Effect of collaterals on deaths and re-infarctions in patients with coronary artery disease: a meta-analysis.

BACKGROUND: It is generally believed that there is a beneficial effect of collaterals on death and re-infarction statistics in patients with coronary artery disease (CAD) but studies to date are small and inconsistent. OBJECTIVE: To meta-analyse the studies published in this field in order to obtain more powerful information. METHODS: We searched Medline and major journals (2000 to 2011) for studies evaluating the effect of coronary collaterals on mortality. Publication bias, lack of heterogeneity, and lack of robustness were assessed using the standard procedures for such purposes. RESULTS: A total of 10 studies describing mortality, enrolling 6791 participants, were included in this analysis. In patients with collateralisation a significant relation with reduced mortality was seen compared with those without collateralisation, at an odds ratio of 0.47, p < 0.0001, and a reduction in deaths and re-infarctions at 0.54, p < 0.0001. Some publication bias, some heterogeneity and some lack of robustness were demonstrated. A meta-regression with the odds ratios of the presence of traditional atherosclerotic risk factors as predictors and the odds ratios of mortality and the composite deaths and re-infarctions as outcome showed no relationships. CONCLUSIONS: In CAD patients from the post-percutaneous coronary intervention era the presence of collaterals reduced mortality by 0.47 (p < 0.0001) and deaths and re-infarctions by 0.54 (p < 0.0001). Furthermore, in the present meta-data, the atherosclerotic risk factors were no more present in patients with collaterals than they were in those without.

Prevalence of iatrogenic admissions to the Departments of Medicine/Cardiology/ Pulmonology in a 1,250 bed general hospital.

A recent meta-analysis in this journal showed incidences between 3.4 and 33.9%. Studies performed by pharmacists and epidemiologists produced lower incidences than internists' studies. We reassessed the prevalence of iatrogenic admissions in a study of internists. Iatrogenic disease was defined as adverse drug reactions according to the World Health Organization Definition and complications induced by non-drug medical interventions. Subsequent admissions at the Departments of Medicine/Cardiology/Pulmonology in a 1,250 bed general hospital in the Netherlands from May 2007 to August 2007 were studied. 2,000 consecutive admissions were studied: 576 (29%, 26-32%) were classified as possibly iatrogenic; out of these 380 (19%, 17-22%) as definitely iatrogenic, out of whom 229 (12%, 10-14%) had already been classified as iatrogenic by the admitting physicians. Patients with cardiac disease, hypertension, gastrointestinal conditions, anticoagulant treatment and use of NSAIDs were, particularly, at risk of iatrogenic admission with percentages of 22 (16-24), 13 (11-18), 12 (9-15), and 7 (5-11) %. An independent predictor of iatrogenic admissions was age with an odds ratio of 1.27 per 10 years (p = 0.0001). 1. At least 19% of admissions to the Departments of Internal Medicine/Cardiology/Pulmonology, and, maybe, even percentages up to 29% were due to adverse drug effects. 2. A large difference between the numbers of iatrogenic admission according to the physicians in charge of admission and the investigators, 229 versus 380 patients, was observed. 3. Most often iatrogenic admissions were observed with cardiac disease, hypertension, gastrointestinal conditions, anticoagulant treatment, and use of NSAIDs.

Methods for analysing cardiovascular studies with repeated measures.

Background. Repeated measurements in a single subject are generally more similar than unrepeated measurements in different subjects. Unrepeated analyses of repeated data cause underestimation of the treatment effects.Objective. To review methods adequate for the analysis of cardiovascular studies with repeated measures.Results. (1) For between-subjects comparisons, summary measures and random-effects mixedlinear models are possible. Examples of summary measures include the area under the curve of drug time-concentration and time-efficacy curves, maximal values, mean values, and changes from baseline. A problem is that precision is lost because averages, rather than individual data, are applied. Random-effects mixed-linear models, available in SPSS statistical software and other software programmes, provide better precision for that purpose. (2) For within-subjects comparisons, repeated-measures ANOVAs are available in SPSS and other software programmes. Subgroup factors such as gender differences and age class can be included.Discussion. For non-Gaussian data, Wilcoxon's and Friedman's tests are available, for binary data McNemar's tests can be used in case of two repeated observations. No standard methods are available for repeated binary measures with more than two observations. The purpose of this review was not to present a complete report but, rather, to underline that ample efforts should be made to account for the special nature of repeated measures. (Neth Heart J 2009;17:429-33.).

