Haitham M. Ahmed

Effects of Physical Activity on Cardiovascular Disease

Much attention has been directed toward lifestyle modifications as effective means of reducing cardiovascular disease risk. In particular, physical activity has been heavily studied because of its well-known effects on metabolic syndrome, insulin sensitivity, cardiovascular disease risk, and all-cause mortality. However, data regarding the effects of exercise on various stages of the atherosclerosis pathway remain conflicting. The investigators review previously published reports for recent observational and interventional trials investigating the effects of physical activity on markers of (or causal factors for) atherosclerotic burden and vascular disease, including serum lipoproteins, systemic inflammation, thrombosis, coronary artery calcium, and carotid intima-media thickness. In conclusion, the data show a correlation between physical activity and triglyceride reduction, apolipoprotein B reduction, high-density lipoprotein increase, change in low-density lipoprotein particle size, increase in tissue plasminogen activator activity, and decrease in coronary artery calcium. Further research is needed to elucidate the effect of physical activity on inflammatory markers and intima-media thickness.

Low-Risk Lifestyle, Coronary Calcium, Cardiovascular Events, and Mortality: Results From MESA

Unhealthy lifestyle habits are a major contributor to coronary artery disease. The purpose of the present study was to investigate the associations of smoking, weight maintenance, physical activity, and diet with coronary calcium, cardiovascular events, and mortality. US participants who were 44-84 years of age (n = 6,229) were followed in the Multi-Ethnic Study of Atherosclerosis from 2000 to 2010. A lifestyle score ranging from 0 to 4 was created using diet, exercise, body mass index, and smoking status. Coronary calcium was measured at baseline and a mean of 3.1 (standard deviation, 1.3) years later to assess calcium progression. Participants who experienced coronary events or died were followed for a median of 7.6 (standard deviation, 1.5) years. Participants with lifestyle scores of 1, 2, 3, and 4 were found to have mean adjusted annual calcium progressions that were 3.5 (95% confidence interval (CI): 0.0, 7.0), 4.2 (95% CI: 0.6, 7.9), 6.8 (95% CI: 2.0, 11.5), and 11.1 (95% CI: 2.2, 20.1) points per year slower, respectively, relative to the reference group (P = 0.003). Unadjusted hazard ratios for death by lifestyle score were as follows: for a score of 1, the hazard ratio was 0.79 (95% CI: 0.61, 1.03); for a score of 2, the hazard ratio was 0.61 (95% CI: 0.46, 0.81); for a score of 3, the hazard ratio was 0.49 (95% CI: 0.32, 0.75); and for a score of 4, the hazard ratio was 0.19 (95% CI: 0.05, 0.75) (P < 0.001 by log-rank test). In conclusion, a combination of regular exercise, healthy diet, smoking avoidance, and weight maintenance was associated with lower coronary calcium incidence, slower calcium progression, and lower all-cause mortality over 7.6 years.

Very large database of lipids: Rationale and design

Blood lipids have major cardiovascular and public health implications. Lipid‐lowering drugs are prescribed based in part on categorization of patients into normal or abnormal lipid metabolism, yet relatively little emphasis has been placed on: (1) the accuracy of current lipid measures used in clinical practice, (2) the reliability of current categorizations of dyslipidemia states, and (3) the relationship of advanced lipid characterization to other cardiovascular disease biomarkers. To these ends, we developed the Very Large Database of Lipids (NCT01698489), an ongoing database protocol that harnesses deidentified data from the daily operations of a commercial lipid laboratory. The database includes individuals who were referred for clinical purposes for a Vertical Auto Profile (Atherotech Inc., Birmingham, AL), which directly measures cholesterol concentrations of low‐density lipoprotein, very low‐density lipoprotein, intermediate‐density lipoprotein, high‐density lipoprotein, their subclasses, and lipoprotein(a). Individual Very Large Database of Lipids studies, ranging from studies of measurement accuracy, to dyslipidemia categorization, to biomarker associations, to characterization of rare lipid disorders, are investigator‐initiated and utilize peer‐reviewed statistical analysis plans to address a priori hypotheses/aims. In the first database harvest (Very Large Database of Lipids 1.0) from 2009 to 2011, there were 1 340 614 adult and 10 294 pediatric patients; the adult sample had a median age of 59 years (interquartile range, 49–70 years) with even representation by sex. Lipid distributions closely matched those from the population‐representative National Health and Nutrition Examination Survey. The second harvest of the database (Very Large Database of Lipids 2.0) is underway. Overall, the Very Large Database of Lipids database provides an opportunity for collaboration and new knowledge generation through careful examination of granular lipid data on a large scale.

Relationship Between Sedentary Behavior and Cardiovascular Risk.

The majority of adults do not meet current guideline recommendations for moderate to vigorous physical activity. Recent research has linked a high amount of sedentary behavior with an increased risk of obesity, diabetes, the metabolic syndrome, cardiovascular disease, and death. This correlation with sedentary behavior even extends to individuals who meet recommended physical activity goals during the remainder of their day, which implies that sedentary behavior may represent a distinct cardiovascular risk factor that is independent of the overall amount of physical activity. During the past several years, there has been significant interest in identifying and understanding the mechanisms through which sedentary behavior affects cardiovascular health. In this review, we critically evaluate the literature pertaining to sedentary behavior and cardiovascular risk with an emphasis on studies published over the past year, and we suggest possible interventions that may help reduce sedentary behavior time.

Joint effects of objectively-measured sedentary time and physical activity on all-cause mortality.

OBJECTIVE Examine the joint effects of objectively-measured sedentary time and moderate-to-vigorous physical activity (MVPA) on all-cause mortality. METHODS The present study included data from the 2003-2006 National Health & Nutrition Examination Survey, with mortality follow-up data (via National Death Index) through 2011 (N=5575U.S. adults). Sedentary time (activity counts/min between 0 and 99) and MVPA (activity counts/min ≥2020) were objectively measured using the ActiGraph 7164 accelerometer. RESULTS The median age of the participants was 50yrs; proportion of men was 50.2%; proportion of whites was 53.8%, 18.7% for blacks; median follow-up was 81months; and 511 deaths occurred over the follow-up period. After adjusting for age, gender, race-ethnicity, cotinine, weight status, poverty level, C-reactive protein and comorbid illness (summed score of 0-8 chronic diseases), and for a 1min increase in MVPA and sedentary time, both MVPA (HRadjusted=0.98; 95% CI: 0.96-0.99; P=0.04) and sedentary time (HRadjusted=1.001; 95% CI: 1.0003-1.002; P=0.008) were independently associated with all-cause mortality. Further, MVPA was associated with all-cause mortality among those with greater (above median) sedentary time (HRadjusted=0.95; 95% CI: 0.93-0.97; P<.001). Sedentary time was not associated with all-cause mortality among those engaging in above median levels of MVPA (HRadjusted=0.998; 95% CI: 0.996-1.001; P=.32), but sedentary time was associated with increased mortality risk among those below median levels of MVPA (HR=1.002; 95% CI: 1.001-1.003; P<0.001). CONCLUSIONS Sedentary time and MVPA are independently associated with all-cause mortality. Above median sedentary time levels did not negate the beneficial effects of MVPA on all-cause mortality risk.

Ratio of Dense to Buoyant LDL Subclass is Associated with LDL Density Phenotype (VLDL-5)

Background: Dense LDL phenotypes are associated with increased atherogenicity, and are commonly evaluated for the purposes of atherosclerosis research and cardiovascular risk discrimination. Objective: To examine the ability of LDL subclasses, expressed as a ratio of dense-to-buoyant subclass, to predict LDL density phenotype. Methods: LDL subclasses and density phenotypes were measured with vertical auto profile ultracentrifugation in 1,339,898 consecutive lipid profiles between 2009 and 2011 from a clinical sample of US adults. Logarithmic LDL density ratio (LLDR) was calculated as ratio of dense-to-buoyant LDL subclasses, ln((LDL3-C + LDL4-C) / (LDL1-C +LDL2-C)); normally distributed after log-transformation. LLDR was compared to density phenotype using ROC C- statistic with optimum sensitivity and specificity cutpoints determined. Results: There was a strong, highly significant, monotonic increase in LLDR across progressively higher density phenotypes (p 0.905, sensitivity 81%, specificity 86%. There was also a positive correlation between LLDR and LDL Max Time (R 2 =0.802). Conclusion: LLDR is a convenient, easily calculated, and continuous variable that is strongly associated with LDL density phenotype and LDL Max Time. Further research is needed to investigate the relationship between lipoprotein density and size, and whether LLDR provides more cardiovascular risk discrimination than LDL density phenotype.

Pasteurella multocida infection in solid organ transplantation

We present a case of fulminant Pasteurella multocida sepsis in a 66-year-old man who had undergone a renal transplant. Our patient lived with two dogs and a cat with which he was very close. We propose that his bacteraemia might have resulted from direct inoculation of P multocida via his cat licking the venous stasis ulcers on his legs. The patients clinical course was complicated by cardiopulmonary failure and he ultimately succumbed to his infection. P multocida is a rare cause of infections in immunocompromised hosts, epidemiologically linked to exposure to cats, dogs, and other animals. This case of P multocida shows the importance of considering this organism in immunocompromised hosts presenting with severe infections, especially if their history shows exposure to domesticated or wild animals known to be potential carriers of this disease. In this Grand Round, we review the clinical features, epidemiology, treatment, and prognosis of P multocida infections with a focus on these features in patients who are immunosuppressed.

