Chrome Extension
WeChat Mini Program
Use on ChatGLM

Differential Impact of Glucose Abnormalities and Iron Overload in TM (TM) and TI(TI): A Comparative Analysis of Diagnostic Approaches and Management Strategies for Optimized Care

Ashraf Soliman,Shayma Ahmed, Fawzia Alyafei, Noora AlHumaidi, Noor Hamed,Ahmed Elawwa,Shaymaa Elsayed, Abbas Noureldin, Nada Alaaraj,Ahmed Khalil

World Journal of Advanced Research and Reviews(2024)

Cited 0|Views0
Abstract
Introduction: Thalassemia syndromes, specifically TM (TM) and TI(TI), are inherited blood disorders characterized by impaired hemoglobin synthesis, leading to chronic anemia. TM requires frequent blood transfusions, causing iron overload and elevating the risk for glucose metabolism issues, while TI, with fewer transfusions, experiences a lower incidence of these metabolic complications. Objectives: The review aims to compare glucose abnormalities, iron overload patterns, diagnostic approaches, iron chelation efficacy, and metabolic complications between TM and TI, offering insights into optimizing clinical management for each condition. Methods: A comprehensive literature review was conducted on studies from the past two decades, focusing on glucose metabolism, iron overload, and related complications in TM and TI patients. Data sources included PubMed, ScienceDirect, and Google Scholar, emphasizing studies that examined glucose abnormalities, iron accumulation, and treatment efficacy. Results: The findings indicate that TM patients have a higher prevalence of glucose abnormalities due to more severe iron overload, predominantly affecting pancreatic beta-cell function and insulin sensitivity. In contrast, TI patients generally exhibit milder metabolic complications due to less frequent transfusions and lower iron loads. Diagnostic tools like the Oral Glucose Tolerance Test (OGTT) and Continuous Glucose Monitoring (CGM) have been shown to detect early glucose abnormalities. Iron chelation therapy, critical for TM, is often more intensive, while TI patients benefit from intermittent chelation, effectively controlling iron without extensive intervention. Additionally, TM patients frequently require pharmacologic glycemic therapy, such as insulin or oral hypoglycemics, to manage more severe glucose dysregulation, whereas TI patients typically maintain stable glucose levels with lifestyle modifications. Discussion: TM and TI patients show distinct profiles in glucose dysregulation and iron overload. TM's high transfusion dependency results in rapid iron accumulation, necessitating aggressive iron chelation and regular glucose monitoring to mitigate the risk of diabetes. OGTT remains a viable option both for TM and TI. Individualized chelation strategies based on transfusion needs and iron levels are essential to minimize glucose-related complications, particularly in TM patients. Conclusions: TM patients experience higher and earlier glucose abnormalities compared to TI, primarily due to transfusion-induced iron overload. Personalized management involving intensive chelation, glucose monitoring, and lifestyle modifications can improve outcomes, especially in TM. For TI patients, milder chelation and lifestyle interventions suffice to maintain stable glucose levels. This review highlights the need for tailored approaches to address the unique challenges in glucose and iron management in TM and TI.
More
Translated text
求助PDF
上传PDF
Bibtex
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
  • Pretraining has recently greatly promoted the development of natural language processing (NLP)
  • We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
  • We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
  • The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
  • Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest