[Show abstract][Hide abstract] ABSTRACT: A noninvasive system for determining left ventricular (LV) filling pressure may help to improve personalized fluid removal goals in hemodialysis patients. We previously showed that the change in photoplethysmography (PPG) pulse amplitude measured by finger PPG during a Valsalva maneuver correlates with invasively measured left ventricular end-diastolic pressure (LVEDP). This key PPG change, the ratio of finger PPG pulse amplitude at end-Valsalva to baseline, is known as the Pulse Amplitude Ratio, PAR. The objective of this study was to determine how PAR changes after fluid removal in hemodialysis.
We tested subjects with end-stage renal disease, before and after hemodialysis. Each subject performed a Valsalva maneuver with an effort of 20 mmHg for 10 s, guided by the device display. Finger PPG was recorded continuously before and during the maneuver. PAR was calculated automatically.
Twenty-seven subjects (21 Males) ages 25-75 years were tested. Access sites were AV-fistulas of the arm predominantly. Weight decreased from 99.7 ± 36.9 kg to 97.0 ± 36.0 kg (p < 0.0003) with an average fluid removal of 3.07 ± 1.08 l. Correspondingly, PAR decreased from 0.74 ± 0.24 to 0.62 ± 0.23 (p = 0.003). The change in PAR was correlated with baseline PAR (r = 0.48, p = 0.01).
An index of left heart filling pressure obtained noninvasively using finger photoplethysmography during the Valsalva maneuver is sensitive enough to detect reductions in filling pressure after fluid removal with hemodialysis. Further studies are warranted to determine if this method can be used to guide fluid removal during hemodialysis.
[Show abstract][Hide abstract] ABSTRACT: Using combined individual patient data from prospective studies, we explored sex differences in depression and prognosis post-myocardial infarction (MI) and determined whether disease indices could account for found differences.
Individual patient data analysis of 10,175 MI patients who completed diagnostic interviews or depression questionnaires from 16 prospective studies from the MINDMAPS study was conducted. Multilevel logistic and Cox regression models were used to determine sex differences in prevalence of depression and sex-specific effects of depression on subsequent outcomes.
Combined interview and questionnaire data from observational studies showed that 36% (635/1760) of women and 29% (1575/5526) of men reported elevated levels of depression (age-adjusted odds ratio = 0.68, 95% confidence interval [CI] = 0.60-0.77). The risk for all-cause mortality associated with depression was higher in men (hazard ratio = 1.38, 95% CI = 1.30-1.47) than in women (hazard ratio = 1.22, 95% CI = 1.14-1.31; sex by depression interaction: p < .001). Low left ventricular ejection fraction (LVEF) was associated with higher depression scores in men only (sex by LVEF interaction: B = 0.294, 95% CI = 0.090-0.498), which attenuated the sex difference in the association between depression and prognosis.
The prevalence of depression post-MI was higher in women than in men, but the association between depression and cardiac prognosis was worse for men. LVEF was associated with depression in men only and accounted for the increased risk of all-cause mortality in depressed men versus women, suggesting that depression in men post-MI may, in part, reflect cardiovascular disease severity.
Psychosomatic Medicine 04/2015; 77(4). DOI:10.1097/PSY.0000000000000174 · 3.47 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Background
Although a number of risk factors are known to predict mortality within the first years after myocardial infarction, little is known about interactions between risk factors, whereas these could contribute to accurate differentiation of patients with higher and lower risk for mortality. This study explored the effect of interactions of risk factors on all-cause mortality in patients with myocardial infarction based on individual patient data meta-analysis.Methods
Prospective data for 10,512 patients hospitalized for myocardial infarction were derived from 16 observational studies (MINDMAPS). Baseline measures included a broad set of risk factors for mortality such as age, sex, heart failure, diabetes, depression, and smoking. All two-way and three-way interactions of these risk factors were included in Lasso regression analyses to predict time-to-event related all-cause mortality. The effect of selected interactions was investigated with multilevel Cox regression models.ResultsLasso regression selected five two-way interactions, of which four included sex. The addition of these interactions to multilevel Cox models suggested differential risk patterns for males and females. Younger women (age <50) had a higher risk for all-cause mortality than men in the same age group (HR 0.7 vs. 0.4), while men had a higher risk than women if they had depression (HR 1.4 vs. 1.1) or a low left ventricular ejection fraction (HR 1.7 vs. 1.3). Predictive accuracy of the Cox model was better for men than for women (area under the curves: 0.770 vs. 0.754).Conclusions
Interactions of well-known risk factors for all-cause mortality after myocardial infarction suggested important sex differences. This study gives rise to a further exploration of prediction models to improve risk assessment for men and women after myocardial infarction.
