Rossi’s Principles of Transfusion Medicine

Individuals with sickle cell disease (SCD) experience cognitive deficits; however, it remains unclear whether medical treatments for SCD improve cognition. Given that executive abilities are typically impaired in individuals with SCD, they were the focus of the current study. Our primary hypothesis was that executive abilities would be higher acutely soon after a blood transfusion in children and young adults with SCD. We used tests from the NIH Toolbox to assess executive abilities in 27 participants with SCD receiving chronic transfusion in comparison to 34 participants with SCD receiving hydroxyurea (HU) and 41 non-SCD demographically matched controls, all of whom were tested at two time points. Participants in the transfusion group completed cognitive testing within 3 days after a transfusion (soon after transfusion) and then within 3 days before their next transfusion (long after transfusion) over an interval of 3-7 weeks. We found that executive abilities were significantly poorer for the transfusion and HU groups than for the control group. In support of our primary hypothesis, executive abilities for the transfusion group were significantly better soon after a transfusion compared to long after a transfusion, χ2 (1) = 17.8, P < .0001. Our results demonstrate that executive abilities were higher acutely following a blood transfusion. These findings have implications for daily functioning, medical decision making, and academic achievement in children and young adults with SCD.

Higher executive abilities following a blood transfusion in children and young adults with sickle cell disease

https://onlinelibrary.wiley.com/doi/pdfdirect/10.1111/trf.16935

Racial differences in red blood cell transfusion in hospitalized patients with anemia

Outpatients with hematologic disease often receive red cell transfusion to treat anemia and fatigue. The effect of transfusion on fatigue-related quality of life and how well this effect is sustained has not been quantified. The study aim was to describe the early and sustained impact over 4 weeks of red cells on patient-reported fatigue in outpatients age ≥ 50 receiving transfusion as routine clinical care. FACIT-Fatigue scale scores were measured pre-transfusion and at visits targeting 3, 7, and 28 days post-transfusion. Group-based trajectory modeling of patient fatigue scores by study day was used to identify the number of distinct trajectories (Groups), then longitudinal mixed effects modeling of fatigue scores was used to estimate group-specific mean improvements early after transfusion and between days 3 and 28 post-transfusion. Four distinct fatigue score trajectory groups were identified and were found to be correlated with baseline fatigue scores (means 12, 26, 34, and 47 points). In the three groups with the lowest fatigue trajectories (indicating greater fatigue), improvements in fatigue early after transfusion achieved the established minimum clinically important difference (≥ 3 points, Group p = 0.0039). In all trajectory groups, mean fatigue levels did not change significantly between 3 and 28 days (± 1 point, Group p = 0.60). Patient-reported fatigue varies widely among older adult outpatients with hematologic disorders. Nonetheless, trajectory modeling suggests that most anemic patients can expect a noticeable improvement in fatigue in the first few days after transfusion that generally is sustained up to 4 weeks.

Early and sustained improvement in fatigue-related quality of life following red blood cell transfusion in outpatients

Aortic dissection continues to be responsible for significant morbidity and mortality, although recent advances in medical data assimilation and in experimental and in silico models have improved our understanding of the initiation and progression of the accumulation of blood within the aortic wall. Hence, there remains a pressing necessity for innovative and enhanced models to more accurately characterize the associated pathological changes. Early on, experimental models were employed to uncover mechanisms in aortic dissection, such as hemodynamic changes and alterations in wall microstructure, and to assess the efficacy of medical implants. While experimental models were once the only option available, more recently they are also being used to validate in silico models. Based on an improved understanding of the deteriorated microstructure of the aortic wall, numerous multiscale material models have been proposed in recent decades to study the state of stress in dissected aortas, including the changes associated with damage and failure. Furthermore, when integrated with accessible patient-derived medical data, in silico models prove to be an invaluable tool for identifying correlations between hemodynamics, wall stresses, or thrombus formation in the deteriorated aortic wall. They are also advantageous for model-guided design of medical implants with the aim of evaluating the deployment and migration of implants in patients. Nonetheless, the utility of in silico models depends largely on patient-derived medical data, such as chosen boundary conditions or tissue properties. In this review article, our objective is to provide a thorough summary of medical data elucidating the pathological alterations associated with this disease. Concurrently, we aim to assess experimental models, as well as multiscale material and patient data-informed in silico models, that investigate various aspects of aortic dissection. In conclusion, we present a discourse on future perspectives, encompassing aspects of disease modeling, numerical challenges, and clinical applications, with a particular focus on aortic dissection. The aspiration is to inspire future studies, deepen our comprehension of the disease, and ultimately shape clinical care and treatment decisions.

