Secondary left ventricular ejection fraction response to beta blocker therapy in heart failure patients

Chronic β-blocker treatment improves survival and left ventricular ejection fraction (LVEF) in patients with systolic heart failure (HF). Data on whether the improvement in LVEF after β-blocker therapy is sustained for a long term or whether there is a loss in LVEF after an initial gain is not known. Our study sought to determine the prevalence and prognostic role of secondary decline in LVEF in chronic systolic HF patients on β-blocker therapy and characterize these patients. Retrospective chart review of HF hospitalizations fulfilling Framingham Criteria was performed at the MEDVAMC between April 2000 and June 2006. Follow up vital status and recurrent hospitalizations were ascertained until May 2010. Three groups of patients were identified based on LVEF response to beta blockers; group A with secondary decline in LVEF following an initial increase, group B with progressive increase in LVEF and group C with progressive decline in LVEF. Covariate adjusted Cox proportional hazard models were used to examine differences in heart failure re-hospitalizations and all cause mortality between the groups. Twenty five percent (n=27) of patients had a secondary decline in LVEF following an initial gain. The baseline, peak and final LVEF in this group were 27.6±12%, 40.1±14% and 27.4±13% respectively. The mean nadir LVEF after decline was 27.4±13% and this decline occurred at a mean interval of 2.8±1.9 years from the day of beta blocker initiation. These patients were older, more likely to be whites, had advanced heart failure (NYHA class III/IV) more due to a non ischemic etiology compared to groups B & C. They were also more likely to be treated with metoprolol (p=0.03) compared to the other two groups. No significant differences were observed in combined risk of all cause mortality and HF re-hospitalization [hazard ratio 0.80, 95% CI 0.47 to 1.38, p=0.42]. No significant difference was observed in survival estimates between the groups. In conclusion, a late decline in LVEF does occur in a significant proportion of heart failure patients treated with beta blockers, more so in patients treated with metoprolol.^

Effect of smoking on the association between periodontitis and incidence of coronary heart disease: The Atherosclerosis Risk in Communities Study

Multiple studies have shown an association between periodontitis and coronary heart disease due to the chronic inflammatory nature of periodontitis. Also, studies have indicated similar risk factors and patho-physiologic mechanisms for periodontitis and CHD. Among these factors, smoking has been the most discussed common risk factor and some studies suggested the periodontitis - CHD association to be largely a result of confounding due to smoking or inadequate adjustment for it. We conducted a secondary data analysis of the Dental ARIC Study, an ancillary study to the ARIC Study, to evaluate the effect of smoking on the periodontitis - CHD association using three periodontitis classifications namely, BGI, AAP-CDC, and Dental-ARIC classification (Beck et al 2001). We also compared these results with edentulous ARIC participants. Using Cox proportional hazard models, we found that the individuals with the most severe form of periodontitis in each of the three classifications (BGI: HR = 1.56, 95%CI: 1.15 – 2.13; AAP-CDC: HR = 1.42, 95%CI: 1.13 – 1.79; and Dental-ARIC: HR = 1.49, 95%CI: 1.22 – 1.83) were at a significantly higher risk of incident CHD in the unadjusted models; whereas only BGI-P3 showed statistically significant increased risk in the smoking adjusted models (HR = 1.43, 95%CI: 1.04 – 1.96). However none of the categories in any of the classifications showed significant association when a list of traditional CHD risk factors was introduced into the models. On the other hand, edentulous participants showed significant results when compared to the dentate ARIC participants in the crude (HR = 1.56, 95%CI: 1.34 – 1.82); smoking adjusted (HR = 1.39, 95%CI: 1.18 – 1.64) age, race and sex adjusted (HR = 1.52, 95%CI: 1.30 – 1.77); and ARIC traditional risk factors (except smoking) adjusted (HR = 1.27, 95%CI: 1.02 – 1.57) models. Also, the risk remained significantly higher even when smoking was introduced in the age, sex and race adjusted model (HR = 1.38, 95%CI: 1.17 – 1.63). Smoking did not reduce the hazard ratio by more than 8% when it was included in any of the Cox models. ^ This is the first study to include the three most recent case definitions of periodontitis simultaneously while looking at its association with incident coronary heart disease. We found smoking to be partially confounding the periodontitis and coronary heart disease association and edentulism to be significantly associated with incident CHD even after adjusting for smoking and the ARIC traditional risk factors. The difference in the three periodontitis classifications was not found to be statistical significant when they were tested for equality of the area under their ROC curves but this should not be confused with their clinical significance.^