BMC Medicine 12/2014; 12(1):242. DOI:10.1186/PREACCEPT-1708900131424681 · 7.25 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Objectives: To combine individual patient data (IPD) from prospective studies on the association between depression after myocardial infarction (post-MI) and all-cause mortality (ACM) and cardiovascular events (CVE) into one single database. To investigate to what extent disease severity and other medical risk factors explain the association, and to what extent post-MI depression independently predicts prognosis.
Design: IPD meta-analysis using multilevel, multivariable Cox regression analyses.
Data sources: PubMed, Embase, and PsychINFO were searched from inception to January 5th, 2011.
Eligibility criteria for selecting studies: Studies investigating the impact of post-MI depression on cardiovascular outcome, defined as all-cause mortality and cardiac events, were identified. Authors were contacted and invited to contribute their data to a combined database of individual patient data.
Results: Sixteen research groups contributed data, resulting in a combined database of 10,175 post-MI patients. This yielded an HR (adjusted for age and sex) of 1.32 (95%CI 1.26 to 1.38, p<0.001) for ACM, and 1.19 (95%CI 1.14 to 1.24, p<0.001) for CVE. HRs adjusted for disease severity and other medical risk factors were attenuated by 28% (ACM) and 25% (CVE).
Conclusion: The association between post-MI depression and ACM or CVE is substantially attenuated after adjustment for cardiac disease severity and other medical risk factors. Still, depression remains independently and significantly associated with (cardiac) prognosis, with a 22% higher risk of ACM and a 13% higher risk of CVE for each SD increase in depression severity.
The British Journal of Psychiatry 08/2013; 203(2):90-102. DOI:10.1192/bjp.bp.112.111195 · 7.99 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: This review broadly covers advances in heart failure, which is responsible for significant morbidity, mortality, and cost in the United States. It is a heterogeneous condition, and accurate classification helps ensure appropriate application of evidence-based therapies. Hemodynamics are important in acute heart failure syndromes and may help tailor therapy. Neurohormonal modulation forms the cornerstone of chronic systolic heart failure treatment but does not affect outcomes in diastolic heart failure where management goals emphasize optimization of central volume, blood pressure, and atrial rhythm, as well as the treatment of comorbidities. Frontiers of heart failure therapy range from advances in pharmacology (novel inotropic agents and neurohormonal modulators), to cell biology (nucleic acid-based drugs and cell therapy) to biomedical engineering (devices such as ultrafiltration, biventricular pacemakers, implantable cardiac defibrillators, remote monitoring systems, and left ventricular assist devices), and to health systems (risk stratification and integrated care of comorbidities). The ultimate frontier will be to integrate these data effectively to ensure that patients with heart failure consistently receive the best evidenced-based care possible.
The American journal of medicine 01/2013; 126(1):6-12.e6. DOI:10.1016/j.amjmed.2012.04.033 · 5.00 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Determining the prognosis of patients with heart failure is essential for patient management and clinical trial conduct. The relative value of traditional prognostic criteria remains unclear and the assessment of long-term prognosis for individual patients is problematic.
To determine the ability of clinical, hemodynamic and echocardiographic parameters to predict the long-term prognosis of patients with idiopathic dilated cardiomyopathy.
