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Abstract Background Prior research reveals that processes and outcomes of cardiac care differ across sociodemographic strata. One potential contributing factor to such differences is the personality traits of individuals within these strata. We examined the association between risk-taking attitudes and cardiac patients' clinical and demographic characteristics, the likelihood of undergoing invasive cardiac procedures and survival. Methods We studied a large inception cohort of patients who underwent cardiac catheterization between July 1998 and December 2001. Detailed clinical and demographic data were collected at time of cardiac catheterization and through a mailed survey one year post-catheterization. The survey included three general risk attitude items from the Jackson Personality Inventory. Patients' (n = 6294) attitudes toward risk were categorized as risk-prone versus non-risk-prone and were assessed for associations with baseline clinical and demographic characteristics, treatment received (i.e., medical therapy, coronary artery bypass graft (CABG) surgery, percutaneous coronary intervention (PCI)), and survival (to December 2005). Results 2827 patients (45%) were categorized as risk-prone. Having risk-prone attitudes was associated with younger age (p < .001), male sex (p < .001), current smoking (p < .001) and higher household income (p < .001). Risk-prone patients were more likely to have CABG surgery in unadjusted (Odds Ratio [OR] = 1.21; 95% CI 1.08–1.36) and adjusted (OR = 1.18; 95% CI 1.02–1.36) models, but were no more likely to have PCI or any revascularization. Having risk-prone attitudes was associated with better survival in an unadjusted survival analysis (Hazard Ratio [HR] = 0.78 (95% CI 0.66–0.93), but not in a risk-adjusted analysis (HR = 0.92, 95% CI 0.77–1.10). Conclusion These exploratory findings suggest that patient attitudes toward risk taking may contribute to some of the documented differences in use of invasive cardiac procedures. An awareness of these associations could help healthcare providers as they counsel patients regarding cardiac care decisions.

Abstract Background We have previously described a method for dealing with missing data in a prospective cardiac registry initiative. The method involves merging registry data to corresponding ICD-9-CM administrative data to fill in missing data 'holes'. Here, we describe the process of translating our data merging solution to ICD-10, and then validating its performance. Methods A multi-step translation process was undertaken to produce an ICD-10 algorithm, and merging was then implemented to produce complete datasets for 1995–2001 based on the ICD-9-CM coding algorithm, and for 2002–2005 based on the ICD-10 algorithm. We used cardiac registry data for patients undergoing cardiac catheterization in fiscal years 1995–2005. The corresponding administrative data records were coded in ICD-9-CM for 1995–2001 and in ICD-10 for 2002–2005. The resulting datasets were then evaluated for their ability to predict death at one year. Results The prevalence of the individual clinical risk factors increased gradually across years. There was, however, no evidence of either an abrupt drop or rise in prevalence of any of the risk factors. The performance of the new data merging model was comparable to that of our previously reported methodology: c-statistic = 0.788 (95% CI 0.775, 0.802) for the ICD-10 model versus c-statistic = 0.784 (95% CI 0.780, 0.790) for the ICD-9-CM model. The two models also exhibited similar goodness-of-fit. Conclusion The ICD-10 implementation of our data merging method performs as well as the previously-validated ICD-9-CM method. Such methodological research is an essential prerequisite for research with administrative data now that most health systems are transitioning to ICD-10.

Abstract Background Although there have been substantial medical advances that improve the outcomes following cardiac ischemic events, gender differences in the treatment and course of recovery for patients with coronary artery disease (CAD) continue to exist. There is a general paucity of data comparing the health related quality of life (HRQOL) in men and women undergoing treatment for CAD. The purpose of this study was to compare HRQOL outcomes of men and women in Alberta, at one-year following initial catheterization, after adjustment for known demographic, co-morbid, and disease severity predictors of outcome. Method The HRQOL outcome data were collected by means of a self-reported questionnaire mailed to patients on or near the one-year anniversary of their initial cardiac catheterization. Using the Seattle Angina Questionnaire (SAQ), 5 dimensions of HRQOL were measured: exertional capacity, anginal stability, anginal frequency, quality of life and treatment satisfaction. Data from the APPROACH registry were used to risk-adjust the SAQ scale scores. Two analytical strategies were used including general least squares linear modeling, and proportional odds modeling sometimes referred to as the "ordinal logistic modeling". Results 3392 (78.1%) patients responded to the follow-up survey. The adjusted proportional odds ratios for men relative to women (PORs > 1 = better) indicated that men reported significantly better HRQOL on all 5 SAQ dimensions as compared to women. (PORs: Exertional Capacity 3.38 (2.75–4.15), Anginal Stability 1.23 (1.03–1.47), Anginal Frequency 1.70 (1.43–2.01), Treatment Satisfaction 1.27 (1.07–1.50), and QOL 1.74 (1.48–2.04). Conclusions Women with CAD consistently reported worse HRQOL at one year follow-up compared to men. These findings underline the fact that conclusions based on research performed on men with CAD may not be valid for women and that more gender-related research is needed. Future studies are needed to further examine gender differences in psychosocial adjustment following treatment for CAD, as adjustment for traditional clinical variables fails to explain sex differences in health related quality of life outcomes.

How well anthropometric indices such as body mass index (BMI), waist circumference, waist-stature ratio, and waist index correlate with direct measures of body composition (lean body mass, body fat) in men and women with chronic heart failure (CHF) has not been reported. Body composition was assessed by dual-energy x-ray absorptiometry in 140 patients with CHF. Age-adjusted Pearson correlations between each index and measures of body composition for men and women were calculated. Diagnostic accuracy of detecting obesity or high central fat was also examined. In men, all of the anthropometric indices except waist index were just as strongly correlated with lean body mass (correlation coefficients varied between 0.56 for waist-stature ratio to 0.74 for BMI) as with percentage of body fat (correlation coefficients varied between 0.72 for BMI to 0.79 for waist circumference). In women, all 4 anthropometric measures were unable to significantly differentiate between body fat and lean body mass. The positive likelihood ratios for the detection of obesity varied between 2.26 for waist circumference and 3.42 for BMI, waist-stature ratio, and waist index. Anthropometric indices do not accurately reflect body composition in patients with CHF, especially in women. When accurate assessment of body composition is required, direct measurements should be obtained.

BackgroundWe examined the validity of leg-to-leg bioelectrical impedance analysis (BIA) and near-infrared interactance (NIR) to assess body composition in chronic heart failure (CHF) patients.Methods and resultsA total of 140 patients with CHF were enrolled in this cross-sectional study between June 2008 and July 2009. Dual energy x-ray absorptiometry (DEXA) served as the reference standard. A priori, desired precision levels were set at ± 3.5% body fat and ± 3.5 kg lean body mass. Mean age was 63, 74% were male, and 90% were Caucasian. BIA- and NIR-ascertained percent body fat and lean body mass were highly correlated to DEXA. Mean differences and limits of agreement for NIR were -0.3% ± 5.1% for percent body fat and 2.9 kg ± 4.3 kg for lean body mass. Mean difference and limits of agreement for BIA percent body fat was 0.8% ± 5.8%. BIA lean body mass showed poor agreement with DEXA because of variable limits of agreement across the range of measurement (Pitman's test P < .0001).ConclusionsIn patients with CHF, both NIR and BIA accurately measure body fat. However, both methods were imprecise. NIR overestimated lean body mass and BIA was not useful to assess this parameter. Further study is required, including examination of the utility of these field methods in serially assessing body composition.