Subjective well -being as predictor of mortality, heart disease, and obesity: Prospective evidence from the Alameda County Study

Based on the World Health Organization's (1965) definition of health, understanding of health requires understanding of positive psychological states. Subjective Well-being (SWB) is a major indicator of positive psychological states. Up to date, most studies of SWB have been focused on its distributions and determinants. However, study of its consequences, especially health consequences, is lacking. This dissertation research examined Subjective Well-being, as operationally defined by constructs drawn from the framework of Positive Psychology, and its sub-scores (Positive Feelings and Negative Feelings) as predictors of three major health outcomes—mortality, heart disease, and obesity. The research used prospective data from the Alameda County Study over 29 years (1965–1994), based on a stratified, randomized, representative sample of the general public in Alameda County, California (Baseline N = 6928). ^ Multivariate analyses (Survival analyses using sequential Cox Proportional Hazard models in the cases of mortality and heart disease, and sequential Logistic Regression analyses in the case of obesity) were performed as the main methods to evaluate the associations of the predictors and the health outcomes. The results revealed that SWB reduced risks of all-cause mortality, natural-cause mortality, and cardiovascular mortality. Positive feelings not only had an even stronger protective effect against all-cause, natural-cause and cardiovascular mortality, but also predicted decreased unnatural-cause mortality which includes deaths from suicide, homicide, accidents, mental disorders, drug dependency, as well as alcohol-related liver diseases. These effects were significant even after adjusted for age, gender, education, and various physical health measures, and, in the case of cardiovascular mortality, obesity and health practices (alcohol consumption, smoking, and physical activities). However, these two positive psychological indicators, SWB and positive feelings, did not predict obesity. And negative feelings had no significant effect on any of the health outcomes evaluated, i.e., all-cause mortality, natural- and unnatural-cause mortality, cardiovascular mortality, or obesity, after covariates were controlled. These findings were discussed (1) in comparison with relevant existing studies, (2) in terms of their implications in health research and promotion, (3) in terms of the independence of positive and negative feelings, and (4) from a Positive Psychology perspective and its significance in Public Health research and practice. ^

Effects of informative censoring on the hazard function: Application to the proportional hazards regression model

The standard analyses of survival data involve the assumption that survival and censoring are independent. When censoring and survival are related, the phenomenon is known as informative censoring. This paper examines the effects of an informative censoring assumption on the hazard function and the estimated hazard ratio provided by the Cox model.^ The limiting factor in all analyses of informative censoring is the problem of non-identifiability. Non-identifiability implies that it is impossible to distinguish a situation in which censoring and death are independent from one in which there is dependence. However, it is possible that informative censoring occurs. Examination of the literature indicates how others have approached the problem and covers the relevant theoretical background.^ Three models are examined in detail. The first model uses conditionally independent marginal hazards to obtain the unconditional survival function and hazards. The second model is based on the Gumbel Type A method for combining independent marginal distributions into bivariate distributions using a dependency parameter. Finally, a formulation based on a compartmental model is presented and its results described. For the latter two approaches, the resulting hazard is used in the Cox model in a simulation study.^ The unconditional survival distribution formed from the first model involves dependency, but the crude hazard resulting from this unconditional distribution is identical to the marginal hazard, and inferences based on the hazard are valid. The hazard ratios formed from two distributions following the Gumbel Type A model are biased by a factor dependent on the amount of censoring in the two populations and the strength of the dependency of death and censoring in the two populations. The Cox model estimates this biased hazard ratio. In general, the hazard resulting from the compartmental model is not constant, even if the individual marginal hazards are constant, unless censoring is non-informative. The hazard ratio tends to a specific limit.^ Methods of evaluating situations in which informative censoring is present are described, and the relative utility of the three models examined is discussed. ^