Mechanisms of Aortic Dissection: From Pathological Changes to Experimental and In Silico Models

BACKGROUND AND OBJECTIVE Guidelines suggest that red-blood-cell transfusion decisions for most hospitalized patients be based on haemoglobin (Hb) concentration and the presence of symptoms of anaemia, including fatigue. However, studies differ in whether transfusion is associated with improvements in fatigue. One explanation is that the benefit of transfusion varies by baseline fatigue levels, which existing studies have not examined. The objective of this study was to determine whether the association between transfusion during hospitalization and improvements in fatigue 30 days postdischarge varies by baseline fatigue level. METHODS A prospective observational study of hospitalized general medicine patients with any Hb <9 g/dl. Patients with sickle cell anaemia and gastrointestinal bleeding were excluded since these diagnoses have alternative transfusion practices. Patients with depression were excluded because their fatigue is not primarily due to anaemia. Fatigue was measured during an in-person interview and a 30-day postdischarge phone interview. Hb values and receipt of a transfusion were collected from hospital administrative data. Linear regression was used to test associations between 'change in fatigue', Hb concentration and receipt of a transfusion. RESULTS Transfusion interacted with nadir Hb was associated with reduced fatigue postdischarge for patients with higher baseline fatigue (20% most fatigued: β = 12, P = 0·02; 10% most fatigued: β = 17, P = 0·02). Patients <50 years old with high baseline fatigue had large reductions in fatigue from transfusion (20%: β = 23, P = 0·02; 10%: β = 29, P = 0·03). CONCLUSIONS Transfusion during hospitalization is associated with reduced fatigue 30 days postdischarge in patients with higher levels of baseline fatigue.

The effect of red-blood-cell transfusion on fatigue in hospitalized patients with anaemia.

Revascularizations and Limb Outcomes of Hospitalized Patients with Diabetic Peripheral Arterial Disease in the Contemporary Era.

Genetic Risk Score Can Supplement Current Guidelines To Identify Patients At Elevated Risk For Abdominal Aortic Aneurysms

Background: The objective of this study was to create normative growth curves for pediatric upper airway volume using 3D computed tomography with emphasis on the neonatal age group. Methods: We completed a single-institution, retrospective review of all patients with available CT scans between the ages of 0 and 60 months. Patients were excluded if they exhibited any maxillofacial dysmorphism or upper airway pathology or if scans showed the presence of airway appliances or tubes. 3D volumetric upper airway analysis was performed and 2D cephalometric measurements and growth parameters including height, weight and age were recorded for all patients. Linear regression analysis was used to develop a prediction model for airway volume in terms of age adjusting for cephalometric and growth parameters stratified by sex and the resulting model was used to create separate percentile curves for each sex group. Results: The growth curves were created based on CT scans from 217 healthy patients. Mean airway volume was significantly larger in males than females (3.23 ± 1.98 mm3 vs 2.61 ± 1.64 mm3, p = 0.017). Conclusions: Normative growth curves for neonatal and pediatric upper airway volume are a useful tool for tracking changes in airway volume in the growing infant.

Creating Normative Growth Curves for Pediatric Upper Airway Volume

Hybridising the Armamentarium: Exploring New Approaches to Arteriovenous Graft Repair.

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

David Jiang

Author Tools

Chat about Author