We investigated the ability of clinical, hemodynamic and echocardiographic parameters to predict the long-term prognosis of individual patients in a large, representative, contemporary cohort of idiopathic dilated cardiomyopathy (IDCM) patients referred to Johns Hopkins from 1997 to 2004 for evaluation of cardiomyopathy. In all patients a baseline history was taken, and physical examination, laboratory studies, echocardiogram, right heart catheterization and endomyocardial biopsy were performed.
In 171 IDCM patients followed for a median 3.5 years, there were 50 long-term event-free survivors (LTS) (median survival 6.4 years) and 34 patients died or underwent ventricular assist device placement or transplantation within 5 years (NLTS; non-long-term survivors) (median time to event 1.83 years. Established risk factors (gender, race, presence of diabetes, serum creatinine, sodium) and the use of accepted heart failure medications (angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, beta blockers) were similar between the two groups. Although LTS had younger age, higher ejection fraction (EF) and lower New York Heart Association (NYHA) class at presentation, the positive predictive value of an EF < 25% was 64% (95% CI 41%-79%) and that of NYHA class > 2 was 53% (95% CI 36-69%). A logistic model incorporating these three variables incorrectly classified 29% of patients.
IDCM exhibits a highly variable natural history and standard clinical predictors have limited ability to classify IDCM patients into broad prognostic categories. These findings suggest that there are important host-environmental factors still unappreciated in the biology of IDCM.
The Israel Medical Association journal: IMAJ 11/2012; 14(11):666-71. · 0.90 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Depressed older individuals have a higher mortality than older persons without depression. Depression is associated with physical inactivity, and low levels of physical activity have been shown in some cohorts to be a partial mediator of the relationship between depression and cardiovascular events and mortality.
A cohort of 5888 individuals (mean 72.8 ± 5.6 years, 58% female, 16% African-American) from four US communities was followed for an average of 10.3 years. Self-reported depressive symptoms (10-item Center for Epidemiological Studies Depression Scale) were assessed annually and self-reported physical activity was assessed at baseline and at 3 and 7 years. To estimate how much of the increased risk of cardiovascular mortality associated with depressive symptoms was due to physical inactivity, Cox regression with time-varying covariates was used to determine the percentage change in the log HR of depressive symptoms for cardiovascular mortality after adding physical activity variables.
At baseline, 20% of participants scored above the cut-off for depressive symptoms. There were 2915 deaths (49.8%), of which 1176 (20.1%) were from cardiovascular causes. Depressive symptoms and physical inactivity each independently increased the risk of cardiovascular mortality and were strongly associated with each other (all p < 0.001). Individuals with both depressive symptoms and physical inactivity had greater cardiovascular mortality than those with either individually (p < 0.001, log rank test). Physical inactivity reduced the log HR of depressive symptoms for cardiovascular mortality by 26% after adjustment. This was similar for persons with (25%) and without (23%) established coronary heart disease.
Physical inactivity accounted for a significant proportion of the risk of cardiovascular mortality due to depressive symptoms in older adults, regardless of coronary heart disease status.
[Show abstract][Hide abstract] ABSTRACT: In spite of their widespread use in other fields, global measures of health are not commonly used in determining the prognosis of patients with myocardial infarction (MI). The objective of the present study was to ascertain the relationship between self-assessed physical health at the time of the MI and long-term mortality.
This was a prospective cohort study of 284 patients with MI admitted to an academic community hospital between July 1995 and December 1996 who completed the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The physical component scale from the SF-36 was used as a self-assessment of physical health. All-cause mortality was assessed 10 years later by using the Social Security Death Index.
Patients with lower self-reported physical health were significantly more likely to be women; older; depressed; have a history of coronary artery disease; have a family history of MI; have a non-Q wave MI; have a Killip class 3 or 4 MI; have hypertension, diabetes mellitus, renal insufficiency, and chronic obstructive pulmonary disease; and have a longer hospitalization period. Patients with higher physical component scores had significantly lower mortality in the 10 years after MI and this persisted after adjusting for confounders (hazard ratio = 0.97 [95% CI 0.96-0.99], P = .001).