Meta-analysis of recent studies on patients admitted to hospital due to adverse drug effects.

The use of drugs has expanded during the previous decade. However, earlier studies on patients admitted for adverse drugs effects (ADEs) have been heterogeneous. The objectives of this study were to assess the number of recent admissions to hospital due to ADEs and to assess the degree of heterogeneity in recent studies. Prospective studies published in the past decade were therefore pooled and compared with the pooled results from earlier studies. The pooled overall percentage in recent studies (n = 20) was 5.4% (5.0 - 5.8) and this did not significantly differ from that in the earlier studies (n = 21, pooled percentage 4.7%, 3.1 - 6.2). The studies were clinically very heterogeneous with percentages of ADEs between 3.4 and 33.2%. The nature of the patient group could be held largely responsible for the clinical heterogeneity observed.

Accuracy assessments of quantitative diagnostic tests for clinical research.

BACKGROUND: Clinical research is impossible without accurate diagnostic tests. The methods for assessing accuracy of quantitative diagnostic tests are not routinely used by the scientific community. OBJECTIVE AND METHODS: To review the advantages and disadvantages of methods that could be used for that purpose. Using real data examples we review seven possible methods. RESULTS AND CONCLUSIONS: Simple linear regression testing the presence of a significant correlation between the new test data (x-axis data) and the control test data (y-axis data) is not accurate for testing the validity of a novel quantitative diagnostic test. Accurate methods using linear regression include the following. First, from y = a + b x, test the hypothesis that b is statistically significantly larger than zero, than test the hypothesis that b = 1.000 and a = 0.000. Second, if "the b = 1.000 and a = 0.000 hypothesis" cannot be confirmed, then use as criterion for validation a squared correlation-coefficient r2 or intraclass correlation of > 95%, or a relative residual variance of < 5%. If the new test is validated this way, then the predicted control-test-values are calculated from the equation y = a + bx. The above three methods assume uncertainty of the new test data, but not of the control test data. Deming regression, Passing-Bablok regression, paired Student's t-tests, and Altman-Bland plots assume uncertainty of both the new test and the control test. This is rarely a condition for validation, and carries the risk of unneeded loss of sensitivity of testing. However, if the control test is not the gold standard test and it is decided to account the uncertainty of the control test, then Passing-Bablok regression is the only method that adjusts for non-normal data as frequently observed in practice.

Lifestyle interventions in the management of hypertension: a survey based on the opinion of 105 practitioners.

BACKGROUND: Lifestyle interventions in the management of hypertension were beneficial in published studies. OBJECTIVE: To evaluate (1) which lifestyle recommendations are given by physicians and to what extent the possibility of drug-induced hypertension is addressed; (2) to study the characteristics of the physicians who more often perform lifestyle interventions. METHODS: General practitioners in the area of Dordrecht were asked whether or not they included lifestyle advice in the management of their patients' hypertension. RESULTS: Of the 176 physicians invited, 105 consented to take part. Measures to reduce body weight, stopping smoking, and physical exercise advice were given by 94, 92, and 92% of the physicians, respectively. Advice on psychological relaxation and reducing liquorice (Dutch: drop) intake was only given by 23 and 32%. Rural physicians were more active: they more often recommended quitting smoking (p<0.02), reducing weight (p<0.02), and participating in sporting activities (p<0.02). And so were older physicians: they more often recommended starting low-calorie diets (p<0.05), stopping liquorice consumption (p<0.04) and emphasised drug compliance (p<0.02). Increased blood pressure as a side effect of concomitant medications, other than nonsteroidal anti-inflammatory drugs and oral contraceptives, was virtually never addressed. CONCLUSIONS: (1) Advice to reduce body weight, stop smoking, and increase physical exercise are the only lifestyle recommendations routinely given, (2) rural physicians and older physicians were more active in giving non-drug treatments, (3) increased blood pressure as a side effect of medications was virtually never addressed. (Neth Heart J 2009;17:9-12.).

Random effects models in clinical research.

