194 research outputs found

    Are concomitant treatments confounding factors in randomized controlled trials on intensive blood-glucose control in type 2 diabetes? a systematic review

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    International audienceBackgroundOpen-label, randomized controlled trials (RCTs) are subject to observer bias. If patient management is conducted without blinding, a difference between groups may be explained by other factors than study treatment. One factor may come from taking concomitant treatments with an efficacy on the studied outcomes. In type 2 diabetes, some antihypertensive or lipid-lowering drugs are effective against diabetic complications. We wanted to determine if these concomitant treatments were correctly reported in articles of RCTs on type 2 diabetes and if they might have influenced the outcome.MethodsWe performed a systematic review using Medline, Embase, and the Cochrane Library (from January 1950 to July 2010). Open-label RCTs assessing the effectiveness of intensive blood-glucose control in type 2 diabetes were included. We chose five therapeutic classes with proven efficacy against diabetes complications: angiotensin-converting enzyme inhibitors (ACEIs), angiotensin II receptor antagonists (AIIRAs), fibrates, statins, and aspirin. Differences between concomitant treatments were considered statistically significant when p ResultsA total of eight open-label RCTs were included, but only three (37.5%) of them published concomitant treatments. In two studies (ACCORD and ADVANCE), a statistically significant difference was observed between the two groups for aspirin (p = 0.02) and ACEIs (p = 0.02).ConclusionsFew concomitant treatments were published in this sample of open-label RCTs. We cannot completely eliminate an observer bias for these studies. This bias probably influenced the results to an extent that has yet to be determined

    Programmed death-1 levels correlate with increased mortality, nosocomial infection and immune dysfunctions in septic shock patients

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    International audienceINTRODUCTION: Septic shock remains a major health care problem worldwide. Sepsis-induced immune alterations are thought to play a major role in patients' mortality and susceptibility to nosocomial infections. Programmed death-1 (PD-1) receptor system constitutes a newly described immunoregulatory pathway that negatively controls immune responses. It has recently been shown that PD-1 knock-out mice exhibited a lower mortality in response to experimental sepsis. The objective of the present study was to investigate PD-1-related molecule expressions in septic shock patients. METHODS: This prospective and observational study included 64 septic shock patients, 13 trauma patients and 49 healthy individuals. PD-1-related-molecule expressions were measured by flow cytometry on circulating leukocytes. Plasmatic interleukin (IL)-10 concentration as well as ex vivo mitogen-induced lymphocyte proliferation were assessed. RESULTS: We observed that septic shock patients displayed increased PD-1, PD-Ligand1 (PD-L1) and PD-L2 monocyte expressions and enhanced PD-1 and PD-L1 CD4+ T lymphocyte expressions at day 1-2 and 3-5 after the onset of shock in comparison with patients with trauma and healthy volunteers. Importantly, increased expressions were associated with increased occurrence of secondary nosocomial infections and mortality after septic shock as well as with decreased mitogen-induced lymphocyte proliferation and increased circulating IL-10 concentration. CONCLUSIONS: These findings indicate that PD-1-related molecules may constitute a novel immunoregulatory system involved in sepsis-induced immune alterations. Results should be confirmed in a larger cohort of patients. This may offer innovative therapeutic perspectives on the treatment of this hitherto deadly disease

    The Global Risk Approach Should Be Better Applied in French Hypertensive Patients: A Comparison between Simulation and Observation Studies

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    The prediction of the public health impact of a preventive strategy provides valuable support for decision-making. International guidelines for hypertension management have introduced the level of absolute cardiovascular risk in the definition of the treatment target population. The public health impact of implementing such a recommendation has not been measured.We assessed the efficiency of three treatment scenarios according to historical and current versions of practice guidelines on a Realistic Virtual Population representative of the French population aged from 35 to 64 years: 1) BP≥160/95 mm Hg; 2) BP≥140/90 mm Hg and 3) BP≥140/90 mm Hg plus increased CVD risk. We compared the eligibility following the ESC guidelines with the recently observed proportion of treated amongst hypertensive individuals reported by the Etude Nationale Nutrition Santé survey. Lowering the threshold to define hypertension multiplied by 2.5 the number of eligible individuals. Applying the cardiovascular risk rule reduced this number significantly: less than 1/4 of hypertensive women under 55 years and less than 1/3 of hypertensive men below 45 years of age. This was the most efficient strategy. Compared to the simulated guidelines application, men of all ages were undertreated (between 32 and 60%), as were women over 55 years (70%). By contrast, younger women were over-treated (over 200%).The global CVD risk approach to decide for treatment is more efficient than the simple blood pressure level. However, lack of screening rather than guideline application seems to explain the low prescription rates among hypertensive individuals in France. Multidimensional analyses required to obtain these results are possible only through databases at the individual level: realistic virtual populations should become the gold standard for assessing the impact of public health policies at the national level

    Virtual Patients and Sensitivity Analysis of the Guyton Model of Blood Pressure Regulation: Towards Individualized Models of Whole-Body Physiology

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    Mathematical models that integrate multi-scale physiological data can offer insight into physiological and pathophysiological function, and may eventually assist in individualized predictive medicine. We present a methodology for performing systematic analyses of multi-parameter interactions in such complex, multi-scale models. Human physiology models are often based on or inspired by Arthur Guyton's whole-body circulatory regulation model. Despite the significance of this model, it has not been the subject of a systematic and comprehensive sensitivity study. Therefore, we use this model as a case study for our methodology. Our analysis of the Guyton model reveals how the multitude of model parameters combine to affect the model dynamics, and how interesting combinations of parameters may be identified. It also includes a “virtual population” from which “virtual individuals” can be chosen, on the basis of exhibiting conditions similar to those of a real-world patient. This lays the groundwork for using the Guyton model for in silico exploration of pathophysiological states and treatment strategies. The results presented here illustrate several potential uses for the entire dataset of sensitivity results and the “virtual individuals” that we have generated, which are included in the supplementary material. More generally, the presented methodology is applicable to modern, more complex multi-scale physiological models
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