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STUDY OBJECTIVE: The aim of this study was to investigate the efficacy of a two-step patient blood management (PBM) program in red blood cell (RBC) transfusion requirements among patients undergoing elective cardiopulmonary bypass (CPB) surgery. DESIGN: Prospective, non-randomized, two-step protocol design. SETTING: Cardiac surgery department of Clinique Pasteur, Toulouse, France. PATIENTS: 897 patients undergoing for elective CPB surgery. INTERVENTIONS: We conducted a two-steps protocol: PBMe and PBMc. PBMe involved a short quality improvement program for health care workers, while PBMc introduced a systematic approach to pre- and postoperative correction of deficiencies, incorporating iron injections, oral vitamins, and erythropoiesis-stimulating agents. MEASUREMENTS: The PBM program's effectiveness was evaluated through comparison with a pre-PBM retrospective cohort after propensity score matching. The primary objective was the proportion of patients requiring RBC transfusions during their hospital stay. Secondary objectives were also analyzed. MAIN RESULTS: After matching, 343 patients were included in each group. Primary outcomes were observed in 35.7% (pre-PBM), 26.7% (PBMe), and 21.1% (PBMc) of patients, resulting in a significant reduction (40.6%) in the overall RBC transfusion rate. Both the PBMe and PBMc groups exhibited significantly lower risks of RBC transfusion compared to the pre-PBM group, with adjusted odds ratios of 0.59 [95% CI 0.44-0.79] and 0.44 [95% CI 0.32-0.60], respectively. Secondary endpoints included reductions in transfusions exceeding 2 units, total RBC units transfused, administration of allogeneic blood products, and total bleeding volume recorded on Day 1. There were no significant differences noted in mortality rates or the duration of hospital stays. CONCLUSIONS: This study suggests that health care education and systematic deficiency correction are associated with reduced RBC transfusion rates in elective CPB surgery. However, further randomized, controlled studies are needed to validate these findings and refine their clinical application.
ABSTRACT
OBJECTIVES: Prevention of cardiovascular disease (CVD) and dementia is a key health priority among older adults. Understanding individuals' attitudes to, the prevention of these conditions, particularly when delivered through novel eHealth tools, could help in designing effective prevention programmes. The aim of the study was to explore the attitudes of older adults at increased risk of CVD and dementia regarding engagement in eHealth self-management prevention programmes, and to describe the facilitators and barriers. DESIGN: A qualitative research approach was used. Data were collected through eight focus groups in Finland, France and the Netherlands. Data were analysed following the principles of grounded theory. SETTING AND PARTICIPANTS: Forty-four community-dwellers aged 65+ at risk of CVD were recruited from a previous trial cohort in Finland, and through general practices in France and the Netherlands. RESULTS: The study identified three categories: access to reliable information, trust in the healthcare providers and burden and stigma of dementia. A core category was also identified: the interactive process of the three categories influencing engagement in self-management prevention programme. The categories were interconnected through an interactive process and influenced by the local healthcare culture and context which shaped them differently, becoming either facilitators or barriers to engage in eHealth self-management prevention programmes. CONCLUSIONS: The study emphasises the importance of considering the interactions between the identified categories in this study, grounded in the local healthcare culture and context in further developments of eHealth self-management interventions that aim to prevent CVD and dementia. TRIAL REGISTRATION NUMBER: ISRCTN48151589.
Subject(s)
Cardiovascular Diseases , Dementia , Telemedicine , Aged , Attitude , Cardiovascular Diseases/prevention & control , Dementia/prevention & control , Finland , France , Humans , Netherlands , Qualitative ResearchABSTRACT
At the design of clinical trial operation, a question of a paramount interest is how long it takes to recruit a given number of patients. Modelling the recruitment dynamics is the necessary step to answer this question. Poisson-gamma model provides very convenient, flexible and realistic approach. This model allows predicting the trial duration using data collected at an interim time with very good accuracy. A natural question arises: how to evaluate the parameters of recruitment model before the trial begins? The question is harder to handle as there are no recruitment data available for this trial. However, if there exist similar completed trials, it is appealing to use data from these trials to investigate feasibility of the recruitment process. In this paper, the authors explore the recruitment data of two similar clinical trials (Intergroupe Francais du Myélome 2005 and 2009). It is shown that the natural idea of plugging the historical rates estimated from the completed trial in the same centres of the new trial for predicting recruitment is not a relevant strategy. In contrast, using the parameters of a gamma distribution of the rates estimated from the completed trial in the recruitment dynamic model of the new trial provides reasonable predictive properties with relevant confidence intervals. Copyright © 2017 John Wiley & Sons, Ltd.
