Brodde M, Schmidt H, et al. High density lipoprotein (HDL)-associated sphingosine 1-phosphate (S1P) inhibits macrophage apoptosis by stimulating STAT3 activity and survivin expression. Atherosclerosis. 2017;257:29–37. Epub 2016/12/31. pmid:28038379.
- 38. Ronda N, Poti F, Palmisano A, Gatti R, Orlandini G, Maggiore U, et al. Effects of the radiocontrast agent iodixanol on endothelial cell morphology and function. Vascular pharmacology. 2013;58(1–2):39–47. Epub 2012/09/19. pmid:22985912.
- 39. Tunstall-Pedoe H, Woodward M. By neglecting deprivation, cardiovascular risk scoring will exacerbate social gradients in disease. Heart (British Cardiac Society). 2006;92(3):307–10. Epub 2005/09/17. pmid:16166099; PubMed Central PMCID: PMCPMC1860840.