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Plasma Transfusion Demystified: A Review of the Key Factors Influencing the Response to Plasma Transfusion.

ABSTRACT: Many studies have suggested that inappropriate plasma usage is common. An important factor contributing to futile plasma administration in most patients is the nonlinear relationship between coagulation-factor levels and the volume of plasma transfused. In this review, a validated mathematical model and data from the literature will be used to illuminate 3 key properties of plasma transfusion. Those properties are as follows: the effect of plasma transfusion on international normalized ratio (INR) is transient; for the same volume of transfused plasma, a greater reduction in INR is observed at higher initial INRs; and the effect of plasma transfusion on INR correction (ie, the difference between initial and final INRs) diminishes as more plasma is transfused. Frequent misunderstanding of these properties may contribute to inappropriate plasma usage. Therefore, this review will assist physicians in navigating these common pitfalls. Stronger understanding of these principles may result in a reduction of inappropriate plasma transfusions, thus potentially enhancing patient safety and reducing healthcare costs.

SUBMITTER: Bryan AW

PROVIDER: S-EPMC6251590 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Plasma Transfusion Demystified: A Review of the Key Factors Influencing the Response to Plasma Transfusion.

Bryan Allen W AW Staley Elizabeth M EM Kennell Timothy T Feldman Alexander Z AZ Williams Lance A LA Pham Huy P HP

Laboratory medicine 20170501 2

Many studies have suggested that inappropriate plasma usage is common. An important factor contributing to futile plasma administration in most patients is the nonlinear relationship between coagulation-factor levels and the volume of plasma transfused. In this review, a validated mathematical model and data from the literature will be used to illuminate 3 key properties of plasma transfusion. Those properties are as follows: the effect of plasma transfusion on international normalized ratio (IN ...[more]

PMID: 28444398

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Project description:BackgroundNon-adherence is widespread problem. Adherence is a crucial point for the success and the safe use of therapies. The objective of this overview (review of reviews) was to identify factors that influence adherence in chronic physical conditions.MethodsA systematic literature search was performed in Medline and Embase (1990 to July 2013). Publications were screened according to predefined inclusion criteria. The study quality was assessed using AMSTAR. Both process steps were carried out independently by two reviewers. Relevant data on study characteristics and results were extracted in piloted standardized tables by one reviewer and checked by a second. Data were synthesized using a standardized quantitative approach by two reviewers.ResultsSeven systematic reviews were included. Higher education and employment seem to have a positive effect on adherence. Ethnic minorities seem to be less adherent. Co-payments and higher medication cost seems to have negative effect on adherence. In contrast financial status/income and marital status seem to have no influence on adherence. The effect of therapy related factors was mostly unclear or had no effect. Only the number of different medications in heart failure patients showed the tendency of an effect. Indicators of regime complexity showed consistently a negative effect direction. Duration of disease seems to have no effect on adherence. There is the tendency that higher or middle age is associated with higher adherence. But in more than half of the reviews the effect was unclear. There is no clear effect of physical as well as mental comorbidity. Only one review showed the tendency of an effect for mental comorbidity. Also for gender the effect is not clear because the effect direction was heterogenic between and within the systematic reviews.ConclusionThe presented overview shows factors than can potentially have influence on adherence. Only for a few factors the influence on adherence was consistent. Most factors showed heterogeneous results regarding statistical significance and/or effect direction. However, belonging to an ethnic minority, unemployment and cost for the patient for their medications showed consistently a negative effect on adherence which indicates that there is a social gradient.

Project description:MotivationDeep learning has become the dominant technology for protein contact prediction. However, the factors that affect the performance of deep learning in contact prediction have not been systematically investigated.ResultsWe analyzed the results of our three deep learning-based contact prediction methods (MULTICOM-CLUSTER, MULTICOM-CONSTRUCT and MULTICOM-NOVEL) in the CASP13 experiment and identified several key factors [i.e. deep learning technique, multiple sequence alignment (MSA), distance distribution prediction and domain-based contact integration] that influenced the contact prediction accuracy. We compared our convolutional neural network (CNN)-based contact prediction methods with three coevolution-based methods on 75 CASP13 targets consisting of 108 domains. We demonstrated that the CNN-based multi-distance approach was able to leverage global coevolutionary coupling patterns comprised of multiple correlated contacts for more accurate contact prediction than the local coevolution-based methods, leading to a substantial increase of precision by 19.2 percentage points. We also tested different alignment methods and domain-based contact prediction with the deep learning contact predictors. The comparison of the three methods showed deeper sequence alignments and the integration of domain-based contact prediction with the full-length contact prediction improved the performance of contact prediction. Moreover, we demonstrated that the domain-based contact prediction based on a novel ab initio approach of parsing domains from MSAs alone without using known protein structures was a simple, fast approach to improve contact prediction. Finally, we showed that predicting the distribution of inter-residue distances in multiple distance intervals could capture more structural information and improve binary contact prediction.Availability and implementationhttps://github.com/multicom-toolbox/DNCON2/.Supplementary informationSupplementary data are available at Bioinformatics online.

Project description:BackgroundVaccine preventable diseases are still the most common cause of childhood mortality, with an estimated 3 million deaths every year, mainly in Africa and Asia. An estimate of 29% deaths among children aged 1-59 months were due to vaccine preventable diseases. Despite the benefits of childhood immunisation, routine vaccination coverage for all recommended Expanded Programme on Immunization vaccines has remained poor in some African countries, such as Nigeria (31%), Ethiopia (43%), Uganda (55%) and Ghana (57%). The aim of this study is to collate evidence on the factors that influence childhood immunisation uptake in Africa, as well as to provide evidence for future researchers in developing, implementing and evaluating intervention among African populations which will improve childhood immunisation uptake.MethodsWe conducted a systematic review of articles on the factors influencing under-five childhood immunisation uptake in Africa. This was achieved by using various keywords and searching multiple databases (Medline, PubMed, CINAHL and Psychology & Behavioral Sciences Collection) dating back from inception to 2020.ResultsOut of 18,708 recorded citations retrieved, 10,396 titles were filtered and 324 titles remained. These 324 abstracts were screened leading to 51 included studies. Statistically significant factors found to influence childhood immunisation uptake were classified into modifiable and non-modifiable factors and were further categorised into different groups based on relevance. The modifiable factors include obstetric factors, maternal knowledge, maternal attitude, self-efficacy and maternal outcome expectation, whereas non-modifiable factors were sociodemographic factors of parent and child, logistic and administration factors.ConclusionDifferent factors were found to influence under-five childhood immunisation uptake among parents in Africa. Immunisation health education intervention among pregnant women, focusing on the significant findings from this systematic review, would hopefully improve childhood immunisation uptake in African countries with poor coverage rates.

Dataset Information

Plasma Transfusion Demystified: A Review of the Key Factors Influencing the Response to Plasma Transfusion.

Publications

Plasma Transfusion Demystified: A Review of the Key Factors Influencing the Response to Plasma Transfusion.

Similar Datasets

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