Psychosocial distress is a common phenomenon in patients with heart failure (HF). The aim of this study was to analyze psychosocial co-symptoms and their relationship with clinical and ...sociodemographic factors.
In 363 primary care patients with HF, anxiety, depression and negative affectivity (HADS, DS-14), disease coping (FKV) and social support (F-SozU) were measured by validated questionnaires. Severity of HF (according to NYHA classification and Goldman's Specific Activity Scale) and sociodemographic characteristics were documented by self-report instruments.
Increased anxiety and/or depression was found in 29.2% of patients. Anxiety and depression scores were significantly higher than in the German general population (p < 0.005). They were furthermore associated with NYHA and Goldman class (anxiety: p = 0.001; depression: p = 0.001). One third of the sample showed the type D personality pattern, which has been associated with increased mortality in cardiac patients. While HF severity correlated positively with psychological distress, patients living together with other persons had lower HF class than those living alone. Using regression analysis, sociodemographic and psychological variables predicted perceived severity of HF in 20.3% if measured by Goldman's scale (significant for sex, age, depressive symptoms and disease coping), and in 18.6% if measured by NYHA (significant for anxiety).
Severity of HF symptoms and psychosocial factors are interrelated. Self-reported severity of HF is substantially influenced by demographic and psychological variables. In this, it is not relevant if severity is measured by a nonvalidated (NYHA) or a validated instrument (Goldman).
In primary care patients with HF, psychosocial co-symptoms are frequent and interfere with perceived severity of disease. Psychological distress should be considered important in diagnostics and treatment, especially in patients living alone.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Screening of primary care patients at risk for left ventricular systolic dysfunction by a simple blood-test might reduce referral rates for echocardiography. Whether or not natriuretic peptide ...testing is a useful and cost-effective diagnostic instrument in primary care settings, however, is still a matter of debate.
N-terminal pro-brain natriuretic peptide (NT-proBNP) levels, clinical information, and echocardiographic data of left ventricular systolic function were collected in 542 family practice patients with at least one cardiovascular risk factor. We determined the diagnostic power of the NT-proBNP assessment in ruling out left ventricular systolic dysfunction and compared it to a risk score derived from a logistic regression model of easily acquired clinical information.
23 of 542 patients showed left ventricular systolic dysfunction. Both NT-proBNP and the clinical risk score consisting of dyspnea at exertion and ankle swelling, coronary artery disease and diuretic treatment showed excellent diagnostic power for ruling out left ventricular systolic dysfunction. AUC of NT-proBNP was 0.83 (95% CI, 0.75 to 0.92) with a sensitivity of 0.91 (95% CI, 0.71 to 0.98) and a specificity of 0.46 (95% CI, 0.41 to 0.50). AUC of the clinical risk score was 0.85 (95% CI, 0.79 to 0.91) with a sensitivity of 0.91 (95% CI, 0.71 to 0.98) and a specificity of 0.64 (95% CI, 0.59 to 0.67). 148 misclassifications using NT-proBNP and 55 using the clinical risk score revealed a significant difference (McNemar test; p < 0.001) that was based on the higher specificity of the clinical risk score.
The evaluation of clinical information is at least as effective as NT-proBNP testing in ruling out left ventricular systolic dysfunction in family practice patients at risk. If these results are confirmed in larger cohorts and in different samples, family physicians should be encouraged to rely on the diagnostic power of the clinical information from their patients.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
International disease management guidelines recommend the regular assessment of depression and anxiety in heart failure patients. Currently there is little data on the effect of screening for ...depression and anxiety on the quality of life and the prognosis of heart failure (HF). We will investigate the association between the recognition of current depression/anxiety by the general practitioner (GP) and the quality of life and the patients' prognosis.
