Intravenous Heparin, Thrombolytics, and Medical Marketing

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74985/1/j.1540-8183.1991.tb01002.x.pd

Launching PCORnet, a national patient-centered clinical research network

The Patient-Centered Outcomes Research Institute (PCORI) has launched PCORnet, a major initiative to support an effective, sustainable national research infrastructure that will advance the use of electronic health data in comparative effectiveness research (CER) and other types of research. In December 2013, PCORI's board of governors funded 11 clinical data research networks (CDRNs) and 18 patient-powered research networks (PPRNs) for a period of 18 months. CDRNs are based on the electronic health records and other electronic sources of very large populations receiving healthcare within integrated or networked delivery systems. PPRNs are built primarily by communities of motivated patients, forming partnerships with researchers. These patients intend to participate in clinical research, by generating questions, sharing data, volunteering for interventional trials, and interpreting and disseminating results. Rapidly building a new national resource to facilitate a large-scale, patient-centered CER is associated with a number of technical, regulatory, and organizational challenges, which are described here

Prospective relationships between body weight and physical activity: an observational analysis from the NAVIGATOR study

Objectives: While bidirectional relationships exist between body weight and physical activity, direction of causality remains uncertain and previous studies have been limited by self-reported activity or weight and small sample size. We investigated the prospective relationships between weight and physical activity. Design: Observational analysis of data from the Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) study, a double-blinded randomised clinical trial of nateglinide and valsartan, respectively. Setting Multinational study of 9306 participants. Participants: Participants with biochemically confirmed impaired glucose tolerance had annual measurements of both weight and step count using research grade pedometers, worn for 7 days consecutively. Along with randomisation to valsartan or placebo plus nateglinide or placebo, participants took part in a lifestyle modification programme. Outcome measures: Longitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates. Analysis was then repeated with physical activity as response value and weight as predictor value. Only participants with a response value preceded by at least three annual response values were included. Results: Adequate data were available for 2811 (30%) of NAVIGATOR participants. Previous weight (χ2=16.8; p<0.0001), but not change in weight (χ2=0.1; p=0.71) was inversely associated with subsequent step count, indicating lower subsequent levels of physical activity in heavier individuals. Change in step count (χ2=5.9; p=0.02) but not previous step count (χ2=0.9; p=0.34) was inversely associated with subsequent weight. However, in the context of trajectories already established for weight (χ2 for previous weight measurements 747.3; p<0.0001) and physical activity (χ2 for previous step count 432.6; p<0.0001), these effects were of limited clinical importance. Conclusions: While a prospective bidirectional relationship was observed between weight and physical activity, the magnitude of any effect was very small in the context of natural trajectories already established for these variables

Importance of clinical measures of ischemia in the prognosis of patients with documented coronary artery disease

AbstractTo examine the value of clinical measures of ischemia for stratifying prognosis, 5,886 consecutive patients who had symptomatic significant (≥75% stenosis) coronary artery disease were studied. Using the Cox regression model in a randomly selected half of the patients, the prognostically independent clinical variables were weighted and arranged into a simple angina score: angina score = angina course × (1 + daily angina frequency) + ST-T changes, where angina course was equal to 3 if unstable or variant angina was present, 2 if the patient's angina was progressive with nocturnal episodes, 1 if it was progressive without nocturnal symptoms and 0 if it was stable; 6 points were added for the presence of “ischemic” ST-T changes. This angina score was then validated in an independent patient sample.The score was a more powerful predictor of prognosis than was any individual anginal descriptor. Furthermore, the angina score added significant independent prognostic information to the patient's age, sex, coronary anatomy and left ventricular function. Patients with three vessel disease and a normal ventricle (n = 1,233) had a 2 year infarction-free survival rate of 90% with an angina score of 0 and a 68% survival rate with an angina score ≥9. With an ejection fraction <50% and three vessel disease (n = 1,116), the corresponding infarction-free survival figures were 76 and 56%. Thus, a careful summarization of clinical markers of ischemia in the form of an angina score can provide a powerful prognostic tool and may aid clinicians in identifying high risk patients who are candidates for aggressive therapeutic interventions