Subject(s)
Clinical Trials as Topic/methods , Patient Selection , Poisson Distribution , Clinical Trials, Phase III as Topic , Computer Simulation , Humans , Models, Statistical , Monte Carlo Method , Multiple Myeloma/therapy , Research DesignABSTRACT
Recruiting patients is a crucial step of a clinical trial. Estimation of the trial duration is a question of paramount interest. Most techniques are based on deterministic models and various ad hoc methods neglecting the variability in the recruitment process. To overpass this difficulty the so-called Poisson-gamma model has been introduced involving, for each centre, a recruitment process modelled by a Poisson process whose rate is assumed constant in time and gamma-distributed. The relevancy of this model has been widely investigated. In practice, rates are rarely constant in time, there are breaks in recruitment (for instance week-ends or holidays). Such information can be collected and included in a model considering piecewise constant rate functions yielding to an inhomogeneous Cox model. The estimation of the trial duration is much more difficult. Three strategies of computation of the expected trial duration are proposed considering all the breaks, considering only large breaks and without considering breaks. The bias of these estimations procedure are assessed by means of simulation studies considering three scenarios of breaks simulation. These strategies yield to estimations with a very small bias. Moreover, the strategy with the best performances in terms of prediction and with the smallest bias is the one which does not take into account of breaks. This result is important as, in practice, collecting breaks data is pretty hard to manage.
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INTRODUCTION: Cardiovascular disease and dementia share a number of risk factors including hypertension, hypercholesterolaemia, smoking, obesity, diabetes and physical inactivity. The rise of eHealth has led to increasing opportunities for large-scale delivery of prevention programmes encouraging self-management. The aim of this study is to investigate whether a multidomain intervention to optimise self-management of cardiovascular risk factors in older individuals, delivered through an coach-supported interactive internet platform, can improve the cardiovascular risk profile and reduce the risk of cardiovascular disease and cognitive decline. METHODS AND ANALYSIS: HATICE is a multinational, multicentre, prospective, randomised, open-label blinded end point (PROBE) trial with 18â months intervention. Recruitment of 2600 older people (≥65â years) at increased risk of cardiovascular disease will take place in the Netherlands, Finland and France. Participants randomised to the intervention condition will have access to an interactive internet platform, stimulating self-management of vascular risk factors, with remote support by a coach. Participants in the control group will have access to a static internet platform with basic health information.The primary outcome is a composite score based on the average z-score of the difference between baseline and 18â months follow-up values of systolic blood pressure, low-density-lipoprotein and body mass index. Main secondary outcomes include the effect on the individual components of the primary outcome, the effect on lifestyle-related risk factors, incident cardiovascular disease, mortality, cognitive functioning, mood and cost-effectiveness. ETHICS AND DISSEMINATION: The study was approved by the medical ethics committee of the Academic Medical Center in Amsterdam, the Comité de Protection des Personnes Sud Ouest et Outre Mer in France and the Northern Savo Hospital District Research Ethics Committee in Finland.We expect that data from this study will result in a manuscript published in a peer-reviewed clinical open access journal. TRIAL REGISTRATION NUMBER: ISRCTN48151589.
Subject(s)
Cardiovascular Diseases/prevention & control , Cognitive Dysfunction/prevention & control , Counseling/methods , Healthy Aging , Aged , Aged, 80 and over , Cost-Benefit Analysis , Female , Finland , France , Humans , Internet/statistics & numerical data , Life Style , Male , Netherlands , Prospective Studies , Research Design , Risk Factors , Self-ManagementABSTRACT
Taking a decision on the feasibility and estimating the duration of patients' recruitment in a clinical trial are very important but very hard questions to answer, mainly because of the huge variability of the system. The more elaborated works on this topic are those of Anisimov and co-authors, where they investigate modelling of the enrolment period by using Gamma-Poisson processes, which allows to develop statistical tools that can help the manager of the clinical trial to answer these questions and thus help him to plan the trial. The main idea is to consider an ongoing study at an intermediate time, denoted t(1). Data collected on [0,t(1)] allow to calibrate the parameters of the model, which are then used to make predictions on what will happen after t(1). This method allows us to estimate the probability of ending the trial on time and give possible corrective actions to the trial manager especially regarding how many centres have to be open to finish on time. In this paper, we investigate a Pareto-Poisson model, which we compare with the Gamma-Poisson one. We will discuss the accuracy of the estimation of the parameters and compare the models on a set of real case data. We make the comparison on various criteria : the expected recruitment duration, the quality of fitting to the data and its sensitivity to parameter errors. We discuss the influence of the centres opening dates on the estimation of the duration. This is a very important question to deal with in the setting of our data set. In fact, these dates are not known. For this discussion, we consider a uniformly distributed approach. Finally, we study the sensitivity of the expected duration of the trial with respect to the parameters of the model : we calculate to what extent an error on the estimation of the parameters generates an error in the prediction of the duration.