In this multicenter, prospective, observational study 3,950 patients with HF are recruited by general practices in Germany. The patients fill out questionnaires at baseline and 12-month follow-up. At baseline the GPs are interviewed regarding the somatic and psychological comorbidities of their patients. During the follow-up assessment, data on hospitalization and mortality are provided by the general practice. Based on baseline data, the patients are allocated into three observation groups: HF patients with depression and/or anxiety recognized by their GP (P+/+), those with depression and/or anxiety not recognized (P+/-) and patients without depression and/or anxiety (P-/-). We will perform multivariate regression models to investigate the influence of the recognition of depression and/or anxiety on quality of life at 12 month follow-up, as well as its influences on the prognosis (hospital admission, mortality).
We will display the frequency of GP-acknowledged depression and anxiety and the frequency of installed therapeutic strategies. We will also describe the frequency of depression and anxiety missed by the GP and the resulting treatment gap. Effects of correctly acknowledged and missed depression/anxiety on outcome, also in comparison to the outcome of subjects without depression/anxiety will be addressed. In case results suggest a treatment gap of depression/anxiety in patients with HF, the results of this study will provide methodological advice for the efficient planning of further interventional research.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Generation and analysis of time-series data is relevant to many quantitative fields ranging from economics to fluid mechanics. In the physical sciences, structures such as metastable and coherent ...sets, slow relaxation processes, collective variables dominant transition pathways or manifolds and channels of probability flow can be of great importance for understanding and characterizing the kinetic, thermodynamic and mechanistic properties of the system. Deeptime is a general purpose Python library offering various tools to estimate dynamical models based on time-series data including conventional linear learning methods, such as Markov state models (MSMs), Hidden Markov Models and Koopman models, as well as kernel and deep learning approaches such as VAMPnets and deep MSMs. The library is largely compatible with scikit-learn, having a range of Estimator classes for these different models, but in contrast to scikit-learn also provides deep Model classes, e.g. in the case of an MSM, which provide a multitude of analysis methods to compute interesting thermodynamic, kinetic and dynamical quantities, such as free energies, relaxation times and transition paths. The library is designed for ease of use but also easily maintainable and extensible code. In this paper we introduce the main features and structure of the deeptime software.
It is not well established how psychosocial factors like social support and depression affect health-related quality of life in multimorbid and elderly patients. We investigated whether depressive ...mood mediates the influence of social support on health-related quality of life.
Cross-sectional data of 3,189 multimorbid patients from the baseline assessment of the German MultiCare cohort study were used. Mediation was tested using the approach described by Baron and Kenny based on multiple linear regression, and controlling for socioeconomic variables and burden of multimorbidity.
Mediation analyses confirmed that depressive mood mediates the influence of social support on health-related quality of life (Sobel's p < 0.001). Multiple linear regression showed that the influence of depressive mood (β = -0.341, p < 0.01) on health-related quality of life is greater than the influence of multimorbidity (β = -0.234, p < 0.01).
Social support influences health-related quality of life, but this association is strongly mediated by depressive mood. Depression should be taken into consideration in research on multimorbidity, and clinicians should be aware of its importance when caring for multimorbid patients.
ISRCTN89818205.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
With increasing life expectancy the number of people affected by multimorbidity rises. Knowledge of factors associated with health-related quality of life in multimorbid people is scarce. We aimed to ...identify the factors that are associated with self-rated health (SRH) in aged multimorbid primary care patients.
Cross-sectional study with 3,189 multimorbid primary care patients aged from 65 to 85 years recruited in 158 general practices in 8 study centers in Germany. Information about morbidity, risk factors, resources, functional status and socio-economic data were collected in face-to-face interviews. Factors associated with SRH were identified by multivariable regression analyses.
Depression, somatization, pain, limitations of instrumental activities (iADL), age, distress and Body Mass Index (BMI) were inversely related with SRH. Higher levels of physical activity, income and self-efficacy expectation had a positive association with SRH. The only chronic diseases remaining in the final model were Parkinson's disease and neuropathies. The final model accounted for 35% variance of SRH. Separate analyses for men and women detected some similarities; however, gender specific variation existed for several factors.
In multimorbid patients symptoms and consequences of diseases such as pain and activity limitations, as well as depression, seem to be far stronger associated with SRH than the diseases themselves. High income and self-efficacy expectation are independently associated with better SRH and high BMI and age with low SRH.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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