BACKGROUND: In clinical trials a fixed effects research model assumes that the patients selected for a specific treatment have the same true quantitative effect and that the differences observed are residual error. If, however, we have reasons to believe that certain patients respond differently from others, then the spread in the data is caused not only by the residual error but also by between-patient differences. The latter situation requires a random effects model. OBJECTIVE: To explain random effects models in analysis of variance and to give examples of studies qualifying for them. RESULTS: If in a particular study the data are believed to be different from one assessing doctor to the other, and if we have no prior theory that 1 or 2 assessing doctors produced the highest scores, but rather expect there may be heterogeneity in the population of doctors at large, then a random effects model will be appropriate. For that purpose between-doctor variability is compared to within-doctor variability. If the data of 2 separate studies of the same new treatment are analyzed simultaneously, it will be safe to consider an interaction effect between the study number and treatment efficacy. If the interaction is significant, a random effects model with the study number as random variable, will be adequate. For that purpose the treatment effect is tested against the interaction effect. In a multicenter study the data are at risk of interaction between centers and treatment efficacy. If this interaction is significant, a random effects model with the health center as random variable, will be adequate. The treatment effect is tested not against residual but against the interaction. If in a crossover study a treatment difference is not observed, this may be due to random subgroup effects. A post-hoc random effects model, with patients effect as random variable, testing the treatment effect against treatments x patients interaction, will be appropriate. DISCUSSION: Random effects research models enable the assessment of an entire sample of data for subgroup differences without need to split the data into subgroups. Clinical investigators, in general, are hardly aware of this possibility and, therefore, wrongly assess random effects as fixed effects leading to a biased interpretation of the data.

The effect of physical, social and psychological factors on drug compliance in patients with mild hypertension.

BACKGROUND: In patients with hypertension noncompliance with drug treatment is between 15 to 54%, and has been recognised as a relevant contributor to the burden of cardiovascular morbidity. Up to 92% of patients experience unpleasant symptoms with their condition and, particularly in these patients, the symptoms experienced may enhance compliance. OBJECTIVE: To simultaneously assess the effects of physical, social and psychological factors on noncompliance. METHODS: Patients with mild hypertension despite drug treatment, from the departments of cardiology and internal medicine, were requested to answer a self-administered questionnaire addressing the presence of physical symptoms as well as psychosocial factors. The questionnaire was based on previously used test batteries and consisted of two lists of physical complaints and four lists addressing the four domains of planned behaviour regarding medical non-adherence according to Baron and Byrne. These domains mainly assess psychosocial factors. Each list consisted of three or more items and each item was scored on fiveto seven-point scales. Mean scores were used for assessment. The lists were also separately assessed for internal consistency and reliability using Cronbach's alphas. One-way analysis of variance and multivariate analysis of variance (MANOVA) with compliance as outcome variable and the physical, social and psychological variables as indicator variables were used for data analysis. MANOVA was adjusted for multiple testing. RESULTS: Many patients experienced physical symptoms due to hypertension, such as tiredness (31%), hot flushes (28%), headache (24%), reduced daily life energy (23%), palpitations (22%), with 95% confidence intervals between 16 to 38%. Scores for physical symptoms and social factors did not differ between self-reported adherers (n=165) and nonadherers (n=11). However, the score for psychological factors was significantly larger in the adherers than in the non-adherers, 5.05 versus 3.06, p<0.018. The MANOVA showed a significant overall difference between the adherers and non-adherers in the data at p<0.012, which was mainly due to the score for psychological factors. Conclusion. The effect of physical symptoms on non-compliance in mildly hypertensive patients is negligible. So is the effect of social factors. Psychological factors such as lacking a sense of guilt, regret and shame are major determinants of non-compliance. Physicians may play an educational role in improving their patients' compliance by addressing these determinants. We should add that the conclusions should be made with reservations, given the small number of non-adherers in our sample. (Neth Heart J 2008;16:197-200.).

Cardiovascular drug trials: how to examine interaction, and why so.

