Study Design and Setting: The authors developed a cumulative complexity model, which integrates existing literature and emphasizes how clinical and social factors accumulate and interact to complicate patient care. A narrative literature selleck chemicals llc review is used
to explicate the model.
Results: The model emphasizes a core, patient-level mechanism whereby complicating factors impact care and outcomes: the balance between patient workload of demands and patient capacity to address demands. Workload encompasses the demands on the patient’s time and energy, including demands of treatment, self-care, and life in general. Capacity concerns ability to handle work (e.g., functional morbidity, financial/social resources, literacy). Workload-capacity EX 527 price imbalances comprise the mechanism driving patient complexity. Treatment and illness burdens serve as feedback loops, linking negative outcomes to further imbalances, such that complexity may accumulate over time.
Conclusion: With its components largely supported by existing literature, the model has implications for analytic design, clinical epidemiology, and clinical practice. (c) 2012 Elsevier Inc. All rights reserved.”
“Background: Patent foramen ovale (PFO) is considered to be a risk factor for ischemic cerebrovascular disease (ICVD),
especially in young people. However, the potential pathophysiological
relevance in ischemic stroke is controversial and in need of further investigation. In this study, we examined the conventional risk factors and the distribution of 100 polymorphisms in 47 suspected susceptibility genes for ICVD in stroke patients with or without a PFO. Methods: In the South Stockholm Ischemic Stroke Study, 928 ICVD patients and 602 controls were genotyped for 100 different gene GANT61 datasheet polymorphisms. The stroke patients also underwent relevant investigation and standardized blood tests. Patients who underwent transeosophageal echocardiography as part of their investigation were divided into groups that either had or did not have a PFO. Results: There were no significant differences in the 2 groups with regard to conventional risk factors or blood analyses. Three different polymorphisms located in the prothrombin, F2 (20210G/A), and apolipoprotein-C3 (-641A/C and -455T/A) genes were significantly associated with ICVD and PFO. The strongest association was found for F2 (P = .0049; odds ratio 26.4). Conclusions: We found that F2, which previously has been described as being a possible link between PFO and ICVD, was significantly associated with ICVD and PFO. There was also a trend toward an association between 2 other polymorphisms in the APO-CIII gene and PFO and ICVD.