Use of Sex-Specific Clinical and Exercise Risk Scores to Identify Patients at Increased Risk for All-Cause Mortality

Importance Risk assessment tools for exercise treadmill testing may have limited external validity. Cardiovascular mortality has decreased in recent decades, and women have been underrepresented in prior cohorts. Objectives To determine whether exercise and clinical variables are associated with differential mortality outcomes in men and women and to assess whether sex-specific risk scores better estimate all-cause mortality. Design, Setting, and Participants This retrospective cohort study included 59 877 patients seen at the Cleveland Clinic Foundation (CCF cohort) from January 1, 2000, through December 31, 2010, and 49 278 patients seen at the Henry Ford Hospital (FIT cohort) from January 1, 1991, through December 31, 2009. All patients were 18 years or older and underwent exercise treadmill testing. Data were analyzed from January 1, 2000, to October 27, 2011, in the CCF cohort and from January 1, 1991, to April 1, 2013, in the FIT cohort. Main Outcomes and Measurements The CCF cohort was divided randomly into derivation and validation samples, and separate risk scores were developed for men and women. Net reclassification, C statistics, and integrated discrimination improvement were used to compare the sex-specific risk scores with other tools that have all-cause mortality as the outcome. Discrimination and calibration were also evaluated with these sex-specific risk scores in the FIT cohort. Results The CCF cohort included 59 877 patients (59.4% men; 40.5% women) with a median (interquartile range [IQR]) age of 54 (45-63) years and 2521 deaths (4.2%) during a median follow-up of 7 (IQR, 4.1-9.6) years. The FIT cohort included 49 278 patients (52.5% men; 47.4% women) with a median (IQR) age of 54 (46-64) years and 6643 deaths (13.5%) during a median (IQR) follow-up of 10.2 (7-13.4) years. C statistics for the sex-specific risk scores in the CCF validation sample were higher (0.79 in women and 0.81 in men) than C statistics using other tools in women (0.70 for Duke Treadmill Score; 0.74 for Lauer nomogram) and men (0.72 for Duke Treadmill Score; 0.75 for Lauer nomogram). Net reclassification and integrated discrimination improvement were superior with the sex-specific risk scores, mostly owing to correct reclassification of events. The sex-specific risk scores in the FIT cohort demonstrated similar discrimination (C statistic, 0.78 for women and 0.79 for men), and calibration was reasonable. Conclusions and Relevance Sex-specific risk scores better estimate mortality in patients undergoing exercise treadmill testing. In particular, these sex-specific risk scores help to identify patients at the highest residual risk in the present era.

Modifiable lifestyle risks, cardiovascular disease, and all-cause mortality.

This is a commentary on article Carlsson AC, Wandell PE, Gigante B, Leander K, Hellenius ML, de Faire U. Seven modifiable lifestyle factors predict reduced risk for ischemic cardiovascular disease and all-cause mortality regardless of body mass index: a cohort study. Int J Cardiol. 2013;168(2):946-52.

Using Machine Learning to Define the Association between Cardiorespiratory Fitness and All-Cause Mortality (from the Henry Ford Exercise Testing Project)

Previous studies have demonstrated that cardiorespiratory fitness is a strong marker of cardiovascular health. Machine learning (ML) can enhance the prediction of outcomes through classification techniques that classify the data into predetermined categories. The aim of the analysis is to compare the prediction of 10 years of all-cause mortality (ACM) using statistical logistic regression (LR) and ML approaches in a cohort of patients who underwent exercise stress testing. We included 34,212 patients (55% males, mean age 54 ± 13 years) free of coronary artery disease or heart failure who underwent exercise treadmill stress testing between 1991 and 2009 and had complete 10-year follow-up. The primary outcome of this analysis was ACM at 10 years. The probability of 10-years ACM was calculated using statistical LR and ML, and the accuracy of these methods was calculated and compared. A total of 3,921 patients died at 10 years. Using statistical LR, the sensitivity to predict ACM was 44.9% (95% confidence interval [CI] 43.3% to 46.5%), whereas the specificity was 93.4% (95% CI 93.1% to 93.7%). The sensitivity of ML to predict ACM was 87.4% (95% CI 86.3% to 88.4%), whereas the specificity was 97.2% (95% CI 97.0% to 97.4%). The ML approach was associated with improved model discrimination (area under the curve for ML [0.923 (95% CI 0.917 to 0.928)]) compared with statistical LR (0.836 [95% CI 0.829 to 0.846], p<0.0001). In conclusion, our analysis demonstrates that ML provides better accuracy and discrimination of the prediction of ACM among patients undergoing stress testing.