BACKGROUND: In practice the benefit of cardiovascular medicines is less consistent than it is in clinical trials. This is due to multiple uncontrolled factors that co-determine the efficacy of the new treatment. In statistical terms, they interact with the new treatment. Interaction effects are rarely assessed in cardiovascular trials. OBJECTIVE: To review (1) important factors that may interact with the treatment efficacy, (2) how to examine such factors, and (3) why so. RESULTS: Important factors include (a) possible risk factors such as specific patient characteristics, and concomitant medications, and (b) study-specific aspects such as heterogeneities of investigators, health centres, and individual patients including patient compliance. Such factors can be assessed by comparing subgroups. A common but incorrect approach is the comparison of the significances of difference between treatment modalities in either subgroup. Instead, a direct comparison of effect sizes relative to the standard errors is adequate. As an alternative, regression modelling is adequate and convenient. Results of interaction assessments are post-hoc and, therefore, of an exploratory and unconfirmed nature. So, why should they be performed? In cardiovascular research the effects of patient characteristics and drug-drug interactions on drug efficacies are numerous. It is valuable to account at least post-hoc for such mechanisms. Second, current cardiovascular trials involve heterogeneous health centres, investigators, and patient groups. Accounting for these heterogeneities can be helpful to better predict individual responses in future patients. CONCLUSION: Cardiovascular trials enrolling patient groups at risk for heterogeneity should include at least a post-hoc assessment for interaction. Correct and incorrect methods for that purpose are described. Interaction assessments are helpful to better predict the efficacy/safety of new cardiovascular medicines in the future treatment of subgroups of patients. (Neth Heart J 2007;15:61-6.).

Nebivolol: a review of its clinical and pharmacological characteristics.

Nebivolol is a cardioselective lipophilic beta-blocker devoid of intrinsic sympathomimetic and membrane-stabilizing actions. The pharmacological profile differs from that of conventional cardioselective beta3-blockers in that it displays nitric oxide- (NO) mediated vasodilator activity. The net hemodynamic effect of nebivolol is the result of a balance between the depressant effects of beta3-blockade and an action that tends to maintain cardiac output, presumably connected with its afterload reducing vasodilator effect. Recent studies suggest that nebivolol may also restore endothelial dysfunction. Long-term follow-up studies indicate that the compound is efficacious and safe both in patients with mild hypertension and those with stable angina. An interesting effect of chronic nebivolol therapy in elderly patients with mild hypertension is the reversal of a depressor effect into a pressor effect on standing. This action indicates that nebivolol has advantages over other antihypertensive drugs and that it may protect elderly hypertensive patients from orthostatic complaints. The observation that nebivolol improves exercise capacity in non-claudicant hypertensives is also of clinical interest. Nebivolol resembles serotonin reuptake inhibitors in that it is metabolized by CYP450 2D6 and, therefore, concomitant treatment with serotonin uptake inhibitors may lead to overdosing. Nebivolol compared to placebo does not significantly reduce the mortality risk in elderly subjects. The effects of biological age and comorbidities may be responsible for this finding. In conclusion, clinical studies suggest that nebivolol is effective and safe in patients with hypertension, angina pectoris and heart failure. The beneficial effects on endothelial function, autonomic control and exercise capacity are of considerable clinical interest.

Nationwide efficacy-safety study of nebivolol in mildly hypertensive patients.

Nebivolol has been adequately tested in clinical efficacy trials of patients with mild hypertension. Clinical efficacy trials or their meta-analyses did not accurately predict the outcome of subsequent large studies. The primary objective was to assess the efficacy/safety of nebivolol 5-10 mg daily in a nationwide study of patients with mild hypertension. Secondary objectives were (1) to compare efficacy/safety as monotherapy versus add-on therapy and (2) to assess the effect of nebivolol on ISH. This was an open-label, 6-week follow-up study of 6,356 patients with mild hypertension or ISH, as defined by the 1999 World Health Organization guidelines, recruited from 2,700 facilities. Previous monotherapies were continued except for beta-blockers. Results are reported as means+/-SDs. Intention-to-treat analysis is given. A total of 5,740 patients completed the study; of the withdrawals, 90% were lost for follow-up or were noncompliant, 38% were untreated before, 23% had beta-blockers. In the accumulated data, mean systolic and diastolic blood pressures fell by 24+/-14 and 13+/-9 mm Hg (both P<0.001). The differences between the blood pressure-reducing effects of nebivolol monotherapy and add-on therapy were not statistically significant: 28+/-16 and 22+/-14 mm Hg for systolic and 15+/-11 and 11+/-8 mm Hg for diastolic blood pressures. Adverse events were limited to 0.5% of the patients, no serious adverse events were observed. In the ISH patients, diastolic blood pressure fell by 4+/-6 mm Hg compared with 15+/-10 mm Hg in the no-ISH patients (P<0.01). Efficacy-safety effects of nebivolol in patients with mild hypertension can be generalized in a nationwide assessment. The efficacy of nebivolol as monotherapy and as the efficacy as add-on therapy are very similar. Nebivolol is highly efficacious in patients with ISH.