These data suggest that self-assessed physical health provides information on the long-term prognosis of patients with MI above and beyond that provided by traditional risk predictors.
Journal of cardiopulmonary rehabilitation and prevention 01/2010; 30(1):35-9. DOI:10.1097/HCR.0b013e3181c85a11 · 1.58 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Self-report measures of health status predict mortality in several groups of patients with cardiovascular disease, although overlap with symptoms of depression may reduce or eliminate this relationship. The association between self-reported health status and mortality has not been examined in patients hospitalized for acute coronary syndrome (ACS). The objective was to investigate whether the Physical Component Summary (PCS) and Mental Component Summary (MCS) scores of the SF-12 predicted 12-month all-cause mortality after controlling for cardiac risk factors and symptoms of depression.
The SF-12 and Beck Depression Inventory were administered 2-5 days after admission to 800 ACS patients from 12 coronary care units. Logistic regression was used to assess the relationship of the PCS and MCS with mortality 12 months later, controlling for age, sex, cardiac diagnosis (acute myocardial infarction vs. unstable angina), Killip class, history of myocardial infarction, and in-hospital depressive symptoms.
Lower scores on the SF-12 PCS (worse health) were associated with a significantly higher risk of mortality [odds ratio (OR)=0.94, 95% confidence interval (CI)=0.92-0.97, P<.001]. MCS scores failed to reach significance (OR=0.98, CI=0.95-1.00, P=.053). The PCS significantly predicted mortality even after controlling for other cardiac risk factors and depressive symptoms (OR=0.96, CI=0.93-0.99, P=.008), equivalent to a 34% increase in risk per 10-point (1 SD) decrement in PCS scores.
The brief SF-12 PCS presents an attractive option for improving risk stratification among hospitalized ACS patients.
Journal of Psychosomatic Research 01/2009; 65(6):587-93. DOI:10.1016/j.jpsychores.2008.06.004 · 2.74 Impact Factor
[Show abstract][Hide abstract] ABSTRACT: Killip classification is an independent predictor of early mortality after myocardial infarction, and the presence of left ventricular systolic dysfunction (left ventricular ejection fraction <50%) and high Killip class predicts poor short-term prognosis. The long-term prognostic significance of Killip class and left ventricular systolic dysfunction, however, is unknown.
We studied the impact of Killip class and left ventricular systolic dysfunction on all-cause mortality (assessed in May 2007 using the Social Security Death Index) in myocardial infarction patients admitted from July 1995 to December 1996.
Of 282 patients, 60% (n=168) were Killip class 1, 23% (n=64) were Killip class 2, and 17% (n=50) were Killip class 3 or 4. Patients with higher Killip class were older and more likely to have diabetes, a non-Q-wave myocardial infarction, renal insufficiency, chronic obstructive pulmonary disease, and left ventricular systolic dysfunction. There were 152 deaths at 10 years after myocardial infarction, and patients with Killip class 2, 3, or 4 had higher mortality compared with Killip class 1 in unadjusted analyses. Patients with left ventricular systolic dysfunction and Killip class of 2 or more had significantly higher 10-year mortality (70 deaths or 76.9%) compared with Killip class 1 patients without left ventricular systolic dysfunction (29 deaths or 34.5%, P <.001). This risk persisted after adjusting for demographics, cardiovascular risk factors, and co-morbidities. Much of the risk was explained by deaths in the first 5 years after myocardial infarction.
Killip class is a strong predictor of long-term mortality, and patients with high Killip class and left ventricular systolic dysfunction are at highest risk.
The American journal of medicine 11/2008; 121(11):1015-8. DOI:10.1016/j.amjmed.2008.06.020 · 5.00 Impact Factor