Chronic nitrate therapy in patients with angina with comorbidity.

In a retrospective study from the Dutch Mononitrate Quality of Life (DUMQOL) Study Group, the authors found that patients with angina with concomitant diabetes or hypercholesterolemia derived more benefit from changing over to a once-daily nitrate treatment regimen than did patients without angina. The aim of this study was to assess this issue prospectively. In an open-label study, patients with stable angina pectoris from facilities in Germany, Portugal, and me Czech Republic were treated for 3 months with multiple daily doses and subsequently for 3 more months with once-daily isosorbide mononitrate/dinitrate. After the first and second 3-month periods, they were assessed by a validated QOL battery including domains for mobility, side effects, life satisfaction, anginal pain, and psychological distress. In the 1045 patients who participated in the study, the mean summary domain scores varied from 5 to 16 points and score improvements from 1.6 to 4.3 points. In the patients without concomitant hypertension and smokers, domain scores improved less than they did in the patients without, with differences in domain score improvements up to 1.0 points (P<0.001), which is substantial considering the range of improvement was between 1.6 and 4.3 points. In the patients with diabetes mellitus or hypercholesterolemia, a reverse pattern was observed with differences in domain score improvements up to 0.4 points (P<0.05). Patients with angina with diabetes or hypercholesterolemia derived more benefit from an asymmetric regimen of isosorbide mononitrate/dinitrate than did patients without. Patients with angina with hypertension and smokers benefited less. Differences in endothelial function may be involved.

Quality of life of patients on the waiting list for coronary angiography.

BACKGROUND: Providing adequate medical information and ensuring that patients do not identify with fellow-sufferers who are doing worse are significant contributors to a better quality of life (QOL) in cardiac patients. In addition, in these patients gender and the level of psychic tension are significant predictors of QOL. We do not know (1) whether we can improve QOL by increasing patients' ability to cope with the unpleasant aspects of the underlying condition, (2) whether gender and level of psychic tension interact or act independently. OBJECTIVE: To assess both questions. METHODS: Thirty-eight patients on the waiting list for coronary angiography were assessed with validated test batteries. To increase the patients' ability to cope, they were randomly assigned to read either (1) the comments of a patient who had previously been treated successfully or (2) general information. The former information, unlike the latter, was assumed to improve coping ability and, thus, provide better QOL. Homogeneity of the patient group was estimated by Cronbach's alphas. For analysis, linear regression and general factorial analyses of variance were applied. RESULTS: The group was psychologically homogeneous as indicated by Cronbach's alphas which were generally over 75%. There was a significant or close to significant association between the use of coping information and a better mobility and social performance QOL (p<0.05 and p<0.06). High levels of psychic tension were associated with low self-perceived QOL and low psychological scores (both p<0.02). Female gender was associated with lower mobility, lower psychological scores and lower overall QOL (p<0.05, p<0.02 and p<0.05). A significant or close to significant interaction was observed between gender and psychic tension as combined determinants of self-perceived QOL, mobility index, and overall QOL index (p<0.03, p<0.09, and p<0.05). Separate assessments of these determinants showed that female gender was the strongest determinant of a low QOL. CONCLUSION: In patients on the waiting list for coronary angiography, an increased ability to cope with the unpleasant aspects of a possible underlying heart condition improves QOL. Female gender and a high level of psychic tension place patients at risk for a low QOL. It is to be hoped that this paper will raise physicians' awareness of these psychological mechanisms and that they will be given adequate attention in the future, particularly in female patients.

Variability in clinical data is often more useful than the mean: illustration of concept and simple methods of assessment.

BACKGROUND: Clinical investigators, although they are generally familiar with testing differences between averages, have difficulty testing differences between variabilities. OBJECTIVE: To give examples of situations where variability is more relevant than averages and to describe simple methods for testing such data. RESULTS: Examples include: (1) testing drugs with small therapeutic indices, (2) testing variability in drug response, (3) assessing pill diameters or pill weights, (4) comparing patient groups for variability in patient characteristics, (5) assessing the variability in duration of clinical treatment, (6) finding the best method for patient assessment. Various fields of research, particularly in clinical pharmacology, make use of test procedures that implicitly, address the variability in the data. Tests specially designed for testing variability in data include the chi2-test for one sample, the F-test for 2 samples and Bartlett's or Levene's test for 3 or more samples. Additional methods include (1) the comparison of confidence intervals, and (2) testing confidence intervals against prior defined intervals of therapeutic tolerance or equivalence. Many of these tests are available in Excel and other statistical software programs and one such program is described. CONCLUSIONS: In the analysis of clinical data the variability in the data is often more important than averages. Eight simple methods for assessment variability are described to illustrate the value and importance of putting more emphasis on and this parameter.

Problems in regression modeling of randomized clinical trials.

BACKGROUND: Data modeling can be applied to improving the precision of clinical studies and multiple regression modeling is increasingly used for this purpose. OBJECTIVE: To assess the uncertainties and risks of misinterpretations commonly encountered in regression analyses and rarely communicated in research papers. RESULTS: Regression analyses add uncertainties to the data in the form of subjective judgments and uncertainty about the appropriate transformation of the data. Additional flaws include; the assumption that baseline characteristics are independent of treatment efficacies; the loss of sensitivity of testing if the models do not fit the data well enough; the risk that clinical phenomena like toxicity effects and complete remissions go unobserved; the risk of clinically unrealistic results if multiple variables are included. CONCLUSION: Regression analyses, although a very good tool for exploratory research, are not sufficiently reliable for randomized clinical trials.

Genetic polymorphisms and endothelial dysfunction in patients with essential hypertension: a cross-sectional case-control study.

BACKGROUND: Both in animal models and humans an association between endothelial constitutive nitric oxide synthase (ecNOS) gene polymorphism and the development of hypertension has been found. However, the relation between ecNOS polymorphism and endothelial function in patients with hypertension has not been systematically studied. Genes of the renin-angiotensin system include the angiotensin-converting enzyme (ACE) gene, and the angiotensin II type 1 receptor (ATIR) gene, and have been associated with essential hypertension. However, no consistent data are available about the relation between polymorphisms of these genes and the presence of endothelial dysfunction in such patients. OBJECTIVES: To assess the presence of genetic polymorphisms and of endothelial dysfunction in patients with essential hypertension. To determine the effects of gene polymorphisms on endothelial dysfunction in these subjects. METHODS: In 129 patients with essential hypertension and the same number of age-matched controls polymorphisms of the ecNOS gene, ACE gene, and AT1R gene were analysed by polymerase chain reactions. Endothelial function was assessed by maximal endothelial dependent vasodilation in response to reactive hyperaemia using high resolution ultrasound examinations of the brachial arteries. To assess correlation between genetic markers, endothelial function, and the presence of hypertension both univariate and multivariate analyses were used including Pearson's and Spearman's correlation coefficients, and multiple logistic regressions. RESULTS: The size of endothelium-dependent vasodilation between patients and controls differed by 16% (p<0.02). However, the presence of genetic polymorphisms of the ecNOS, ACE, and AT1R genes did not significantly differ between patients and controls. Neither were there any statistically significant differences in endothelial function between various genotypes of the three genes. This was so for both the patients and the controls, although in all of these comparisons the controls overall displayed a slightly better endothelial function than the patients did. Multiple regression analysis with endothelial dysfunction as dependent and the presence of gene polymorphisms as independent variables did not reveal any significant correlation either. CONCLUSION: A significant relation between endothelial dysfunction and essential hypertension was demonstrated. However, no relations between genetic markers and the presence of essential hypertension or between endothelial dysfunction and genetic markers were established. The failure of our study to demonstrate the latter may be due to confounders. Also, other genes may be more important in the pathogenesis of endothelial dysfunction and essential hypertension. The current study underscores that endothelial dysfunction and hypertension are not simple genetic disorders, and that they are, essentially, multicausal.